Computationally modeling how mutations affect protein-protein binding not only helps uncover the biophysics of protein interfaces, but also enables the redesign and optimization of protein interactions. Traditional high-throughput methods for estimating binding free energy changes are currently limited to mutations directly at the interface due to difficulties in accurately modeling how long-distance mutations propagate their effects through the protein structure. However, the modeling and design of such mutations is of substantial interest as it allows for greater control and flexibility in protein design applications. We have developed a method that combines high-throughput Rosetta-based side-chain optimization with conformational sampling using classical molecular dynamics simulations, finding significant improvements in our ability to accurately predict long-distance mutational perturbations to protein binding. Our approach uses an analytical framework grounded in alchemical free energy calculations while enabling exploration of a vastly larger sequence space. When comparing to experimental data, we find that our method can predict internal long-distance mutational perturbations with a level of accuracy similar to that of traditional methods in predicting the effects of mutations at the protein-protein interface. This work represents a new and generalizable approach to optimize protein free energy landscapes for desired biological functions.

The transactive response (TAR) DNA/RNA-binding protein 43 (TDP-43) can self-assemble into both functional stress granules via liquid-liquid phase separation (LLPS) and pathogenic amyloid fibrillary aggregates that are closely linked to amyotrophic lateral sclerosis. Previous experimental studies reported that the low complexity domain (LCD) of TDP-43 plays an essential role in the LLPS and aggregation of the full-length protein, and it alone can also undergo LLPS to form liquid droplets mainly via intermolecular interactions in the 321-340 region. And the ALS-associated M337V mutation impairs LCD's LLPS and facilitates liquid-solid phase transition. However, the underlying atomistic mechanism is not well understood. Herein, as a first step to understand the M337V-caused LLPS disruption of TDP-43 LCD mediated by the 321-340 region and the fibrillization enhancement, we investigated the conformational properties of monomer/dimer of TDP-43321-340 peptide and its M337V mutant by performing extensive all-atom explicit-solvent replica exchange molecular dynamic simulations. Our simulations demonstrate that M337V mutation alters the residue regions with high helix/β-structure propensities and thus affects the conformational ensembles of both monomer and dimer. M337V mutation inhibits helix formation in the N-terminal Ala-rich region and the C-terminal mutation site region, while facilitating their long β-sheet formation, albeit with a minor impact on the average probability of both helix structure and β-structure. Further analysis of dimer system shows that M337V mutation disrupts inter-molecular helix-helix interactions and W334-W334 π-π stacking interactions which were reported to be important for the LLPS of TDP-43 LCD, whereas enhances the overall peptide residue-residue interactions and weakens peptide-water interactions, which is conducive to peptide fibrillization. This study provides mechanistic insights into the M337V-mutation-induced impairment of phase separation and facilitation of fibril formation of TDP-43 LCD.

Alzheimer's disease (AD) is the most common cause of dementia in the elderly, with some known classical factors. Cicer arietinum (Leguminosae) is a source of protein for humans and contains albumin, globulin, glutelin, and prolamin. The protein content of two cultivars of C. arietinum, Hashem and Mansour, was isolated to evaluate their inhibition activity against acetylcholinesterase (AChE), butyrylcholine esterase (BChE), and β-amyloid peptide (βA) aggregation. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and molecular docking were also applied to evaluate the content and determine the potential of each chickpea protein to interact with AChE, respectively. Obtained data showed that proteins from both cultivars could inhibit AChE with IC50 of 17.73 (0.03) and 22.20 (0.06) μg/mL, respectively, with no activity on BChE. The 50 μg/mL protein concentration of each cultivar suppressed βA accumulation (Mansour: 25.66 % and Hashem: 21.69 %) and showed bio-metal chelating activity. SDS-PAGE analysis revealed relatively different protein patterns, though the Mansour cultivar contained some protein bands with molecular weights of 18, 24, and 70 KDa were estimated to belong to vicilin and legumin, which were absent in the Hashem protein mass. Molecular docking showed that legumin and especially vicilin have good potential to interact with AChE. The chickpea proteins showed inhibitory activity against AChE, which might be due to the vicilin and legumin fractions. The characterization of the inhibitory effect of each protein band could be promising in finding new therapeutic peptide candidates to treat Alzheimer's in the future, although more experimental work is needed in this issue. This article is protected by copyright. All rights reserved.

The two-component regulatory system (TCS) is a major regulatory system in bacteria that occurs in response to environmental changes and involves the sensor histidine kinase (HK) protein and response regulator (RR) protein. Among the TCSs, PhoR/PhoB is crucial for bacteria to adapt to changes in environmental phosphate concentrations. In addition, recent studies have shown that PhoR binding to the MgtC virulence factor activates phosphate transport for normal pathogenesis. In this work, we determined the crystal structure of the catalytic ATP binding domain of the PhoR sensor histidine kinase from Vibrio cholera, compared the structure with the known HK protein structures and discussed the potential binding interface with MgtC. This article is protected by copyright. All rights reserved.

Protein-protein interactions (PPIs) are attractive targets as they are critical in a variety of biological processes and pathologies. As an illustration, the interleukin 3 (IL-3) and its α subunit receptor (IL-3Rα) are two proteins belonging to the cytokine or receptor βc family and are involved in several disorders like inflammatory diseases or hematological malignancies. This PPI exhibits a low binding affinity and a complex formed by a mutant form of IL-3 (superkine) and IL-3Rα have emerged from the literature, with an increase of the affinity. Therefore, in this study, we performed molecular dynamics simulations and binding energy calculation in order to evaluate protein dynamics and to characterize the main interactions between IL-3 and IL-3Rα, considering both wild-type and mutant. First, in the case of IL-3Rα/IL-3 wild-type complex, IL-3Rα can adopt three different conformations essentially driven by NTD domain, including the open and closed conformations, previously observed in crystal structures. Additionally, our results reveal a third conformation that has a distinct interaction profile that the others. Interestingly, these conformational changes are attenuated in IL-3Rα/IL-3 mutant complex. Then, we highlighted the contribution of different residues which interact principally with IL-3 or IL-3Rα conserved region. As for the mutated residue at position 135 of IL-3, other residues such as IL-3 E138, IL-3 D40, IL-3Rα Y279, IL-3Rα K235 or IL-3Rα R277 seem important for a low or a high binding affinity. Altogether these findings yield new information that could be exploited in a drug discovery process. This article is protected by copyright. All rights reserved.

Voltage-gated ion channels play essential physiological roles in action potential generation and propagation. Peptidic toxins from animal venoms target ion channels and provide useful scaffolds for the rational design of novel channel modulators with enhanced potency and subtype selectivity. Despite recent progress in obtaining experimental structures of peptide toxin-ion channel complexes, structural determination of peptide toxins bound to ion channels in physiologically important states remains challenging. Here we describe an application of RosettaDock approach to the structural modeling of peptide toxins interactions with ion channels. We tested this approach on 10 structures of peptide toxin-ion channel complexes and demonstrated that it can sample near-native structures in all tested cases. Our approach will be useful for improving the understanding of the molecular mechanism of natural peptide toxin modulation of ion channel gating and for the structural modeling of novel peptide-based ion channel modulators.

Specific proteins found in food sources tend to aggregate into fibrils under heat treatment; studying these aggregation processes and developing tools to control protein heat-induced aggregation is an active area of research. Phthalocyanine complexes are known to exhibit antiprionic and anti-fibrillogenic activity. Thus, the anti-fibrillogenic effect of a series of Zr phthalocyanines with different out-of-plane coordinated ligands, namely positively charged (PcZrLys2 ), negatively charged (PcZrCitr2 ), and group able to form disulfide bridges (PcZrS2 ), on the heat-induced aggregation of such proteins as BLG, insulin, and lysozyme was studied. The inhibition of reaction activity up to about 90% was observed in the presence of these compounds for all proteins. The effective concentration of the inhibitor was calculated for the compound with the highest activity (PcZrS2 ) to be 10.6 ± 3.6 and 7.3 ± 1.2 μM/L, respectively. Fluorescence spectroscopy studies demonstrated similar binding constants of three phthalocyanines binding with BLG globule. This is consistent with the results of molecular dynamics simulation, which imply the interaction of the globule with the tetrapyrrole macrocycle of phthalocyanine, leading to the globule stabilization. At the same time, TEM shows that in the presence of phthalocyanine PcZrS2 , thinner and longer fibrils were formed compared to control in all three proteins (BLG, insulin, and lysozyme). Thus, we can conclude that phthalocyanine PcZrS2 affects the amyloid aggregation's general mechanism, which is typical for proteins of different structures. Therefore, the phthalocyanine PcZrS2 is proposed as an anti-amyloidogenic agent suppressing heat-induced aggregation of proteins of different structures, making it potentially suitable for application in the food industry.

Protein structure prediction is one of the big problems of modern biophysics: current attempts to predict the tertiary protein structure from amino acid sequence are successful mostly when the use of big data and machine learning allows one to reduce the "prediction problem" to the "problem of recognition". Despite recent successes of DL, classical methods do not yet have such accuracy in the prediction of stable conformations. Therefore, in this work we developed evolutionary algorithm USPEX to predict proteins structure based on its amino acid sequence, since this approach is more general. Moreover, we compared frequently used force fields for the task of protein structure prediction. Protein structure relaxation and energy calculations were performed using Tinker (with several different force fields) and Rosetta (with REF2015 force field) codes. To create new generations of protein models in the USPEX algorithm, we developed novel variational operators. The test of the new method on seven proteins having (for simplicity) no cis-proline (with ω≈0°) residues, and a length of up to 100 residues, revealed that our algorithm predicts tertiary structures of proteins with high accuracy. The comparison of the final potential energies of the predicted protein structures obtained using the USPEX and the Rosetta Abinitio methods showed that in most cases the developed algorithm found structures with close or even lower potential energy (Amber/Charmm/Oplsaal) and scoring function (REF2015). While USPEX has clearly demonstrated its ability to find very deep energy minima, our study showed that the existing force fields are not sufficiently accurate for a precise blind prediction of protein structures without further experimental verification.

Protein expression and function in eukaryotic cells are tightly harmonized processes modulated by the combination of different layers of regulation, including transcription, processing, stability, and translation of messenger RNA, as well as assembly, maturation, sorting, recycling, and degradation of polypeptides. Integrating all these pathways and the protein quality control machinery, deputed to avoid the production and accumulation of aberrantly folded proteins, determines protein homeostasis. Over the last decade, the combined development of accurate time-resolved experimental techniques and efficient computer simulations has opened the possibility of investigating biological mechanisms at atomic resolution with physics-based models. A meaningful example is the reconstruction of protein folding pathways at atomic resolution, which has enabled the characterization of the folding kinetics of biologically relevant globular proteins consisting of a few hundred amino acids. Combining these innovative computational technologies with rigorous experimental approaches reveals the existence of non-native metastable states transiently appearing along the folding process of such proteins. Here, we review the primary evidence indicating that these protein folding intermediates could play roles in disparate biological processes, from the post-translational regulation of protein expression to disease-relevant protein misfolding mechanisms. Finally, we discuss how the information encoded into protein folding pathways could be exploited to design an entirely new generation of pharmacological agents capable of promoting the selective degradation of protein targets.