Structure-guided pharmacophore based virtual screening, docking, and molecular dynamics to discover repurposed drugs as novel inhibitors against endoribonuclease Nsp15 of SARS-CoV-2.

COVID-19 (Corona Virus Disease of 2019) caused by the novel 'Severe Acute Respiratory Syndrome Coronavirus-2' (SARS-CoV-2) has wreaked havoc on human health and the global economy. As a result, for new medication development, it's critical to investigate possible therapeutic targets against the novel virus. 'Non-structural protein 15' (Nsp15) endonuclease is one of the crucial targets which helps in the replication of virus and virulence in the host immune system. Here, in the current study, we developed the structure-based pharmacophore model based on Nsp15-UMP interactions and virtually screened several databases against the selected model. To validate the screening process, we docked the top hits obtained after secondary filtering (Lipinski's rule of five, ADMET & Topkat) followed by 100 ns molecular dynamics (MD) simulations. Next, to revalidate the MD simulation studies, we have calculated the binding free energy of each complex using the MM-PBSA procedure. The discovered repurposed drugs can aid the rational design of novel inhibitors for Nsp15 of the SARS-CoV-2 enzyme and may be considered for immediate drug development.

Pharmacophore modeling, docking and molecular dynamics simulation for identification of novel human protein kinase C beta (PKCß) inhibitors.

Protein kinase Cß (PKCß) is considered as an attractive molecular target for the treatment of COVID-19-related acute respiratory distress syndrome (ARDS). Several classes of inhibitors have been already identified. In this article, we developed and validated ligand-based PKCß pharmacophore models based on the chemical structures of the known inhibitors. The most accurate pharmacophore model, which correctly predicted more than 70% active compounds of test set, included three aromatic pharmacophore features without vectors, one hydrogen bond acceptor pharmacophore feature, one hydrophobic pharmacophore feature and 158 excluded volumes. This pharmacophore model was used for virtual screening of compound collection in order to identify novel potent PKCß inhibitors. Also, molecular docking of compound collection was performed and 28 compounds which were selected simultaneously by two approaches as top-scored were proposed for further biological research. Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-02075-y.

Synthesis and evaluation of imidazole-bearing chalcones as a potential treatment for pulmonary aspergillosis

Pulmonary aspergillosis (PA) is a category of respiratory illnesses that significantly impacts the lives of immunocompromised individuals. However, new classifications of secondary infections like influenza associated aspergillosis (IAA) and COVID-19 associated pulmonary aspergillosis (CAPA) only exacerbate matters by expanding the demographic beyond the immunocompromised. Meanwhile anti-fungal resistant strains of Aspergillus are causing current treatments to act less effectively. Symptoms can range from mild (difficulty breathing, and expectoration of blood) to severe (multi organ failure, and neurological disease). Millions are affected yearly, and mortality rates range from 20-90% making it imperative to develop novel medicines to curtail this evolving group of diseases. Chalcones and imidazoles are current antifungal pharmacophores used to treat PA. Chalcones are a group of plant-derived flavonoids that have a variety of pharmacological effects, such as, antibacterial, anticancer, antimicrobial, and anti-inflammatory activities. Imidazoles are another class of drug that possess antibacterial, antiprotozoal, and anthelmintic activities. The increase in antifungal resistant Aspergillus and Candida species make it imperative for us to synthesize novel pharmacophores for therapeutic use. Our objective was to synthesize a chalcone and imidazole into a single pharmacophore and to evaluate its effectiveness against three different fungi from the Aspergillus or Candida species. The chalcones were synthesized via the Claisen-Schmidt aldol condensation of 4-(1H-Imizadol-1-yl) benzaldehyde with various substituted acetophenones using aqueous sodium hydroxide in methanol. The anti-fungal activity of the synthesized chalcones were evaluated via a welldiffusion assay against Aspergillus fumigatus, Aspergillus niger, and Candida albicans. The data obtained suggests that chalcone derivatives with electron-withdrawing substituents are moderately effective against Aspergillus and has the potential for further optimization as a treatment for pulmonary aspergillosis. This project was supported by grants from the National Institutes of Health (NIH), National Institute of General Medicine Sciences (NIGMS), IDeA Networks of Biomedical Research Excellence (INBRE), Award number: P20GM103466. The content is solely the responsibility of the authors and do not necessarily represent the official views of the NIH.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

An In-silico Multi-Targeted Approach in Search of Potential Drug Candi-date(s) Against SARS-CoV-2 Lung Infection

Background: The multitargeted computational approach for the design of drugs to treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lung infection from herbal sources may lead to compound(s) that is/are safe (derived from natural sources), effective (act on predefined targets) and broad spectrum (active in both, adult and juvenile population). Objective(s): The present work aims at developing a specific and effective treatment for a lung infection in both the adult and juvenile population, caused due to SARS-CoV-2 through a computational approach. Method(s): A systematic virtual screening of 27 phytoconstituents from 11 Indian herbs with antiviral, anti-inflammatory, and immunomodulatory activity was performed. After applying the Lipinski rule of five, 19 compounds that fitted well were subjected to molecular docking studies using Molegro virtual docker 6.0 with two targets viz. SARS-CoV-2 main protease (Mpro) (PDB ID 6LU7) and ACE receptor (PDB ID 6M0J). The best-docked complexes were used to develop a merged feature pharmacophore using Lig-andscout software, to know the structural requirements to develop multitarget inhibitor(s) of SARS-CoV-2. Drug likeliness and ADMET studies were also performed. Result(s): The results revealed that Syringin, a glycoside from Tinospora cordifolia, has a good binding affinity towards both targets as compared to Remdesivir. Furthermore, drug likeliness and ADMET studies established its better bioavailability and low toxicity. Conclusion(s): The pharmacophores developed from protein-ligand complexes provided an important understanding to design multitarget inhibitor(s) of SARS-CoV-2 to treat COVID-19 lung infection in both the adult and juvenile populations. Syringin may be subjected to further wet-lab studies to establish the results obtained through in-silico studies.Copyright © 2022 Bentham Science Publishers.

Computational Study Reveals the Inhibitory Effects of Chemical Constituents from Azadirachta indica (Indian Neem) Against Delta and Omicron Variants of SARS-CoV-2

Background: The newly emerged delta and omicron variants of severe acute respiratory syn-drome coronavirus (SARS-CoV-2) have affected millions of individuals globally with increased transmis-sible and infectivity rates. Although, numerous vaccines are available or under clinical trials to combat the SARS-CoV-2 and its variant, still, a therapeutic agent is awaited. Objective(s): The present work is focused on rigorous screening of chemical constituents of Azadirachta indica (A. indica) against delta and omicron variants of SARS-CoV-2 via inhibition of S-glycoprotein. Method(s): Total, 10 compounds of A. indica were subjected to molecular docking and pharmacophore modeling studies against the S-glycoprotein of delta and omicron variants of SARS-CoV-2. Furthermore, homology modeling was performed for omicron S-glycoprotein with the help of SWISS-MODEL and aligned by PyMOL software. Later on, the residues of protein were verified in the allowed region via Ramachandran plot. In addition, our docking results have also been validated by MMGBSA binding free energy calculations. Result(s): Our computed study demonstrated that nimbolinin B12-methyl ether and nimbidinin showed promising docking scores (>-6.0) as compared to docking scores (< 6.0) of reference drug 'camostat' against S-glycoproteins of both delta and omicron variants. Redocking by using MMGBSA calculation also reveals that both these compounds can effectively bind within the pockets of said protein receptors Conclusion(s): Nimbolinin B12-methyl ether and nimbidinin have potent anti-SARS-CoV activity against delta and omicron variants and thus, A. indica might be a useful source for developing novel anti-SARS-CoV-2 therapeutic agents.Copyright © 2022 Bentham Science Publishers.

Identification of SARS-CoV-2 RNA dependent RNA polymerase inhibitors using pharmacophore modelling, molecular docking and molecular dynamics simulation approaches.

The RNA-dependent RNA polymerase (RdRp) is one of the crucial enzymes in severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) catalysing the replication of RNA, therefore acts as a potential target for antiviral drug design. The fixation of a ligand in the active site of RdRp may alter the SARS-CoV-2 life cycle. Present work aimed at identifying novel inhibitors of the SARS-CoV-2 RdRp enzyme by performing pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation (MDS). Initially, the pharmacophore model of SARS-CoV-2 RdRp was constructed and the resulting model was used to screen compounds from ChEMBL, ZINC and PubChem databases. During the investigation, 180 compounds were screened using the above model and subjected to molecular docking with RdRp. Two compounds viz. ChEMBL1276156 and PubChem135548348 showed a strong binding affinity with RdRp than its standard inhibitor, Remdesivir. Toxicity prediction of these two compounds reveals their non-toxic nature. These compounds were further subjected to MDS for 100 ns to check their stability after binding with RdRp. The MDS of RdRp-ChEMBL1276156 and RdRp-PubChem135548348 complexes show enhanced stability in comparison to the RdRp-Remdesivir complex. The average interaction energy calculated after 100 ns of MDS was -146.56 and -172.68 KJ mol-1 for RdRp-CHEMBL1276156 complex and RdRp-PubChem135548348 complex, respectively, while -59.90 KJ mol-1 for RdRp-Remdesivir complex. The current investigation reveals that these two compounds are potent inhibitors of SARS-CoV-2 RdRp and they could be tested in the experimental condition to evaluate their efficacy against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Molecular dynamics simulation, 3D-pharmacophore and scaffold hopping analysis in the design of multi-target drugs to inhibit potential targets of COVID-19.

SARS-CoV-2 has posed serious threat to the health and has inflicted huge costs in the world. Discovering potent compounds is a critical step to inhibit coronavirus. 3CLpro and RdRp are the most conserved targets associated with COVID-19. In this study, three-dimensional pharmacophore modeling, scaffold hopping, molecular docking, structure-based virtual screening, QSAR-based ADMET predictions and molecular dynamics analysis were used to identify inhibitors for these targets. Binding free energies estimated by molecular docking for each ligand in different binding sites of RdRp were used to predict the active site. Previously reported active 3CLpro and RdRp inhibitors were used to build a pharmacophore model to develop different scaffolds. Structure-based simulations and pharmacophore modeling based on Hip Hop algorithm converged in a state that suggest hydrogen bond acceptor and donor features have a critical role in the two binding sites. Further validations indicated that the best pharmacophore model has fairly good correlation values compared with approved inhibitors. Structure-based simulation results approved that GLu166 and Gln189 in 3CLpro and Lys551 and Glu811 in RdRp, are critical residues for dual activities. Ten compounds were extracted from pharmacophore-based virtual screening in six databases. The results, gained by repurposing approach, suggest the effectiveness of these ten compounds with different scaffolds as possible inhibitors of the two targets. Some quinoline-based hybrid derivatives also were designed. QSAR descriptors plot predicted that the scaffolds have had accepted pharmacokinetic profiles. Multiple molecular dynamics simulations in 100 ns and MM/PBSA studies of some reference inhibitors and the novel compounds in complex with both targets demonstrated stable complexes and confirmed the interaction modes. Based on different computational methods, COVID-19 multi-target inhibitors are proposed.

Virtual screening and structure-based 3D pharmacophore approach to identify small-molecule inhibitors of SARS-CoV-2 Mpro.

The outbreak caused by a coronavirus 2 has required quick and potential treatment strategies. The main protease enzyme Mpro plays an important role in the viral replication which renders it an important target for discovering SARS-CoV-2 inhibitors. In this study, 3D pharmacophore structure-based virtual screening and molecular docking were conducted using MOE and Bristol University Docking Engine (BUDE). Around 400,000 molecules of ZINC15 database were docked against the crystal structure of main protease, followed by 3D pharmacophore filtration. Six top-ranked hits (ZINC58717986, ZINC60399606, ZINC58662884, ZINC45988635, ZINC54706757 and ZINC17320595) were identified based on their strong spatial affinity and forming H-bonds with key residues H41, E166, Q189 and T190 of the binding pocket of Mpro SARS-CoV-2. The 6 hits subjected to molecular dynamics simulations for 100 ns followed by binding free energy calculations using MM-PBSA technique. Interestingly, three hits showed free binding energy (ΔGbinding) lower than tert-butyl N-[1-[(2S)-1-[[(2S)-4-(benzylamino)-3,4-dioxo-1-[(3S)-2-oxopyrrolidin-3-yl]butan-2-yl]amino]-3-cyclopropyl-1-oxopropan-2-yl]-2-oxopyridin-3-yl]carbamate (α-ketoamide 13 b) (ΔGbinding) -76.67 ± 0.5 kJ/mol which suggested their potential against SARS-CoV-2. The best binding free energy candidates, ZINC58717986 (ΔGbinding) -98.41 ± 0.7 kJ/mol. The second-best hit candidate, ZINC54706757 (ΔGbinding) -83.4 ± 0.6 kJ/mol and the third one ZINC17320595 (ΔGbinding) -78.85 ± 0.5 kJ/mol. Per residue decomposition free energy indicates H41, S46, H164, E166, D187, Q189 and Q192 are hot spot residues while residues M49, M165, L167 and P168 contribute to the hydrophobic interactions. The pharmacokinetic study suggests that the selected 6 hits possess drug-like properties. The 3D pharmacophore virtual screening, molecular dynamics and MM-PBSA approaches facilitated identification 3 promising hits with low free binding energy as SARS-CoV-2 inhibitors.Communicated by Ramaswamy H. Sarma.

Exploiting the co-crystal ligands shape, features and structure-based approaches for identification of SARS-CoV-2 Mpro inhibitors.

SARS-CoV-2 enters the host cell through the ACE2 receptor and replicates its genome using an RNA-Dependent RNA Polymerase (RDRP). The functional RDRP is released from pro-protein pp1ab by the proteolytic activity of Main protease (Mpro) which is encoded within the viral genome. Due to its vital role in proteolysis of viral polyprotein chains, it has become an attractive potential drug target. We employed a hierarchical virtual screening approach to identify small synthetic protease inhibitors. Statistically optimized molecular shape and color-based features (various functional groups) from co-crystal ligands were used to screen different databases through various scoring schemes. Then, the electrostatic complementarity of screened compounds was matched with the most active molecule to further reduce the hit molecules' size. Finally, five hundred eighty-seven molecules were docked in Mpro catalytic binding site, out of which 29 common best hits were selected based on Glide and FRED scores. Five best-fitting compounds in complex with Mpro were subjected to MD simulations to analyze their structural stability and binding affinities with Mpro using MM/GB(PB)SA models. Modeling results suggest that identified hits can act as the lead compounds for designing better active Mpro inhibitors to enhance the chemical space to combat COVID-19.Communicated by Ramaswamy H. Sarma.

Multidimensional virtual screening approaches combined with drug repurposing to identify potential covalent inhibitors of SARS-CoV-2 3CL protease.

The outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused an unprecedented global pandemic, and new cases are still on the rise due to the absence of effective medicines. However, developing new drugs within a short time is extremely difficult. Repurposing the existing drugs provides a fast and effective strategy to identify promising inhibitors. Here we focus on the screening of drugs database for discovering potential covalent inhibitors that target 3-chymotrypsin-like protease (3CLpro), an essential enzyme mediating viral replication and transcription. Firstly, we constructed a receptor-ligand pharmacophore model and verified it through decoy set. The importance of pharmacophore features was evaluated by combining molecular dynamics simulation with interaction analyses. Then, covalent docking was used to perform further screening. According to docking score and Prime/Molecular Mechanics Generalized Born Surface Area (MM-GBSA) score, total ten compounds obtained good scores and successfully established covalent bonds with the catalytic Cys145 residue. They also formed favorable interactions with key residues in active sites and closely integrated with 3CLpro with binding modes similar to known 3CLpro inhibitor. Finally, the top four hits DB08732, DB04653, DB01871 and DB07299 were further subjected to 100 ns molecular dynamics (MD) simulation and MM-GBSA binding free energy calculations. The results suggest that the four candidates show good binding affinities for 3CLpro, which warrants further evaluation for their in-vitro/in-vivo activities. Overall, our research methods provide a valuable reference for discovering promising inhibitors against SARS-CoV-2 and help to fight against the epidemic.Communicated by Ramaswamy H. Sarma.

Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics.

Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19.

Targeting Olokizumab-Interleukin 6 interaction interface to discover novel IL-6 inhibitors.

The IL-6/IL-6R or IL-6/GP130 protein-protein interactions play a significant role in controlling the development of chronic inflammatory diseases, such as rheumatoid arthritis, Castleman disease, psoriasis, and, most recently, COVID-19. Modulating or antagonizing protein-protein interactions of IL6 binding to its receptors by oral drugs promises similar efficacy to biological therapy in patients, namely monoclonal antibodies. In this study, we used a crystal structure of the Fab part of olokizumab in a complex with IL-6 (PDB ID: 4CNI) to uncover starting points for small molecule IL-6 antagonist discovery. Firstly, a structure­based pharmacophore model of the protein active site cavity was generated to identify possible candidates, followed by virtual screening with a significant database Drugbank. After the docking protocol validation, a virtual screening by molecular docking was carried out and a total of 11 top hits were reported. Detailed analysis of the best scoring molecules was performed with ADME/T analysis and molecular dynamics simulation. Furthermore, the Molecular Mechanics-Generalized Born Surface Area (MM/GBSA) technique has been utilized to evaluate the free binding energy. Based on the finding, one newly obtained compound in this study, namely DB15187, may serve as a lead compound for the discovery of IL-6 inhibitors.Communicated by Ramaswamy H. Sarma.

Identification of Natural Lead Compounds against Hemagglutinin-Esterase Surface Glycoprotein in Human Coronaviruses Investigated via MD Simulation, Principal Component Analysis, Cross-Correlation, H-Bond Plot and MMGBSA.

The pandemic outbreak of human coronavirus is a global health concern that affects people of all ages and genders, but there is currently still no effective, approved and potential drug against human coronavirus, as many other coronavirus vaccines have serious side effects while the development of small antiviral inhibitors has gained tremendous attention. For this research, HE was used as a therapeutic target, as the spike protein displays a high binding affinity for both host ACE2 and viral HE glycoprotein. Molecular docking, pharmacophore modelling and virtual screening of 38,000 natural compounds were employed to find out the best natural inhibitor against human coronaviruses with more efficiency and fewer side effects and further evaluated via MD simulation, PCA, DCCR and MMGBSA. The lead compound 'Calceolarioside B' was identified on the basis of pharmacophoric features which depict favorable binding (ΔGbind -37.6799 kcal/mol) with the HE(5N11) receptor that describes positive correlation movements in active site residues with better stability, a robust H-bond network, compactness and reliable ADMET properties. The Fraxinus sieboldiana Blume plant containing the Calceolarioside B compound could be used as a potential inhibitor that shows a higher efficacy and potency with fewer side effects. This research work will aid investigators in the testing and identification of chemicals that are effective and useful against human coronavirus.

Mechanism-based approaches of 1,3,4 thiadiazole scaffolds as potent enzyme inhibitors for cytotoxicity and antiviral activity

Significant progress in understanding cancer pathogenesis, it remains one of the leading causes of death after cardiovascular diseases. Similarly viral infections have emerged from wildlife or re-emerged, generating serious threats to the global health. As a result, there is an urgent need for the development of novel, more effective anticancer and antiviral therapeutics. Scientists, medicinal chemists and researchers are continuously finding novel targets, mechanisms and molecules against theses severe and dangerous infections. Therefore, ongoing extensively study and research emphasizes 1,3,4 thiadiazole pharmacophore have versatile pharmacological actions. Due to mesoionic behaviour of 1,3,4 thiadiazole pharmacophore allows to enter and easily cross biological membrane which allow to interact various biological proteins. In this review study an attempt has been made of various mechanisms involved in cancer and viral prevalence with updated studies done so far. This review study also findings the role of 1,3,4 thiadiazole motif in the management of various cancers and viral infection. This study also highlighting research statics on clinical trials and various patents containing 1,3,4 thiadiazole derivatives. © 2022 The Author(s)

Identifying non-nucleoside inhibitors of RNA-dependent RNA-polymerase of SARS-CoV-2 through per-residue energy decomposition-based pharmacophore modeling, molecular docking, and molecular dynamics simulation.

BACKGROUND AND OBJECTIVE: The current coronavirus disease-2019 (COVID-19) pandemic has triggered a worldwide health and economic crisis. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes the disease and completes its life cycle using the RNA-dependent RNA-polymerase (RdRp) enzyme, a prominent target for antivirals. In this study, we have computationally screened ∼690 million compounds from the ZINC20 database and 11,698 small molecule inhibitors from DrugBank to find existing and novel non-nucleoside inhibitors for SARS-CoV-2 RdRp. METHODS: Herein, a combination of the structure-based pharmacophore modeling and hybrid virtual screening methods, including per-residue energy decomposition-based pharmacophore screening, molecular docking, pharmacokinetics, and toxicity evaluation were employed to retrieve novel as well as existing RdRp non-nucleoside inhibitors from large chemical databases. Besides, molecular dynamics simulation and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) method were used to investigate the binding stability and calculate the binding free energy of RdRp-inhibitor complexes. RESULTS: Based on docking scores and significant binding interactions with crucial residues (Lys553, Arg557, Lys623, Cys815, and Ser816) in the RNA binding site of RdRp, three existing drugs, ZINC285540154, ZINC98208626, ZINC28467879, and five compounds from ZINC20 (ZINC739681614, ZINC1166211307, ZINC611516532, ZINC1602963057, and ZINC1398350200) were selected, and the conformational stability of RdRp due to their binding was confirmed through molecular dynamics simulation. The free energy calculations revealed these compounds possess strong binding affinities for RdRp. In addition, these novel inhibitors exhibited drug-like features, good absorption, distribution, metabolism, and excretion profile and were found to be non-toxic. CONCLUSION: The compounds identified in the study by multifold computational strategy can be validated in vitro as potential non-nucleoside inhibitors of SARS-CoV-2 RdRp and holds promise for the discovery of novel drugs against COVID-19 in future.

Molecular docking, pharmacophore modelling, MD simulation and in silico ADMET study reveals bitter cola constituents as potential inhibitors of SARS-CoV-2 main protease and RNA dependent-RNA polymerase.

A mini survey was employed in the search of herbs and spices which people believe could prevent them from contracting COVID-19. Phytochemicals which have been earlier implicated for the bioactivity of the afore-mentioned herbs and spices were identified through literature search. The phytochemicals were then subjected to pharmacore modelling, molecular docking and molecular dynamics simulation in order to identify phytochemicals that could serve as inhibitors of 3-Chymotryprin-like protease and RNA dependent-RNA polymerase of SARS-CoV-2. The drug-likeness and toxicity profile of the phytochemicals were afterwards predicted via ADMET studies. The mini survey showed ginger, garlic, bitter cola, as the lead-herbs which could find application in anti- COVID-19 therapy. Literature search revealed 27 phytochemicals were implicated for bioactivity of these herbs. Of these 27 phytoconstituents that were docked with 3-chymotrypsin-like protease and RNA dependent-RNA polymerase, the constituents of bitter cola had lower docking scores than other phytochemicals. MD simulation results showed that Garcinia biflavonoid I displayed less comformational changes and the better binding free energy. Also, the garcinia biflavonoids had relatively safe ADMET predictions. Hence, Garcinia biflavonoids and some other constituents of bitter cola could be further modified so as to obtain safe pharmaceutical intervention for the COVID-19 challenge.Communicated by Ramaswamy H. Sarma.

Discovery of natural-derived Mpro inhibitors as therapeutic candidates for COVID-19: Structure-based pharmacophore screening combined with QSAR analysis.

The main protease (Mpro ) is an essential enzyme for the life cycle of SARS-CoV-2 and a validated target for treatment of COVID-19 infection. Structure-based pharmacophore modeling combined with QSAR calculations were employed to identify new chemical scaffolds of Mpro inhibitors from natural products repository. Hundreds of pharmacophore models were manually built from their corresponding X-ray crystallographic structures. A pharmacophore model that was validated by receiver operating characteristic (ROC) curve analysis and selected using the statistically optimum QSAR equation was implemented as a 3D-search tool to mine AnalytiCon Discovery database of natural products. Captured hits that showed the highest predicted inhibitory activities were bioassayed. Three active Mpro inhibitors (pseurotin A, lactupicrin, and alpinetin) were successfully identified with IC50 values in low micromolar range.

Lead optimization, pharmacophore development and scaffold design of protein kinase CK2 inhibitors as potential COVID-19 therapeutics.

Therapeutic agents being designed against COVID-19 have targeted either the virus directly or the host cellular machinery. A particularly attractive host target is the ubiquitous and constitutively active serine-threonine kinase, Protein kinase CK2 (CK2). CK2 enhances viral protein synthesis by inhibiting the sequestration of host translational machinery as stress granules and assists in viral egression via association with the N-protein at filopodial protrusions of the infected cell. CK2 inhibitors such as Silmitasertib have been proposed as possible therapeutic candidates in COVID-19 infections. The present study aims to optimize Silmitasertib, develop pharmacophore models and design unique scaffolds to modulate CK2. The lead optimization phase involved the generation of compounds structurally similar to Silmitasertib via bioisostere replacement followed by a multi-stage docking approach to identify drug-like candidates. Molecular dynamics (MD) simulations were performed for two promising candidates (ZINC-43206125 and PC-57664175) to estimate their binding stability and interaction. Top scoring candidates from the lead optimization phase were utilized to build ligand-based pharmacophore models. These models were then merged with structure-based pharmacophores (e-pharmacophores) to build a hybrid hypothesis. This hybrid hypothesis was validated against a decoy set and used to screen a diverse kinase inhibitors library to identify favored chemical features in the retrieved actives. These chemical features include; an anion, an aromatic ring and an H-bond acceptor. Based on the knowledge of these features; de-novo scaffold design was carried out which identified phenindiones, carboxylated steroids, macrocycles and peptides as novel scaffolds with the potential to modulate CK2.Communicated by Ramaswamy H. Sarma.

Rational approaches to discover SARS-CoV-2/ACE2 interaction inhibitors: Pharmacophore-based virtual screening, molecular docking, molecular dynamics and binding free energy studies.

The lack of effective treatment remains a bottleneck in combating the current coronavirus family pandemic, particularly coronavirus 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The infection of host cells by SARS-CoV-2 is mediated by the binding of its receptor-binding domain (RBD) on the spike (S) glycoprotein to the host angiotensin-converting enzyme (ACE2) receptor. As all developed and available vaccines against COVID-19 do not provide long-term immunity, the creation of an effective drug for the treatment of COVID-19 is necessary and cannot be ignored. Therefore, the aim of this study is to present a computational screening method to identify potential inhibitor candidates with a high probability of blocking the binding of RBD to the ACE2 receptor. Pharmacophore mapping, molecular docking, molecular dynamics (MD) simulations, and binding free-energy analyses were performed to identify potential inhibitor candidates against ACE2/SARS-CoV-2. In conclusion, we propose the compound PubChem-84280085 as a potential inhibitor of protein-protein interactions to disrupt the binding of the SARS-CoV-2-RBD to the ACE2 receptor.

Discovery of Novel and Highly Potent Inhibitors of SARS CoV-2 Papain-Like Protease Through Structure-Based Pharmacophore Modeling, Virtual Screening, Molecular Docking, Molecular Dynamics Simulations, and Biological Evaluation.

Background and Objective: COVID-19 has struck our society as a great calamity, and the need for effective anti-viral drugs is more urgent than ever. Papain-like protease (PLpro) of SARS CoV-2 plays important roles in virus maturation, dysregulation of host inflammation, and antiviral immune responses, which is being regarded as a promising druggable target for the treatment of COVID-19. Here, we carried out a combined screening approach to identify novel and highly potent PLpro inhibitors for the treatment of COVID-19. Methods: We used a combined screening approach of structure-based pharmacophore modeling and molecular docking to screen an in-house database containing 35,000 compounds. SARS CoV-2 PLpro inhibition assay was used to carry out the biological evaluation of hit compounds. Molecular dynamics (MD) simulations were conducted to check the stability of the PLpro-hit complexes predicted by molecular docking. Results: We found that four hit compounds showed excellent inhibitory activities against PLpro with IC50 values ranging from 0.6 to 2.4 µM. Among them, the most promising compound, hit 2 is the best PLpro inhibitor and its inhibitory activity was about 4 times higher than that of the positive control (GRL0617). The study of MD simulations indicated that four hits could bind stably to the active site of PLpro. Further study of interaction analysis indicated that hit 2 could form hydrogen-bond interactions with the key amino acids such as Gln269 and Asp164 in the PLpro-active site. Conclusion: Hit 2 is a novel and highly potent PLpro inhibitor, which will open the way for the development of clinical PLpro inhibitors for the treatment of COVID-19.