Assessment of protein-protein interfaces in cryo-EM derived assemblies.

Structures of macromolecular assemblies derived from cryo-EM maps often contain errors that become more abundant with decreasing resolution. Despite efforts in the cryo-EM community to develop metrics for map and atomistic model validation, thus far, no specific scoring metrics have been applied systematically to assess the interface between the assembly subunits. Here, we comprehensively assessed protein-protein interfaces in macromolecular assemblies derived by cryo-EM. To this end, we developed Protein Interface-score (PI-score), a density-independent machine learning-based metric, trained using the features of protein-protein interfaces in crystal structures. We evaluated 5873 interfaces in 1053 PDB-deposited cryo-EM models (including SARS-CoV-2 complexes), as well as the models submitted to CASP13 cryo-EM targets and the EM model challenge. We further inspected the interfaces associated with low-scores and found that some of those, especially in intermediate-to-low resolution (worse than 4 Å) structures, were not captured by density-based assessment scores. A combined score incorporating PI-score and fit-to-density score showed discriminatory power, allowing our method to provide a powerful complementary assessment tool for the ever-increasing number of complexes solved by cryo-EM.

Mapping major SARS-CoV-2 drug targets and assessment of druggability using computational fragment screening: Identification of an allosteric small-molecule binding site on the Nsp13 helicase.

The 2019 emergence of, SARS-CoV-2 has tragically taken an immense toll on human life and far reaching impacts on society. There is a need to identify effective antivirals with diverse mechanisms of action in order to accelerate preclinical development. This study focused on five of the most established drug target proteins for direct acting small molecule antivirals: Nsp5 Main Protease, Nsp12 RNA-dependent RNA polymerase, Nsp13 Helicase, Nsp16 2'-O methyltransferase and the S2 subunit of the Spike protein. A workflow of solvent mapping and free energy calculations was used to identify and characterize favorable small-molecule binding sites for an aromatic pharmacophore (benzene). After identifying the most favorable sites, calculated ligand efficiencies were compared utilizing computational fragment screening. The most favorable sites overall were located on Nsp12 and Nsp16, whereas the most favorable sites for Nsp13 and S2 Spike had comparatively lower ligand efficiencies relative to Nsp12 and Nsp16. Utilizing fragment screening on numerous possible sites on Nsp13 helicase, we identified a favorable allosteric site on the N-terminal zinc binding domain (ZBD) that may be amenable to virtual or biophysical fragment screening efforts. Recent structural studies of the Nsp12:Nsp13 replication-transcription complex experimentally corroborates ligand binding at this site, which is revealed to be a functional Nsp8:Nsp13 protein-protein interaction site in the complex. Detailed structural analysis of Nsp13 ZBD conformations show the role of induced-fit flexibility in this ligand binding site and identify which conformational states are associated with efficient ligand binding. We hope that this map of over 200 possible small-molecule binding sites for these drug targets may be of use for ongoing discovery, design, and drug repurposing efforts. This information may be used to prioritize screening efforts or aid in the process of deciphering how a screening hit may bind to a specific target protein.

Viral macrodomains: a structural and evolutionary assessment of the pharmacological potential.

Viral macrodomains possess the ability to counteract host ADP-ribosylation, a post-translational modification implicated in the creation of an antiviral environment via immune response regulation. This brought them into focus as promising therapeutic targets, albeit the close homology to some of the human macrodomains raised concerns regarding potential cross-reactivity and adverse effects for the host. Here, we evaluate the structure and function of the macrodomain of SARS-CoV-2, the causative agent of COVID-19. We show that it can antagonize ADP-ribosylation by PARP14, a cellular (ADP-ribosyl)transferase necessary for the restriction of coronaviral infections. Furthermore, our structural studies together with ligand modelling revealed the structural basis for poly(ADP-ribose) binding and hydrolysis, an emerging new aspect of viral macrodomain biology. These new insights were used in an extensive evolutionary analysis aimed at evaluating the druggability of viral macrodomains not only from the Coronaviridae but also Togaviridae and Iridoviridae genera (causing diseases such as Chikungunya and infectious spleen and kidney necrosis virus disease, respectively). We found that they contain conserved features, distinct from their human counterparts, which may be exploited during drug design.

Searching for target-specific and multi-targeting organics for Covid-19 in the Drugbank database with a double scoring approach.

The current outbreak of Covid-19 infection due to SARS-CoV-2, a virus from the coronavirus family, has become a major threat to human healthcare. The virus has already infected more than 44 M people and the number of deaths reported has reached more than 1.1 M which may be attributed to lack of medicine. The traditional drug discovery approach involves many years of rigorous research and development and demands for a huge investment which cannot be adopted for the ongoing pandemic infection. Rather we need a swift and cost-effective approach to inhibit and control the viral infection. With the help of computational screening approaches and by choosing appropriate chemical space, it is possible to identify lead drug-like compounds for Covid-19. In this study, we have used the Drugbank database to screen compounds against the most important viral targets namely 3C-like protease (3CLpro), papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp) and the spike (S) protein. These targets play a major role in the replication/transcription and host cell recognition, therefore, are vital for the viral reproduction and spread of infection. As the structure based computational screening approaches are more reliable, we used the crystal structures for 3C-like main protease and spike protein. For the remaining targets, we used the structures based on homology modeling. Further, we employed two scoring methods based on binding free energies implemented in AutoDock Vina and molecular mechanics-generalized Born surface area approach. Based on these results, we propose drug cocktails active against the three viral targets namely 3CLpro, PLpro and RdRp. Interestingly, one of the identified compounds in this study i.e. Baloxavir marboxil has been under clinical trial for the treatment of Covid-19 infection. In addition, we have identified a few compounds such as Phthalocyanine, Tadalafil, Lonafarnib, Nilotinib, Dihydroergotamine, R-428 which can bind to all three targets simultaneously and can serve as multi-targeting drugs. Our study also included calculation of binding energies for various compounds currently under drug trials. Among these compounds, it is found that Remdesivir binds to targets, 3CLpro and RdRp with high binding affinity. Moreover, Baricitinib and Umifenovir were found to have superior target-specific binding while Darunavir is found to be a potential multi-targeting drug. As far as we know this is the first study where the compounds from the Drugbank database are screened against four vital targets of SARS-CoV-2 and illustrates that the computational screening using a double scoring approach can yield potential drug-like compounds against Covid-19 infection.

Fast Identification of Possible Drug Treatment of Coronavirus Disease-19 (COVID-19) through Computational Drug Repurposing Study.

The recent outbreak of novel coronavirus disease-19 (COVID-19) calls for and welcomes possible treatment strategies using drugs on the market. It is very efficient to apply computer-aided drug design techniques to quickly identify promising drug repurposing candidates, especially after the detailed 3D structures of key viral proteins are resolved. The virus causing COVID-19 is SARS-CoV-2. Taking advantage of a recently released crystal structure of SARS-CoV-2 main protease in complex with a covalently bonded inhibitor, N3 (Liu et al., 10.2210/pdb6LU7/pdb), I conducted virtual docking screening of approved drugs and drug candidates in clinical trials. For the top docking hits, I then performed molecular dynamics simulations followed by binding free energy calculations using an end point method called MM-PBSA-WSAS (molecular mechanics/Poisson-Boltzmann surface area/weighted solvent-accessible surface area; Wang, Chem. Rev. 2019, 119, 9478; Wang, Curr. Comput.-Aided Drug Des. 2006, 2, 287; Wang; ; Hou J. Chem. Inf. Model., 2012, 52, 1199). Several promising known drugs stand out as potential inhibitors of SARS-CoV-2 main protease, including carfilzomib, eravacycline, valrubicin, lopinavir, and elbasvir. Carfilzomib, an approved anticancer drug acting as a proteasome inhibitor, has the best MM-PBSA-WSAS binding free energy, -13.8 kcal/mol. The second-best repurposing drug candidate, eravacycline, is synthetic halogenated tetracycline class antibiotic. Streptomycin, another antibiotic and a charged molecule, also demonstrates some inhibitory effect, even though the predicted binding free energy of the charged form (-3.8 kcal/mol) is not nearly as low as that of the neutral form (-7.9 kcal/mol). One bioactive, PubChem 23727975, has a binding free energy of -12.9 kcal/mol. Detailed receptor-ligand interactions were analyzed and hot spots for the receptor-ligand binding were identified. I found that one hot spot residue, His41, is a conserved residue across many viruses including SARS-CoV, SARS-CoV-2, MERS-CoV, and hepatitis C virus (HCV). The findings of this study can facilitate rational drug design targeting the SARS-CoV-2 main protease.

α-Ketoamides as Broad-Spectrum Inhibitors of Coronavirus and Enterovirus Replication: Structure-Based Design, Synthesis, and Activity Assessment.

The main protease of coronaviruses and the 3C protease of enteroviruses share a similar active-site architecture and a unique requirement for glutamine in the P1 position of the substrate. Because of their unique specificity and essential role in viral polyprotein processing, these proteases are suitable targets for the development of antiviral drugs. In order to obtain near-equipotent, broad-spectrum antivirals against alphacoronaviruses, betacoronaviruses, and enteroviruses, we pursued a structure-based design of peptidomimetic α-ketoamides as inhibitors of main and 3C proteases. Six crystal structures of protease-inhibitor complexes were determined as part of this study. Compounds synthesized were tested against the recombinant proteases as well as in viral replicons and virus-infected cell cultures; most of them were not cell-toxic. Optimization of the P2 substituent of the α-ketoamides proved crucial for achieving near-equipotency against the three virus genera. The best near-equipotent inhibitors, 11u (P2 = cyclopentylmethyl) and 11r (P2 = cyclohexylmethyl), display low-micromolar EC50 values against enteroviruses, alphacoronaviruses, and betacoronaviruses in cell cultures. In Huh7 cells, 11r exhibits three-digit picomolar activity against the Middle East Respiratory Syndrome coronavirus.

Risk assessment and genomic characterization of Zika virus in China and its surrounding areas.

BACKGROUND: Zika virus (ZIKV) has emerged as a global pathogen causing significant public health concerns. China has reported several imported cases where ZIKV were carried by travelers who frequently travel between China and ZIKV-endemic regions. To fully characterize the ZIKV strains isolated from the cases reported in China and assess the risk of ZIKV transmission in China, comprehensive phylogenetic and genetic analyses were performed both on all ZIKV sequences of China and on a group of scientifically selected ZIKV sequences reported in some of the top interested destinations for Chinese travelers. METHODS: ZIKV genomic sequences were retrieved from the National Center for Biotechnology Information database through stratified sampling. Recombination event detection, maximum likelihood (ML) phylogenetic analysis, molecular clock analysis, selection pressure analysis, and amino acid substitution analysis were used to reconstruct the epidemiology and molecular transmission of ZIKV. RESULTS: The present study investigated 18 ZIKV sequences from China and 70 sequences from 16 selected countries. Recombination events rarely happens in all ZIKV Asian lineage. ZIKV genomes were generally undergone episodic positive selection (17 sites), and only one site was under pervasive positive selection. All ZIKV imported into China were Asian lineage and were assigned into two clusters: Venezuela-origin (cluster A) and Samoa-origin cluster (cluster B) with common ancestor from French Polynesia. The time of most recent common ancestors of Cluster A dated to approximately 2013/11 (95% highest posterior density [HPD] 2013/06, 2014/03) and cluster B dated to 2014/08 (95% HPD 2014/02, 2015/01). Cluster B is more variable than Cluster A in comparison with other clusters, but no varied site of biological significance was revealed. ZIKV strains in Southeast Asia countries are independent from strains in America epidemics. CONCLUSIONS: The genetic evolution of ZIKV is conservative. There are two independent introductions of ZIKV into China and China is in danger of autochthonous transmission of ZIKV because of high-risk surrounding areas. Southeast Asia areas have high risk of originating the next large-scale epidemic ZIKV strains.

Exploring the Drug Resistance of HCV Protease.

Hepatitis C virus (HCV) currently affects several million people across the globe. One of the major classes of drugs against HCV inhibits the NS3/4A protease of the polyprotein chain. Efficacy of these drugs is severely limited due to the high mutation rate that results in several genetically related quasispecies. The molecular mechanism of drug resistance is frequently deduced from structural studies and binding free energies. However, prediction of new mutations requires the evaluation of both binding free energy of the drug as well as the parameters (kcat and KM) for the natural substrate. The vitality values offer a good approach to investigate and predict mutations that render resistance to the inhibitor. A successful mutation should only affect the binding of the drug and not the catalytic activity and binding of the natural substrate. In this article, we have calculated the vitality values for four known drug inhibitors that are either currently in use or in clinical trials, evaluating binding free energies by the relevant PDLD/S-LRA method and activation barriers by the EVB method. The molecular details pertaining to resistance are also discussed. We show that our calculations are able to reproduce the catalytic effects and binding free energies in a good agreement with the corresponding observed values. Importantly, previous computational approaches have not been able to achieve this task. The trend for the vitality values is in accordance with experimental findings. Finally, we calculate the vitality values for mutations that have either not been studied experimentally or reported for some inhibitors.

PepComposer: computational design of peptides binding to a given protein surface.

There is a wide interest in designing peptides able to bind to a specific region of a protein with the aim of interfering with a known interaction or as starting point for the design of inhibitors. Here we describe PepComposer, a new pipeline for the computational design of peptides binding to a given protein surface. PepComposer only requires the target protein structure and an approximate definition of the binding site as input. We first retrieve a set of peptide backbone scaffolds from monomeric proteins that harbor the same backbone arrangement as the binding site of the protein of interest. Next, we design optimal sequences for the identified peptide scaffolds. The method is fully automatic and available as a web server at http://biocomputing.it/pepcomposer/webserver.

Large-scale structure-activity relationship study of hepatitis C virus NS5B polymerase inhibition using SMILES-based descriptors.

Hepatitis C virus (HCV) is composed of structural and non-structural proteins involved in viral transcription and propagation. In particular, NS5B is an RNA-dependent RNA polymerase for viral transcription and genome replication and is a target for designing anti-viral agents. In this study, classification and quantitative structure-activity relationship (QSAR) models of HCV NS5B inhibitors were constructed using the Correlation and Logic software. Molecular descriptors for a set of 970 HCV NS5B inhibitors were encoded using the simplified molecular input line entry system notation, and predictive models were built via the Monte Carlo method. The QSAR models provided acceptable correlation coefficients of [Formula: see text] and [Formula: see text] in the ranges of 0.6038-0.7344 and 0.6171-0.7294, respectively, while the classification models displayed sensitivity, specificity, and accuracy in ranges of 88.24-98.84, 83.87-93.94, and 86.50-94.41 %, respectively. Furthermore, molecular fragments as substructures involved in increased and decreased inhibitory activities were explored. The results provide information on QSAR and classification models for high-throughput screening and mechanistic insights into the inhibitory activity of HCV NS5B polymerase.

Generation of a chimeric hepatitis C replicon encoding a genotype-6a NS3 protease and assessment of boceprevir (SCH503034) sensitivity and drug-associated mutations.

BACKGROUND: Genotype (gt)6 HCV is common amongst HCV-positive populations of the Asia-Pacific region but cell culture models for this gt have only recently been developed. Boceprevir (SCH503034) is a clinically available inhibitor of the HCV NS3 protein. We investigated the efficacy of boceprevir for inhibiting replication of a chimeric gt1b replicon encoding a gt6a NS3 protease and defined the development of mutations in the protease when boceprevir treatment was applied. METHODS: We constructed a chimeric gt1b subgenomic replicon encoding a gt6 NS3 protease (NS3p) sequence (gt6NS3p_gt1b). The boceprevir EC50 value against replication of this replicon was determined using quantitative reverse transcriptase PCR. Next-generation sequencing was used to identify nucleotide changes associated with boceprevir resistance. The replication capacities of chimeric replicons containing mutations associated with boceprevir resistance were determined by colony formation efficiency assays. RESULTS: The boceprevir EC50 value for the gt6NS3p_gt1b replicon was 535 ±79 nM. Boceprevir-resistant gt6NS3p_gt1b replicon cell lines could be selected and they demonstrated drug-associated amino acid changes that have previously been reported in other HCV gts. Interestingly, no mutations were observed at A156, a position defined for boceprevir resistance in gt1 NS3p, while mutation at N122, which is rarely reported in boceprevir-resistant gt1 proteases, was frequently observed. Re-introduction of these mutations into the chimeric replicon altered their replication capacity, ranging from complete abolishment of replication (A156T) to increasing replication capacity (V36A, N122S). This report provides the first characterization of gt6 HCV resistance to boceprevir. CONCLUSIONS: A chimeric HCV replicon encoding gt6 NS3 protease is sensitive to boceprevir and develops drug-resistant mutations at amino acid sites previously reported for other gts. Mutation at N122 also appears to be associated with boceprevir resistance in the gt6 NS3 protease.

Immunoreactivity assessment of hepatitis C virus NS3 protease and NS5A proteins expressed in TOPO cloning system.

BACKGROUND: Hepatitis C virus (HCV) is a major cause of acute and chronic liver disease. Numerous screening assays based on the detection of immunoresponses to HCV structural and nonstructural proteins have been designed. Various studies have demonstrated genotype-specific differences in anti-HCV antibody responses to different HCV proteins. METHODS: Full-length NS3 protease and N-terminally truncated NS5A were expressed using pET TOPO 102/D system. Antigenicity of the purified recombinant proteins was assessed by immunoblotting and indirect enzyme-linked immunosorbent assay (ELISA). Furthermore, anti-HCV antibody responses to the recombinant proteins were evaluated in three prevalent genotypes in Iran. RESULTS: We were able to express and purify NS5A and NS3 protease using TOPO cloning system. The HCV NS3 protease and NS5A produced in BL21 Star (DE3) was immunoreactive. Our results demonstrate that NS3 protease and NS5A have good immunoreactivity, but they are not sufficient for detecting all HCV-positive sera. No significant genotype-specific differences were detected in immunoresponses to the recombinant proteins. CONCLUSION: In conclusion, we successfully isolated, expressed, and purified substantial amount of HCV NS3 protease and N-terminally truncated NS5A, and used them as capturing antigens in a screening ELISA assay with high sensitivity, reproducibility, and specificity. Accordingly, it is well confirmed that TOPO cloning system can be used as a dynamic system in order to express higher amount of immunoreactive viral proteins.

An objective assessment of conformational variability in complexes of hepatitis C virus polymerase with non-nucleoside inhibitors.

A major target for antiviral therapy against hepatitis C virus (HCV) is the HCV polymerase nonstructural protein 5B (NS5B). Huge efforts have been devoted to the development of nucleoside and non-nucleoside inhibitors (NNIs) of NS5B. An offshoot of these efforts has been the structural characterization of the interaction of NS5B with NNIs by X-ray crystallography. These works have shown that the conformation of recombinant NS5B is very similar across strains, constructs and complexes, making evaluation of the long-range conformational effects of NNIs nontrivial. Using procedures appropriate to the evaluation of such minor but potentially important differences, we objectively assessed the conformational diversity in the 78 available genotype 1b NS5B structures in the Protein Data Bank. We find that there are 20 significantly different NS5B conformations available, but all are geometrically close to a closed, RNA synthesis initiation-competent one. Within this fairly restricted range, differences can be mapped to movements of NS5B domains and subregions. Most of this information is actually defined by small but significant changes in complexes with NNIs. We thus establish rigorously the moving parts of the NS5B molecular machine and the previously unrecognized hinge points that come into play upon NNI binding. We propose that NNIs binding at three of the four distinct sites specifically inhibit the initiation step by the same mechanism: they prevent NS5B's "thumb" from quite reaching the proper initiation-competent position. Furthermore, we suggest that a small number of critical hinges in the NS5B structure may emerge as sites of resistance mutations during future antiviral treatment.

Improvement of a recombinant antibody-based serological assay for foot-and-mouth disease virus.

Differentiating foot-and-mouth disease virus (FMDV) antibodies generated during a natural infection from those due to vaccination (DIVA) is crucial for proving freedom from disease after an outbreak and allowing resumption of trade in livestock products. The World Organisation for Animal Health (OIE) recommends that FMDV vaccines are composed of inactivated virus that has been purified to remove non-structural viral proteins. Such purified vaccines primarily induce antibodies to viral structural proteins, whereas replicating virus stimulates host antibodies specific for both structural and non-structural proteins. The current preferred FMDV DIVA test is a competitive ELISA (C-ELISA) designed to detect antibodies to the non-structural protein 3ABC. Previously, we described the development of an FMDV DIVA test based entirely on recombinant proteins (the recombinant detecting antibody and the 3ABC coating antigen) produced in Escherichia coli. In this study, we have determined the precise binding site of the recombinant detecting antibody to a conserved sequence within the 3B region of the 3ABC protein, replaced the original E-tag of the detecting antibody with two in-house tags and engineered a direct antibody-reporting enzyme (alkaline phosphatase) fusion protein. These modifications have further improved the DIVA test, providing great potential for large scale production and uptake due to its simplicity, reproducibility and low cost.