The Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) is the virus responsible for the COVID-19 pandemic. COVID-19 continues to cause millions of deaths globally in part due to immune-evading mutations. SARS-CoV-2 main protease (Mpro) is an important enzyme for viral replication and potentially an effective drug target. Mutations affect the dynamics of enzymes and thereby their activity and ability to bind ligands. Here, we use kinematic flexibility analysis (KFA) to identify how mutations and ligand binding changes the conformational flexibility of Mpro. KFA decomposes macromolecules into regions of different flexibility near-instantly from a static structure, allowing conformational dynamics analysis at scale. Altogether, we analyzed 47 mutation sites across 69 Mpro-ligand complexes resulting in more than 3300 different structures which includes 69 mutated structures with all 47 sites mutated simultaneously and 3243 single residue mutated structures. We found that mutations generally increased the conformational flexibility of the protein. Understanding the impact of mutations on the flexibility of Mpro is essential for identifying potential drug targets in the treatment of SARS-CoV-2. Further studies in this area can offer valuable insights into the mechanisms of molecular recognition.

Parasporins of Bacillus thuringiensis (Bt) exhibit specific toxicity to cancer cells. PCR based mining has identified apoptosis inducing parasporin in KAU41 Bt isolate from the Western Ghats of India. The study aimed to clone and overexpress the parasporin of native KAU41 Bt isolate for determining structural and functional characteristics of the protein. Parasporin gene was cloned in pGEM-T, sequenced, sub-cloned in pET30+ and overexpressed in Escherichia coli. The expressed protein was characterized by SDS-PAGE and in silico methods. Cytotoxicity of cleaved peptide was assessed by MTT assay. SDS-PAGE displayed a 31 kDa protein (rp-KAU41) overexpressed. Upon proteinase K digestion, the protein was cleaved into 29 kDa peptide which was found to be cytotoxic to HeLa cells. The protein has a deduced sequence of 267 amino acids with β-strands folding pattern of crystal protein. Even though rp-KAU41 shared a 99.15% identity to chain-A of non-toxic crystal protein, it only showed a less similarity to the existing parasporins like PS4 (38%) and PS5 (24%) in UPGMA analysis, emphasizing the novelty of rp-KAU41. The protein is predicted to have more similarity to the pore forming toxins of Aerolysin superfamily and an additional loop in rp-KAU41 may be contributing towards its cytotoxicity. The molecular docking with caspase 3 resulted in higher Z dock and Z rank score substantiating its role in the activation of intrinsic pathway of apoptosis. The recombinant parasporin protein, rp-KAU41 is presumed to belong to the Aerolysin superfamily. An interaction with caspase 3 substantiates its role in activating the intrinsic pathway of apoptosis in cancer cells.

Capping protein (CP) binds to the barbed end of an actin-filament and inhibits its elongation. CARMIL binds CP and dissociates it from the barbed end of the actin-filament. The binding of CARMIL peptide alters the flexibility of CP, which is considered to facilitate the dissociation. Twinfilin also binds to CP through its C-terminal tail. The complex structures of the CP/twinfilin-tail (TW-tail) peptide indicate that the binding sites of CARMIL and TW-tail overlap. However, TW-tail binding does not facilitate the dissociation of CP from the barbed end. We extensively investigated the flexibilities of CP in the CP/TW-tail or CP/CARMIL complexes using an elastic network model and concluded that TW-tail binding does not alter the flexibility of CP. Our extensive analysis also highlighted that the strong contacts of peptides with the two domains of CP, that is, the CP-L and CP-S domains, are key to changing the flexibilities of CP. CARMIL peptides can interact strongly with both of the domains, while TW-tail peptides exclusively interact with the CP-S domain because the binding site of TW-tail on CP relatively shifts to the CP-S domain compared with that of CP/CARMIL. This result supports our hypothesis that the dissociation of CP from the barbed end is regulated by the flexibility of CP.

Leucine and Isoleucine are two amino acids that differ only by the positioning of one methyl group. This small difference can have important consequences in α-helices, as the β-branching of Ile results in helix destabilization. We set out to investigate whether there are general trends for the occurrences of Leu and Ile residues in the structures and sequences of class A GPCRs (G protein-coupled receptors). GPCRs are integral membrane proteins in which α-helices span the plasma membrane seven times and which play a crucial role in signal transmission. We found that Leu side chains are generally more exposed at the protein surface than Ile side chains. We explored whether this difference might be attributed to different functions of the two amino acids and tested if Leu tunes the hydrophobicity of the transmembrane domain based on the Wimley-White whole-residue hydrophobicity scales. Leu content decreases the variation in hydropathy between receptors and correlates with the non-Leu receptor hydropathy. Both measures indicate that hydropathy is tuned by Leu. To test this idea further, we generated protein sequences with random amino acid compositions using a simple numerical model, in which hydropathy was tuned by adjusting the number of Leu residues. The model was able to replicate the observations made with class A GPCR sequences. We speculate that the hydropathy of transmembrane domains of class A GPCRs is tuned by Leu (and to some lesser degree by Lys and Val) to facilitate correct insertion into membranes and/or to stably anchor the receptors within membranes.

Glioma is a type of tumor that starts in the glial cells of the brain or spine. Since the 1800s, when the disease was first named, its survival rates have always been unsatisfactory. Despite great advances in molecular biology and traditional treatment methods, many questions regarding cancer occurrence and the underlying mechanism remain to be answered. In this study, we assessed the protein structural features of 20 oncogenes and 20 anti-oncogenes via protein structure and dynamic analysis methods and 3D structural and systematic analyses of the structure-function relationships of proteins. All of these results directly indicate that unfavorable group proteins show more complex structures than favorable group proteins. As the tumor cell microenvironment changes, the balance of oncogene-related and anti-oncogene-related proteins is disrupted, and most of the structures of the two groups of proteins will be disrupted. However, more unfavorable group proteins will maintain and refold to achieve their correct shape faster and perform their functions more quickly than favorable group proteins, and the former thus support cancer development. We hope that these analyses will help promote mechanistic research and the development of new treatments for glioma.

We present an in-depth analysis of selected CASP15 targets, focusing on their biological and functional significance. The authors of the structures identify and discuss key protein features and evaluate how effectively these aspects were captured in the submitted predictions. While the overall ability to predict three-dimensional protein structures continues to impress, reproducing uncommon features not previously observed in experimental structures is still a challenge. Furthermore, instances with conformational flexibility and large multimeric complexes highlight the need for novel scoring strategies to better emphasize biologically relevant structural regions. Looking ahead, closer integration of computational and experimental techniques will play a key role in determining the next challenges to be unraveled in the field of structural molecular biology.

The human predictor team PEZYFoldings got first place with the assessor's formulae (3rd place with Global Distance Test Total Score [GDT-TS]) in the single-domain category and 10th place in the multimer category in Critical Assessment of Structure Prediction 15. In this paper, I describe the exact method used by PEZYFoldings in the competition. As AlphaFold2 and AlphaFold-Multimer, developed by DeepMind, were state-of-the-art structure prediction tools, it was assumed that enhancing the input and output of the tools was an effective strategy to obtain the highest accuracy for structure prediction. Therefore, I used additional tools and databases to collect evolutionarily related sequences and introduced a deep-learning-based model in the refinement step. In addition to these modifications, manual interventions were performed to address various tasks. Detailed analyses were performed after the competition to identify the main contributors to performance. Comparing the number of evolutionarily related sequences I used with those of the other teams that provided AlphaFold2's baseline predictions revealed that an extensive sequence similarity search was one of the main contributors. Nonetheless, there were specific targets for which I could not identify any evolutionarily related sequences, resulting in my inability to construct accurate structures for these targets. Notably, I noticed that I had gained large Z-scores with the subunits of H1137, for which I performed manual domain parsing considering the interfaces between the subunits. This finding implies that the manual intervention contributed to my performance. The influence of the refinement model on the accuracy of structure prediction was minimal. I could have predicted structures with a similar level of accuracy without employing the refinement model. However, from the perspective of accuracy self-estimate, many structures demonstrated improvement after refinement. This improvement likely had a substantial influence on improving my position in the assessor's formulae rankings. These results highlight the opportunities for improvement in (1) multimer prediction, (2) building of larger and more diverse databases, and (3) developing tools to predict structures from primary sequences alone. In addition, transferring the manual intervention process to automation is a future concern.

We present VoroIF-GNN (Voronoi InterFace Graph Neural Network), a novel method for assessing inter-subunit interfaces in a structural model of a protein-protein complex, relying solely on the input structure without any additional information. Given a multimeric protein structural model, we derive interface contacts from the Voronoi tessellation of atomic balls, construct a graph of those contacts, and predict the accuracy of every contact using an attention-based GNN. The contact-level predictions are then summarized to produce whole interface-level scores. VoroIF-GNN was blindly tested for its ability to estimate the accuracy of protein complexes during CASP15 and showed strong performance in selecting the best multimeric model out of many. The method implementation is freely available at https://kliment-olechnovic.github.io/voronota/expansion_js/.

The first RNA category of the Critical Assessment of Techniques for Structure Prediction competition was only made possible because of the scientists who provided experimental structures to challenge the predictors. In this article, these scientists offer a unique and valuable analysis of both the successes and areas for improvement in the predicted models. All 10 RNA-only targets yielded predictions topologically similar to experimentally determined structures. For one target, experimentalists were able to phase their x-ray diffraction data by molecular replacement, showing a potential application of structure predictions for RNA structural biologists. Recommended areas for improvement include: enhancing the accuracy in local interaction predictions and increased consideration of the experimental conditions such as multimerization, structure determination method, and time along folding pathways. The prediction of RNA-protein complexes remains the most significant challenge. Finally, given the intrinsic flexibility of many RNAs, we propose the consideration of ensemble models.

Most proteins found in the outer membrane of gram-negative bacteria share a common domain: the transmembrane β-barrel. These outer membrane β-barrels (OMBBs) occur in multiple sizes and different families with a wide range of functions evolved independently by amplification from a pool of homologous ancestral ββ-hairpins. This is part of the reason why predicting their three-dimensional (3D) structure, especially by homology modeling, is a major challenge. Recently, DeepMind's AlphaFold v2 (AF2) became the first structure prediction method to reach close-to-experimental atomic accuracy in CASP even for difficult targets. However, membrane proteins, especially OMBBs, were not abundant during their training, raising the question of how accurate the predictions are for these families. In this study, we assessed the performance of AF2 in the prediction of OMBBs and OMBB-like folds of various topologies using an in-house-developed tool for the analysis of OMBB 3D structures, and barrOs. In agreement with previous studies on other membrane protein classes, our results indicate that AF2 predicts transmembrane β-barrel structures at high accuracy independently of the use of templates, even for novel topologies absent from the training set. These results provide confidence on the models generated by AF2 and open the door to the structural elucidation of novel transmembrane β-barrel topologies identified in high-throughput OMBB annotation studies or designed de novo.

Protein-carbohydrate interactions play a crucial role in mediating several biomolecular recognition events. We attempt to unravel its intricacies by understanding how carbohydrate-binding proteins interpret the glycan code. We aim to decipher lectin-mediated recognition in the endoplasmic reticulum (ER), which plays a crucial role in ER-mediated quality control (ER-QC). The ER-QC functions in three phases-protein folding, transport, and degradation. Altered protein QC leads to ER-related storage disorders. Cargo transport proteins-Ergic53 and Vip36-necessary for maintaining cellular homeostasis-are our primary focus. They recognize monoglucosylated/high mannose N-glycans on the folded glycoproteins. This article reports on the first dynamic investigation of the ER cargo lectins in complex with the high mannose glycans using an advanced sampling technique-replica exchange molecular dynamics to decipher the inherent conformational heterogeneity and the binding mechanism. The study involves simulations for the proteins complexed with three high mannose glycans-Man8B, Man9, and mono-glucosylated glycan. The recognition process is captured using MD simulations to achieve mechanistic insights and characterize the dynamics of glycans in their native and bound states via dihedral angle analysis. Results indicate that the flipped conformation of the glycans was crucial in differentiating their interaction with the proteins. Similar conformers of the glycans are preferred for Ergic53 and Vip36 in their glycan recognition events. Ergic53 preferred Man8B while it was Man9 for Vip36, in coherence with the previous experimental reports. These simulations provide a computational microscopic purview of the mechanism at both spatial and temporal scales. The results correlate with the published experimental data on the specificities of these lectins.

Fatty acid binding proteins (FABPs) are responsible for the long-chain fatty acids (FAs) transport inside the cell. However, despite the years, since their structure is known and the many studies published, there is no definitive answer about the stages of the lipid entry-exit mechanism. Their structure forms a β -barrel of 10 anti-parallel strands with a cap in a helix-turn-helix motif, and there is some consensus on the role of the so-called portal region, involving the second α -helix from the cap ( α 2), β C- β D, and β E- β F turns in FAs exchange. To test the idea of a lid that opens, we performed a soaking experiment on an h-FABP crystal in which the cap is part of the packing contacts, and its movement is strongly restricted. Even in these conditions, we observed the replacement of palmitic acid by 2-Bromohexadecanoic acid (Br-palmitic acid). Our MD simulations reveal a two-step lipid entry process: (i) The travel of the lipid head through the cavity in the order of tens of nanoseconds, and (ii) The accommodation of its hydrophobic tail in hundreds to thousands of nanoseconds. We observed this even in the cases in which the FAs enter the cavity by their tail. During this process, the FAs do not follow a single trajectory, but multiple ones through which they get into the protein cavity. Thanks to the complementary views between experiment and simulation, we can give an approach to a mechanistic view of the exchange process.

Protein-protein association events are involved in many physiological and pathological processes. Cataract disease is a pathology that manifests protein aggregation of crystallins. β-Crystallins are present in a high proportion in the eye lens. Therefore, the structural study of the dimerization properties of crystallins can shed light on the first stages of protein aggregation. In the present work, we examine the protein-protein association profiles of the human βB2-crystallin by employing extensive coarse-grained molecular dynamics (CG-MD) and the Markov state analysis. Interestingly, our results clearly show important changes in the protein dimerization kinetics between wt-HβB2C and the deamidated systems. The two systems show dimeric conformations. However, the association and dissociation rates are very different. Our results show that the deamidated system can associate faster and dissociate slower than the wt- HβB2C. The deamidated system is in a slightly opened conformation with the Greek-key motifs well folded, suggesting that a complete unfolding of the protein is not required for aggregation. Our results describe the first stages of crystallin aggregation due to post-translational modifications.

319-44 is a human monoclonal antibody capable of passively protecting mice against tick-mediated infection with Borreliella burgdorferi, the bacterial genospecies responsible for Lyme disease in North America. In vitro, 319-44 has complement-dependent borreliacidal activity and spirochete agglutinating properties. Here, we report the 2.2 Å-resolution crystal structure of 319-44 Fab fragments in complex with Outer surface protein A (OspA), the ~30 kDa lipoprotein that was the basis of the first-generation Lyme disease vaccine approved in the United States. The 319-44 epitope is focused on OspA β-strands 19, 20, and 21, and the loops between β-strands 16-17, 18-19, and 20-21. Contact with loop 20-21 explains competition with LA-2, the murine monoclonal antibody used to estimate serum borreliacidal activities in the first-generation Lyme disease vaccine clinical trials. A high-resolution B-cell epitope map of OspA will accelerate structure-based design of second generation OspA-based vaccines.

The hypoxia-inducible factor (HIF) prolyl-hydroxylases (human PHD1-3) catalyze prolyl hydroxylation in oxygen-dependent degradation (ODD) domains of HIFα isoforms, modifications that signal for HIFα proteasomal degradation in an oxygen-dependent manner. PHD inhibitors are used for treatment of anemia in kidney disease. Increased erythropoietin (EPO) in patients with familial/idiopathic erythrocytosis and pulmonary hypertension is associated with mutations in EGLN1 (PHD2) and EPAS1 (HIF2α); a drug inhibiting HIF2α activity is used for clear cell renal cell carcinoma (ccRCC) treatment. We report crystal structures of PHD2 complexed with the C-terminal HIF2α-ODD in the presence of its 2-oxoglutarate cosubstrate or N-oxalylglycine inhibitor. Combined with the reported PHD2.HIFα-ODD structures and biochemical studies, the results inform on the different PHD.HIFα-ODD binding modes and the potential effects of clinically observed mutations in HIFα and PHD2 genes. They may help enable new therapeutic avenues, including PHD isoform-selective inhibitors and sequestration of HIF2α by the PHDs for ccRCC treatment.