"Newly Born" proteins, devoid of detectable homology to any other proteins, known as orphan proteins, occur in a single species or within a taxonomically restricted gene family. They are generated by the expression of novel open reading frames, and appear throughout evolution. We were curious if three recently developed programs for predicting protein structures, namely, AlphaFold2, RoseTTAFold, and ESMFold, might be of value for comparison of such "Newly Born" proteins to random polypeptides with amino acid content similar to that of native proteins, which have been called "Never Born" proteins. The programs were used to compare the structures of two sets of "Never Born" proteins that had been expressed-Group 1, which had been shown experimentally to possess substantial secondary structure, and Group 3, which had been shown to be intrinsically disordered. Overall, although the models generated were scored as being of low quality, they nevertheless revealed some general principles. Specifically, all four members of Group 1 were predicted to be compact by all three algorithms, in agreement with the experimental data, whereas the members of Group 3 were predicted to be very extended, as would be expected for intrinsically disordered proteins, again consistent with the experimental data. These predicted differences were shown to be statistically significant by comparing their accessible surface areas. The three programs were then used to predict the structures of three orphan proteins whose crystal structures had been solved, two of which display novel folds. Surprisingly, only for the protein which did not have a novel fold, and was taxonomically restricted, rather than being a true orphan, did all three algorithms predict very similar, high-quality structures, closely resembling the crystal structure. Finally, they were used to predict the structures of seven orphan proteins with well-identified biological functions, whose 3D structures are not known. Two proteins, which were predicted to be disordered based on their sequences, are predicted by all three structure algorithms to be extended structures. The other five were predicted to be compact structures with only two exceptions in the case of AlphaFold2. All three prediction algorithms make remarkably similar and high-quality predictions for one large protein, HCO_11565, from a nematode. It is conjectured that this is due to many homologs in the taxonomically restricted family of which it is a member, and to the fact that the Dali server revealed several nonrelated proteins with similar folds. An animated Interactive 3D Complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:Proteins:3.

In Gram-negative bacteria, lipopolysaccharide (LPS) is an essential component of the asymmetric outer membrane (OM). LptE is an OM lipoprotein that forms a complex with the β-barrel OM protein, LptD. Incorporation of LPS into the OM outer leaflet is essential for bacterial viability, and mediated by the LptD/E complex. The genome of Campylobacter jejuni, a major foodborne pathogen, contains over 20 putative lipoproteins including Cj1090c. Here, we report the crystal structure of Cj1090c at 2.4 Å resolution, revealing structural evidence for LptE in C. jejuni. The analysis of this crystal structure, along with the genomic context, allows us to propose the C. jejuni LPS transport system for the first time, and permits for discussion of the features of the LptD/E complex of C. jejuni.

The human genome codes for 12 annexins with highly homologous membrane-binding cores and unique amino termini, which endow each protein with its specific biological properties. Not unique to vertebrate biology, multiple annexin orthologs are present in almost all eukaryotes. Their ability to combine either dynamically or constitutively with membrane lipid bilayers is hypothetically the key property that has led to their retention and multiple adaptation in eukaryotic molecular cell biology. Annexin genes are differentially expressed in many cell types but their disparate functions are still being discovered after more than 40 years of international research. A picture is emerging from gene knock down and knock out studies of individual annexins that these are important supporters rather than critical players in organism development and normal cell and tissue function. However, they appear to be highly significant "early responders" toward challenges arising from cell and tissue abiotic or biotic stress. In humans, recent focus has been on involvement of the annexin family for its involvement in diverse pathologies, especially cancer. From what has become an exceedingly broad field of investigation, we have selected four annexins in particular: AnxA1, 2, 5, and 6. Present both within and external to cells, these annexins are currently under intensive investigation in translational research as biomarkers of cellular dysfunction and as potential therapeutic targets for inflammatory conditions, neoplasia, and tissue repair. Annexin expression and release in response to biotic stress appears to be a balancing act. Under- or over-expression in different circumstances appears to damage rather than restore a healthy homeostasis. This review reflects briefly on what is already known of the structures and molecular cell biology of these selected annexins and considers their actual and potential roles in human health and disease.

In recent years, the development of bispecific antibodies (bsAbs) has become a major trend in the biopharmaceutical industry. By simultaneously engaging two molecular targets, bsAbs have exhibited unique mechanisms of action that could lead to clinical benefits unattainable by conventional monoclonal antibodies. The type of structure used to construct a bsAb directly influences the distance, angle, degree of freedom, and affinity between the two antibody binding sites and the interaction between the two antigens or the cells where the antigens are located, which have been bound by the antibody. Consequently, the structure of the bsAb is one of the most vital factors affecting its function. Herein, we reported for the first time a novel basic module bsAb format, VFV (Variable domain-Fab-Variable domain). And then, the feasibility of the VFV format was demonstrated by constructing a series of engager-like basic module bsAbs. Next, a series of VFV bsAbs containing Fc (VFV-Ig), Fab (VFV-Fab), or Hinge (VFV-Hinge) were developed based on Hxb module, and all of them had adequate purity and activity. Finally, a T cell engager bsAb with the potential to overcome on-target off-tumor activity was constructed according to the structural characteristics of VFV, which validated that the VFV module can be used as a new brick for the construction of various bsAbs. In a word, the successful construction of this bsAb format for the first time not only enriches the arsenal of the bsAb format, but also provides inspiration for the construction of new bsAbs. Nevertheless, we are fully aware that as a proof-of-concept study, this paper has many shortcomings, and there is still a lot of work to be done to determine whether VFV can serve as a platform for drug development.

Protein structures are stabilized by several types of chemical interactions between amino acids, which can compete with each other. This is the case of chalcogen and hydrogen bonds formed by the thiol group of cysteine, which can form three hydrogen bonds with one hydrogen acceptor and two hydrogen donors and a chalcogen bond with a nucleophile along the extension of the CS bond. A survey of the Protein Data Bank shows that hydrogen bonds are about 40-50 more common than chalcogen bonds, suggesting that they are stronger and, consequently, prevail, though not always. It is also observed that frequently a thiol group that forms a chalcogen bond is also involved, as a hydrogen donor, in a hydrogen bond.

Protein-protein interactions (PPIs) play a crucial role in numerous molecular processes. Despite many efforts, mechanisms governing molecular recognition between interacting proteins remain poorly understood and it is particularly challenging to predict from sequence whether two proteins can interact. Here we present a new method to tackle this challenge using intrinsically disordered regions (IDRs). IDRs are protein segments that are functional despite lacking a single invariant three-dimensional structure. The prevalence of IDRs in eukaryotic proteins suggests that IDRs are critical for interactions. To test this hypothesis, we predicted PPIs using IDR sequences in candidate proteins in humans. Moreover, we divide the PPI prediction problem into two specific subproblems and adapt appropriate training and test strategies based on problem type. Our findings underline the importance of defining clearly the problem type and show that sequences encoding IDRs can aid in predicting specific features of the protein interaction network of intrinsically disordered proteins. Our findings further suggest that accounting for IDRs in future analyses should accelerate efforts to elucidate the eukaryotic PPI network.

The interaction between avidin and its counterpart biotin is one of central importance in biology and has been reproposed and studied at length. However, the binding pocket of avidin is prone to promiscuous binding, able to accommodate even non-biotinylated ligands. Comprehending the factors that distinguish the extremely strong interaction with biotin to other ligands is an important step to fully picture the thermodynamics of these low-affinity complexes. Here, we present the complex between chicken white egg avidin and theophylline (TEP), the xanthine derivative used in the therapy of asthma. In the crystal structure, TEP lies in the biotin-binding pocket with the same orientation and planarity of the aromatic ring of 8-oxodeoxyguanosine. Indeed, its affinity for avidin measured by isothermal titration calorimetry is in the same μM range as those obtained for the previously characterized nucleoside derivatives. By the use of molecular dynamic simulations, we have investigated the most important intermolecular interactions occurring in the avidin-TEP binding pocket and compared them with those obtained for the avidin 8-oxodeoxyguanosine and avidin-biotin complexes. These results testify the capability of avidin to complex purely aromatic molecules.

The RNA-dependent RNA polymerase (RdRp) complex of SARS-CoV-2 lies at the core of its replication and transcription processes. The interfaces between holo-RdRp subunits are highly conserved, facilitating the design of inhibitors with high affinity for the interaction interface hotspots. We, therefore, take this as a model protein complex for the application of a structural bioinformatics protocol to design peptides that inhibit RdRp complexation by preferential binding at the interface of its core subunit nonstructural protein, nsp12, with accessory factor nsp7. Here, the interaction hotspots of the nsp7-nsp12 subunit of RdRp, determined from a long molecular dynamics trajectory, are used as a template. A large library of peptide sequences constructed from multiple hotspot motifs of nsp12 is screened in-silico to determine sequences with high geometric complementarity and interaction specificity for the binding interface of nsp7 (target) in the complex. Two lead designed peptides are extensively characterized using orthogonal bioanalytical methods to determine their suitability for inhibition of RdRp complexation. Binding affinity of these peptides to accessory factor nsp7, determined using a surface plasmon resonance (SPR) assay, is slightly better than that of nsp12: dissociation constant of 133nM and 167nM, respectively, compared to 473nM for nsp12. A competitive ELISA is used to quantify inhibition of nsp7-nsp12 complexation, with one of the lead peptides giving an IC50 of 25μM . Cell penetrability and cytotoxicity are characterized using a cargo delivery assay and MTT cytotoxicity assay, respectively. Overall, this work presents a proof-of-concept of an approach for rational discovery of peptide inhibitors of SARS-CoV-2 protein-protein interactions.

Intrinsically disordered proteins (IDPs) have numerous dynamic conformations. Given the difficulties in tracking temporarily folded states of this kind of protein, methods such as molecular modeling and molecular dynamics (MD) simulations make the process less costly, less laborious, and more detailed. Few plant IDPs have been characterized so far, such as proteins from the Abscisic acid, Stress and Ripening (ASR) family. The present work applied, for the first time, the two above-mentioned tools to test the feasibility of determining a three-dimensional transition model of OsASR5 and to investigate the relationship between OsASR5 and zinc. We found that one of OsASR5's conformers contains α-helices, turns, and loops and that the metal binding resulted in a predominance of α-helix. This stability is possibly imperative for the transcription factor activity. The promoter region of a sugar transporter was chosen to test this hypothesis and free energy calculations showed how the ion is mandatory for this complex formation. The results produced here aim to clarify which conformation the protein in the bound state assumes and which residues are involved in the process, besides developing the understanding of how the flexibility of these proteins can contribute to the response to environmental stresses.

Protein-RNA interactions play vital roles in plethora of biological processes such as regulation of gene expression, protein synthesis, mRNA processing and biogenesis. Identification of RNA-binding residues (RBRs) in proteins is essential to understand RNA-mediated protein functioning, to perform site-directed mutagenesis and to develop novel targeted drug therapies. Moreover, the extensive gap between sequence and structural data restricts the identification of binding sites in unsolved structures. However, efficient use of computational methods demanding only sequence to identify binding residues can bridge this huge sequence-structure gap. In this study, we have extensively studied protein-RNA interface in known RNA-binding proteins (RBPs). We find that the interface is highly enriched in basic and polar residues with Gly being the most common interface neighbor. We investigated several amino acid features and developed a method to predict putative RBRs from amino acid sequence. We have implemented balanced random forest (BRF) classifier with local residue features of protein sequences for prediction. With 5-fold cross-validations, the sequence pattern derived dipeptide composition based BRF model (DCP-BRF) resulted in an accuracy of 87.9%, specificity of 88.8%, sensitivity of 82.2%, Mathew's correlation coefficient of 0.60 and AUC of 0.93, performing better than few existing methods. We further validated our prediction model on known human RBPs through RBR prediction and could map ~54% of them. Further, knowledge of binding site preferences obtained from computational predictions combined with experimental validations of potential RNA binding sites can enhance our understanding of protein-RNA interactions. This may serve to accelerate investigations on functional roles of many novel RBPs.

The ability to control locomotion in a dynamic environment provides a competitive advantage for microorganisms, thus driving the evolution of sophisticated regulatory systems. In total, 19 known categories of chemotaxis systems control motility mediated by flagella or Type IV pili, plus other cellular functions. A key feature that distinguishes chemotaxis systems from generic two-component regulatory systems is separation of receptor and kinase functions into distinct proteins, linked by CheW scaffold proteins. This arrangement allows for formation of varied arrays with remarkable signaling properties. We recently analyzed sequences of CheW-like domains found in CheA kinases and CheW and CheV scaffold proteins. In total, 16 Architectures of CheA, CheW, and CheV proteins contain ~94% of all CheW-like domains and form six Classes with likely functional specializations. We surveyed chemotaxis system categories and proteins containing CheW-like domains in ~1900 prokaryotic species, the most comprehensive analysis to date, revealing new insights. Co-occurrence analyses suggested that many chemotaxis systems occur in non-random combinations within species, implying synergy or antagonism. Furthermore, many Architectures of proteins containing CheW-like domains occurred predominantly with specific categories of chemotaxis systems, suggesting specialized functional interactions. We propose Class 1 (~80%) and Class 6 (~20%) CheW proteins exhibit preferences for distinct chemoreceptor structures. Furthermore, rare (~1%) Class 2 CheW proteins frequently co-occurred with methyl-accepting coiled coil proteins, which contain both receptor and kinase functions and so do not require connection via a CheW scaffold but may benefit from arrays. Last, rare multidomain CheW proteins may interact with different receptors than single-domain CheW proteins.

In the last years, antibodies have emerged as a promising new class of therapeutics, due to their combination of high specificity with long serum half-life and low risk of side-effects. Diabodies are a popular novel antibody format, consisting of two Fv domains connected with short linkers. Like IgG antibodies, they simultaneously bind two target proteins. However, they offer altered properties, given their smaller size and higher rigidity. In this study, we conducted the-to our knowledge-first molecular dynamics (MD) simulations of diabodies and find a surprisingly high conformational flexibility in the relative orientation of the two Fv domains. We observe rigidifying effects through the introduction of disulfide bonds in the Fv -Fv interface and characterize the effect of different disulfide bond locations on the conformation. Additionally, we compare VH -VL orientations and paratope dynamics between diabodies and an antigen binding fragment (Fab) of the same sequence. We find mostly consistent structures and dynamics, indicating similar antigen binding properties. The most significant differences can be found within the CDR-H2 loop dynamics. Of all CDR loops, the CDR-H2 is located closest to the artificial Fv -Fv interface. All examined diabodies show similar VH -VL orientations, Fv -Fv packing and CDR loop conformations. However, the variant with a P14C-K64C disulfide bond differs most from the Fab in our measures, including the CDR-H3 loop conformational ensemble. This suggests altered antigen binding properties and underlines the need for careful validation of the disulfide bond locations in diabodies.

Thermus thermophilus is an extremely thermophilic organism that thrives at a temperature of 65°C. T. thermophilus genome has ~2218 genes, out of which 66% (1482 genes) have been annotated, and the remaining 34% (736 genes) are assigned as hypothetical proteins. In this work, biochemical and biophysical experiments were performed to characterize the hypothetical protein TTHA1873 from T. thermophilus. The hypothetical protein TTHA1873 acts as a nuclease, which indiscreetly cuts methylated and non-methylated DNA in divalent metal ions and relaxes the plasmid DNA in the presence of ATP. The chelation of metal ions with EDTA inhibits its activity. These results suggest that the hypothetical protein TTHA1873 would be a CRISPR-associated protein with non-specific DNase activity and ATP-dependent DNA-relaxing activity.

Machine learning research concerning protein structure has seen a surge in popularity over the last years with promising advances for basic science and drug discovery. Working with macromolecular structure in a machine learning context requires an adequate numerical representation, and researchers have extensively studied representations such as graphs, discretized 3D grids, and distance maps. As part of CASP14, we explored a new and conceptually simple representation in a blind experiment: atoms as points in 3D, each with associated features. These features-initially just the basic element type of each atom-are updated through a series of neural network layers featuring rotation-equivariant convolutions. Starting from all atoms, we further aggregate information at the level of alpha carbons before making a prediction at the level of the entire protein structure. We find that this approach yields competitive results in protein model quality assessment despite its simplicity and despite the fact that it incorporates minimal prior information and is trained on relatively little data. Its performance and generality are particularly noteworthy in an era where highly complex, customized machine learning methods such as AlphaFold 2 have come to dominate protein structure prediction.

The recognition of Cannabis as a source of new compounds suitable for medical use has attracted strong interest from the scientific community in its research, and substantial progress has accumulated regarding cannabinoids' activity; however, a thorough description of their molecular mechanisms of action remains a task to complete. Highlighting their complex pharmacology, the list of cannabinoids' interactors has vastly expanded beyond the canonical cannabinoid receptors. Among those, we have focused our study on the glycine receptor (GlyR), an ion channel involved in the modulation of nervous system responses, including, to our interest, sensitivity to peripheral pain. Here, we report the use of computational methods to investigate possible binding modes between the GlyR and Δ9 -tetrahydrocannabinol (THC). After obtaining a first pose for the THC binding from a biased molecular docking simulation and subsequently evaluating it by molecular dynamic simulations, we found a dynamic system with an identifiable representative binding mode characterized by the specific interaction with two transmembrane residues (Phe293 and Ser296). Complementarily, we assessed the role of membrane cholesterol in this interaction and positively established its relevance for THC binding to GlyR. Lastly, the use of restrained molecular dynamics simulations allowed us to refine the description of the binding mode and of the cholesterol effect. Altogether, our findings contribute to the current knowledge about the GlyR-THC mode of binding and propose a new starting point for future research on how cannabinoids in general, and THC in particular, modulate pain perception in view of its possible clinical applications.

FAD-independent methylene-tetrahydrofolate (methylene-H4 F) reductase (Mfr), recently identified in mycobacteria, catalyzes the reduction of methylene-H4 F to methyl-H4 F with NADH as hydride donor by a ternary complex mechanism. This biochemical reaction corresponds to that of the ubiquitous FAD-dependent methylene-H4 F reductase (MTHFR), although the latter uses a ping-pong mechanism with the prosthetic group as intermediate hydride carrier. Comparative genomics and genetic analyses indicated that Mfr is indispensable for the growth of Mycobacterium tuberculosis, which lacks the MTHFR encoding gene. Therefore, Mfr appears to be an excellent target for the design of antimycobacterial drugs. Here, we report the heterologous production, enzymological characterization, and the crystal structure of Mfr from the thermophilic mycobacterium Mycobacterium hassiacum (hMfr), which shows 78% sequence identity to Mfr from M. tuberculosis. Although hMfr and MTHFR have minor sequence identity and different catalytic mechanisms, their structures are highly similar, thus suggesting a divergent evolution of Mfr and MTHFR from a common ancestor. Most of the important active site residues of MTHFR are conserved and equivalently positioned in the tertiary structure of hMfr. The Glu9Gln variant of hMfr exhibits a drastic reduction of the catalytic activity, which supports the predicted function of the glutamate residue as proton donor in both hMfr and MTHFR. Thus, highly similar binding modes for the C1 -carriers and the reducing agents in hMfr and MTHFR are assumed.

Bacteria are equipped with a diverse set of regulatory tools that allow them to quickly adapt to their environment. The RimK system allows for Pseudomonas spp. to adapt through post-transcriptional regulation by altering the ribosomal subunit RpsF. RimK is found in a wide range of bacteria with a conserved amino acid sequence, however, the genetic context and the role of this protein is highly diverse. By solving and comparing the structures of RimK homologs from two related but functionally divergent systems, we uncovered key structural differences that likely contribute to the different activity levels of each of these homologs. Moreover, we were able to clearly resolve the active site of this protein for the first time, resolving binding of the glutamate substrate. This work advances our understanding of how subtle differences in protein sequence and structure can have profound effects on protein activity, which can in turn result in widespread mechanistic changes.

Annexin A2 (A2) is a member of the Annexin family, which contains Ca2+ -regulated phospholipid-binding proteins. Annexins associate with S100 proteins to form heterotetramers. The A2/S100A10 heterotetramer (A2t) is the most extensively studied of these heterotetramers. It induces membrane microdomain formation, causes membrane budding, and facilitates proliferation of some cancers. In this work, the first molecular dynamics (MD) study on the complete A2t of 868 amino acids was performed. MD trajectories of more than 600 ns each were generated for complete A2t complexes with and without Ca2+ ions. The outward extension of membrane-binding residues A2-K279 and A2-K281 was shown to be inhibited in the absence of Ca2+ as they were captured by Ca2+ -binding residue D322. F-actin binding residue A2-D339 was observed to occupy either an exposed or buried state in the absence of Ca2+ , while it only occupied the buried state in the presence of Ca2+ . The observed motions of the A2t subunits are highly organized with a strongly correlated central region which is negatively correlated with the periphery of the complex. The central region contains the S100A10 (p11) dimer, A2-N, and A2-I, while the periphery contains A2-II, A2-III, and A2-IV. Novel interactions between A2 and p11 were identified. A2 residues outside of A2-N (K80, R77, E82, and R145) had strong interactions with p11. Residue R145 of A2 may have a significant effect on the dynamics of the system, with its interaction resulting in asymmetric motions of A2. The presented results provide novel insights to inform future experimental studies.

The crystal structure of the complex of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco; EC 4.1.1.39) from Archaeoglobus fulgidus (afRubisco) with its products 3PGAs has been determined to a resolution of 1.7 Å and is of the closed form. Type III Rubiscos such as afRubisco have 18 out of the 19 essential amino acid residues of canonical Rubisco; the 19th is Tyr rather than Phe. Superposition with the structure of a complex of the similar tkRubisco with the six-carbon intermediate analog 2CABP shows the same conformation of the 19 residues except for Glu46 and Thr51. Glu46 adopts a unique conformation different from that in other Rubiscos and makes two H-bonds with the ligand 3PGA. Similar to other closed state Rubiscos, the backbone of Thr51 is rotated and the side chain makes an H-bond with the ligand 3PGA. Two product 3PGA molecules are bound at the active site, overlapping well with the 2CABP of tkRubisco/2CABP. The positions of the P1 and P2 phosphate groups differ by 0.4 and 0.53 Å, respectively, between 2CABP and the two 3PGAs. This afRubisco/3PGA complex mimics an intermediate stage of the carboxylation reaction which occurs after the production of the two 3PGA products but before the reopening of the active site. The stability of this complex suggests that the Rubisco active site will not reopen before both 3PGA products are formed.

Porcine circovirus type 2 (PCV2) can cause porcine circovirus-associated disease (PCVAD), which causes significant economic losses to the global pig industry annually. There are no effective antiviral drugs used to control and treat PCV2, and prevention is mainly obtained through vaccination. PCV2 genome replicates through the rolling circle replication (RCR) mechanism involving Rep and Rep', so analyzing the holistic structure of Rep and Rep' will help us better understand the replication process of PCV2. However, there are no reports on the integral structure of Rep' and Rep, which seriously hinders the research of the viral replication. By using the x-ray diffraction method, the structure of the Rep' dimer was resolved by us in this study. Structural analysis revealed that Rep' is a dimer formed by the interaction of the C-terminal domain. The two Rep' form a positively charged groove, which may play an essential role in the viral binding of dsDNA. Together, this study help to understand the replication process of the virus and may also provide new insights into the development of antiviral drugs.

Phosphoenolpyruvate carboxykinases (PEPCK) are a well-studied family of enzymes responsible for the regulation of TCA cycle flux, where they catalyze the interconversion of oxaloacetic acid (OAA) and phosphoenolpyruvate (PEP) using a phosphoryl donor/acceptor. These enzymes have typically been divided into two nucleotide-dependent classes, those that use ATP and those that use GTP. In the 1960's and early 1970's, a group of papers detailed biochemical properties of an enzyme named phosphoenolpyruvate carboxytransphosphorylase (later identified as a third PEPCK) from Propionibacterium freudenreichii (PPi -PfPEPCK), which instead of using a nucleotide, utilized PPi to catalyze the same interconversion of OAA and PEP. The presented work expands upon the initial biochemical experiments for PPi -PfPEPCK and interprets these data considering both the current understanding of nucleotide-dependent PEPCKs and is supplemented with a new crystal structure of PPi -PfPEPCK in complex with malate at a putative allosteric site. Most interesting, the data are consistent with PPi -PfPEPCK being a Fe2+ activated enzyme in contrast with the Mn2+ activated nucleotide-dependent enzymes which in part results in some unique kinetic properties for the enzyme when compared to the more widely distributed GTP- and ATP-dependent enzymes.

Cysteinyl-tRNA synthetase (CysRS) catalyzes the aminoacylation reaction of cysteine to its cognate tRNACys in the first step of protein translation. It is found that CysRS is different from other aaRSs as it transfers cysteine without the need for an editing reaction, which is not applicable in the case of serine despite the similarity in their structures. Surprisingly, the reasons why CysRS has high amino acid specificity are not clear yet. In this research, the binding configurations of Cys-AMP and its near-cognate amino acid Ser-AMP with CysRS are compared by Molecular Dynamics (MD). The results reveal that CysRS screens the substrate Cys-AMP to a certain extent in the process of combination and recognition, thus providing a guarantee for the high selectivity of the next reaction. While Ser-AMP is in a folded state in CysRS. In the meanwhile, the interaction between Cys-AMP and Zn963 in CysRS is much stronger than Ser-AMP. The substrate-assisted aminoacylation mechanism in CysRS is also explored by Quantum Mechanics/Molecular Mechanics (QM/MM) modeling. According to the QM/MM potential energies, the energy barrier of TSCys-AMP is 91.75 kJ/mol, while that of TSSer-AMP is close to 150 kJ/mol. Based on thermochemistry calculations, it is found that the product of Cys-AMP is more stable than the reactant. In contrast, Ser-AMP has a reactant that is more stable than its product. As a result, it reflects that the specificity of CysRS originates from both the kinetic and thermodynamical perspectives of the reaction. Our investigations demonstrate comprehensively on how CysRS recognizes and catalyzes the substrate Cys-AMP, hoping to provide some guidance for researchers in this area.

Five mini proteins mimicking uricase comprising 20, 40, 60, 80, and 100 amino acids were designed based on the conserved active site residues within the same dimer, using the crystal structure of tetrameric uricase from Arthrobacter globiformis (PDB ID: 2yzb) as a template. Based on molecular docking analysis, the smallest mini protein, mp20, shared similar residues to that of native uricase that formed hydrogen bonds with uric acid and was chosen for further studies. Although purified recombinant mp20 did not exhibit uricase activity, it showed specific binding towards uric acid and evinced excellent thermotolerance and structural stability at temperatures ranging from 10°C to 100°C, emulating its natural origin. To explore the potential of mp20 as a bioreceptor in uric acid sensing, mp20 was encapsulated within zeolitic imidazolate framework-8 (mp20@ZIF-8) followed by the modification on rGO-screen printed electrode (rGO/SPCE) to maintain the structural stability. An irreversible anodic peak and increased semicircular arcs of the Nyquist plot with an increase of the analyte concentrations were observed by utilizing cyclic voltammetry and electrochemical impedance spectroscopy (EIS), suggesting the detection of uric acid occurred, which is based on substrate-mp20 interaction.

Computational modeling of protein-DNA complex structures has important implications in biomedical applications such as structure-based, computer aided drug design. A key step in developing methods for accurate modeling of protein-DNA complexes is similarity assessment between models and their reference complex structures. Existing methods primarily rely on distance-based metrics and generally do not consider important functional features of the complexes, such as interface hydrogen bonds that are critical to specific protein-DNA interactions. Here, we present a new scoring function, ComparePD, which takes interface hydrogen bond energy and strength into account besides the distance-based metrics for accurate similarity measure of protein-DNA complexes. ComparePD was tested on two datasets of computational models of protein-DNA complexes generated using docking (classified as easy, intermediate, and difficult cases) and homology modeling methods. The results were compared with PDDockQ, a modified version of DockQ tailored for protein-DNA complexes, as well as the metrics employed by the community-wide experiment CAPRI (Critical Assessment of PRedicted Interactions). We demonstrated that ComparePD provides an improved similarity measure over PDDockQ and the CAPRI classification method by considering both conformational similarity and functional importance of the complex interface. ComparePD identified more meaningful models as compared to PDDockQ for all the cases having different top models between ComparePD and PDDockQ except for one intermediate docking case.

The specific recognition of serum proteins by scavenger receptors is critical and fundamental in many biological processes. However, the underlying mechanism of scavenger receptor-serum protein interaction remains elusive. In this work, taking scavenger receptors class A1 (SR-A1) as an example, we systematically investigate its interaction with human serum albumin (HSA) at different states through a combination of molecular docking and all-atom molecular dynamics simulations. It is found that native HSA can moderately bind to collagen-like (CL) region or scavenger receptor cysteine-rich (SRCR) region, with both electrostatic (ELE) and van der Waals (VDW) interactions, playing important roles. After maleylation, the binding energy, particularly the ELE energy, between HSA and CL region is significantly enhanced, while the binding energy between HSA and SRCR region remains nearly unchanged. Additionally, we also observe that unfolding of the secondary structures in HSA leads to a larger contact surface area between denatured HSA and CL region, but has little impact on the HSA-SRCR region interaction. Therefore, similar to maleylated HSA, denatured HSA is also more likely to bind to the CL region of SR-A1.

Understanding the process of protein-RNA interaction is essential for structural biology. The thermodynamic process is an important part to uncover the protein-RNA interaction mechanism. The regulatory networks between protein and RNA in organisms are dominated by the binding or dissociation in the cells. Therefore, determining the binding affinity for protein-RNA complexes can help us to understand the regulation mechanism of protein-RNA interaction. Since it is time-consuming and labor-intensive to determine the binding affinity for protein-RNA complexes by experimental methods, it is necessary and urgent to develop computational methods to predict that. To develop a binding affinity prediction model, first we update the dataset of protein-RNA binding affinity benchmark (PRBAB), which includes 145 complexes now. Second, we extract the structural features based on complex structure, and then we analyze and select the representative structural features to train the regression model. Third, we random select the subset from the PRBAB2.0 to fit the protein-RNA binding affinity determined by experiment. In the end, we tested our model on the nonredundant PDBbind dataset, and the results showed that Pearson correlation coefficient r = .57 and RMSE = 2.51 kcal/mol. The Pearson correlation coefficient achieves 0.7 while removing 5 complex structures with modified residues/nucleotides and metal ions. While testing on ProNAB, the results showed that 71.60% of the prediction achieves Pearson correlation coefficient r = .61 and RMSE = 1.56 kcal/mol with experiment values.

TcXyn30A from Talaromyces cellulolyticus, which belongs to subfamily 7 of the glycoside hydrolase family 30 (GH30-7), releases xylose from the reducing end of xylan and xylooligosaccharides (XOSs), the so-called reducing-end xylose-releasing exoxylanase (ReX). In this study, the crystal structures of TcXyn30A with and without xylose at subsite +1 (the binding site of the xylose residue at the reducing end) were determined. This is the first report on the structure of ReX in the family GH30-7. TcXyn30A forms a dimer. The complex structure of TcXyn30A with xylose revealed that subsite +1 is located at the dimer interface. TcXyn30A recognizes xylose at subsite +1 composed of amino acid residues from each monomer and blocks substrate binding to subsite +2 by dimer formation. Thus, the dimeric conformation is responsible for ReX activity. The structural comparison between TcXyn30A and the homologous enzyme indicated that subsite -2 is composed of assembled three stacked Trp residues, Trp49, Trp333, and Trp334, allowing TcXyn30A to accommodate xylan and any branched XOSs decorated with a substitution such as α-1,2-linked 4-O-methyl-d-glucuronic acid or α-1,2- and/or -1,3-linked L-arabinofuranose. These findings provide an insight into the structural determinants for ReX activity of TcXyn30A.

The steep rise in protein sequences and structures has paved the way for bioinformatics approaches to predict residue-residue interactions in protein complexes. Multiple sequence alignments are commonly used in contact predictions to identify co-evolving residues. These contacts, however, often include false positives (FPs), which may impair their use to predict three dimensional structures of biomolecular complexes and affect the accuracy of the generated models. Previously, we have developed DisVis to identify FP in mass spectrometry cross-linking data. DisVis allows to assess the accessible interaction space between two proteins consistent with a set of distance restraints. Here, we investigate if a similar approach could be applied to co-evolution predicted contacts in order to improve their precision prior to using them for modeling. We analyze co-evolution contact predictions with DisVis for a set of 26 protein-protein complexes. The DisVis-reranked and the original co-evolution contacts are then used to model the complexes with our integrative docking software HADDOCK using different filtering scenarios. Our results show that HADDOCK is robust with respect to the precision of the predicted contacts due to the 50% random contact removal during docking and can enhance the quality of docking predictions when combined with DisVis filtering for low precision contact data. DisVis can thus have a beneficial effect on low quality data, but overall HADDOCK can accommodate FP restraints without negatively impacting the quality of the resulting models. Other more precision-sensitive docking protocols might, however, benefit from the increased precision of the predicted contacts after DisVis filtering.

Coproporphyrinogen oxidase (CPO) plays important role in the biosynthesis of heme by catalyzing the coproporphyrinogen III to coproporphyrin III. However, in earlier research, it was regarded as the protoporphyrinogen oxidase (PPO) because it can also catalyze the oxidation of protoporphyrinogen IX to protoporphyrin IX. Identification of the commonalities in CPO and PPO would help us to get a further understanding of the enzyme function. In this work, we explored the role of a non-conserved residue, Asp65 in Bacillus subtilis CPO (bsCPO), whose corresponding residues in PPO from various species are neutral or positive residue (arginine in human PPO or asparagine in tobacco PPO, etc.). We found that Asp65 performs its function by forming a polar interaction network with its surrounding residues in bsCPO, which is important for enzymatic activity. This polar network maintains the substrate binding chamber and stabilizes the micro-environment of the isoalloxazine ring of FAD for the substrate-FAD interaction. Both the comparison of the crystal structures of bsCPO with PPO and our previous work showed that a similar polar interaction network is also present in PPOs. The results confirmed our conjecture that non-conserved residues can form a conserved element to maintain the function of CPO or PPO.

Human islet amyloid polypeptide (hIAPP) is a naturally occurring, intrinsically disordered protein (IDP) whose abnormal aggregation into toxic soluble oligomers and insoluble amyloid fibrils is a pathological feature in type-2 diabetes. Rat IAPP (rIAPP) differs from hIAPP by only six amino acids yet has a reduced tendency to aggregate or form fibrils. The structures of the monomeric forms of IAPP are difficult to characterize due to their intrinsically disordered nature. Molecular dynamics simulations can provide a detailed characterization of the monomeric forms of rIAPP and hIAPP in near-physiological conditions. In this work, the conformational landscapes of rIAPP and hIAPP as a function of secondary structure content were predicted using well-tempered bias exchange metadynamics simulations. Several combinations of commonly used biomolecular force fields and water models were tested. The predicted conformational preferences of both rIAPP and hIAPP are typical of IDPs, exhibiting dominant random coil structures but showing a low propensity for transient α-helical conformations. Predicted nuclear magnetic resonance Cα chemical shifts reveal different preferences with each force field towards certain conformations, with AMBERff99SBnmr2/TIP4Pd showing the best agreement with the experiment. Comparisons of secondary structure content demonstrate residue-specific differences between hIAPP and rIAPP that may reflect their different aggregation propensities.

Violacein is a pigment synthesized by gram-negative bacteria with various biological activities such as antimicrobial, antiviral, and anticancer activities. VioD is a key oxygenase converting protodeoxyviolaceinic acid to protoviolaceinic acid in violacein biosynthesis. To elucidate the catalytic mechanism of VioD, here, we resolved two crystal structures of VioD, a binary complex structure containing VioD and a FAD and a ternary complex structure composed of VioD, a FAD and a 2-ethyl-1-hexanol (EHN). Structural analysis revealed a deep funnel like binding pocket with wide entrance, this pocket is positively charged. The EHN is located at the deep bottom of the binding pocket near isoalloxazine ring. Further docking simulation help us to propose the mechanism of the hydroxylation of the substrate catalyzed by VioD. Bioinformatic analysis suggested and emphasized the importance of the conserved residues involved in substrate binding. Our results provide a structural basis for the catalytic mechanism of VioD.

Cystathionine β-synthase (CBS) catalyzes the condensation of l-serine and l-homocysteine to give l-cystathionine in the transsulfuration pathway. Recently, a few O-acetylserine (l-OAS)-dependent CBSs (OCBSs) have been found in bacteria that can exclusively function with l-OAS. CBS from Toxoplasma gondii (TgCBS) can efficiently use both l-serine and l-OAS to form l-cystathionine. In this work, a series of site-specific variants substituting S84, Y160, and Y246 with hydrophobic residues found at the same positions in OCBSs was generated to explore the roles of the hydroxyl moieties of these residues as determinants of l-serine/l-OAS preference in TgCBS. We found that the S84A/Y160F/Y246V triple mutant behaved like an OCBS in terms of both substrate requirements, showing β-replacement activity only with l-OAS, and pH optimum, which is decreased by ~1 pH unit. Formation of a stable aminoacrylate upon reaction with l-serine is prevented by the triple mutation, indicating the importance of the H-bonds between the hydroxyl groups of Y160, Y246, and S84 with l-serine in formation of the intermediate. Analysis of the independent effect of each mutation on TgCBS activity and investigation of the protein-aminoacrylate complex structure allowed for the conclusion that the hydroxyl group of Y246 has a major, but not exclusive, role in controlling the l-serine preference by efficiently stabilizing its leaving group. These studies demonstrate that differences in substrate specificity of CBSs are controlled by natural variations in as few as three residue positions. A better understanding of substrate specificity in TgCBS will facilitate the design of new antimicrobial compounds.

Amyloid-based prions have simple structures, a wide phylogenetic distribution, and a plethora of functions in contemporary organisms, suggesting they may be an ancient phenomenon. However, this hypothesis has yet to be addressed with a systematic, computational, and experimental approach. Here we present a framework to help guide future experimental verification of candidate prions with conserved functions to understand their role in the early stages of evolution and potentially in the origins of life. We identified candidate prions in all high-quality proteomes available in UniProt computationally, assessed their phylogenomic distributions, and analyzed candidate-prion functional annotations. Of the 27 980 560 proteins scanned, 228 561 were identified as candidate prions (~0.82%). Among these candidates, there were 84 Gene Ontology (GO) terms conserved across the three domains of life. We found that candidate prions with a possible role in adaptation were particularly well-represented within this group. We discuss unifying features of candidate prions to elucidate the primeval roles of prions and their associated functions. Candidate prions annotated as transcription factors, DNA binding, and kinases are particularly well suited to generating diverse responses to changes in their environment and could allow for adaptation and population expansion into more diverse environments. We hypothesized that a relationship between these functions and candidate prions could be evolutionarily ancient, even if individual prion domains themselves are not evolutionarily conserved. Candidate prions annotated with these universally occurring functions potentially represent the oldest extant prions on Earth and are therefore excellent experimental targets.

In this perspective, we propose that the folding energy landscapes of model proteases including pepsin and alpha-lytic protease (αLP), which lack thermodynamic stability and fold on the order of months to millennia, respectively, should be viewed as not evolved and fundamentally distinct from their extended zymogen forms. These proteases have evolved to fold with prosegment domains and robustly self-assemble as expected. In this manner, general protein folding principles are strengthened. In support of our view, αLP and pepsin exhibit hallmarks of frustration associated with unevolved folding landscapes, such as non-cooperativity, memory effects, and substantial kinetic trapping. The evolutionary implications of this folding strategy are considered in detail. Direct applications of this folding strategy on enzyme design, finding new drug targets, and constructing tunable folding landscapes are also discussed. Together with certain proteases, growing examples of other folding "exceptions"-including protein fold switching, functional misfolding, and prevalent inability to refold-suggests a paradigm shift in which proteins may evolve to exist in a wide range of energy landscapes and structures traditionally thought to be avoided in nature.

The present state of understanding the mechanism of Spinocerebellar Ataxia-1, a fatal neurodegenerative disease linked to the protein Ataxin-1 (ATXN1), is baffled by a set of self-contradictory, and hence, inconclusive observations. This fallacy poses a bottleneck to the effective designing of curable drugs as the field is currently missing the specific druggable site. To understand the fundamentals of pathogenesis, we tried to decipher the intricacies of the extremely complicated landscape by targeting the relevant species that supposedly dictate the structure-function paradigm. The atomic-level description and characterization of the dynamism of the systems reveal the existence of structural polymorphism in all the leading stakeholders of the overall system. The very existence of conformational heterogeneity in every species creates numerous possible combinations of favorable interactions because of the variability in segmental cross-talks and hence claims its role in the choice of routes between functional activity and dysfunctional disease-causing aggregation. Despite this emergent configurational diversity, there is a common mode of operative intermolecular forces that dictates the extent of stability of all the multimeric complexes due to the localized population of a specific type of residue. The present research proposes a dynamic switch mechanism between aggregability and functional activity, based on the logical interpretation of the estimated variables, which is practically dictated by the effective concentration of the interacting species involved in the cell.

Bacterial fibrillar adhesins are specialized extracellular polypeptides that promote the attachment of bacteria to the surfaces of other cells or materials. Adhesin-mediated interactions are critical for the establishment and persistence of stable bacterial populations within diverse environmental niches and are important determinants of virulence. The fibronectin (Fn)-binding fibrillar adhesin CshA, and its paralogue CshB, play important roles in host colonization by the oral commensal and opportunistic pathogen Streptococcus gordonii. As paralogues are often catalysts for functional diversification, we have probed the early stages of structural and functional divergence in Csh proteins by determining the X-ray crystal structure of the CshB adhesive domain NR2 and characterizing its Fn-binding properties in vitro. Despite sharing a common fold, CshB_NR2 displays an ~1.7-fold reduction in Fn-binding affinity relative to CshA_NR2. This correlates with reduced electrostatic charge in the Fn-binding cleft. Complementary bioinformatic studies reveal that homologues of CshA/B_NR2 domains are widely distributed in both Gram-positive and Gram-negative bacteria, where they are found housed within functionally cryptic multi-domain polypeptides. Our findings are consistent with the classification of Csh adhesins and their relatives as members of the recently defined polymer adhesin domain (PAD) family of bacterial proteins.

Nuclear magnetic resonance (NMR) spectroscopy can reveal conformational states of a protein in physiological conditions. However, sparsely available NMR data for a protein with large degrees of freedom can introduce structural artifacts in the built models. Currently used state-of-the-art methods deriving protein structure and conformation from NMR deploy molecular dynamics (MD) coupled with simulated annealing for building models. We provide an alternate graph-based modeling approach, where we first build substructures from NMR-derived distance-geometry constraints combined in one shot to form the core structure. The remaining molecule with inadequate data is modeled using a hybrid approach respecting the observed distance-geometry constraints. One-shot structure building is rarely undertaken for large and sparse data systems, but our data-driven bottom-up approach makes this uniquely feasible by suitable partitioning of the problem. A detailed comparison of select models with state-of-art methods reveals differences in the secondary structure regions wherein the correctness of our models is confirmed by NMR data. Benchmarking of 106 protein-folds covering 38-282 length structures shows minimal experimental-constraint violations while conforming to other structure quality parameters such as the proper folding, steric clash, and torsion angle violation based on Ramachandran plot criteria. Comparative MD studies using select protein models from a state-of-art method and ours under identical experimental parameters reveal distinct conformational dynamics that could be attributed to protein structure-function. Our work is thus useful in building enhanced NMR-evidence-based models that encapsulate the contextual secondary and tertiary structure variations present during the experimentation and expand the scope of functional inference.

The prolonged circulation of the SARS-CoV-2 virus resulted in the emergence of several viral variants, with different spreading features. Moreover, the increased number of recovered and/or vaccinated people introduced a selective pressure toward variants able to evade the immune system, developed against the former viral versions. This process results in reinfections. Aiming to study the latter process, we first collected a large structural dataset of antibodies in complex with the original version of SARS-CoV-2 Spike protein. We characterized the peculiarities of such antibodies population with respect to a control dataset of antibody-protein complexes, highlighting some statistically significant differences between these two sets of antibodies. Thus, moving our attention to the Spike side of the complexes, we identify the Spike region most prone to interaction with antibodies, describing in detail also the energetic mechanisms used by antibodies to recognize different epitopes. In this framework, fast protocols able to assess the effect of novel mutations on the cohort of developed antibodies would help establish the impact of the variants on the population. Performing a molecular dynamics simulation of the trimeric form of the SARS-CoV-2 Spike protein for the wild type and two variants of concern, that is, the Delta and Omicron variants, we described the physicochemical features and the conformational changes experienced locally by the variants with respect to the original version. Hence, combining the dynamical information with the structural study on the antibody-spike dataset, we quantitatively explain why the Omicron variant has a higher capability of escaping the immune system than the Delta variant, due to the higher conformational variability of the most immunogenic regions. Overall, our results shed light on the molecular mechanism behind the different responses the SARS-CoV-2 variants display against the immune response induced by either vaccines or previous infections. Moreover, our analysis proposes an approach that can be easily extended to both other SARS-CoV-2 variants or different molecular systems.

RNA-binding proteins (RBPs) play significant roles in many biological life activities, many algorithms and tools are proposed to predict RBPs for researching biological mechanisms of RNA-protein binding sites. Deep learning algorithms based on traditional machine learning get better result for predicting RBPs. Recently, deep learning method fused with attention mechanism has attracted huge attention in many fields and gets competitive result. Thus, attention mechanism module may also improve model performance for predicting RNA-protein binding sites. In this study, we propose convolutional residual multi-head self-attention network (CRMSNet) that combines convolutional neural network (CNN), ResNet, and multi-head self-attention blocks to find RBPs for RNA sequence. First, CRMSNet incorporates convolutional neural networks, recurrent neural networks, and multi-head self-attention block. Second, CRMSNet can draw binding motif pictures from the convolutional layer parameters. Third, attention mechanism module combines the local and global RNA sequence information for capturing long sequence feature. CRMSNet gets competitive AUC (area under the receiver operating characteristic [ROC] curve) result in a large-scale dataset RBP-24. And CRMSNet experiment result is also compared with other state-of-the-art methods. The source code of our proposed CRMSNet method can be found in https://github.com/biomg/CRMSNet.

Atomic characterization of large nonfibrillar aggregates of amyloid polypeptides cannot be determined by experimental means. Starting from β-rich aggregates of Y and elongated topologies predicted by coarse-grained simulations and consisting of more than 100 Aβ16-22 peptides, we performed atomistic molecular dynamics (MD), replica exchange with solute scaling (REST2), and umbrella sampling simulations using the CHARMM36m force field in explicit solvent. Here, we explored the dynamics within 3 μs, the free energy landscape, and the potential of mean force associated with either the unbinding of one single peptide in different configurations within the aggregate or fragmentation events of a large number of peptides. Within the time scale of MD and REST2, we find that the aggregates experience slow global conformational plasticity, and remain essentially random coil though we observe slow beta-strand structuring with a dominance of antiparallel beta-sheets over parallel beta-sheets. Enhanced REST2 simulation is able to capture fragmentation events, and the free energy of fragmentation of a large block of peptides is found to be similar to the free energy associated with fibril depolymerization by one chain for longer Aβ sequences.

Forkhead box protein P3 (FOXP3) is known to orchestrate the development and maintenance of T regulatory cells, a cell population specialized in immune suppression and peripheral immune tolerance. FOXP3 activity is fine-tuned through its interaction with several protein-binding partners. By using IntAct database, we retrieved three physical binary interactors: E3 ubiquitin-protein ligase CHIP, Zfp-90, and nuclear receptor ROR-α. Coevolution clusters between FOXP3 and its interactors were identified with the use of iBIS2 algorithm, the iterative version of BIS/BIS2. Most of the coevolving pairs came from some species of monotremes and marsupials, as well as from a group of bats, thus suggesting that protein interactions of FOXP3 with its partners may be changed and/or modulated during mammalian speciation. Furthermore, our analysis would suggest the occurrence of a determinant role of FOXP3 in suppressing pregnancy alloreactions in placental mammals. Similarly, FOXP3, through its interaction with different protein interaction mechanisms, would explain the unique control of inflammatory response to infections in bats. By identifying several inter-protein clusters between the different protein pairs, our findings may provide a guide for new therapeutic approaches to modulate T regulatory suppression and/or enhance immune tolerance.

Thanks to the considerable research which has been undertaken in the last few years to improve our understanding of the biology and mechanism of action of SARS-CoV-2, we know how the virus uses its surface spike protein to infect host cells. The transmembrane prosthesis, serine 2 (TMPRSS2) protein, located on the surface of human cells, recognizes the cleavage site in the spike protein, leading to the release of the fusion peptide and entry of the virus into the host cells. Because of its role, TMPRSS2 has been proposed as a drug target to prevent infection by the virus. In this study, we aim to increase our understanding of TMPRSS2 using long scale microsecond atomistic molecular dynamics simulations, focusing on the conformational changes over time. The comparison between simulations conducted on the protein in the native (apo) and inhibited form (holo), has shown that in the holo form the inhibitor stabilizes the catalytic site and induces rearrangements in the extracellular domain of the protein. In turn, it leads to the formation of a new cavity in the vicinity of the ligand binding pocket that is stable in the microsecond time scale. Given the low specificity of known protease inhibitors, these findings suggest a new potential drug target site that can be used to improve TMPRSS2 specific recognition by newly designed inhibitors.

Trans-sialidase (TS) superfamily of proteins comprises eight subgroups, being the proteins of Group-I (TS-GI) promising immunogens in vaccine approaches against Trypanosoma cruzi. Strikingly, TS-GI antigenic variability among parasite lineages and their influence on vaccine development has not been previously analyzed. Here, a search in GenBank detects 49 TS-GI indexed sequences, whereas the main infecting human different parasite discrete typing units (DTU) are represented. In silico comparison among these sequences indicate that they share an identity above 92%. Moreover, the antigenic regions (T-cell and B-cell epitopes) are conserved in most sequences or present amino acid substitutions that scarcely may alter the antigenicity. Additionally, since the generic term TS is usually used to refer to different immunogens of this broad family, a further in silico analysis of the TS-GI-derived fragments tested in preclinical vaccines was done to determine the coverage and identity among them, showing that overall amino acid identity of vaccine immunogens is high, but the segment coverage varies widely. Accordingly, strong H-2K, H-2I, and B-cell epitopes are dissimilarly represented among vaccine TS-derived fragments depending on the extension of the TG-GI sequence used. Moreover, bioinformatic analysis detected a set of 150 T-cell strong epitopes among the DTU-indexed sequences that strongly bind human HLA-I supertypes. In all currently reported experimental vaccines based on TS-GI fragments, mapping these 150 epitopes showed that they are moderately represented. However, despite vaccine epitopes do not present all the substitutions observed in the DTUs, these regions of the proteins are equally recognized by the same HLAs.  Interestingly, the predictions regarding global and South American population coverage estimated in these 150 epitopes are similar to the estimations in experimental vaccines when the complete sequence of TS-GI is used as an antigen. In silico prediction also shows that a number of these MHC-I restricted T-cell strong epitopes could be also cross-recognized by HLA-I supertypes and H-2Kb or H-2Kd backgrounds, indicating that these mice may be used to improve and facilitate the development of new TS-based vaccines and suggesting an immunogenic and protective potential in humans. Further molecular docking analyses were performed to strengthen these results. Taken together, different strategies that would cover more or eventually fully of these T-cell and also B-cell epitopes to reach a high level of coverage are considered.

Protein glycation can result in the formation of advanced glycation end products (AGEs), which pose a potential health risk due to their association with diabetic complications. Natural products are a source of drugs discovery and the search for potential natural inhibitors of AGEs is of great significance. Glucosinolates (GSLs) mainly from cruciferous plants have potential antioxidant, anti-inflammatory, and anti-glycation activities. In this study, the inhibitory activity of GSLs on bovine serum albumin (BSA) along with its mechanism was investigated by virtual screening and various computational simulation techniques. Virtual screening revealed that 174 GSLs were screened using Maestro based on the glide score and 89% of the compounds were found to have potential anti-glycation ability with the docking scores less than -5 kcal/mol. Molecular docking showed that the top 10 GSLs were bound to the IIA structural domain of BSA. Among them, glucohesperin (1) and 2-hydroxyethyl glucosinolate (2) had the lowest docking scores of -9.428 and -9.333 kcal/mol, respectively, reflecting their good binding affinity. Molecular dynamics simulations of 1 (ΔG = -43.46 kcal/mol) and 2 (ΔG = -43.71 kcal/mol) revealed that the complexes of these two compounds with proteins had good stability. Further binding site analysis suggested that the mechanism of inhibition of protein glycation by these two active ingredients might be through competitive hydrogen bonding to maintain the structural integrity of the protein, thus inhibiting glycation reaction. Moreover, the ADMET values and CYP450 metabolism prediction data were within the recommended values. Therefore, it can be concluded that 1 and 2 may act as potential anti-glycation agents.

The increase of antibiotic-resistant bacterial pathogens has created challenges in treatment and warranted the design of antibiotics against comparatively less exploited targets. The peptidoglycan (PG) biosynthesis delineates unique pathways for the design and development of a novel class of drugs. Mur ligases are an essential component of bacterial cell wall synthesis that play a pivotal role in PG biosynthesis to maintain internal osmotic pressure and cell shape. Inhibition of these enzymes can interrupt bacterial replication and hence, form attractive targets for drug discovery. In the present work, we focused on the PG biosynthesis pathway enzyme, UDP-N-acetylpyruvylglucosamine reductase, from Salmonella enterica serovar Typhi (stMurB). Biophysical characterization of purified StMurB was performed to gauge the molecular interactions and estimate thermodynamic stability for determination of attributes for possible therapeutic intervention. The thermal melting profile of MurB was monitored by circular dichroism and validated through differential scanning calorimetry experiment. Frequently used chemical denaturants, GdmCl and urea, were employed to study the chemical-induced denaturation of stMurB. In the search for natural compound-based inhibitors, against this important drug target, an in silico virtual screening based investigation was conducted with modeled stMurB structure. The three top hits (quercetin, berberine, and scopoletin) returned were validated for complex stability through molecular dynamics simulation. Further, fluorescence binding studies were undertaken for the selected natural compounds with stMurB alone and with NADPH bound form. The compounds scopoletin and berberine, displayed lesser binding to stMurB whereas quercetin exhibited stronger binding affinity than NADPH. This study suggests that quercetin can be evolved as an inhibitor of stMurB enzyme.

σ factors are essential parts of bacterial RNA polymerase (RNAP) as they allow to recognize promotor sequences and initiate transcription. Domain 1.1 of vegetative σ factors occupies the primary channel of RNAP and also prevents binding of the σ factor to promoter DNA alone. Here, we show that domain 1.1 of Bacillus subtilis σA exists in more structurally distinct variants in dynamic equilibrium. The major conformation at room temperature is represented by a previously reported well-folded structure solved by nuclear magnetic resonance (NMR), but 4% of the protein molecules are present in a less thermodynamically favorable state. We show that this population increases with temperature and we predict its significant elevation at higher but still biologically relevant temperatures. We characterized the minor state of the domain 1.1 using specialized methods of NMR. We found that, in contrast to the major state, the detected minor state is partially unfolded. Its propensity to form secondary structure elements is especially decreased for the first and third α helices, while the second α helix and β strand close to the C-terminus are more stable. We also analyzed thermal unfolding of the domain 1.1 and performed functional experiments with full length σA and its shortened version lacking domain 1.1 ( σA_Δ1.1 ). The results revealed that while full length σA increases transcription activity of RNAP with increasing temperature, transcription with σA_Δ1.1 remains constant. In summary, this study reveals conformational dynamics of domain 1.1 and provides a basis for studies of its interaction with RNAP and effects on transcription regulation.

The rapid adaptation of SARS-CoV-2 within the host species and the increased viral transmission triggered the evolution of different SARS-CoV-2 variants. Though numerous monoclonal antibodies (mAbs) have been identified as prophylactic therapy for SARS-CoV-2, the ongoing surge in the number of SARS-CoV-2 infections shows the importance of understanding the mutations in the spike and developing novel vaccine strategies to target all variants. Here, we report the map of experimentally validated 74 SARS-CoV-2 neutralizing mAb binding epitopes of all variants. The majority (87.84%) of the potent neutralizing epitopes are localized to the receptor-binding domain (RBD) and overlap with each other, whereas limited (12.16%) epitopes are found in the N-terminal domain (NTD). Notably, 69 out of 74 mAb targets have at least one mutation at the epitope sites. The potent epitopes found in the RBD show higher mutations (4-10aa) compared to lower or modest neutralizing antibodies, suggesting that these epitopes might co-evolve with the immune pressure. The current study shows the importance of determining the critical mutations at the antibody recognition epitopes, leading to the development of broadly reactive immunogens targeting multiple SARS-CoV-2 variants. Further, vaccines inducing both humoral and cell-mediated immune responses might prevent the escape of SARS-CoV-2 variants from neutralizing antibodies.

Chemotaxis is a fundamental process whereby bacteria seek out nutrient sources and avoid harmful chemicals. For the symbiotic soil bacterium Sinorhizobium meliloti, the chemotaxis system also plays an essential role in the interaction with its legume host. The chemotactic signaling cascade is initiated through interactions of an attractant or repellent compound with chemoreceptors or methyl-accepting chemotaxis proteins (MCPs). S. meliloti possesses eight chemoreceptors to mediate chemotaxis. Six of these receptors are transmembrane proteins with periplasmic ligand-binding domains (LBDs). The specific functions of McpW and McpZ are still unknown. Here, we report the crystal structure of the periplasmic domain of McpZ (McpZPD) at 2.7 Å resolution. McpZPD assumes a novel fold consisting of three concatenated four-helix bundle modules. Through phylogenetic analyses, we discovered that this helical tri-modular domain fold arose within the Rhizobiaceae family and is still evolving rapidly. The structure, offering a rare view of a ligand-free dimeric MCP-LBD, reveals a novel dimerization interface. Molecular dynamics calculations suggest ligand binding will induce conformational changes that result in large horizontal helix movements within the membrane-proximal domains of the McpZPD dimer that are accompanied by a 5 Å vertical shift of the terminal helix toward the inner cell membrane. These results suggest a mechanism of transmembrane signaling for this family of MCPs that entails both piston-type and scissoring movements. The predicted movements terminate in a conformation that closely mirrors those observed in related ligand-bound MCP-LBDs.

This paper aims to understand the binding strategies of a nanobody-protein pair by studying known complexes. Rigid body protein-ligand docking programs produce several complexes, called decoys, which are good candidates with high scores of shape complementarity, electrostatic interactions, desolvation, buried surface area, and Lennard-Jones potentials. However, the decoy that corresponds to the native structure is not known. We studied 36 nanobody-protein complexes from the single domain antibody database, sd-Ab DB, http://www.sdab-db.ca/. For each structure, a large number of decoys are generated using the Fast Fourier Transform algorithm of the software ZDOCK. The decoys were ranked according to their target protein-nanobody interaction energies, calculated by using the Dreiding Force Field, with rank 1 having the lowest interaction energy. Out of 36 protein data bank (PDB) structures, 25 true structures were predicted as rank 1. Eleven of the remaining structures required Ångstrom size rigid body translations of the nanobody relative to the protein to match the given PDB structure. After the translation, the Dreiding interaction (DI) energies of all complexes decreased and became rank 1. In one case, rigid body rotations as well as translations of the nanobody were required for matching the crystal structure. We used a Monte Carlo algorithm that randomly translates and rotates the nanobody of a decoy and calculates the DI energy. Results show that rigid body translations and the DI energy are sufficient for determining the correct binding location and pose of ZDOCK created decoys. A survey of the sd-Ab DB showed that each nanobody makes at least one salt bridge with its partner protein, indicating that salt bridge formation is an essential strategy in nanobody-protein recognition. Based on the analysis of the 36 crystal structures and evidence from existing literature, we propose a set of principles that could be used in the design of nanobodies.

Here, we present the crystal structure of the synthetic peptide KE1, which contains four K-coil heptads separated in the middle by the QFLMLMF heptad. The structure determination reveals the presence of a canonical parallel three stranded coiled coil. The geometric characteristics of this structure are compared with other coiled coils with the same topology. Furthermore, for this topology, the analysis of the propensity of the single amino acid to occupy a specific position in the heptad sequence is reported. A number of viral proteins use specialized coiled coil tail needles to inject their genetic material into the host cells. The simplicity and regularity of the coiled coil arrangement made it an attractive system for de novo design of key molecules in drug delivery systems, vaccines, and therapeutics.

Cervical cancer is the primary cause of mortality among women in developing countries. Preventing cervical cancer is partially possible through early vaccination against the human papillomavirus, the most common cause of the disease. Nevertheless, it is imperative to understand the genetics of the disease progression to develop new therapeutic strategies. The present study aims to identify potential genes and associated pathways associated with cervical squamous cell carcinoma progression. We used an integrative approach by combining differential expression analysis, network biology, and functional enrichment analysis with survival analysis. In the present study, differential expression analysis of the microarray-based gene expression profiles of cervical cancer resulted in identifying a total of 544 significantly differentially expressed genes (DEGs). Further, centrality and network vulnerability analysis of the protein-protein interaction network (PPIN) and not well documented in cervical cancer, resulted in seven proteins (FN1, MCM5, TRIP13, KIF11, TTK, CDC45, and BUB1B), in which four proteins were vulnerable. These genes are mostly enriched in biological processes of cell division, mitotic nuclear division, cell cycle checkpoint, and cell proliferation in gene ontology analysis. The KEGG pathway enrichment analysis of the proteins lists them as mainly associated with the cell cycle. In the survival analysis, it was found that the genes MCM5, FN1, KIF11, and CDC45 were statistically significant prognostic factors for cervical cancer. The outcome of the current study identifies and explores the key role of the candidate genes involved in the progression of cervical cancer.

The human C14orf166 protein, also known as RNA transcription, translation, and transport factor, shows positive modulatory activity on the cellular RNA polymerase II enzyme. This protein is a component of the tRNA-splicing ligase complex and is involved in RNA metabolism. It also functions in the nucleo-cytoplasmic transport of RNA molecules. The C14orf166 protein has been reported to be associated with some types of cancer. It has been shown that the C14orf166 protein binds to the influenza A virus RNA polymerase PA subunit and has a stimulating effect on viral replication. In this study, candidate interactor proteins for influenza A virus PA protein were screened with a Y2H assay using HEK293 Matchmaker cDNA. The C14orf166 protein fragments in different sizes were found to interact with the PA. The three-dimensional structures of the viral PA and C14orf166 proteins interacting with the PA were generated using the I-TASSER algorithm. The interaction models between these proteins were predicted with the ClusPro protein docking algorithm and analyzed with PyMol software. The results revealed that the carboxy-terminal end of the C14orf166 protein is involved in this interaction, and it is highly possible that it binds to the carboxy-terminal of the PA protein. Although amino acid residues in the interaction area of the PA protein with the C14orf166 showed distribution from 450th to 700th position, the intense interaction region was revealed to be at amino acid positions 610-630.

Mastoparan B (MP-B) is an amphiphilic peptide with a potent antimicrobial activity against most Gram-negative bacteria. However, there is little information available on the inhibition of the Acinetobacter baumannii resistance-nodulation-cell-division (RND) efflux pump using this antimicrobial peptide. Here, we carried out a series of in-silico experiments to find the mechanisms underlying the anti-efflux activity of MP-B using a multi-drug resistant (MDR) strain of A. baumannii (AB). According to our findings, MP-B demonstrated a potent antibacterial activity against an MDR-AB (minimum inhibitory concentration [MIC] = 1 μg/mL) followed by a 20-fold reduction in the adeB gene expression in the presence of sub-MIC of this peptide. Using Groningen Machine for Chemicals Simulation (GROMACS) via PyMOL Graphical User Interface (GUI), (we observed that, the AdeB transporter had conserved helix-turn-helix regions and a tight pore rich in Phe and Ala residues. To understand how inhibition of the AdeB is achieved, we generated 20 apo-MP-B poses using the InterPep and SiteMap tools. The high-quality model was created by homology modeling and used for docking via AutoDock/Vina to identify the MP-B binding sites. We established that the most apo-MP-B formed H-bonds to the backbone of five amino acids in the Helix-5. As a result, the dihedral angles of the involved amino acids shift by 9.0-9.6 Ǻ, causing a change in the conformation of the AdeB protein. This led to helix conformation stereoisomerization and block the AdeB activity. MP-B presumably has dual mechanisms. (1) It blocks the AdeB transporter by changing its conformation. (2) MP-B influences the adeB gene expression by binding to G-protein which laterally controls efflux regulators like MarA, RamA, SoxS, and Rob proteins.