An insight into anti-arthritic property of phytochemicals against Rheumatoid arthritis using molecular modelling and docking approach

Arthritis literally refers “joint inflammation”, it is a condition where one or more joints are inflamed. More than 100 different types of Arthritis were identified, most common types are rheumatoid arthritis and osteoarthritis. The present study mainly focuses on the development of the novel phytochemical inhibitors against rheumatoid arthritis and osteoarthritis using an integrative cheminformatics drug discovery platform. In this study, we identified potential 405 phytochemical drug candidates, screened against eight selected targets of rheumatoid arthritis and osteoarthritis using molecular docking tool AutoDock. Three phytochemicals Withanolide, Diosgenin and bamyrin exhibited promising binding towards multiple drug targets selected for this study. When comparing with the binding between reference drugs, withanolide showed highest activity against Interleukin-23, Matrix metalloproteinase-3 and Interleukin 8 with binding energies -11.6, -9.4 and -8.3 kcal/mol respectively. Diosgenin also exhibited best activity against three targets that were Interleukin-23, JNK alpha and MMP-3 with -11.3, -10.4, -9.5 kcal/mol binding energies respectively. This study may be important contributing factor to develop new therapeutic drugs for rheumatoid arthritis and osteoarthritis.

Molecular Modeling Studies of Benzimidazole Nucleus

For the identification of the lead compounds, a molecular docking tool is used. The little structure, namely Ligand, generally holds together the protein places. It describes a similar approach that utilizes to place over another three-dimensional structure of a probable drug on its prospective object sites. Given that, it was worthwhile to build a virtual library of benzimidazole derivatives to find lead structures to test against C. Albicans. The two-dimensional structure of all planned compounds was drawn by using the current version software and pass on to the software window. The energy of all three-dimensional structures was reduced by Molecular Orbital Package up to Root mean square gradient 0.001 and put aside in MDL Molfile (.Mol) format. To assess the likely potential of the Quantitative Structure-Activity Relationship models, the dataset was split into a training set comprising of 32 molecules and a test set of 8 molecules in such a way that the structural variety and an extensive range of biological action in the specific set were added. The IC50 values were transformed to pIC50 to give numerically larger data values.

Computational guided approach for drug repurposing against SARS-CoV-2

Background: In the current SARS-CoV-2 outbreak, drug repositioning emerges as a promising approach to develop efficient therapeutics in comparison to de novo drug development. The present investigation screened 130 US FDA-approved drugs including hypertension, cardiovascular diseases, respiratory tract infections (RTI), antibiotics and antiviral drugs for their inhibitory potential against SARS-CoV-2. Materials & methods: The molecular drug targets against SARS-CoV-2 proteins were determined by the iGEMDOCK computational docking tool. The protein homology models were generated through SWISS Model workspace. The pharmacokinetics of all the ligands was determined by ADMET analysis. Results: The study identified 15 potent drugs exhibiting significant inhibitory potential against SARS-CoV-2. Conclusion: Our investigation has identified possible repurposed drug candidates to improve the current modus operandi of the treatment given to COVID-19 patients.

DINC-COVID: A webserver for ensemble docking with flexible SARS-CoV-2 proteins

MotivationRecent efforts to computationally identify inhibitors for SARS-CoV-2 proteins have largely ignored the issue of receptor flexibility. We have implemented a computational tool for ensemble docking with the SARS-CoV-2 proteins, including the main protease (Mpro), papain-like protease (PLpro) and RNA-dependent RNA polymerase (RdRp).ResultsEnsembles of other SARS-CoV-2 proteins are being prepared and made available through a user-friendly docking interface. Plausible binding modes between conformations of a selected ensemble and an uploaded ligand are generated by DINC, our parallelized meta-docking tool. Binding modes are scored with three scoring functions, and account for the flexibility of both the ligand and receptor. Additional details on our methods are provided in the supplementary material.Availabilitydinc-covid.kavrakilab.orgSupplementary informationDetails on methods for ensemble generation and docking are provided as supplementary data [email protected], [email protected]

WIDOCK: a reactive docking protocol for virtual screening of covalent inhibitors

Here we present WIDOCK, a virtual screening protocol that supports the selection of diverse electrophiles as covalent inhibitors by incorporating ligand reactivity towards cysteine residues into AutoDock4. WIDOCK applies the reactive docking method (Backus et al. in Nature 534:570–574, 2016) and extends it into a virtual screening tool by introducing facile experimental or computational parametrization and a ligand focused evaluation scheme together with a retrospective and prospective validation against various therapeutically relevant targets. Parameters accounting for ligand reactivity are derived from experimental reaction kinetic data or alternatively from computed reaction barriers. The performance of this docking protocol was first evaluated by investigating compound series with diverse warhead chemotypes against KRASG12C, MurA and cathepsin B. In addition, WIDOCK was challenged on larger electrophilic libraries screened against OTUB2 and NUDT7. These retrospective analyses showed high sensitivity in retrieving experimental actives, by also leading to superior ROC curves, AUC values and better enrichments than the standard covalent docking tool available in AutoDock4 when compound collections with diverse warheads were investigated. Finally, we applied WIDOCK for the prospective identification of covalent human MAO-A inhibitors acting via a new mechanism by binding to Cys323. The inhibitory activity of several predicted compounds was experimentally confirmed and the labelling of Cys323 was proved by subsequent MS/MS measurements. These findings demonstrate the usefulness of WIDOCK as a warhead-sensitive, covalent virtual screening protocol.

Design of novel CV-N variants: Modulation of binding dynamics through distal mutations

We develop a computational approach to identify distal residues that allosterically modulate the dynamics of binding sites by combining dynamic coupling with statistical analysis of co-evolution. Putative mutants of these predicted allosteric sites are subjected to Adaptive BP-Dock docking tool for binding analysis. Here, we apply this method to a small lectin, Cyanovirin-N (CV-N), that selectively binds to dimannose. Our computational method points out mutations on I34, that is 16Å away from binding site can modulate binding. Experimental characterization of I34 mutants confirms that I34Y increases affinity towards dimannose, while I34K completely abolish binding. The increased affinity is not due to changes in the binding region, which are conserved in the crystal structure. However, ITC analysis reveals an opposite contribution of TΔS (negative in WT, and positive in I34Y) and suggests that modulation of dynamics (i.e., dynamic allostery) is responsible for the change in binding affinity. Our results point to a novel approach to identify and substitute distal sites, guiding the mutational landscape in glycan-binding proteins to improve binding affinity.

Therapeutics targeting the main protease of SARS-CoV-2 for the treatment of COVID-19: A molecular modeling approach deciphering relative efficacies

The pandemic due to the novel coronavirus 2019, SARS-CoV-2, has led to a global health and economic crisis. The disease, named coronavirus disease (COVID-19), has already affected 3090445 and killed over 217769 people worldwide, as of April 30, 2020. So far, there is no specific effective medicine or vaccine against SARS-CoV-2. Several existing and approved drugs are under clinical studies for re-purposing. However, owing to the emergent situation and thereby to avoid time needed for de novo drug discovery, drug re-purposing remains to be the best option to find an effective therapeutic against the virus. Thus, the preset study was designed to evaluate potency of 82 compound/drugs in inhibiting the main protease (3CLPro) of SARS-CoV-2, using molecular docking tool. This protease is a vital enzyme for replication of the virus, and is thus a promising drug target. The analyzed compounds include 16 known protease inhibitors, two recently suggested α-ketoamides, 24 recently reported putative inhibitors, and 40 phytochemicals. The results indicate that Ritonavir, Indinavir, Montelukast, Nelfinavir, Candoxatril, Tigecycline and Lopinavir to be very potent protease inhibitors. Further, several other drugs and compounds, including phytochemicals, have been identified / predicted to be potent in inhibiting the enzyme. In addition, we hereby report relative efficacies of these compounds in inhibiting 3CLPro. Thus, the present study is significant in the therapeutic intervention of COVID-19.

Approach Towards Drugs Repurposing: Docking Studies with Multiple Target Proteins Associated with SARS-CoV-2

<p>The current pandemic outbreak of COVID-19 due to viral infections by SARS-CoV-2 is now become associated with severe commotion on global healthcare and economy. In this extreme situation when vaccine or drugs against COVID-19 are not available, the only quick and feasible therapeutic alternative would be the drug repurposing approach. In the present work, <i>in silico</i> screening of some antiviral and antiprotozoal drugs using Autodock docking tool was performed. Two known antiviral drugs sorivudine and noricumazole B are predicted to bind to the active site of the viral proteases namely cysteine like protease or 3CL protease (3CLpro) and papain like protease (PLpro) respectively with a highly favorable free energy of binding. Further, the promising molecules were subjected for checking their activity on other molecular targets like spike protein S1, RNA dependent RNA polymerase (RdRp) and angiotensin converting enzyme 2 (ACE2) receptor. But the compounds were found not effective on rest other molecular targets. </p>

Approach Towards Drugs Repurposing: Docking Studies with Multiple Target Proteins Associated with SARS-CoV-2

<p>The current pandemic outbreak of COVID-19 due to viral infections by SARS-CoV-2 is now become associated with severe commotion on global healthcare and economy. In this extreme situation when vaccine or drugs against COVID-19 are not available, the only quick and feasible therapeutic alternative would be the drug repurposing approach. In the present work, <i>in silico</i> screening of some antiviral and antiprotozoal drugs using Autodock docking tool was performed. Two known antiviral drugs sorivudine and noricumazole B are predicted to bind to the active site of the viral proteases namely cysteine like protease or 3CL protease (3CLpro) and papain like protease (PLpro) respectively with a highly favorable free energy of binding. Further, the promising molecules were subjected for checking their activity on other molecular targets like spike protein S1, RNA dependent RNA polymerase (RdRp) and angiotensin converting enzyme 2 (ACE2) receptor. But the compounds were found not effective on rest other molecular targets. </p>

Discovery of Potential Inhibitors of SARS-CoV-2 (COVID-19) Main Protease (Mpro) from Nigella Sativa (Black Seed) by Molecular Docking Study

Purpose: A new human coronavirus (SARS-CoV-2), triggering pneumonia is termed as Coronavirus Disease-19 (COVID-19). There is an alarming situation now as this new virus is spreading around the world. At present, there are no specific treatments for COVID-19. Nigella sativa is known as Prophetic Medicine as its use has been mentioned in Prophetic Hadith, as natural remedy for all the diseases except death. Seeds and oils of N. sativa have a long history of folklore usage in various system of medicine such as Unani & Tibb, Ayurveda & Siddha in the treatment of different diseases and ailments. The aim of this research is to provide potential inhibitor of SARS-CoV-2 Mpro . Method: The Molecular docking tool was used to optimize the binding affinities of chemical constituents of N. sativa with SARS-CoV-2 Mpro . Results: Many constituents from N. Sativa have shown better binding affinity than reported drugs with SARS-CoV-2 Mpro i.e. the alpha-hederin, Stigmasterol glucoside, Nigellidine-4-O-sulfite, Nigellidine, Sterol-3-β-D-glucoside, Dithymoquinone, beta-sitosterol have binding affinities (kcal/mol) -9, -8.1, -8, -7.7, -7.7, -7.4, -7.4, -6.9 and no. of hydrogen bonds formed are 06, 04, 03, 03, 03, 00 and 01 respectively. Conclusions: There is rationale and pre-clinical evidence of effectiveness of N. Sativa that it may be helpful for the treatment of COVID-19 and can serve as potential natural candidate. However, more studies should be conducted to collect high quality data and scientific evidences of N. Sativa to use it against COVID-19 clinically.