Impact of Remdesivir Incorporation along the Primer Strand on SARS-CoV-2 RNA-Dependent RNA Polymerase

Computational studies on the functional and structural impact of pathogenic mutations in enzymes

Enzymes are critical biological catalysts involved in maintaining the intricate balance of metabolic processes within living organisms. Mutations in enzymes can result in disruptions to their functionality that may lead to a range of diseases. This review focuses on computational studies that investigate the effects of disease-associated mutations in various enzymes. Through molecular dynamics simulations, multiscale calculations, and machine learning approaches, computational studies provide detailed insights into how mutations impact enzyme structure, dynamics, and catalytic activity. This review emphasizes the increasing impact of computational simulations in understanding molecular mechanisms behind enzyme (dis)function by highlighting the application of key computational methodologies to selected enzyme examples, aiding in the prediction of mutation effects and the development of therapeutic strategies.

Probing allosteric communication with combined molecular dynamics simulations and network analysis

Understanding the allosteric mechanisms within biomolecules involved in diseases is of paramount importance for drug discovery. Indeed, characterizing communication pathways and critical hotspots in signal transduction can guide a rational approach to leverage allosteric modulation for therapeutic purposes. While the atomistic signatures of allosteric processes are difficult to determine experimentally, computational methods can be a remarkable resource. Network analysis built on Molecular Dynamics simulation data is particularly suited in this respect and is gradually becoming of routine use. Herein, we collect the recent literature in the field, discussing different aspects and available options for network construction and analysis. We further highlight interesting refinements and extensions, eventually providing our perspective on this topic.

Effects of the Y432S Cancer-Associated Variant on the Reaction Mechanism of Human DNA Polymerase κ

Human DNA polymerases are vital for genetic information management. Their function involves catalyzing the synthesis of DNA strands with unparalleled accuracy, which ensures the fidelity and stability of the human genomic blueprint. Several disease-associated mutations and their functional impact on DNA polymerases have been reported. One particular polymerase, human DNA polymerase kappa (Pol κ), has been reported to be susceptible to several cancer-associated mutations. The Y432S mutation in Pol κ, associated with various cancers, is of interest due to its impact on polymerization activity and markedly reduced thermal stability. Here, we have used computational simulations to investigate the functional consequences of the Y432S using classical molecular dynamics (MD) and coupled quantum mechanics/molecular mechanics (QM/MM) methods. Our findings suggest that Y432S induces structural alterations in domains responsible for nucleotide addition and ternary complex stabilization while retaining structural features consistent with possible catalysis in the active site. Calculations of the minimum energy path associated with the reaction mechanism of the wild type (WT) and Y432S Pol κ indicate that, while both enzymes are catalytically competent (in terms of energetics and the active site's geometries), the cancer mutation results in an endoergic reaction and an increase in the catalytic barrier. Interactions with a third magnesium ion and environmental effects on nonbonded interactions, particularly involving key residues, contribute to the kinetic and thermodynamic distinctions between the WT and mutant during the catalytic reaction. The energetics and electronic findings suggest that active site residues favor the catalytic reaction with dCTP3- over dCTP4-.

SARS-CoV-2 RNA-Dependent RNA Polymerase Follows Asynchronous Translocation Pathway for Viral Transcription and Replication

Translocation is one essential step for the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) to exert viral replication and transcription. Although cryo-EM structures of SARS-CoV-2 RdRp are available, the molecular mechanisms of dynamic translocation remain elusive. Herein, we constructed a Markov state model based on extensive molecular dynamics simulations to elucidate the translocation dynamics of the SARS-CoV-2 RdRp. We identified two intermediates that pinpoint the rate-limiting step of translocation and characterize the asynchronous movement of the template-primer duplex. The 3'-terminal nucleotide in the primer strand lags behind due to the uneven distribution of protein-RNA interactions, while the translocation of the template strand is delayed by the hurdle residue K500. Even so, the two strands share the same "ratchet" to stabilize the polymerase in the post-translocation state, suggesting a Brownian-ratchet model. Overall, our study provides intriguing insights into SARS-CoV-2 replication and transcription, which would open a new avenue for drug discoveries.

Leveraging QM/MM and Molecular Dynamics Simulations to Decipher the Reaction Mechanism of the Cas9 HNH Domain to Investigate Off-Target Effects

The clustered regularly interspaced short palindromic repeats (CRISPR) technology is an RNA-guided targeted genome-editing tool using Cas family proteins. Two magnesium-dependent nuclease domains of the Cas9 enzyme, termed HNH and RuvC, are responsible for cleaving the target DNA (t-DNA) and nontarget DNA strands, respectively. The HNH domain is believed to determine the DNA cleavage activity of both endonuclease domains and is sensitive to complementary RNA-DNA base pairing. However, the underlying molecular mechanisms of CRISPR-Cas9, by which it rebukes or accepts mismatches, are poorly understood. Thus, investigation of the structure and dynamics of the catalytic state of Cas9 with either matched or mismatched t-DNA can provide insights into improving its specificity by reducing off-target cleavages. Here, we focus on a recently discovered catalytic-active form of the Streptococcus pyogenes Cas9 (SpCas9) and employ classical molecular dynamics and coupled quantum mechanics/molecular mechanics simulations to study two possible mechanisms of t-DNA cleavage reaction catalyzed by the HNH domain. Moreover, by designing a mismatched t-DNA structure called MM5 (C to G at the fifth position from the protospacer adjacent motif region), the impact of single-guide RNA (sgRNA) and t-DNA complementarity on the catalysis process was investigated. Based on these simulations, our calculated binding affinities, minimum energy paths, and analysis of catalytically important residues provide atomic-level details of the differences between matched and mismatched cleavage reactions. In addition, several residues exhibit significant differences in their catalytic roles for the two studied systems, including K253, K263, R820, K896, and K913.

Current understanding of nucleoside analogs inhibiting the SARS-CoV-2 RNA-dependent RNA polymerase

Since the outbreak of the COVID-19 pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA-dependent RNA polymerase (RdRp) has become a main target for antiviral therapeutics due to its essential role in viral replication and transcription. Thus, nucleoside analogs structurally resemble the natural RdRp substrate and hold great potential as inhibitors. Until now, extensive experimental investigations have been performed to explore nucleoside analogs to inhibit the RdRp, and concerted efforts have been made to elucidate the underlying molecular mechanisms further. This review begins by discussing the nucleoside analogs that have demonstrated inhibition in the experiments. Second, we examine the current understanding of the molecular mechanisms underlying the action of nucleoside analogs on the SARS-CoV-2 RdRp. Recent findings in structural biology and computational research are presented through the classification of inhibitory mechanisms. This review summarizes previous experimental findings and mechanistic investigations of nucleoside analogs inhibiting SARS-CoV-2 RdRp. It would guide the rational design of antiviral medications and research into viral transcriptional mechanisms.

The NCIWEB Server: A Novel Implementation of the Noncovalent Interactions Index for Biomolecular Systems

It is well-known that the activity and function of proteins is strictly correlated with their secondary, tertiary, and quaternary structures. Their biological role is regulated by their conformational flexibility and global fold, which, in turn, is largely governed by complex noncovalent interaction networks. Because of the large size of proteins, the analysis of their noncovalent interaction networks is challenging, but can provide insights into the energetics of conformational changes or protein-protein and protein-ligand interactions. The noncovalent interaction (NCI) index, based on the reduced density gradient, is a well-established tool for the detection of weak contacts in biological systems. In this work, we present a web-based application to expand the use of this index to proteins, which only requires a molecular structure as input and provides a mapping of the number, type, and strength of noncovalent interactions. Structure preparation is automated and allows direct importing from the PDB database, making this server (https://nciweb.dsi.upmc.fr) accessible to scientists with limited experience in bioinformatics. A quick overview of this tool and concise instructions are presented, together with an illustrative application.

Investigation of the Inhibition Mechanism of Xanthine Oxidoreductase by Oxipurinol: A Computational Study

Xanthine oxidoreductase (XOR) is an enzyme found in various organisms. It converts hypoxanthine to xanthine and urate, which are crucial steps in purine elimination in humans. Elevated uric acid levels can lead to conditions like gout and hyperuricemia. Therefore, there is significant interest in developing drugs that target XOR for treating these conditions and other diseases. Oxipurinol, an analogue of xanthine, is a well-known inhibitor of XOR. Crystallographic studies have revealed that oxipurinol directly binds to the molybdenum cofactor (MoCo) in XOR. However, the precise details of the inhibition mechanism are still unclear, which would be valuable for designing more effective drugs with similar inhibitory functions. In this study, molecular dynamics and quantum mechanics/molecular mechanics calculations are employed to investigate the inhibition mechanism of XOR by oxipurinol. The study examines the structural and dynamic effects of oxipurinol on the pre-catalytic structure of the metabolite-bound system. Our results provide insights on the reaction mechanism catalyzed by the MoCo center in the active site, which aligns well with experimental findings. Furthermore, the results provide insights into the residues surrounding the active site and propose an alternative mechanism for developing alternative covalent inhibitors.

Computational Characterization of the Inhibition Mechanism of Xanthine Oxidoreductase by Topiroxostat

Xanthine oxidase (XO) is a member of the molybdopterin-containing enzyme family. It interconverts xanthine to uric acid as the last step of purine catabolism in the human body. The high uric acid concentration in the blood directly leads to human diseases like gout and hyperuricemia. Therefore, drugs that inhibit the biosynthesis of uric acid by human XO have been clinically used for many years to decrease the concentration of uric acid in the blood. In this study, the inhibition mechanism of XO and a new promising drug, topiroxostat (code: FYX-051), is investigated by employing molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) calculations. This drug has been reported to act as both a noncovalent and covalent inhibitor and undergoes a stepwise inhibition by all its hydroxylated metabolites, which include 2-hydroxy-FYX-051, dihydroxy-FYX-051, and trihydroxy-FYX-051. However, the detailed mechanism of inhibition of each metabolite remains elusive and can be useful for designing more effective drugs with similar inhibition functions. Hence, herein we present the computational investigation of the structural and dynamical effects of FYX-051 and the calculated reaction mechanism for all of the oxidation steps catalyzed by the molybdopterin center in the active site. Calculated results for the proposed reaction mechanisms for each metabolite's inhibition reaction in the enzyme's active site, binding affinities, and the noncovalent interactions with the surrounding amino acid residues are consistent with previously reported experimental findings. Analysis of the noncovalent interactions via energy decomposition analysis (EDA) and noncovalent interaction (NCI) techniques suggests that residues L648, K771, E802, R839, L873, R880, R912, F914, F1009, L1014, and A1079 can be used as key interacting residues for further hybrid-type inhibitor development.

State-of-the-Art Molecular Dynamics Simulation Studies of RNA-Dependent RNA Polymerase of SARS-CoV-2

Molecular dynamics (MD) simulations are powerful theoretical methods that can reveal biomolecular properties, such as structure, fluctuations, and ligand binding, at the level of atomic detail. In this review article, recent MD simulation studies on these biomolecular properties of the RNA-dependent RNA polymerase (RdRp), which is a multidomain protein, of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are presented. Although the tertiary structures of RdRps in SARS-CoV-2 and SARS-CoV are almost identical, the RNA synthesis activity of RdRp of SARS-CoV is higher than SARS-CoV-2. Recent MD simulations observed a difference in the dynamic properties of the two RdRps, which may cause activity differences. RdRp is also a drug target for Coronavirus disease 2019 (COVID-19). Nucleotide analogs, such as remdesivir and favipiravir, are considered to be taken up by RdRp and inhibit RNA replication. Recent MD simulations revealed the recognition mechanism of RdRp for these drug molecules and adenosine triphosphate (ATP). The ligand-recognition ability of RdRp decreases in the order of remdesivir, favipiravir, and ATP. As a typical recognition process, it was found that several lysine residues of RdRp transfer these ligand molecules to the binding site such as a “bucket brigade.” This finding will contribute to understanding the mechanism of the efficient ligand recognition by RdRp. In addition, various simulation studies on the complexes of SARS-CoV-2 RdRp with several nucleotide analogs are reviewed, and the molecular mechanisms by which these compounds inhibit the function of RdRp are discussed. The simulation studies presented in this review will provide useful insights into how nucleotide analogs are recognized by RdRp and inhibit the RNA replication.