Nisha Amarnath Jonniya

Bio: Nisha Amarnath Jonniya is an academic researcher from Indian Institute of Technology Indore. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 6, co-authored 15 publications receiving 149 citations.

Elucidating Biophysical Basis of Binding of Inhibitors to SARS-CoV-2 Main Protease by Using Molecular Dynamics Simulations and Free Energy Calculations

Abstract: The recent outbreak of novel "coronavirus disease 2019" (COVID-19) has spread rapidly worldwide, causing a global pandemic. In the present work, we have elucidated the mechanism of binding of two inhibitors, namely α-ketoamide and Z31792168, to SARS-CoV-2 main protease (Mpro or 3CLpro) by using all-atom molecular dynamics simulations and free energy calculations. We calculated the total binding free energy (ΔGbind) of both inhibitors and further decomposed ΔGbind into various forces governing the complex formation using the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method. Our calculations reveal that α-ketoamide is more potent (ΔGbind= - 9.05 kcal/mol) compared to Z31792168 (ΔGbind= - 3.25 kcal/mol) against COVID-19 3CLpro. The increase in ΔGbind for α-ketoamide relative to Z31792168 arises due to an increase in the favorable electrostatic and van der Waals interactions between the inhibitor and 3CLpro. Further, we have identified important residues controlling the 3CLpro-ligand binding from per-residue based decomposition of the binding free energy. Finally, we have compared ΔGbind of these two inhibitors with the anti-HIV retroviral drugs, such as lopinavir and darunavir. It is observed that α-ketoamide is more potent compared to lopinavir and darunavir. In the case of lopinavir, a decrease in van der Waals interactions is responsible for the lower binding affinity compared to α-ketoamide. On the other hand, in the case of darunavir, a decrease in the favorable intermolecular electrostatic and van der Waals interactions contributes to lower affinity compared to α-ketoamide. Our study might help in designing rational anti-coronaviral drugs targeting the SARS-CoV-2 main protease.Communicated by Ramaswamy H. Sarma.

Investigating Phosphorylation-Induced Conformational Changes in WNK1 Kinase by Molecular Dynamics Simulations.

Abstract: The With-No-Lysine (WNK) kinase is considered to be a master regulator for various cation-chloride cotransporters involved in maintaining cell-volume and ion homeostasis. Here, we have investigated...

Computational Investigation of Structural Dynamics of SARS-CoV-2 Methyltransferase-Stimulatory Factor Heterodimer Nsp16/nsp10 Bound to the Cofactor SAM

Abstract: Recently, a highly contagious novel coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has emerged, posing a global threat to public health. Identifying a potential target and developing vaccines or antiviral drugs is an urgent demand in the absence of approved therapeutic agents. The 5'-capping mechanism of eukaryotic mRNA and some viruses such as coronaviruses (CoVs) are essential for maintaining the RNA stability and protein translation in the virus. SARS-CoV-2 encodes S-adenosyl-L-methionine (SAM) dependent methyltransferase (MTase) enzyme characterized by nsp16 (2'-O-MTase) for generating the capped structure. The present study highlights the binding mechanism of nsp16 and nsp10 to identify the role of nsp10 in MTase activity. Furthermore, we investigated the conformational dynamics and energetics behind the binding of SAM to nsp16 and nsp16/nsp10 heterodimer by employing molecular dynamics simulations in conjunction with the Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) method. We observed from our simulations that the presence of nsp10 increases the favorable van der Waals and electrostatic interactions between SAM and nsp16. Thus, nsp10 acts as a stimulator for the strong binding of SAM to nsp16. The hydrophobic interactions were predominately identified for the nsp16-nsp10 interactions. Also, the stable hydrogen bonds between Ala83 (nsp16) and Tyr96 (nsp10), and between Gln87 (nsp16) and Leu45 (nsp10) play a vital role in the dimerization of nsp16 and nsp10. Besides, Computational Alanine Scanning (CAS) mutagenesis was performed, which revealed hotspot mutants, namely I40A, V104A, and R86A for the dimer association. Hence, the dimer interface of nsp16/nsp10 could also be a potential target in retarding the 2'-O-MTase activity in SARS-CoV-2. Overall, our study provides a comprehensive understanding of the dynamic and thermodynamic process of binding nsp16 and nsp10 that will contribute to the novel design of peptide inhibitors based on nsp16.

Investigating specificity of the anti-hypertensive inhibitor WNK463 against With-No-Lysine kinase family isoforms via multiscale simulations

Abstract: The With-No-Lysine (WNK) kinase family plays a significant role in regulating cation-chloride cotransporters, blood pressure and body fluid homeostasis. Mutations in the gene of WNK family, especia...

Exploring the energetic basis of binding of currently used drugs against HIV-1 subtype CRF01_AE protease via molecular dynamics simulations.

Abstract: Non-B strains cause nearly 90% of the worldwide human immunodeficiency virus (HIV) infections. At the same time, the protease inhibitors (PIs) were designed for subtype B. Therefore, the use of PIs in the non-B subtype context requires further investigation. Herein, we have investigated the effectiveness of currently used four PIs, namely atazanavir, darunavir, lopinavir, and tipranavir against subtype CRF01_AE (PRCRF) by employing the MD/MMPBSA (molecular dynamics/molecular mechanics Poisson-Boltzmann surface area) scheme. Our investigation reveals that tipranavir is the most potent inhibitor against PRCRF while the other three PIs display a similar binding affinity. The energetic penalty arises due to the desolvation of polar groups always disfavor the association between PRCRF and PI, and this contribution is the least in the case of tipranavir/PRCRF compared to the other three PI-PRCRF complexes resulting in a better binding affinity for tipranavir. Further, it is revealed that the primary interaction controlling the binding of inhibitors with PRCRF is the van der Waals forces. The dynamic cross-correlation map and principal component analysis show that the anti-correlated motion at the flap region of PRCRF is diminished after the ligand binding. Further, our studies indicate that D25' forms a stable H-bond with darunavir, lopinavir, and tipranavir, while D25 forms a stable H-bond with atazanavir. The per-residue based decomposition of free energy reveals the actual residual origin of the binding free energy and identify the hotspot residues. Overall, the data presented in this study can guide the computer-aided rational design of more potent drugs targetting HIV-1 PRCRF.Communicated by Ramaswamy H. Sarma.

Potential bioactive glycosylated flavonoids as SARS-CoV-2 main protease inhibitors: A molecular docking and simulation studies.

Abstract: A novel coronavirus responsible of acute respiratory infection closely related to SARS-CoV has recently emerged. So far there is no consensus for drug treatment to stop the spread of the virus. Discovery of a drug that would limit the virus expansion is one of the biggest challenges faced by the humanity in the last decades. In this perspective, to test existing drugs as inhibitors of SARS-CoV-2 main protease is a good approach. Among natural phenolic compounds found in plants, fruit, and vegetables; flavonoids are the most abundant. Flavonoids, especially in their glycosylated forms, display a number of physiological activities, which makes them interesting to investigate as antiviral molecules. The flavonoids chemical structures were downloaded from PubChem and protease structure 6LU7 was from the Protein Data Bank site. Molecular docking study was performed using AutoDock Vina. Among the tested molecules Quercetin-3-O-rhamnoside showed the highest binding affinity (-9,7 kcal/mol). Docking studies showed that glycosylated flavonoids are good inhibitors for the SARS-CoV-2 protease and could be further investigated by in vitro and in vivo experiments for further validation. MD simulations were further performed to evaluate the dynamic behavior and stability of the protein in complex with the three best hits of docking experiments. Our results indicate that the rutin is a potential drug to inhibit the function of Chymotrypsin-like protease (3CL pro) of Coronavirus.

Plant-derived natural polyphenols as potential antiviral drugs against SARS-CoV-2 via RNA-dependent RNA polymerase (RdRp) inhibition: an in-silico analysis.

Abstract: The sudden outburst of Coronavirus disease (COVID-19) caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) poses a massive threat to global public health. Currently, no therapeutic drug or vaccine exists to treat COVID-19. Due to the time taking process of new drug development, drug repurposing might be the only viable solution to tackle COVID-19. RNA-dependent RNA polymerase (RdRp) catalyzes SARS-CoV-2 RNA replication and hence, is an obvious target for antiviral drug design. Interestingly, several plant-derived polyphenols effectively inhibit the RdRp of other RNA viruses. More importantly, polyphenols have been used as dietary supplementations for a long time and played beneficial roles in immune homeostasis. We were curious to study the binding of polyphenols with SARS-CoV-2 RdRp and assess their potential to treat COVID-19. Herein, we made a library of polyphenols that have shown substantial therapeutic effects against various diseases. They were successfully docked in the catalytic pocket of RdRp. The investigation reveals that EGCG, theaflavin (TF1), theaflavin-3'-O-gallate (TF2a), theaflavin-3'-gallate (TF2b), theaflavin 3,3'-digallate (TF3), hesperidin, quercetagetin, and myricetin strongly bind to the active site of RdRp. Further, a 150-ns molecular dynamic simulation revealed that EGCG, TF2a, TF2b, TF3 result in highly stable bound conformations with RdRp. The binding free energy components calculated by the MM-PBSA also confirm the stability of the complexes. We also performed a detailed analysis of ADME prediction, toxicity prediction, and target analysis for their druggability. Overall, our results suggest that EGCG, TF2a, TF2b, TF3 can inhibit RdRp and represent an effective therapy for COVID-19. Communicated by Ramaswamy H. Sarma.

Virtual screening-driven drug discovery of SARS-CoV2 enzyme inhibitors targeting viral attachment, replication, post-translational modification and host immunity evasion infection mechanisms.

Abstract: The novel coronavirus SARS-CoV2, the causative agent of the pandemic disease COVID-19, emerged in December 2019 forcing lockdown of communities in many countries. The absence of specific drugs and vaccines, the rapid transmission of the virus, and the increasing number of deaths worldwide necessitated the discovery of new substances for anti-COVID-19 drug development. With the aid of bioinformatics and computational modelling, ninety seven antiviral secondary metabolites from fungi were docked onto five SARS-CoV2 enzymes involved in viral attachment, replication, post-translational modification, and host immunity evasion infection mechanisms followed by molecular dynamics simulation and in silico ADMET prediction (absorption, distribution, metabolism, excretion and toxicity) of the hit compounds. Thus, three fumiquinazoline alkaloids scedapin C (15), quinadoline B (19) and norquinadoline A (20), the polyketide isochaetochromin D1 (8), and the terpenoid 11a-dehydroxyisoterreulactone A (11) exhibited high binding affinities on the target proteins, papain-like protease (PLpro), chymotrypsin-like protease (3CLpro), RNA-directed RNA polymerase (RdRp), non-structural protein 15 (nsp15), and the spike binding domain to GRP78. Molecular dynamics simulation was performed to optimize the interaction and investigate the stability of the top-scoring ligands in complex with the five target proteins. All tested complexes were found to have dynamic stability. Of the five top-scoring metabolites, quinadoline B (19) was predicted to confer favorable ADMET values, high gastrointestinal absorptive probability and poor blood-brain barrier crossing capacities.Communicated by Ramaswamy H. Sarma.

Chemical-informatics approach to COVID-19 drug discovery: Monte Carlo based QSAR, virtual screening and molecular docking study of some in-house molecules as papain-like protease (PLpro) inhibitors.

Abstract: World Health Organization characterized novel coronavirus disease (COVID-19), caused by severe acute respiratory syndrome (SARS) coronavirus-2 (SARS-CoV-2) as world pandemic This infection has been spreading alarmingly by causing huge social and economic disruption In order to response quickly, the inhibitors already designed against different targets of previous human coronavirus infections will be a great starting point for anti-SARS-CoV-2 inhibitors In this study, our approach integrates different ligand based drug design strategies of some in-house chemicals The study design was composed of some major aspects: (a) classification QSAR based data mining of diverse SARS-CoV papain-like protease (PLpro) inhibitors, (b) QSAR based virtual screening (VS) to identify in-house molecules that could be effective against putative target SARS-CoV PLpro and (c) finally validation of hits through receptor-ligand interaction analysis This approach could be used to aid in the process of COVID-19 drug discovery It will introduce key concepts, set the stage for QSAR based screening of active molecules against putative SARS-CoV-2 PLpro enzyme Moreover, the QSAR models reported here would be of further use to screen large database This study will assume that the reader is approaching the field of QSAR and molecular docking based drug discovery against SARS-CoV-2 PLpro with little prior knowledgeCommunicated by Ramaswamy H Sarma

Molecular Basis of SARS-CoV-2 Infection and Rational Design of Potential Antiviral Agents: Modeling and Simulation Approaches.

Abstract: The emergence in late 2019 of the coronavirus SARS-CoV-2 has resulted in the breakthrough of the COVID-19 pandemic that is presently affecting a growing number of countries. The development of the pandemic has also prompted an unprecedented effort of the scientific community to understand the molecular bases of the virus infection and to propose rational drug design strategies able to alleviate the serious COVID-19 morbidity. In this context, a strong synergy between the structural biophysics and molecular modeling and simulation communities has emerged, resolving at the atomistic level the crucial protein apparatus of the virus and revealing the dynamic aspects of key viral processes. In this Review, we focus on how in silico studies have contributed to the understanding of the SARS-CoV-2 infection mechanism and the proposal of novel and original agents to inhibit the viral key functioning. This Review deals with the SARS-CoV-2 spike protein, including the mode of action that this structural protein uses to entry human cells, as well as with nonstructural viral proteins, focusing the attention on the most studied proteases and also proposing alternative mechanisms involving some of its domains, such as the SARS unique domain. We demonstrate that molecular modeling and simulation represent an effective approach to gather information on key biological processes and thus guide rational molecular design strategies.