High-confidence placement of low-occupancy fragments into electron density using the anomalous signal of sulfur and halogen atoms.

Fragment-based drug design using X-ray crystallography is a powerful technique to enable the development of new lead compounds, or probe molecules, against biological targets. This study addresses the need to determine fragment binding orientations for low-occupancy fragments with incomplete electron density, an essential step before further development of the molecule. Halogen atoms play multiple roles in drug discovery due to their unique combination of electronegativity, steric effects and hydrophobic properties. Fragments incorporating halogen atoms serve as promising starting points in hit-to-lead development as they often establish halogen bonds with target proteins, potentially enhancing binding affinity and selectivity, as well as counteracting drug resistance. Here, the aim was to unambiguously identify the binding orientations of fragment hits for SARS-CoV-2 nonstructural protein 1 (nsp1) which contain a combination of sulfur and/or chlorine, bromine and iodine substituents. The binding orientations of carefully selected nsp1 analogue hits were focused on by employing their anomalous scattering combined with Pan-Dataset Density Analysis (PanDDA). Anomalous difference Fourier maps derived from the diffraction data collected at both standard and long-wavelength X-rays were compared. The discrepancies observed in the maps of iodine-containing fragments collected at different energies were attributed to site-specific radiation-damage stemming from the strong X-ray absorption of I atoms, which is likely to cause cleavage of the C-I bond. A reliable and effective data-collection strategy to unambiguously determine the binding orientations of low-occupancy fragments containing sulfur and/or halogen atoms while mitigating radiation damage is presented.

Identification of novel and potential inhibitors against the dengue virus NS2B/NS3 protease using virtual screening and biomolecular simulations.

Approximately 3.9 billion individuals are vulnerable to dengue infection, a prevalent cause of tropical diseases worldwide. Currently, no drugs are available for preventing or treating Flavivirus diseases, including Dengue, West Nile, and the more recent Zika virus. The highly conserved Flavivirus NS2B-NS3 protease, crucial for viral replication, is a promising therapeutic target. This study employed in-silico methodologies to identify novel and potentially effective anti-dengue small molecules. A pharmacophore model was constructed using an experimentally validated NS2B-NS3 inhibitor, with the Gunner Henry score confirming the model's validity. The Natural Product Activity and Species Source (NPASS) database was screened using the validated pharmacophore model, yielding a total of 60 hits against the NS2B-NS3 protease. Furthermore, the docking finding reveals that our newly identified compounds from the NPASS database have enhanced binding affinities and established significant interactions with allosteric residues of the target protein. MD simulation and post-MD analysis further validated this finding. The free binding energy was computed in terms of MM-GBSA analysis, with the total binding energy for compound 1 (-57.3 ± 2.8 and - 52.9 ± 1.9 replica 1 and 2) indicating a stronger binding affinity for the target protein. Overall, this computational study identified these compounds as potential hit molecules, and these findings can open up a new avenue to explore and develop inhibitors against Dengue virus infection.

Generalized open-source workflows for atomistic molecular dynamics simulations of viral helicases.

Viral helicases are promising targets for the development of antiviral therapies. Given their vital function of unwinding double-stranded nucleic acids, inhibiting them blocks the viral replication cycle. Previous studies have elucidated key structural details of these helicases, including the location of substrate binding sites, flexible domains, and the discovery of potential inhibitors. Here we present a series of new Galaxy tools and workflows for performing and analyzing molecular dynamics simulations of viral helicases. We first validate them by demonstrating recapitulation of data from previous simulations of Zika (NS3) and SARS-CoV-2 (NSP13) helicases in apo and complex with inhibitors. We further demonstrate the utility and generalizability of these Galaxy workflows by applying them to new cases, proving their usefulness as a widely accessible method for exploring antiviral activity.

The step-by-step assembly mechanism of secreted flavivirus NS1 tetramer and hexamer captured at atomic resolution.

Flaviviruses encode a conserved, membrane-associated nonstructural protein 1 (NS1) with replication and immune evasion functions. The current knowledge of secreted NS1 (sNS1) oligomers is based on several low-resolution structures, thus hindering the development of drugs and vaccines against flaviviruses. Here, we revealed that recombinant sNS1 from flaviviruses exists in a dynamic equilibrium of dimer-tetramer-hexamer states. Two DENV4 hexameric NS1 structures and several tetrameric NS1 structures from multiple flaviviruses were solved at atomic resolution by cryo-EM. The stacking of the tetrameric NS1 and hexameric NS1 is facilitated by the hydrophobic ß-roll and connector domains. Additionally, a triacylglycerol molecule located within the central cavity may play a role in stabilizing the hexamer. Based on differentiated interactions between the dimeric NS1, two distinct hexamer models (head-to-head and side-to-side hexamer) and the step-by-step assembly mechanisms of NS1 dimer into hexamer were proposed. We believe that our study sheds light on the understanding of the NS1 oligomerization and contributes to NS1-based therapies.

A Perspective on Protein Structure Prediction Using Quantum Computers.

Despite the recent advancements by deep learning methods such as AlphaFold2, in silico protein structure prediction remains a challenging problem in biomedical research. With the rapid evolution of quantum computing, it is natural to ask whether quantum computers can offer some meaningful benefits for approaching this problem. Yet, identifying specific problem instances amenable to quantum advantage and estimating the quantum resources required are equally challenging tasks. Here, we share our perspective on how to create a framework for systematically selecting protein structure prediction problems that are amenable for quantum advantage, and estimate quantum resources for such problems on a utility-scale quantum computer. As a proof-of-concept, we validate our problem selection framework by accurately predicting the structure of a catalytic loop of the Zika Virus NS3 Helicase, on quantum hardware.

Assessing nanobody interaction with SARS-CoV-2 Nsp9.

The interaction between SARS-CoV-2 non-structural protein Nsp9 and the nanobody 2NSP90 was investigated by NMR spectroscopy using the paramagnetic perturbation methodology PENELOP (Paramagnetic Equilibrium vs Nonequilibrium magnetization Enhancement or LOss Perturbation). The Nsp9 monomer is an essential component of the replication and transcription complex (RTC) that reproduces the viral gRNA for subsequent propagation. Therefore preventing Nsp9 recruitment in RTC would represent an efficient antiviral strategy that could be applied to different coronaviruses, given the Nsp9 relative invariance. The NMR results were consistent with a previous characterization suggesting a 4:4 Nsp9-to-nanobody stoichiometry with the occurrence of two epitope pairs on each of the Nsp9 units that establish the inter-dimer contacts of Nsp9 tetramer. The oligomerization state of Nsp9 was also analyzed by molecular dynamics simulations and both dimers and tetramers resulted plausible. A different distribution of the mapped epitopes on the tetramer surface with respect to the former 4:4 complex could also be possible, as well as different stoichiometries of the Nsp9-nanobody assemblies such as the 2:2 stoichiometry suggested by the recent crystal structure of the Nsp9 complex with 2NSP23 (PDB ID: 8dqu), a nanobody exhibiting essentially the same affinity as 2NSP90. The experimental NMR evidence, however, ruled out the occurrence in liquid state of the relevant Nsp9 conformational change observed in the same crystal structure.

Copper(II) coordination to the intrinsically disordered region of SARS-CoV-2 Nsp1.

The intrinsically disordered C-terminal peptide region of severe acute respiratory syndrome coronavirus 2 nonstructural protein-1 (Nsp1-CT) inhibits host protein synthesis by blocking messenger RNA (mRNA) access to the 40S ribosome entrance tunnel. Aqueous copper(II) ions bind to the disordered peptide with micromolar affinity, creating a possible strategy to restore protein synthesis during host infection. Electron paramagnetic resonance (EPR) and tryptophan fluorescence measurements on a 10-residue model of the disordered protein region (Nsp1-CT10), combined with advanced quantum mechanics calculations, suggest that the peptide binds to copper(II) as a multidentate ligand. Two optimized computational models of the copper(II)-peptide complexes were derived: One corresponding to pH 6.5 and the other describing the complex at pH 7.5 to 8.5. Simulated EPR spectra based on the calculated model structures are in good agreement with experimental spectra.

Natural evidence of coronaviral 2'-O-methyltransferase activity affecting viral pathogenesis via improved substrate RNA binding.

Previous studies through targeted mutagenesis of K-D-K-E motif have demonstrated that 2'-O-MTase activity is essential for efficient viral replication and immune evasion. However, the K-D-K-E catalytic motif of 2'-O-MTase is highly conserved across numerous viruses, including flaviviruses, vaccinia viruses, coronaviruses, and extends even to mammals. Here, we observed a stronger 2'-O-MTase activity in SARS-CoV-2 compared to SARS-CoV, despite the presence of a consistently active catalytic center. We further identified critical residues (Leu-36, Asn-138 and Ile-153) which served as determinants of discrepancy in 2'-O-MTase activity between SARS-CoV-2 and SARS-CoV. These residues significantly enhanced the RNA binding affinity of 2'-O-MTase and boosted its versatility toward RNA substrates. Of interest, a triple substitution (Leu36 → Ile36, Asn138 → His138, Ile153 → Leu153, from SARS-CoV-2 to SARS-CoV) within nsp16 resulted in a proportional reduction in viral 2'-O-methylation and impaired viral replication. Furthermore, it led to a significant upregulation of type I interferon (IFN-I) and proinflammatory cytokines both in vitro and vivo, relying on the cooperative sensing of melanoma differentiation-associated protein 5 (MDA5) and laboratory of genetics and physiology 2 (LGP2). In conclusion, our findings demonstrated that alterations in residues other than K-D-K-E of 2'-O-MTase may affect viral replication and subsequently influence pathogenesis. Monitoring changes in nsp16 residues is crucial as it may aid in identifying and assessing future alteration in viral pathogenicity resulting from natural mutations occurring in nsp16.

Flavivirus Zika NS4A protein forms large oligomers in liposomes and in mild detergent.

In flaviviruses such as Dengue or Zika, non-structural (NS) NS4A protein forms homo-oligomers, participates in membrane remodelling and is critical for virulence. In both viruses, mature NS4A has the same length and three predicted hydrophobic domains. The oligomers formed by Dengue NS4A are reported to be small (n = 2, 3), based on denaturing SDS gels, but no high-resolution structure of a flavivirus NS4A protein is available, and the size of the oligomer in lipid membranes is not known. Herein we show that crosslinking Zika NS4A protein in lipid membranes results in oligomers at least up to hexamers. Further, sedimentation velocity shows that NS4A in mild detergent C14-betaine appears to be in fast equilibrium between at least two species, where one is smaller, and the other larger, than a trimer or a tetramer. Consistently, sedimentation equilibrium data was best fitted to a model involving an equilibrium between dimers (n = 2) and hexamers (n = 6). Overall, the large, at least hexameric, oligomers obtained herein in liposomes and in mild detergent are more likely to represent the forms of NS4A present in cell membranes.

Inhibition of mRNA nuclear export promotes SARS-CoV-2 pathogenesis.

The nonstructural protein 1 (Nsp1) of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) is a virulence factor that targets multiple cellular pathways to inhibit host gene expression and antiviral response. However, the underlying mechanisms of the various Nsp1-mediated functions and their contributions to SARS-CoV-2 virulence remain unclear. Among the targets of Nsp1 is the mRNA (messenger ribonucleic acid) export receptor NXF1-NXT1, which mediates nuclear export of mRNAs from the nucleus to the cytoplasm. Based on Nsp1 crystal structure, we generated mutants on Nsp1 surfaces and identified an acidic N-terminal patch that is critical for interaction with NXF1-NXT1. Photoactivatable Nsp1 probe reveals the RNA Recognition Motif (RRM) domain of NXF1 as an Nsp1 N-terminal binding site. By mutating the Nsp1 N-terminal acidic patch, we identified a separation-of-function mutant of Nsp1 that retains its translation inhibitory function but substantially loses its interaction with NXF1 and reverts Nsp1-mediated mRNA export inhibition. We then generated a recombinant (r)SARS-CoV-2 mutant on the Nsp1 N-terminal acidic patch and found that this surface is key to promote NXF1 binding and inhibition of host mRNA nuclear export, viral replication, and pathogenicity in vivo. Thus, these findings provide a mechanistic understanding of Nsp1-mediated mRNA export inhibition and establish the importance of this pathway in the virulence of SARS-CoV-2.

Secreted dengue virus NS1 from infection is predominantly dimeric and in complex with high-density lipoprotein.

Severe dengue infections are characterized by endothelial dysfunction shown to be associated with the secreted nonstructural protein 1 (sNS1), making it an attractive vaccine antigen and biotherapeutic target. To uncover the biologically relevant structure of sNS1, we obtained infection-derived sNS1 (isNS1) from dengue virus (DENV)-infected Vero cells through immunoaffinity purification instead of recombinant sNS1 (rsNS1) overexpressed in insect or mammalian cell lines. We found that isNS1 appeared as an approximately 250 kDa complex of NS1 and ApoA1 and further determined the cryoEM structures of isNS1 and its complex with a monoclonal antibody/Fab. Indeed, we found that the major species of isNS1 is a complex of the NS1 dimer partially embedded in a high-density lipoprotein (HDL) particle. Crosslinking mass spectrometry studies confirmed that the isNS1 interacts with the major HDL component ApoA1 through interactions that map to the NS1 wing and hydrophobic domains. Furthermore, our studies demonstrated that the sNS1 in sera from DENV-infected mice and a human patient form a similar complex as isNS1. Our results report the molecular architecture of a biological form of sNS1, which may have implications for the molecular pathogenesis of dengue.

Characterization of nsp1 Binding to the Viral RNA Leader Sequence of Severe Acute Respiratory Syndrome Coronavirus.

Nonstructural protein 1 (nsp1) of the severe acute respiratory syndrome coronavirus (SCOV1 and SCOV2) acts as a host shutoff protein by blocking the translation of host mRNAs and triggering their decay. Surprisingly, viral RNA, which resembles host mRNAs containing a 5'-cap and a 3'-poly(A) tail, escapes significant translation inhibition and RNA decay, aiding viral propagation. Current literature proposes that, in SCOV2, nsp1 binds the viral RNA leader sequence, and the interaction may serve to distinguish viral RNA from host mRNA. However, a direct binding between SCOV1 nsp1 and the corresponding RNA leader sequence has not been established yet. Here, we show that SCOV1 nsp1 binds to the SCOV1 RNA leader sequence but forms multiple complexes at a high concentration of nsp1. These complexes are marginally different from complexes formed with SCOV2 nsp1. Finally, mutations of the RNA stem-loop did not completely abolish RNA binding by nsp1, suggesting that an RNA secondary structure is more important for binding than the sequence itself. Understanding the nature of binding of nsp1 to viral RNA will allow us to understand how this viral protein selectively suppresses host gene expression.

Development of a Fluorescent Assay and Imidazole-Containing Inhibitors by Targeting SARS-CoV-2 Nsp13 Helicase.

Nsp13, a non-structural protein belonging to the coronavirus family 1B (SF1B) helicase, exhibits 5'-3' polarity-dependent DNA or RNA unwinding using NTPs. Crucially, it serves as a key component of the viral replication-transcription complex (RTC), playing an indispensable role in the coronavirus life cycle and thereby making it a promising target for broad-spectrum antiviral therapies. The imidazole scaffold, known for its antiviral potential, has been proposed as a potential scaffold. In this study, a fluorescence-based assay was designed by labeling dsDNA substrates with a commercial fluorophore and monitoring signal changes upon Nsp13 helicase activity. Optimization and high-throughput screening validated the feasibility of this approach. In accordance with the structural characteristics of ADP, we employed a structural-based design strategy to synthesize three classes of imidazole-based compounds through substitution reaction. Through in vitro activity research, pharmacokinetic parameter analysis, and molecular docking simulation, we identified compounds A16 (IC50 = 1.25 µM) and B3 (IC50 = 0.98 µM) as potential lead antiviral compounds for further targeted drug research.

Structure-Based Virtual Screening for Methyltransferase Inhibitors of SARS-CoV-2 nsp14 and nsp16.

The ongoing COVID-19 pandemic still threatens human health around the world. The methyltransferases (MTases) of SARS-CoV-2, specifically nsp14 and nsp16, play crucial roles in the methylation of the N7 and 2'-O positions of viral RNA, making them promising targets for the development of antiviral drugs. In this work, we performed structure-based virtual screening for nsp14 and nsp16 using the screening workflow (HTVS, SP, XP) of Schrödinger 2019 software, and we carried out biochemical assays and molecular dynamics simulation for the identification of potential MTase inhibitors. For nsp14, we screened 239,000 molecules, leading to the identification of three hits A1-A3 showing N7-MTase inhibition rates greater than 60% under a concentration of 50 µM. For the SAM binding and nsp10-16 interface sites of nsp16, the screening of 210,000 and 237,000 molecules, respectively, from ZINC15 led to the discovery of three hit compounds B1-B3 exhibiting more than 45% of 2'-O-MTase inhibition under 50 µM. These six compounds with moderate MTase inhibitory activities could be used as novel candidates for the further development of anti-SARS-CoV-2 drugs.

3D-QSAR and molecular docking studies of peptide-hybrids as dengue virus NS2B/NS3 protease inhibitors.

Global warming and climate change have made dengue disease a global health issue. More than 50 % of the world's population is at danger of dengue virus (DENV) infection, according to the World Health Organization (WHO). Therefore, a clinically approved dengue fever vaccination and effective treatment are needed. Peptide medication development is new pharmaceutical research. Here we intend to recognize the structural features inhibiting the DENV NS2B/NS3 serine protease for a series of peptide-hybrid inhibitors (R1-R2-Lys-R3-NH2) by the 3D-QSAR technique. Comparative molecular field analysis (q2 = 0.613, r2 = 0.938, r2pred = 0.820) and comparative molecular similarity indices analysis (q2 = 0.640, r2 = 0.928, r2pred = 0.693) were established, revealing minor, electropositive, H-bond acceptor groups at the R1 position, minor, electropositive, H-bond donor groups at the R2 position, and bulky, hydrophobic groups at the R3 position for higher inhibitory activity. Docking studies revealed extensive H-bond and hydrophobic interactions in the binding of tripeptide analogues to the NS2B/NS3 protease. This study provides an insight into the key structural features for the design of peptide-based inhibitors of DENV NS2B/NS3 protease.

The Inhibitory Effects of the Herbals Secondary Metabolites (7α-acetoxyroyleanone, Curzerene, Incensole, Harmaline, and Cannabidiol) on COVID-19: A Molecular Docking Study.

BACKGROUND: Since the COVID-19 outbreak in early 2020, researchers and studies are continuing to find drugs and/or vaccines against the disease. As shown before, medicinal plants can be very good sources against viruses because of their secondary compounds which may cure diseases and help in survival of patients. There is a growing trend in the filed patents in this field. AIMS: In the present study, we test and suggest the inhibitory potential of five herbal based extracts including 7α-acetoxyroyleanone, Curzerene, Incensole, Harmaline, and Cannabidiol with antivirus activity on the models of the significant antiviral targets for COVID-19 like spike glycoprotein, Papain-like protease (PLpro), non-structural protein 15 (NSP15), RNA-dependent RNA polymerase and core protease by molecular docking study. METHODS: The Salvia rythida root was extracted, dried, and pulverized by a milling machine. The aqueous phase and the dichloromethane phase of the root extractive were separated by two-phase extraction using a separatory funnel. The separation was performed using the column chromatography method. The model of the important antivirus drug target of COVID-19 was obtained from the Protein Data Bank (PDB) and modified. TO study the binding difference between the studied molecules, the docking study was performed. RESULTS: These herbal compounds are extracted from Salvia rhytidea, Curcuma zeodaria, Frankincense, Peganum harmala, and Cannabis herbs, respectively. The binding energies of all compounds on COVID-19 main targets are located in the limited area of 2.22-5.30 kcal/mol. This range of binding energies can support our hypothesis for the presence of the inhibitory effects of the secondary metabolites of mentioned structures on COVID-19. Generally, among the investigated herbal structures, Cannabidiol and 7α- acetoxyroyleanone compounds with the highest binding energy have the most inhibitory potential. The least inhibitory effects are related to the Curzerene and Incensole structures by the lowest binding affinity. CONCLUSION: The general arrangement of the basis of the potential barrier of binding energies is in the order below: Cannabidiol > 7α-acetoxyroyleanone > Harmaline> Incensole > Curzerene. Finally, the range of docking scores for investigated herbal compounds on the mentioned targets indicates that the probably inhibitory effects on these targets obey the following order: main protease> RNA-dependent RNA polymerase> PLpro> NSP15> spike glycoprotein.

Serotype-Specific Regulation of Dengue Virus NS5 Protein Subcellular Localization.

Dengue virus (DENV) nonstructural protein 5 (NS5), consisting of methyltransferase and RNA-dependent RNA polymerase (RdRp) domains, is critical for viral RNA synthesis within endoplasmic reticulum-derived replication complexes in the cytoplasm. However, a significant proportion of NS5 is localized to the nucleus of infected cells for DENV2, 3, and 4, whereas DENV1 NS5 is localized diffusely in the cytoplasm. We still have an incomplete understanding of how the DENV NS5 subcellular localization is regulated. Within NS5, two putative nuclear localization signal (NLS) sequences have been identified: NLSCentral residing in the palm of the RdRp domain as well as the recently discovered NLSC-term residing in the flexible region at the C-terminal of the RdRp domain. We have previously shown that DENV2 NS5 nuclear localization can be significantly reduced by single-point mutations to the NLSC-term. Here, we present biochemical, virological, and structural data demonstrating that the relative importance of either NLS in NS5 nuclear localization is unique to each of the four DENV serotypes. DENV1 NS5's cytoplasmic localization appears to be due to a functionally weak interaction between its NLSCentral and importin-α (IMPα), while DENV2 NS5 is almost exclusively nuclear through its NLSC-term's strong interaction with IMPα. Both NLSs of DENV3 NS5 appear to contribute to directing its nuclear localization. Lastly, in the case of DENV4, the regulation of its NS5 nuclear localization remains an enigma but appears to be associated with its NLSC-term.

The Inhibition of NS2B/NS3 Protease: A New Therapeutic Opportunity to Treat Dengue and Zika Virus Infection.

In the global pandemic scenario, dengue and zika viruses (DENV and ZIKV, respectively), both mosquito-borne members of the flaviviridae family, represent a serious health problem, and considering the absence of specific antiviral drugs and available vaccines, there is a dire need to identify new targets to treat these types of viral infections. Within this drug discovery process, the protease NS2B/NS3 is considered the primary target for the development of novel anti-flavivirus drugs. The NS2B/NS3 is a serine protease that has a dual function both in the viral replication process and in the elusion of the innate immunity. To date, two main classes of NS2B/NS3 of DENV and ZIKV protease inhibitors have been discovered: those that bind to the orthosteric site and those that act at the allosteric site. Therefore, this perspective article aims to discuss the main features of the use of the most potent NS2B/NS3 inhibitors and their impact at the social level.

Cheminformatics approach to identify andrographolide derivatives as dual inhibitors of methyltransferases (nsp14 and nsp16) of SARS-CoV-2.

The Covid-19 pandemic outbreak has accelerated tremendous efforts to discover a therapeutic strategy that targets severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to control viral infection. Various viral proteins have been identified as potential drug targets, however, to date, no specific therapeutic cure is available against the SARS-CoV-2. To address this issue, the present work reports a systematic cheminformatic approach to identify the potent andrographolide derivatives that can target methyltransferases of SARS-CoV-2, i.e. nsp14 and nsp16 which are crucial for the replication of the virus and host immune evasion. A consensus of cheminformatics methodologies including virtual screening, molecular docking, ADMET profiling, molecular dynamics simulations, free-energy landscape analysis, molecular mechanics generalized born surface area (MM-GBSA), and density functional theory (DFT) was utilized. Our study reveals two new andrographolide derivatives (PubChem CID: 2734589 and 138968421) as natural bioactive molecules that can form stable complexes with both proteins via hydrophobic interactions, hydrogen bonds and electrostatic interactions. The toxicity analysis predicts class four toxicity for both compounds with LD50 value in the range of 500-700 mg/kg. MD simulation reveals the stable formation of the complex for both the compounds and their average trajectory values were found to be lower than the control inhibitor and protein alone. MMGBSA analysis corroborates the MD simulation result and showed the lowest energy for the compounds 2734589 and 138968421. The DFT and MEP analysis also predicts the better reactivity and stability of both the hit compounds. Overall, both andrographolide derivatives exhibit good potential as potent inhibitors for both nsp14 and nsp16 proteins, however, in-vitro and in vivo assessment would be required to prove their efficacy and safety in clinical settings. Moreover, the drug discovery strategy aiming at the dual target approach might serve as a useful model for inventing novel drug molecules for various other diseases.

Interface design of SARS-CoV-2 symmetrical nsp7 dimer and machine learning-guided nsp7 sequence prediction reveals physicochemical properties and hotspots for nsp7 stability, adaptation, and therapeutic design.

The COVID-19 pandemic, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), necessitates a profound understanding of the virus and its lifecycle. As an RNA virus with high mutation rates, SARS-CoV-2 exhibits genetic variability leading to the emergence of variants with potential implications. Among its key proteins, the RNA-dependent RNA polymerase (RdRp) is pivotal for viral replication. Notably, RdRp forms dimers via non-structural protein (nsp) subunits, particularly nsp7, crucial for efficient viral RNA copying. Similar to the main protease (Mpro) of SARS-CoV-2, there is a possibility that the nsp7 might also undergo mutational selection events to generate more stable and adaptable versions of nsp7 dimer during virus evolution. However, efforts to obtain such cohesive and comprehensive information are lacking. To address this, we performed this study focused on deciphering the molecular intricacies of nsp7 dimerization using a multifaceted approach. Leveraging computational protein design (CPD), machine learning (ML), AlphaFold v2.0-based structural analysis, and several related computational approaches, we aimed to identify critical residues and mutations influencing nsp7 dimer stability and adaptation. Our methodology involved identifying potential hotspot residues within the dimeric nsp7 interface using an interface-based CPD approach. Through Rosetta-based symmetrical protein design, we designed and modulated nsp7 dimerization, considering selected interface residues. Analysis of physicochemical features revealed acceptable structural changes and several structural and residue-specific insights emphasizing the intricate nature of such protein-protein complexes. Our ML models, particularly the random forest regressor (RFR), accurately predicted binding affinities and ML-guided sequence predictions corroborated CPD findings, elucidating potential nsp7 mutations and their impact on binding affinity. Validation against clinical sequencing data demonstrated the predictive accuracy of our approach. Moreover, AlphaFold v2.0 structural analyses validated optimal dimeric configurations of affinity-enhancing designs, affirming methodological precision. Affinity-enhancing designs exhibited favourable energetics and higher binding affinity as compared to their counterparts. The obtained physicochemical properties, molecular interactions, and sequence predictions advance our understanding of SARS-CoV-2 evolution and inform potential avenues for therapeutic intervention against COVID-19.