Thermal Titration Molecular Dynamics (TTMD): Not Your Usual Post-Docking Refinement.

Molecular docking is one of the most widely used computational approaches in the field of rational drug design, thanks to its favorable balance between the rapidity of execution and the accuracy of provided results. Although very efficient in exploring the conformational degrees of freedom available to the ligand, docking programs can sometimes suffer from inaccurate scoring and ranking of generated poses. To address this issue, several post-docking filters and refinement protocols have been proposed throughout the years, including pharmacophore models and molecular dynamics simulations. In this work, we present the first application of Thermal Titration Molecular Dynamics (TTMD), a recently developed method for the qualitative estimation of protein-ligand unbinding kinetics, to the refinement of docking results. TTMD evaluates the conservation of the native binding mode throughout a series of molecular dynamics simulations performed at progressively increasing temperatures with a scoring function based on protein-ligand interaction fingerprints. The protocol was successfully applied to retrieve the native-like binding pose among a set of decoy poses of drug-like ligands generated on four different pharmaceutically relevant biological targets, including casein kinase 1δ, casein kinase 2, pyruvate dehydrogenase kinase 2, and SARS-CoV-2 main protease.

Identification of Potential Antiviral Inhibitors from Hydroxychloroquine and 1,2,4,5-Tetraoxanes Analogues and Investigation of the Mechanism of Action in SARS-CoV-2.

This study aimed to identify potential inhibitors and investigate the mechanism of action on SARS-CoV-2 ACE2 receptors using a molecular modeling study and theoretical determination of biological activity. Hydroxychloroquine was used as a pivot structure and antimalarial analogues of 1,2,4,5 tetraoxanes were used for the construction and evaluation of pharmacophoric models. The pharmacophore-based virtual screening was performed on the Molport® database (~7.9 million compounds) and obtained 313 structures. Additionally, a pharmacokinetic study was developed, obtaining 174 structures with 99% confidence for human intestinal absorption and penetration into the blood-brain barrier (BBB); posteriorly, a study of toxicological properties was realized. Toxicological predictions showed that the selected molecules do not present a risk of hepatotoxicity, carcinogenicity, mutagenicity, and skin irritation. Only 54 structures were selected for molecular docking studies, and five structures showed binding affinity (ΔG) values satisfactory for ACE2 receptors (PDB 6M0J), in which the molecule MolPort-007-913-111 had the best ΔG value of -8.540 Kcal/mol, followed by MolPort-002-693-933 with ΔG = -8.440 Kcal/mol. Theoretical determination of biological activity was realized for 54 structures, and five molecules showed potential protease inhibitors. Additionally, we investigated the Mpro receptor (6M0K) for the five structures via molecular docking, and we confirmed the possible interaction with the target. In parallel, we selected the TopsHits 9 with antiviral potential that evaluated synthetic accessibility for future synthesis studies and in vivo and in vitro tests.

Molecular Docking and Molecular Dynamics Simulations Discover Curcumin Analogue as a Plausible Dual Inhibitor for SARS-CoV-2.

Recently, the world has been witnessing a global pandemic with no effective therapeutics yet, while cancer continues to be a major disease claiming many lives. The natural compound curcumin is bestowed with multiple medicinal applications in addition to demonstrating antiviral and anticancer activities. In order to elucidate the impact of curcumin on COVID-19 and cancer, the current investigation has adapted several computational techniques to unfold its possible inhibitory activity. Accordingly, curcumin and similar compounds and analogues were retrieved and assessed for their binding affinities at the binding pocket of SARS-CoV-2 main protease and DDX3. The best binding pose was escalated to molecular dynamics simulation (MDS) studies to assess the time dependent stability. Our findings have rendered one compound that has demonstrated good molecular dock score complemented by key residue interactions and have shown stable MDS results inferred by root mean square deviation (RMSD), radius of gyration (Rg), binding mode, hydrogen bond interactions, and interaction energy. Essential dynamics results have shown that the systemadapts minimum energy conformation to attain a stable state. The discovered compound (curA) could act as plausible inhibitor against SARS-CoV-2 and DDX3. Furthermore, curA could serve as a chemical scaffold for designing and developing new compounds.

Interaction of Spike protein and lipid membrane of SARS-CoV-2 with Ursodeoxycholic acid, an in-silico analysis.

Numerous repositioned drugs have been sought to decrease the severity of SARS-CoV-2 infection. It is known that among its physicochemical properties, Ursodeoxycholic Acid (UDCA) has a reduction in surface tension and cholesterol solubilization, it has also been used to treat cholesterol gallstones and viral hepatitis. In this study, molecular docking was performed with the SARS-CoV-2 Spike protein and UDCA. In order to confirm this interaction, we used Molecular Dynamics (MD) in "SARS-CoV-2 Spike protein-UDCA". Using another system, we also simulated MD with six UDCA residues around the Spike protein at random, naming this "SARS-CoV-2 Spike protein-6UDCA". Finally, we evaluated the possible interaction between UDCA and different types of membranes, considering the possible membrane conformation of SARS-CoV-2, this was named "SARS-CoV-2 membrane-UDCA". In the "SARS-CoV-2 Spike protein-UDCA", we found that UDCA exhibits affinity towards the central region of the Spike protein structure of - 386.35 kcal/mol, in a region with 3 alpha helices, which comprises residues from K986 to C1032 of each monomer. MD confirmed that UDCA remains attached and occasionally forms hydrogen bonds with residues R995 and T998. In the presence of UDCA, we observed that the distances between residues atoms OG1 and CG2 of T998 in the monomers A, B, and C in the prefusion state do not change and remain at 5.93 ± 0.62 and 7.78 ± 0.51 Å, respectively, compared to the post-fusion state. Next, in "SARS-CoV-2 Spike protein-6UDCA", the three UDCA showed affinity towards different regions of the Spike protein, but only one of them remained bound to the region between the region's heptad repeat 1 and heptad repeat 2 (HR1 and HR2) for 375 ps of the trajectory. The RMSD of monomer C was the smallest of the three monomers with a value of 2.89 ± 0.32, likewise, the smallest RMSF was also of the monomer C (2.25 ± 056). In addition, in the simulation of "SARS-CoV-2 membrane-UDCA", UDCA had a higher affinity toward the virion-like membrane; where three of the four residues remained attached once they were close (5 Å, to the centre of mass) to the membrane by 30 ns. However, only one of them remained attached to the plasma-like membrane and this was in a cluster of cholesterol molecules. We have shown that UDCA interacts in two distinct regions of Spike protein sequences. In addition, UDCA tends to stay bound to the membrane, which could potentially reduce the internalization of SARS-CoV-2 in the host cell.

Medical Significance of Uterine Corpus Endometrial Carcinoma Patients Infected With SARS-CoV-2 and Pharmacological Characteristics of Plumbagin.

Background: Clinically, evidence shows that uterine corpus endometrial carcinoma (UCEC) patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may have a higher death-rate. However, current anti-UCEC/coronavirus disease 2019 (COVID-19) treatment is lacking. Plumbagin (PLB), a pharmacologically active alkaloid, is an emerging anti-cancer inhibitor. Accordingly, the current report was designed to identify and characterize the anti-UCEC function and mechanism of PLB in the treatment of patients infected with SARS-CoV-2 via integrated in silico analysis. Methods: The clinical analyses of UCEC and COVID-19 in patients were conducted using online-accessible tools. Meanwhile, in silico methods including network pharmacology and biological molecular docking aimed to screen and characterize the anti-UCEC/COVID-19 functions, bio targets, and mechanisms of the action of PLB. Results: The bioinformatics data uncovered the clinical characteristics of UCEC patients infected with SARS-CoV-2, including specific genes, health risk, survival rate, and prognostic index. Network pharmacology findings disclosed that PLB-exerted anti-UCEC/COVID-19 effects were achieved through anti-proliferation, inducing cytotoxicity and apoptosis, anti-inflammation, immunomodulation, and modulation of some of the key molecular pathways associated with anti-inflammatory and immunomodulating actions. Following molecular docking analysis, in silico investigation helped identify the anti-UCEC/COVID-19 pharmacological bio targets of PLB, including mitogen-activated protein kinase 3 (MAPK3), tumor necrosis factor (TNF), and urokinase-type plasminogen activator (PLAU). Conclusions: Based on the present bioinformatic and in silico findings, the clinical characterization of UCEC/COVID-19 patients was revealed. The candidate, core bio targets, and molecular pathways of PLB action in the potential treatment of UCEC/COVID-19 were identified accordingly.

Identification of antiviral phytochemicals as a potential SARS-CoV-2 main protease (Mpro) inhibitor using docking and molecular dynamics simulations.

Novel SARS-CoV-2, an etiological factor of Coronavirus disease 2019 (COVID-19), poses a great challenge to the public health care system. Among other druggable targets of SARS-Cov-2, the main protease (Mpro) is regarded as a prominent enzyme target for drug developments owing to its crucial role in virus replication and transcription. We pursued a computational investigation to identify Mpro inhibitors from a compiled library of natural compounds with proven antiviral activities using a hierarchical workflow of molecular docking, ADMET assessment, dynamic simulations and binding free-energy calculations. Five natural compounds, Withanosides V and VI, Racemosides A and B, and Shatavarin IX, obtained better binding affinity and attained stable interactions with Mpro key pocket residues. These intermolecular key interactions were also retained profoundly in the simulation trajectory of 100 ns time scale indicating tight receptor binding. Free energy calculations prioritized Withanosides V and VI as the top candidates that can act as effective SARS-CoV-2 Mpro inhibitors.

Inhibition of Cysteine Proteases by 6,6'-Dihydroxythiobinupharidine (DTBN) from Nuphar lutea.

The specificity of inhibition by 6,6'-dihydroxythiobinupharidine (DTBN) on cysteine proteases was demonstrated in this work. There were differences in the extent of inhibition, reflecting active site structural-steric and biochemical differences. Cathepsin S (IC50 = 3.2 µM) was most sensitive to inhibition by DTBN compared to Cathepsin B, L and papain (IC50 = 1359.4, 13.2 and 70.4 µM respectively). DTBN is inactive for the inhibition of Mpro of SARS-CoV-2. Docking simulations suggested a mechanism of interaction that was further supported by the biochemical results. In the docking results, it was shown that the cysteine sulphur of Cathepsin S, L and B was in close proximity to the DTBN thiaspirane ring, potentially forming the necessary conditions for a nucleophilic attack to form a disulfide bond. Covalent docking and molecular dynamic simulations were performed to validate disulfide bond formation and to determine the stability of Cathepsins-DTBN complexes, respectively. The lack of reactivity of DTBN against SARS-CoV-2 Mpro was attributed to a mismatch of the binding conformation of DTBN to the catalytic binding site of Mpro. Thus, gradations in reactivity among the tested Cathepsins may be conducive for a mechanism-based search for derivatives of nupharidine against COVID-19. This could be an alternative strategy to the large-scale screening of electrophilic inhibitors.

Network pharmacology and molecular docking analysis on mechanisms of Tibetan Hongjingtian (Rhodiola crenulata) in the treatment of COVID-19.

Introduction. Coronavirus disease 2019 (COVID-19) is a highly contagious disease and ravages the world.Hypothesis/Gap Statement. We proposed that R. crenulata might have potential value in the treatment of COVID-19 patients by regulating the immune response and inhibiting cytokine storm.Aim. We aimed to explore the potential molecular mechanism for Rhodiola crenulata (R. crenulata), against the immune regulation of COVID-19, and to provide a referenced candidate Tibetan herb (R. crenulata) to overcome COVID-19.Methodology. Components and targets of R. crenulata were retrieved from the TCMSP database. GO analysis and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment were built by R bioconductor package to explore the potential biological effects for targets of R. crenulata. The R. crenulata-compound-target network, target pathway network and protein-protein interaction (PPI) network were constructed using Cytoscape 3.3.0. Autodock 4.2 and Discovery Studio software were applied for molecular docking.Result. Four bioactive components (quercetin, kaempferol, kaempferol-3-O-α-l-rhamnoside and tamarixetin) and 159 potential targets of R. crenulata were identified from the TCMSP database. The result of GO annotation and KEGG-pathway-enrichment analyses showed that target genes of R. crenulata were associated with inflammatory response and immune-related signalling pathways, especially IL-17 signalling pathway, and TNF signalling pathway. Targets-pathway network and PPI network showed that IL-6, IL-1B and TNF-α were considered to be hub genes. Molecular docking showed that core compound (quercetin) had a certain affinity with IL-1ß, IL-6 and TNF-α.Conclusion. R. crenulata might play an anti-inflammatory and immunoregulatory role in the cytokine storm of COVID-19.

Ayurveda botanicals in COVID-19 management: An in silico multi-target approach.

The Coronavirus disease (COVID-19) caused by the virus SARS-CoV-2 has become a global pandemic in a very short time span. Currently, there is no specific treatment or vaccine to counter this highly contagious disease. There is an urgent need to find a specific cure for the disease and global efforts are directed at developing SARS-CoV-2 specific antivirals and immunomodulators. Ayurvedic Rasayana therapy has been traditionally used in India for its immunomodulatory and adaptogenic effects, and more recently has been included as therapeutic adjuvant for several maladies. Amongst several others, Withania somnifera (Ashwagandha), Tinospora cordifolia (Guduchi) and Asparagus racemosus (Shatavari) play an important role in Rasayana therapy. The objective of this study was to explore the immunomodulatory and anti SARS-CoV2 potential of phytoconstituents from Ashwagandha, Guduchi and Shatavari using network pharmacology and docking. The plant extracts were prepared as per ayurvedic procedures and a total of 31 phytoconstituents were identified using UHPLC-PDA and mass spectrometry studies. To assess the immunomodulatory potential of these phytoconstituents an in-silico network pharmacology model was constructed. The model predicts that the phytoconstituents possess the potential to modulate several targets in immune pathways potentially providing a protective role. To explore if these phytoconstituents also possess antiviral activity, docking was performed with the Spike protein, Main Protease and RNA dependent RNA polymerase of the virus. Interestingly, several phytoconstituents are predicted to possess good affinity for the three targets, suggesting their application for the termination of viral life cycle. Further, predictive tools indicate that there would not be adverse herb-drug pharmacokinetic-pharmacodynamic interactions with concomitantly administered drug therapy. We thus make a compelling case to evaluate the potential of these Rasayana botanicals as therapeutic adjuvants in the management of COVID-19 following rigorous experimental validation.

SARS-CoV-2 entry inhibitors by dual targeting TMPRSS2 and ACE2: An in silico drug repurposing study.

The coronavirus disease (COVID-19) is spreading between human populations mainly through nasal droplets. Currently, the vaccines have great hope, but it takes years for testing its efficacy in human. As there is no specific drug treatment available for COVID-19 pandemic, we explored in silico repurposing of drugs with dual inhibition properties by targeting transmembrane serine protease 2 (TMPRSS2) and human angiotensin-converting enzyme 2 (ACE2) from FDA-approved drugs. The TMPRSS2 and ACE2 dual inhibitors in COVID-19 would be a novel antiviral class of drugs called "entry inhibitors." For this purpose, approximately 2800 US-FDA approved drugs were docked using a virtual docking tool with the targets TMPRSS2 and ACE2. The best-fit drugs were selected as per docking scores and visual outcomes. Later on, drugs were selected on the basis of molecular dynamics simulations. The drugs alvimopan, arbekacin, dequalinum, fleroxacin, lopinavir, and valrubicin were shortlisted by visual analysis and molecular dynamics simulations. Among these, lopinavir and valrubicin were found to be superior in terms of dual inhibition. Thus, lopinavir and valrubicin have the potential of dual-target inhibition whereby preventing SARS-CoV-2 entry to the host. For repurposing of these drugs, further screening in vitro and in vivo would help in exploring clinically.

Computational study of the therapeutic potentials of a new series of imidazole derivatives against SARS-CoV-2.

Owing to the urgent need for therapeutic interventions against the SARS-coronavirus 2 (SARS-CoV-2) pandemic, we employed an in silico approach to evaluate the SARS-CoV-2 inhibitory potential of newly synthesized imidazoles. The inhibitory potentials of the compounds against SARS-CoV-2 drug targets - main protease (Mpro), spike protein (Spro) and RNA-dependent RNA polymerase (RdRp) were investigated through molecular docking analysis. The binding free energy of the protein-ligand complexes were estimated, pharmacophore models were generated and the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of the compounds were determined. The compounds displayed various levels of binding affinities for the SARS-CoV-2 drug targets. Bisimidazole C2 scored highest against all the targets, with its aromatic rings including the two imidazole groups contributing to the binding. Among the phenyl-substituted 1H-imidazoles, C9 scored highest against all targets. C11 scored highest against Spro and C12 against Mpro and RdRp among the thiophene-imidazoles. The compounds interacted with HIS 41 - CYS 145 and GLU 288 - ASP 289 - GLU 290 of Mpro, ASN 501 of Spro receptor binding motif and some active site amino acids of RdRp. These novel imidazole compounds could be further developed as drug candidates against SARS-CoV-2 following lead optimization and experimental studies.

Main protease inhibitors and drug surface hotspots for the treatment of COVID-19: A drug repurposing and molecular docking approach.

Here, drug repurposing and molecular docking were employed to screen approved MPP inhibitors and their derivatives to suggest a specific therapeutic agent for the treatment of COVID-19. The approved MPP inhibitors against HIV and HCV were prioritized, while RNA dependent RNA Polymerase (RdRp) inhibitor remdesivir including Favipiravir, alpha-ketoamide were studied as control groups. The target drug surface hotspot was also investigated through the molecular docking technique. Molecular dynamics was performed to determine the binding stability of docked complexes. Absorption, distribution, metabolism, and excretion analysis was conducted to understand the pharmacokinetics and drug-likeness of the screened MPP inhibitors. The results of the study revealed that Paritaprevir (-10.9 kcal/mol) and its analog (CID 131982844) (-16.3 kcal/mol) showed better binding affinity than the approved MPP inhibitors compared in this study, including remdesivir, Favipiravir, and alpha-ketoamide. A comparative study among the screened putative MPP inhibitors revealed that the amino acids T25, T26, H41, M49, L141, N142, G143, C145, H164, M165, E166, D187, R188, and Q189 are at potentially critical positions for being surface hotspots in the MPP of SARS-CoV-2. The top 5 predicted drugs (Paritaprevir, Glecaprevir, Nelfinavir, and Lopinavir) and the topmost analog showed conformational stability in the active site of the SARS-CoV-2 MP protein. The study also suggested that Paritaprevir and its analog (CID 131982844) might be effective against SARS-CoV-2. The current findings are limited to in silico analysis and lack in vivo efficacy testing; thus, we strongly recommend a quick assessment of Paritaprevir and its analog (CID 131982844) in a clinical trial.

Development of potent and selective inhibitors targeting the papain-like protease of SARS-CoV-2.

The COVID-19 pandemic has been disastrous to society and effective drugs are urgently needed. The papain-like protease domain (PLpro) of SARS-CoV-2 (SCoV2) is indispensable for viral replication and represents a putative target for pharmacological intervention. In this work, we describe the development of a potent and selective SCoV2 PLpro inhibitor, 19. The inhibitor not only effectively blocks substrate cleavage and immunosuppressive function imparted by PLpro, but also markedly mitigates SCoV2 replication in human cells, with a submicromolar IC50. We further present a convenient and sensitive activity probe, 7, and complementary assays to readily evaluate SCoV2 PLpro inhibitors in vitro or in cells. In addition, we disclose the co-crystal structure of SCoV2 PLpro in complex with a prototype inhibitor, which illuminates their detailed binding mode. Overall, these findings provide promising leads and important tools for drug discovery aiming to target SCoV2 PLpro.

Computational hunting of natural active compounds as an alternative for Remdesivir to target RNA-dependent polymerase.

The hunt for potential lead/drug molecules from different resources, especially from natural resources, for possible treatment of COVID-19 is ongoing. Several compounds have already been identified, but only a few are good enough to show potential against the virus. Among the identified druggable target proteins of SARS-CoV-2, this study focuses on non-structural RNA-dependent RNA polymerase protein (RdRp), a well-known enzyme for both viral genome replication and viral mRNA synthesis, and is therefore considered to be the primary target. In this study, the virtual screening followed by an in-depth docking study of the Compounds Library found that natural compound Cyclocurcumin and Silybin B have strong interaction with RdRp and much better than the remdesivir with free binding energy and inhibition constant value as êzŒ-6.29 kcal/mol and 58.39 µMêzŒ, and êzŒ-7.93kcal/mol and 45.3 µMêzŒ, respectively. The finding indicated that the selected hits (Cyclocurcumin and Silybin B) could act as non-nucleotide anti-polymerase agents, and can be further optimized as a potential inhibitor of RdRp by benchwork experiments.

Computational insights into tetracyclines as inhibitors against SARS-CoV-2 Mpro via combinatorial molecular simulation calculations.

The COVID-19 pandemic raised by SARS-CoV-2 is a public health emergency. However, lack of antiviral drugs and vaccine against human coronaviruses demands a concerted approach to challenge the SARS-CoV-2 infection. Under limited resource and urgency, combinatorial computational approaches to identify the potential inhibitor from known drugs could be applied against risen COVID-19 pandemic. Thereof, this study attempted to purpose the potent inhibitors from the approved drug pool against SARS-CoV-2 main protease (Mpro). To circumvent the issue of lead compound from available drugs as antivirals, antibiotics with broad spectrum of viral activity, i.e. doxycycline, tetracycline, demeclocycline, and minocycline were chosen for molecular simulation analysis against native ligand N3 inhibitor in SARS-CoV-2 Mpro crystal structure. Molecular docking simulation predicted the docking score >-7 kcal/mol with significant intermolecular interaction at the catalytic dyad (His41 and Cys145) and other essential substrate binding residues of SARS-CoV-2 Mpro. The best ligand conformations were further studied for complex stability and intermolecular interaction profiling with respect to time under 100 ns classical molecular dynamics simulation, established the significant stability and interactions of selected antibiotics by comparison to N3 inhibitor. Based on combinatorial molecular simulation analysis, doxycycline and minocycline were selected as potent inhibitor against SARS-CoV-2 Mpro which can used in combinational therapy against SARS-CoV-2 infection.

In silico Nigellidine (N. sativa) bind to viral spike/active-sites of ACE1/2, AT1/2 to prevent COVID-19 induced vaso-tumult/vascular-damage/comorbidity.

COVID-19, a global-pandemic binds human-lung-ACE2. ACE2 causes vasodilatation. ACE2 works in balance with ACE1. The vaso-status maintains blood-pressure/vascular-health which is demolished in Covid-19 manifesting aldosterone/salt-deregulations/inflammations/endothelial-dysfunctions/hyper-hypo- tension, sepsis/hypovolemic-shock and vessel-thrombosis/coagulations. Here, nigellidine, an indazole-alkaloid was analyzed by molecular-docking for binding to different Angiotensin-binding-proteins (enzymes, ACE1(6en5)/ACE2(4aph)/receptors, AT1(6os1)/AT2(5xjm)) and COVID-19 spike-glycoprotein(6vsb). Nigellidine strongly binds to the spike-protein at the hinge-region/active-site-opening which may hamper proper-binding of nCoV2-ACE2 surface. Nigellidine effectively binds in the Angiotensin- II binding-site/entry-pocket (-7.54 kcal/mol, -211.76, Atomic-Contact-Energy; ACE-value) of ACE2 (Ki 8.68 and 8.3 µmol) in comparison to known-binder EGCG (-4.53) and Theaflavin-di-gallate (-2.85). Nigellidine showed strong-binding (Ki, 50.93 µmol/binding-energy -5.48 kcal/mol) to mono/multi-meric ACE1. Moreover, it binds Angiotensin-receptors, AT1/AT2 (Ki, 42.79/14.22 µmol, binding-energy, -5.96/-6.61 kcal/mol) at active-sites, respectively. This article reports the novel binding of nigellidine and subsequent blockage of angiotensin-binding proteins. The ACEs-blocking could restore Angiotensin-level, restrict vaso-turbulence in Covid patients and receptor-blocking might stop inflammatory/vascular impairment. Nigellidine may slowdown the vaso-fluctuations due to Angiotensin-deregulations in Covid patients. Angiotensin II-ACE2 binding (ACE-value -294.81) is more favorable than nigellidine-ACE2. Conversely, nigellidine-ACE1 binding-energy/Ki is lower than nigellidine-ACE2 values indicating a balanced-state between constriction-dilatation. Moreover, nigellidine binds to the viral-spike, closer-proximity to its ACE2 binding-domain. Taken together, Covid patients/elderly-patients, comorbid-patients (with hypertensive/diabetic/cardiac/renal-impairment, counting >80% of non-survivors) could be greatly benefited.

Evolutionary and structural analysis elucidates mutations on SARS-CoV2 spike protein with altered human ACE2 binding affinity.

The recognition of ACE2 by the receptor-binding domain (RBD) of spike protein mediates host cell entry. The objective of the work is to identify SARS-CoV2 spike variants that emerged during the pandemic and evaluate their binding affinity with ACE2. Evolutionary analysis of 2178 SARS-CoV2 genomes identifies RBD variants that are under selection bias. The binding efficacy of these RBD variants to the ACE2 has been analyzed by using protein-protein docking and binding free energy calculations. Pan-proteomic analysis reveals 113 mutations among them 33 are parsimonious. Evolutionary analysis reveals five RBD variants A348T, V367F, G476S, V483A, and S494P are under strong positive selection bias. Variations at these sites alter the ACE2 binding affinity. A348T, G476S, and V483A variants display reduced affinity to ACE2 in comparison to the Wuhan SARS-CoV2 spike protein. While the V367F and S494P population variants display a higher binding affinity towards human ACE2. Reorientation of several crucial residues at the RBD-ACE2 interface facilitates additional hydrogen bond formation for the V367F variant which enhances the binding energy during ACE2 recognition. On the other hand, the enhanced binding affinity of S494P is attributed to strong interfacial complementarity between the RBD and ACE2.

Immunoinformatics and Molecular Docking Studies Predicted Potential Multiepitope-Based Peptide Vaccine and Novel Compounds against Novel SARS-CoV-2 through Virtual Screening.

BACKGROUND: Coronaviruses (CoVs) are enveloped positive-strand RNA viruses which have club-like spikes at the surface with a unique replication process. Coronaviruses are categorized as major pathogenic viruses causing a variety of diseases in birds and mammals including humans (lethal respiratory dysfunctions). Nowadays, a new strain of coronaviruses is identified and named as SARS-CoV-2. Multiple cases of SARS-CoV-2 attacks are being reported all over the world. SARS-CoV-2 showed high death rate; however, no specific treatment is available against SARS-CoV-2. METHODS: In the current study, immunoinformatics approaches were employed to predict the antigenic epitopes against SARS-CoV-2 for the development of the coronavirus vaccine. Cytotoxic T-lymphocyte and B-cell epitopes were predicted for SARS-CoV-2 coronavirus protein. Multiple sequence alignment of three genomes (SARS-CoV, MERS-CoV, and SARS-CoV-2) was used to conserved binding domain analysis. RESULTS: The docking complexes of 4 CTL epitopes with antigenic sites were analyzed followed by binding affinity and binding interaction analyses of top-ranked predicted peptides with MHC-I HLA molecule. The molecular docking (Food and Drug Regulatory Authority library) was performed, and four compounds exhibiting least binding energy were identified. The designed epitopes lead to the molecular docking against MHC-I, and interactional analyses of the selected docked complexes were investigated. In conclusion, four CTL epitopes (GTDLEGNFY, TVNVLAWLY, GSVGFNIDY, and QTFSVLACY) and four FDA-scrutinized compounds exhibited potential targets as peptide vaccines and potential biomolecules against deadly SARS-CoV-2, respectively. A multiepitope vaccine was also designed from different epitopes of coronavirus proteins joined by linkers and led by an adjuvant. CONCLUSION: Our investigations predicted epitopes and the reported molecules that may have the potential to inhibit the SARS-CoV-2 virus. These findings can be a step towards the development of a peptide-based vaccine or natural compound drug target against SARS-CoV-2.

Drug design and repurposing with DockThor-VS web server focusing on SARS-CoV-2 therapeutic targets and their non-synonym variants.

The COVID-19 caused by the SARS-CoV-2 virus was declared a pandemic disease in March 2020 by the World Health Organization (WHO). Structure-Based Drug Design strategies based on docking methodologies have been widely used for both new drug development and drug repurposing to find effective treatments against this disease. In this work, we present the developments implemented in the DockThor-VS web server to provide a virtual screening (VS) platform with curated structures of potential therapeutic targets from SARS-CoV-2 incorporating genetic information regarding relevant non-synonymous variations. The web server facilitates repurposing VS experiments providing curated libraries of currently available drugs on the market. At present, DockThor-VS provides ready-for-docking 3D structures for wild type and selected mutations for Nsp3 (papain-like, PLpro domain), Nsp5 (Mpro, 3CLpro), Nsp12 (RdRp), Nsp15 (NendoU), N protein, and Spike. We performed VS experiments of FDA-approved drugs considering the therapeutic targets available at the web server to assess the impact of considering different structures and mutations to identify possible new treatments of SARS-CoV-2 infections. The DockThor-VS is freely available at www.dockthor.lncc.br .

Optimization Rules for SARS-CoV-2 Mpro Antivirals: Ensemble Docking and Exploration of the Coronavirus Protease Active Site.

Coronaviruses are viral infections that have a significant ability to impact human health. Coronaviruses have produced two pandemics and one epidemic in the last two decades. The current pandemic has created a worldwide catastrophe threatening the lives of over 15 million as of July 2020. Current research efforts have been focused on producing a vaccine or repurposing current drug compounds to develop a therapeutic. There is, however, a need to study the active site preferences of relevant targets, such as the SARS-CoV-2 main protease (SARS-CoV-2 Mpro), to determine ways to optimize these drug compounds. The ensemble docking and characterization work described in this article demonstrates the multifaceted features of the SARS-CoV-2 Mpro active site, molecular guidelines to improving binding affinity, and ultimately the optimization of drug candidates. A total of 220 compounds were docked into both the 5R7Z and 6LU7 SARS-CoV-2 Mpro crystal structures. Several key preferences for strong binding to the four subsites (S1, S1', S2, and S4) were identified, such as accessing hydrogen binding hotspots, hydrophobic patches, and utilization of primarily aliphatic instead of aromatic substituents. After optimization efforts using the design guidelines developed from the molecular docking studies, the average docking score of the parent compounds was improved by 6.59 -log10(Kd) in binding affinity which represents an increase of greater than six orders of magnitude. Using the optimization guidelines, the SARS-CoV-2 Mpro inhibitor cinanserin was optimized resulting in an increase in binding affinity of 4.59 -log10(Kd) and increased protease inhibitor bioactivity. The results of molecular dynamic (MD) simulation of cinanserin-optimized compounds CM02, CM06, and CM07 revealed that CM02 and CM06 fit well into the active site of SARS-CoV-2 Mpro [Protein Data Bank (PDB) accession number 6LU7] and formed strong and stable interactions with the key residues, Ser-144, His-163, and Glu-166. The enhanced binding affinity produced demonstrates the utility of the design guidelines described. The work described herein will assist scientists in developing potent COVID-19 antivirals.