Pathophysiology of chikungunya virus infection associated with fatal outcomes.

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that causes acute, subacute, and chronic human arthritogenic diseases and, in rare instances, can lead to neurological complications and death. Here, we combined epidemiological, virological, histopathological, cytokine, molecular dynamics, metabolomic, proteomic, and genomic analyses to investigate viral and host factors that contribute to chikungunya-associated (CHIK) death. Our results indicate that CHIK deaths are associated with multi-organ infection, central nervous system damage, and elevated serum levels of pro-inflammatory cytokines and chemokines compared with survivors. The histopathologic, metabolite, and proteomic signatures of CHIK deaths reveal hemodynamic disorders and dysregulated immune responses. The CHIKV East-Central-South-African lineage infecting our study population causes both fatal and survival cases. Additionally, CHIKV infection impairs the integrity of the blood-brain barrier, as evidenced by an increase in permeability and altered tight junction protein expression. Overall, our findings improve the understanding of CHIK pathophysiology and the causes of fatal infections.

Thermostability Enhancement of GH 62 α-l-Arabinofuranosidase by Directed Evolution and Rational Design.

GH 62 arabinofuranosidases are known for their excellent specificity for arabinoxylan of agroindustrial residues and their synergism with endoxylanases and other hemicellulases. However, the low thermostability of some GH enzymes hampers potential industrial applications. Protein engineering research highly desires mutations that can enhance thermostability. Therefore, we employed directed evolution using one round of error-prone PCR and site-saturation mutagenesis for thermostability enhancement of GH 62 arabinofuranosidase from Aspergillus fumigatus. Single mutants with enhanced thermostability showed significant ΔΔG changes (<-2.5 kcal/mol) and improvements in perplexity scores from evolutionary scale modeling inverse folding. The best mutant, G205K, increased the melting temperature by 5 °C and the energy of denaturation by 41.3%. We discussed the functional mechanisms for improved stability. Analyzing the adjustments in α-helices, ß-sheets, and loops resulting from point mutations, we have obtained significant knowledge regarding the potential impacts on protein stability, folding, and overall structural integrity.

Computational Analysis of SAM Analogs as Methyltransferase Inhibitors of nsp16/nsp10 Complex from SARS-CoV-2.

Methyltransferases (MTases) enzymes, responsible for RNA capping into severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are emerging important targets for the design of new anti-SARS-CoV-2 agents. Here, analogs of S-adenosylmethionine (SAM), obtained from the bioisosteric substitution of the sulfonium and amino acid groups, were evaluated by rigorous computational modeling techniques such as molecular dynamics (MD) simulations followed by relative binding free analysis against nsp16/nsp10 complex from SARS-CoV-2. The most potent inhibitor (2a) shows the lowest binding free energy (-58.75 Kcal/mol) and more potency than Sinefungin (SFG) (-39.8 Kcal/mol), a pan-MTase inhibitor, which agrees with experimental observations. Besides, our results suggest that the total binding free energy of each evaluated SAM analog is driven by van der Waals interactions which can explain their poor cell permeability, as observed in experimental essays. Overall, we provide a structural and energetic analysis for the inhibition of the nsp16/nsp10 complex involving the evaluated SAM analogs as potential inhibitors.

Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces.

We have used molecular dynamics (MD) simulations with hybrid quantum mechanics/molecular mechanics (QM/MM) potentials to investigate the reaction mechanism for covalent inhibition of cathepsin K and assess the reversibility of inhibition. The computed free energy profiles suggest that a nucleophilic attack by the catalytic cysteine on the inhibitor warhead and proton transfer from the catalytic histidine occur in a concerted manner. The results indicate that the reaction is more strongly exergonic for the alkyne-based inhibitors, which bind irreversibly to cathepsin K, than for the nitrile-based inhibitor odanacatib, which binds reversibly. Gas-phase energies were also calculated for the addition of methanethiol to structural prototypes for a number of warheads of interest in cysteine protease inhibitor design in order to assess electrophilicity. The approaches presented in this study are particularly applicable to assessment of novel warheads, and computed transition state geometries can be incorporated into molecular models for covalent docking.

Evaluating QM/MM Free Energy Surfaces for Ranking Cysteine Protease Covalent Inhibitors.

One tactic for cysteine protease inhibition is to form a covalent bond between an electrophilic atom of the inhibitor and the thiol of the catalytic cysteine. In this study, we evaluate the reaction free energy obtained from a hybrid quantum mechanical/molecular mechanical (QM/MM) free energy profile as a predictor of affinity for reversible, covalent inhibitors of rhodesain. We demonstrate that the reaction free energy calculated with the PM6/MM potential is in agreement with the experimental data and suggest that the free energy profile for covalent bond formation in a protein environment may be a useful tool for the inhibitor design.

Molecular description of α-keto-based inhibitors of cruzain with activity against Chagas disease combining 3D-QSAR studies and molecular dynamics.

In this work, a group of α-keto-based inhibitors of the cruzain enzyme with anti-chagas activity was selected for a three-dimensional quantitative structure-activity relationship study (3D-QSAR) combined with molecular dynamics (MD). Firstly, statistical models based on Partial Least Square (PLS) regression were developed employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) descriptors. Validation parameters (q2 and r2 )for the models were, respectively, 0.910 and 0.997 (CoMFA) and 0.913 and 0.992 (CoMSIA). In addition, external validation for the models using a test group revealed r2pred  = 0.728 (CoMFA) and 0.971 (CoMSIA). The most relevant aspect in this study was the generation of molecular fields in both favorable and unfavorable regions based on the models developed. These fields are important to interpret modifications necessary to enhance the biological activities of the inhibitors. This analysis was restricted considering the inhibitors in a fixed conformation, not interacting with their target, the cruzain enzyme. Then, MD was employed taking into account important variables such as time and temperature. MD helped describe the behavior of the inhibitors and their properties showed similar results as those generated by QSAR-3D study.

Computational analyses of interactions between ALK-5 and bioactive ligands: insights for the design of potential anticancer agents.

Activin Receptor-Like Kinase 5 (ALK-5) is related to some types of cancer, such as breast, lung, and pancreas. In this study, we have used molecular docking, molecular dynamics simulations, and free energy calculations in order to explore key interactions between ALK-5 and six bioactive ligands with different ranges of biological activity. The motivation of this work is the lack of crystal structure for inhibitor-protein complexes for this set of ligands. The understanding of the molecular structure and the protein-ligand interaction could give support for the development of new drugs against cancer. The results show that the calculated binding free energy using MM-GBSA, MM-PBSA, and SIE is correlated with experimental data with r2 = 0.88, 0.80, and 0.94, respectively, which indicates that the calculated binding free energy is in excellent agreement with experimental data. In addition, the results demonstrate that H bonds with Lys232, Glu245, Tyr249, His283, Asp351, and one structural water molecule play an important role for the inhibition of ALK-5. Overall, we discussed the main interactions between ALK-5 and six inhibitors that may be used as starting points for designing new molecules to the treatment of cancer.