SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions.

SCoV2-MD (www.scov2-md.org) is a new online resource that systematically organizes atomistic simulations of the SARS-CoV-2 proteome. The database includes simulations produced by leading groups using molecular dynamics (MD) methods to investigate the structure-dynamics-function relationships of viral proteins. SCoV2-MD cross-references the molecular data with the pandemic evolution by tracking all available variants sequenced during the pandemic and deposited in the GISAID resource. SCoV2-MD enables the interactive analysis of the deposited trajectories through a web interface, which enables users to search by viral protein, isolate, phylogenetic attributes, or specific point mutation. Each mutation can then be analyzed interactively combining static (e.g. a variety of amino acid substitution penalties) and dynamic (time-dependent data derived from the dynamics of the local geometry) scores. Dynamic scores can be computed on the basis of nine non-covalent interaction types, including steric properties, solvent accessibility, hydrogen bonding, and other types of chemical interactions. Where available, experimental data such as antibody escape and change in binding affinities from deep mutational scanning experiments are also made available. All metrics can be combined to build predefined or custom scores to interrogate the impact of evolving variants on protein structure and function.

Conformational response to ligand binding of TMPRSS2, a protease involved in SARS-CoV-2 infection: Insights through computational modeling.

Thanks to the considerable research which has been undertaken in the last few years to improve our understanding of the biology and mechanism of action of SARS-CoV-2, we know how the virus uses its surface spike protein to infect host cells. The transmembrane prosthesis, serine 2 (TMPRSS2) protein, located on the surface of human cells, recognizes the cleavage site in the spike protein, leading to the release of the fusion peptide and entry of the virus into the host cells. Because of its role, TMPRSS2 has been proposed as a drug target to prevent infection by the virus. In this study, we aim to increase our understanding of TMPRSS2 using long scale microsecond atomistic molecular dynamics simulations, focusing on the conformational changes over time. The comparison between simulations conducted on the protein in the native (apo) and inhibited form (holo), has shown that in the holo form the inhibitor stabilizes the catalytic site and induces rearrangements in the extracellular domain of the protein. In turn, it leads to the formation of a new cavity in the vicinity of the ligand binding pocket that is stable in the microsecond time scale. Given the low specificity of known protease inhibitors, these findings suggest a new potential drug target site that can be used to improve TMPRSS2 specific recognition by newly designed inhibitors.

Target Prediction by Multiple Virtual Screenings: Analyzing the SARS-CoV-2 Phenotypic Screening by the Docking Simulations Submitted to the MEDIATE Initiative.

Phenotypic screenings are usually combined with deconvolution techniques to characterize the mechanism of action for the retrieved hits. These studies can be supported by various computational analyses, although docking simulations are rarely employed. The present study aims to assess if multiple docking calculations can prove successful in target prediction. In detail, the docking simulations submitted to the MEDIATE initiative are utilized to predict the viral targets involved in the hits retrieved by a recently published cytopathic screening. Multiple docking results are combined by the EFO approach to develop target-specific consensus models. The combination of multiple docking simulations enhances the performances of the developed consensus models (average increases in EF1% value of 40% and 25% when combining three and two docking runs, respectively). These models are able to propose reliable targets for about half of the retrieved hits (31 out of 59). Thus, the study emphasizes that docking simulations might be effective in target identification and provide a convincing validation for the collaborative strategies that inspire the MEDIATE initiative. Disappointingly, cross-target and cross-program correlations suggest that common scoring functions are not specific enough for the simulated target.

Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel.

(1) Background: Virtual screening campaigns require target structures in which the pockets are properly arranged for binding. Without these, MD simulations can be used to relax the available target structures, optimizing the fine architecture of their binding sites. Among the generated frames, the best structures can be selected based on available experimental data. Without experimental templates, the MD trajectories can be filtered by energy-based criteria or sampled by systematic analyses. (2) Methods: A blind and methodical analysis was performed on the already reported MD run of the hTRPM8 tetrameric structures; a total of 50 frames underwent docking simulations by using a set of 1000 ligands including 20 known hTRPM8 modulators. Docking runs were performed by LiGen program and involved the frames as they are and after optimization by SCRWL4.0. For each frame, all four monomers were considered. Predictive models were developed by the EFO algorithm based on the sole primary LiGen scores. (3) Results: On average, the MD simulation progressively enhances the performance of the extracted frames, and the optimized structures perform better than the non-optimized frames (EF1% mean: 21.38 vs. 23.29). There is an overall correlation between performances and volumes of the explored pockets and the combination of the best performing frames allows to develop highly performing consensus models (EF1% = 49.83). (4) Conclusions: The systematic sampling of the entire MD run provides performances roughly comparable with those previously reached by using rationally selected frames. The proposed strategy appears to be helpful when the lack of experimental data does not allow an easy selection of the optimal structures for docking simulations. Overall, the reported docking results confirm the relevance of simulating all the monomers of an oligomer structure and emphasize the efficacy of the SCRWL4.0 method to optimize the protein structures for docking calculations.

The Spike Mutants Website: A Worldwide Used Resource against SARS-CoV-2.

A large number of SARS-CoV-2 mutations in a short period of time has driven scientific research related to vaccines, new drugs, and antibodies to combat the new variants of the virus. Herein, we present a web portal containing the structural information, the tridimensional coordinates, and the molecular dynamics trajectories of the SARS-CoV-2 spike protein and its main variants. The Spike Mutants website can serve as a rapid online tool for investigating the impact of novel mutations on virus fitness. Taking into account the high variability of SARS-CoV-2, this application can help the scientific community when prioritizing molecules for experimental assays, thus, accelerating the identification of promising drug candidates for COVID-19 treatment. Below we describe the main features of the platform and illustrate the possible applications for speeding up the drug discovery process and hypothesize new effective strategies to overcome the recurrent mutations in SARS-CoV-2 genome.

Structural Evolution of Delta (B.1.617.2) and Omicron (BA.1) Spike Glycoproteins.

The vast amount of epidemiologic and genomic data that were gathered as a global response to the COVID-19 pandemic that was caused by SARS-CoV-2 offer a unique opportunity to shed light on the structural evolution of coronaviruses and in particular on the spike (S) glycoprotein, which mediates virus entry into the host cell by binding to the human ACE2 receptor. Herein, we carry out an investigation into the dynamic properties of the S glycoprotein, focusing on the much more transmissible Delta and Omicron variants. Notwithstanding the great number of mutations that have accumulated, particularly in the Omicron S glycoprotein, our data clearly showed the conservation of some structural and dynamic elements, such as the global motion of the receptor binding domain (RBD). However, our studies also revealed structural and dynamic alterations that were concentrated in the aa 627-635 region, on a small region of the receptor binding motif (aa 483-485), and the so-called "fusion-peptide proximal region". In particular, these last two S regions are known to be involved in the human receptor ACE2 recognition and membrane fusion. Our structural evidence, therefore, is likely involved in the observed different transmissibility of these S mutants. Finally, we highlighted the role of glycans in the increased RBD flexibility of the monomer in the up conformation of Omicron.

Altered Local Interactions and Long-Range Communications in UK Variant (B.1.1.7) Spike Glycoprotein.

The COVID-19 pandemic is caused by SARS-CoV-2. Currently, most of the research efforts towards the development of vaccines and antibodies against SARS-CoV-2 were mainly focused on the spike (S) protein, which mediates virus entry into the host cell by binding to ACE2. As the virus SARS-CoV-2 continues to spread globally, variants have emerged, characterized by multiple mutations of the S glycoprotein. Herein, we employed microsecond-long molecular dynamics simulations to study the impact of the mutations of the S glycoprotein in SARS-CoV-2 Variant of Concern 202012/01 (B.1.1.7), termed the "UK variant", in comparison with the wild type, with the aim to decipher the structural basis of the reported increased infectivity and virulence. The simulations provided insights on the different dynamics of UK and wild-type S glycoprotein, regarding in particular the Receptor Binding Domain (RBD). In addition, we investigated the role of glycans in modulating the conformational transitions of the RBD. The overall results showed that the UK mutant experiences higher flexibility in the RBD with respect to wild type; this behavior might be correlated with the increased transmission reported for this variant. Our work also adds useful structural information on antigenic "hotspots" and epitopes targeted by neutralizing antibodies.

Combining Different Docking Engines and Consensus Strategies to Design and Validate Optimized Virtual Screening Protocols for the SARS-CoV-2 3CL Protease.

The 3CL-Protease appears to be a very promising medicinal target to develop anti-SARS-CoV-2 agents. The availability of resolved structures allows structure-based computational approaches to be carried out even though the lack of known inhibitors prevents a proper validation of the performed simulations. The innovative idea of the study is to exploit known inhibitors of SARS-CoV 3CL-Pro as a training set to perform and validate multiple virtual screening campaigns. Docking simulations using four different programs (Fred, Glide, LiGen, and PLANTS) were performed investigating the role of both multiple binding modes (by binding space) and multiple isomers/states (by developing the corresponding isomeric space). The computed docking scores were used to develop consensus models, which allow an in-depth comparison of the resulting performances. On average, the reached performances revealed the different sensitivity to isomeric differences and multiple binding modes between the four docking engines. In detail, Glide and LiGen are the tools that best benefit from isomeric and binding space, respectively, while Fred is the most insensitive program. The obtained results emphasize the fruitful role of combining various docking tools to optimize the predictive performances. Taken together, the performed simulations allowed the rational development of highly performing virtual screening workflows, which could be further optimized by considering different 3CL-Pro structures and, more importantly, by including true SARS-CoV-2 3CL-Pro inhibitors (as learning set) when available.

Combining Molecular Dynamics and Docking Simulations to Develop Targeted Protocols for Performing Optimized Virtual Screening Campaigns on The hTRPM8 Channel.

BACKGROUND: There is an increasing interest in TRPM8 ligands of medicinal interest, the rational design of which can be nowadays supported by structure-based in silico studies based on the recently resolved TRPM8 structures. Methods: The study involves the generation of a reliable hTRPM8 homology model, the reliability of which was assessed by a 1.0 µs MD simulation which was also used to generate multiple receptor conformations for the following structure-based virtual screening (VS) campaigns; docking simulations utilized different programs and involved all monomers of the selected frames; the so computed docking scores were combined by consensus approaches based on the EFO algorithm. Results: The obtained models revealed very satisfactory performances; LiGen™ provided the best results among the tested docking programs; the combination of docking results from the four monomers elicited a markedly beneficial effect on the computed consensus models. Conclusions: The generated hTRPM8 model appears to be amenable for successful structure-based VS studies; cross-talk modulating effects between interacting monomers on the binding sites can be accounted for by combining docking simulations as performed on all the monomers; this strategy can have general applicability for docking simulations involving quaternary protein structures with multiple identical binding pockets.

Computational Studies of SARS-CoV-2 3CLpro: Insights from MD Simulations.

Given the enormous social and health impact of the pandemic triggered by severe acute respiratory syndrome 2 (SARS-CoV-2), the scientific community made a huge effort to provide an immediate response to the challenges posed by Coronavirus disease 2019 (COVID-19). One of the most important proteins of the virus is an enzyme, called 3CLpro or main protease, already identified as an important pharmacological target also in SARS and Middle East respiratory syndrome virus (MERS) viruses. This protein triggers the production of a whole series of enzymes necessary for the virus to carry out its replicating and infectious activities. Therefore, it is crucial to gain a deeper understanding of 3CLpro structure and function in order to effectively target this enzyme. All-atoms molecular dynamics (MD) simulations were performed to examine the different conformational behaviors of the monomeric and dimeric form of SARS-CoV-2 3CLpro apo structure, as revealed by microsecond time scale MD simulations. Our results also shed light on the conformational dynamics of the loop regions at the entry of the catalytic site. Studying, at atomic level, the characteristics of the active site and obtaining information on how the protein can interact with its substrates will allow the design of molecules able to block the enzymatic function crucial for the virus.

A Comprehensive Mapping of the Druggable Cavities within the SARS-CoV-2 Therapeutically Relevant Proteins by Combining Pocket and Docking Searches as Implemented in Pockets 2.0.

(1) Background: Virtual screening studies on the therapeutically relevant proteins of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) require a detailed characterization of their druggable binding sites, and, more generally, a convenient pocket mapping represents a key step for structure-based in silico studies; (2) Methods: Along with a careful literature search on SARS-CoV-2 protein targets, the study presents a novel strategy for pocket mapping based on the combination of pocket (as performed by the well-known FPocket tool) and docking searches (as performed by PLANTS or AutoDock/Vina engines); such an approach is implemented by the Pockets 2.0 plug-in for the VEGA ZZ suite of programs; (3) Results: The literature analysis allowed the identification of 16 promising binding cavities within the SARS-CoV-2 proteins and the here proposed approach was able to recognize them showing performances clearly better than those reached by the sole pocket detection; and (4) Conclusions: Even though the presented strategy should require more extended validations, this proved successful in precisely characterizing a set of SARS-CoV-2 druggable binding pockets including both orthosteric and allosteric sites, which are clearly amenable for virtual screening campaigns and drug repurposing studies. All results generated by the study and the Pockets 2.0 plug-in are available for download.

Binding Mode Exploration of B1 Receptor Antagonists' by the Use of Molecular Dynamics and Docking Simulation-How Different Target Engagement Can Determine Different Biological Effects.

The kinin B1 receptor plays a critical role in the chronic phase of pain and inflammation. The development of B1 antagonists peaked in recent years but almost all promising molecules failed in clinical trials. Little is known about these molecules' mechanisms of action and additional information will be necessary to exploit the potential of the B1 receptor. With the aim of contributing to the available knowledge of the pharmacology of B1 receptors, we designed and characterized a novel class of allosteric non-peptidic inhibitors with peculiar binding characteristics. Here, we report the binding mode analysis and pharmacological characterization of a new allosteric B1 antagonist, DFL20656. We analyzed the binding of DFL20656 by single point mutagenesis and radioligand binding assays and we further characterized its pharmacology in terms of IC50, B1 receptor internalization and in vivo activity in comparison with different known B1 antagonists. We highlighted how different binding modes of DFL20656 and a Merck compound (compound 14) within the same molecular pocket can affect the biological and pharmacological properties of B1 inhibitors. DFL20656, by its peculiar binding mode, involving tight interactions with N114, efficiently induced B1 receptor internalization and evoked a long-lasting effect in an in vivo model of neuropathic pain. The pharmacological characterization of different B1 antagonists highlighted the effects of their binding modes on activity, receptor occupancy and internalization. Our results suggest that part of the failure of most B1 inhibitors could be ascribed to a lack of knowledge about target function and engagement.

Pathway involving the N155H mutation in HIV-1 integrase leads to dolutegravir resistance.

Background: Dolutegravir, an integrase strand-transfer inhibitor (STI), shows a high genetic barrier to resistance. Dolutegravir is reported to be effective against viruses resistant to raltegravir and elvitegravir. In this study, we report the case of a patient treated with dolutegravir monotherapy. Failure of dolutegravir treatment was observed concomitant with the appearance of N155H-K211R-E212T mutations in the integrase (IN) gene in addition to the polymorphic K156N mutation that was present at baseline in this patient. Methods: The impact of N155H-K156N-K211R-E212T mutations was studied in cell-free, culture-based assays and by molecular modelling. Results: Cell-free and culture-based assays confirm that selected mutations in the patient, in the context of the polymorphic mutation K156N present at the baseline, lead to high resistance to dolutegravir requiring that the analysis be done at timepoints longer than usual to properly reveal the results. Interestingly, the association of only N155H and K156N is sufficient for significant resistance to dolutegravir. Modelling studies showed that dolutegravir is less stable in IN/DNA complexes with respect to the WT sequence. Conclusions: Our results indicate that the stability of STI IN/DNA complexes is an important parameter that must be taken into account when evaluating dolutegravir resistance. This study confirms that a pathway including N155H can be selected in patients treated with dolutegravir with the help of the polymorphic K156N that acts as a secondary mutation that enhances the resistance to dolutegravir.

Real-life 3D therapy failure: Analysis of NS5A 93H RAS plus 108 K polymorphism in complex with ombitasvir by molecular modeling.

We report a real-life 3D therapy failure in a patient treated with ombitasvir (OMV)/paritaprevir/ritonavir and dasabuvir without ribavirin (3D-R). He had therapy failure at week 12 after the end of treatment. We detected resistance-associated substitutions (RASs) plus polymorphisms on NS3, NS5A, and NS5B target regions by population sequencing (15% cut-off) at baseline, at relapse and during follow-up. About this, NS5A RASs generally persist longer than resistances in the other target genes and may impact treatment outcome. Therefore, to evaluate OMV drug-resistance mechanism, we studied the acquired RAS plus polymorphisms on NS5A phosphoprotein by computational studies. OMV showed a higher affinity towards baseline and 93H/108 K mutant structure (follow-up) with respect to 93H/R108 mutant structure (relapse) on phosphoprotein. By Molecular Dynamics simulations (MDs), structural information about the protein stability in presence of OMV were observed. According to our data, molecular modeling approach has proved to be a powerful method to evaluate the impact of these RASs plus specific amino acid (AA) changes on phosphoprotein.

Identification of G-quadruplex DNA/RNA binders: Structure-based virtual screening and biophysical characterization.

BACKGROUND: Recent findings demonstrated that, in mammalian cells, telomere DNA (Tel) is transcribed into telomeric repeat-containing RNA (TERRA), which is involved in fundamental biological processes, thus representing a promising anticancer target. For this reason, the discovery of dual (as well as selective) Tel/TERRA G-quadruplex (G4) binders could represent an innovative strategy to enhance telomerase inhibition. METHODS: Initially, docking simulations of known Tel and TERRA active ligands were performed on the 3D coordinates of bimolecular G4 Tel DNA (Tel2) and TERRA (TERRA2). Structure-based pharmacophore models were generated on the best complexes and employed for the virtual screening of ~257,000 natural compounds. The 20 best candidates were submitted to biophysical assays, which included circular dichroism and mass spectrometry at different K+ concentrations. RESULTS: Three hits were here identified and characterized by biophysical assays. Compound 7 acts as dual Tel2/TERRA2 G4-ligand at physiological KCl concentration, while hits 15 and 17 show preferential thermal stabilization for Tel2 DNA. The different molecular recognition against the two targets was also discussed. CONCLUSIONS: Our successful results pave the way to further lead optimization to achieve both increased selectivity and stabilizing effect against TERRA and Tel DNA G4s. GENERAL SIGNIFICANCE: The current study combines for the first time molecular modelling and biophysical assays applied to bimolecular DNA and RNA G4s, leading to the identification of innovative ligand chemical scaffolds with a promising anticancer profile. This article is part of a Special Issue entitled "G-quadruplex" Guest Editor: Dr. Concetta Giancola and Dr. Daniela Montesarchio.

Structure of human TRPM8 channel.

TRPM8 is a non-selective cation channel permeable to both monovalent and divalent cations that is activated by multiple factors, such as temperature, voltage, pressure, and changes in osmolality. It is a therapeutic target for anticancer drug development, and its modulators can be utilized for several pathological conditions. Here, we present a cryo-electron microscopy structure of a human TRPM8 channel in the closed state that was solved at 2.7 Å resolution. Our structure comprises the most complete model of the N-terminal pre-melastatin homology region. We also visualized several lipids that are bound by the protein and modeled how the human channel interacts with icilin. Analyses of pore helices in available TRPM structures showed that all these structures can be grouped into different closed, desensitized and open state conformations based on the register of the pore helix S6 which positions particular amino acid residues at the channel constriction.

Diketo acid inhibitors of nsp13 of SARS-CoV-2 block viral replication.

For RNA viruses, RNA helicases have long been recognized to play critical roles during virus replication cycles, facilitating proper folding and replication of viral RNAs, therefore representing an ideal target for drug discovery. SARS-CoV-2 helicase, the non-structural protein 13 (nsp13) is a highly conserved protein among all known coronaviruses, and, at the moment, is one of the most explored viral targets to identify new possible antiviral agents. In the present study, we present six diketo acids (DKAs) as nsp13 inhibitors able to block both SARS-CoV-2 nsp13 enzymatic functions. Among them four compounds were able to inhibit viral replication in the low micromolar range, being active also on other human coronaviruses such as HCoV229E and MERS CoV. The experimental investigation of the binding mode revealed ATP-non-competitive kinetics of inhibition, not affected by substrate-displacement effect, suggesting an allosteric binding mode that was further supported by molecular modelling calculations predicting the binding into an allosteric conserved site located in the RecA2 domain.

DHFR Inhibitors Display a Pleiotropic Anti-Viral Activity against SARS-CoV-2: Insights into the Mechanisms of Action.

During the COVID-19 pandemic, drug repurposing represented an effective strategy to obtain quick answers to medical emergencies. Based on previous data on methotrexate (MTX), we evaluated the anti-viral activity of several DHFR inhibitors in two cell lines. We observed that this class of compounds showed a significant influence on the virus-induced cytopathic effect (CPE) partly attributed to the intrinsic anti-metabolic activity of these drugs, but also to a specific anti-viral function. To elucidate the molecular mechanisms, we took advantage of our EXSCALATE platform for in-silico molecular modelling and further validated the influence of these inhibitors on nsp13 and viral entry. Interestingly, pralatrexate and trimetrexate showed superior effects in counteracting the viral infection compared to other DHFR inhibitors. Our results indicate that their higher activity is due to their polypharmacological and pleiotropic profile. These compounds can thus potentially give a clinical advantage in the management of SARS-CoV-2 infection in patients already treated with this class of drugs.

MEDIATE - Molecular DockIng at homE: Turning collaborative simulations into therapeutic solutions.

INTRODUCTION: Collaborative computing has attracted great interest in the possibility of joining the efforts of researchers worldwide. Its relevance has further increased during the pandemic crisis since it allows for the strengthening of scientific collaborations while avoiding physical interactions. Thus, the E4C consortium presents the MEDIATE initiative which invited researchers to contribute via their virtual screening simulations that will be combined with AI-based consensus approaches to provide robust and method-independent predictions. The best compounds will be tested, and the biological results will be shared with the scientific community. AREAS COVERED: In this paper, the MEDIATE initiative is described. This shares compounds' libraries and protein structures prepared to perform standardized virtual screenings. Preliminary analyses are also reported which provide encouraging results emphasizing the MEDIATE initiative's capacity to identify active compounds. EXPERT OPINION: Structure-based virtual screening is well-suited for collaborative projects provided that the participating researchers work on the same input file. Until now, such a strategy was rarely pursued and most initiatives in the field were organized as challenges. The MEDIATE platform is focused on SARS-CoV-2 targets but can be seen as a prototype which can be utilized to perform collaborative virtual screening campaigns in any therapeutic field by sharing the appropriate input files.

Computational Insights into the Sequence-Activity Relationships of the NGF(1-14) Peptide by Molecular Dynamics Simulations.

The Nerve Growth Factor (NGF) belongs to the neurothrophins protein family involved in the survival of neurons in the nervous system. The interaction of NGF with its high-affinity receptor TrkA mediates different cellular pathways related to Alzheimer's disease, pain, ocular dysfunction, and cancer. Therefore, targeting NGF-TrkA interaction represents a valuable strategy for the development of new therapeutic agents. In recent years, experimental studies have revealed that peptides belonging to the N-terminal domain of NGF are able to partly mimic the biological activity of the whole protein paving the way towards the development of small peptides that can selectively target specific signaling pathways. Hence, understanding the molecular basis of the interaction between the N-terminal segment of NGF and TrkA is fundamental for the rational design of new peptides mimicking the NGF N-terminal domain. In this study, molecular dynamics simulation, binding free energy calculations and per-residue energy decomposition analysis were combined in order to explore the molecular recognition pattern between the experimentally active NGF(1-14) peptide and TrkA. The results highlighted the importance of His4, Arg9 and Glu11 as crucial residues for the stabilization of NGF(1-14)-TrkA interaction, thus suggesting useful insights for the structure-based design of new therapeutic peptides able to modulate NGF-TrkA interaction.