A computational approach to drug repurposing against SARS-CoV-2 RNA dependent RNA polymerase (RdRp)

First report on chemometrics-driven multilayered lead prioritization in addressing oxysterol-mediated overexpression of G protein-coupled receptor 183

Contemporary research has convincingly demonstrated that upregulation of G protein-coupled receptor 183 (GPR183), orchestrated by its endogenous agonist, 7α,25-dihydroxyxcholesterol (7α,25-OHC), leads to the development of cancer, diabetes, multiple sclerosis, infectious, and inflammatory diseases. A recent study unveiled the cryo-EM structure of 7α,25-OHC bound GPR183 complex, presenting an untapped opportunity for computational exploration of potential GPR183 inhibitors, which served as our inspiration for the current work. A predictive and validated two-dimensional QSAR model using genetic algorithm (GA) and multiple linear regression (MLR) on experimental GPR183 inhibition data was developed. QSAR study highlighted that structural features like dissimilar electronegative atoms, quaternary carbon atoms, and CH2RX fragment (X: heteroatoms) influence positively, while the existence of oxygen atoms with a topological separation of 3, negatively affects GPR183 inhibitory activity. Post assessment of true external set prediction capability, the MLR model was deployed to screen 12,449 DrugBank compounds, followed by a screening pipeline involving molecular docking, druglikeness, ADMET, protein-ligand stability assessment using deep learning algorithm, molecular dynamics, and molecular mechanics. The current findings strongly evidenced DB05790 as a potential lead for prospective interference of oxysterol-mediated GPR183 overexpression, warranting further in vitro and in vivo validation.

Therapeutic Management with Repurposing Approaches: A Mystery During COVID-19 Outbreak

The ubiquitous pandemic that emerged due to COVID-19 affected the whole planet. People all over the globe became vulnerable to the unpredictable emergence of coronavirus. The sudden emergence of respiratory disease in coronavirus infected several patients. This affected human life drastically, from mild symptoms to severe illness, leading to mortality. COVID-19 is an exceptionally communicable disease caused by SARS-CoV-2. According to a genomic study, the viral spike RBD interactions with the host ACE2 protein from several coronavirus strains and the interaction between RBD and ACE2 highlighted the potential change in affinity from the virus causing the COVID-19 outbreak to a progenitor type of SARS-CoV-2. SARS-CoV-2, which could be the principal reservoir, is phylogenetically related to the SARS-like bat virus. Other research works reported that intermediary hosts for the transmission of viruses to humans could include cats, bats, snakes, pigs, ferrets, orangutans, and monkeys. Even with the arrival of vaccines and individuals getting vaccinated and treated with FDAapproved repurposed drugs like Remdesivir, the first and foremost steps aimed towards the possible control and minimization of community transmission of the virus include social distancing, self-realization, and self-health care. In this review paper, we discussed and summarized various approaches and methodologies adopted and proposed by researchers all over the globe to help with the management of this zoonotic outbreak by following repurposed approaches.

SARS-CoV-2 RNA-Dependent RNA Polymerase Follows Asynchronous Translocation Pathway for Viral Transcription and Replication

Translocation is one essential step for the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) to exert viral replication and transcription. Although cryo-EM structures of SARS-CoV-2 RdRp are available, the molecular mechanisms of dynamic translocation remain elusive. Herein, we constructed a Markov state model based on extensive molecular dynamics simulations to elucidate the translocation dynamics of the SARS-CoV-2 RdRp. We identified two intermediates that pinpoint the rate-limiting step of translocation and characterize the asynchronous movement of the template-primer duplex. The 3'-terminal nucleotide in the primer strand lags behind due to the uneven distribution of protein-RNA interactions, while the translocation of the template strand is delayed by the hurdle residue K500. Even so, the two strands share the same "ratchet" to stabilize the polymerase in the post-translocation state, suggesting a Brownian-ratchet model. Overall, our study provides intriguing insights into SARS-CoV-2 replication and transcription, which would open a new avenue for drug discoveries.

Combining computational and experimental evidence on the activity of antimalarial drugs on papain-like protease of SARS-CoV-2: A repurposing study

The development of inhibitors that target the papain-like protease (PLpro) has the potential to counteract the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the agent causing coronavirus disease 2019 (COVID-19). Based on a consideration of its several downstream effects, interfering with PLpro would both revert immune suppression exerted by the virus and inhibit viral replication. By following a repurposing strategy, the current study evaluates the potential of antimalarial drugs as PLpro inhibitors, and thereby the possibility of their use for treatment of SARS-CoV-2 infection. Computational tools were employed for structural analysis, molecular docking, and molecular dynamics simulations to screen antimalarial drugs against PLpro, and in silico data were validated by in vitro experiments. Virtual screening highlighted amodiaquine and methylene blue as the best candidates, and these findings were complemented by the in vitro results that indicated amodiaquine as a μM PLpro deubiquitinase inhibitor. The results of this study demonstrate that the computational workflow adopted here can correctly identify active compounds. Thus, the highlighted antimalarial drugs represent a starting point for the development of new PLpro inhibitors through structural optimization.

In silico identification of novel benzophenone-coumarin derivatives as SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) inhibitors

In this study, we propose our novel benzophenone-coumarin derivatives (BCDs) as potent inhibitors of the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 virus, one of the key targets that are involved in the viral genome replication. We aim to evaluate the in silico antiviral potential of BCDs against this protein target, which involves molecular docking simulations, druglikeliness and pharmacokinetic evaluations, PASS analysis, molecular dynamics simulations, and computing binding free energy. Out of all the BCDs screened through these parameters, BCD-8 was found to be the most efficient and potent inhibitor of SARS-CoV-2 RdRp. During molecular docking simulation, BCD-8 showed an extensive molecular interaction in comparison with that of the standard control used, remdesivir. The druglikeliness and pharmacokinetic analyses also proved the efficiency of BCD-8 as an effective drug without adverse effects. Further, pharmacological potential analysis through PASS depicted the antiviral property of BCD-8. With these findings, we performed molecular dynamics simulations, where BCD-8 edged out remdesivir with its exemplary stable interaction with SARS-CoV-2 RdRp. Furthermore, binding free energy of both BCD-8 and remdesivir was calculated, where BCD-8 showed a lower binding energy and standard deviations in comparison with that of remdesivir. Moreover, being a non-nucleoside analogue, BCD-8 can be used effectively against SARS-CoV-2, whereas nucleoside analogues like remdesivir may become non-functional or less functional due to exonuclease activity of nsp14 of the virus. Therefore, we propose BCD-8 as a SARS-CoV-2 RdRp inhibitor, showing higher predicted efficiency than remdesivir in all the in silico experiments conducted.Communicated by Ramaswamy H. Sarma.

Finding potential inhibitors against RNA-dependent RNA polymerase (RdRp) of bovine ephemeral fever virus (BEFV): an in-silico study

The bovine ephemeral fever virus (BEFV) is an enzootic agent that affects millions of bovines and causes major economic losses. Though the virus is seasonally reported with a very high morbidity rate (80-100%) from African, Australian, and Asiatic continents, it remains a neglected pathogen in many of its endemic areas, with no proper therapeutic drugs or vaccines presently available for treatment. The RNA-dependent RNA polymerase (RdRp) catalyzes the viral RNA synthesis and is an appropriate candidate for antiviral drug developments. We utilized integrated computational tools to build the 3D model of BEFV-RdRp and then predicted its probable active binding sites. The virtual screening and optimization against these active sites, using several small-molecule inhibitors from a different category of Life Chemical database and FDA-approved drugs from the ZINC database, was performed. We found nine molecules that have docking scores varying between -6.84 to -10.43 kcal/mol. Furthermore, these complexes were analyzed for their conformational dynamics and thermodynamic stability using molecular dynamics simulations in conjunction with the molecular mechanics generalized Born surface area (MM-GBSA) scheme. The binding free energy calculations depict that the electrostatic interactions play a dominant role in the RdRp-inhibitor binding. The hot spot residues, such as Arg565, Asp631, Glu633, Asp740, and Glu707, were found to control the RdRp-inhibitor interaction. The ADMET analysis strongly suggests favorable pharmacokinetics of these compounds that may prove useful for treating the BEFV ailment. Overall, we anticipate that these findings would help explore and develop a wide range of anti-BEFV therapy.Communicated by Ramaswamy H. Sarma.

Discovering new potential inhibitors to SARS-CoV-2 RNA dependent RNA polymerase (RdRp) using high throughput virtual screening and molecular dynamics simulations

RNA dependent RNA polymerase (RdRp), is an essential in the RNA replication within the life cycle of the severely acute respiratory coronavirus-2 (SARS-CoV-2), causing the deadly respiratory induced sickness COVID-19. Remdesivir is a prodrug that has seen some success in inhibiting this enzyme, however there is still the pressing need for effective alternatives. In this study, we present the discovery of four non-nucleoside small molecules that bind favorably to SARS-CoV-2 RdRp over the active form of the popular drug remdesivir (RTP) and adenosine triphosphate (ATP) by utilizing high-throughput virtual screening (HTVS) against the vast ZINC compound database coupled with extensive molecular dynamics (MD) simulations. After post-trajectory analysis, we found that the simulations of complexes containing both ATP and RTP remained stable for the duration of their trajectories. Additionally, it was revealed that the phosphate tail of RTP was stabilized by both the positive amino acid pocket and magnesium ions near the entry channel of RdRp which includes residues K551, R553, R555 and K621. It was also found that residues D623, D760, and N691 further stabilized the ribose portion of RTP with U10 on the template RNA strand forming hydrogen pairs with the adenosine motif. Using these models of RdRp, we employed them to screen the ZINC database of ~ 17 million molecules. Using docking and drug properties scoring, we narrowed down our selection to fourteen candidates. These were subjected to 200 ns simulations each underwent free energy calculations. We identified four hit compounds from the ZINC database that have similar binding poses to RTP while possessing lower overall binding free energies, with ZINC097971592 having a binding free energy two times lower than RTP.

SARS-CoV-2 VOCs, Mutational diversity and clinical outcome: Are they modulating drug efficacy by altered binding strength?

The global COVID-19 pandemic continues due to emerging Severe Acute Respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC). Here, we performed comprehensive analysis of in-house sequenced SARS-CoV-2 genome mutations dynamics in the patients infected with the VOCs - Delta and Omicron, within Recovered and Mortality patients. Statistical analysis highlighted significant mutations - T4685A, N4992N, and G5063S in RdRp; T19R in NTD spike; K444N and N532H in RBD spike, associated with Delta mortality. Mutations, T19I in NTD spike, Q493R and N440K in the RBD spike were significantly associated with Omicron mortality. We performed molecular docking for possible effect of significant mutations on the binding of Remdesivir. We found that Remdesivir showed less binding efficacy with the mutant Spike protein of both Delta and Omicron mortality compared to recovered patients. This indicates that mortality associated mutations could have a modulatory effect on drug binding which could be associated with disease outcome.

Repurposing drugs to treat cardiovascular disease in the era of precision medicine

Drug repurposing is the use of a given therapeutic agent for indications other than that for which it was originally designed or intended. The concept is appealing because of potentially lower development costs and shorter timelines than are needed to produce a new drug. To date, drug repurposing for cardiovascular indications has been opportunistic and driven by knowledge of disease mechanisms or serendipitous observation rather than by systematic endeavours to match an existing drug to a new indication. Innovations in two areas of personalized medicine — computational approaches to associate drug effects with disease signatures and predictive model systems to screen drugs for disease-modifying activities — support efforts that together create an efficient pipeline to systematically repurpose drugs to treat cardiovascular disease. Furthermore, new experimental strategies that guide the medicinal chemistry re-engineering of drugs could improve repurposing efforts by tailoring a medicine to its new indication. In this Review, we summarize the historical approach to repurposing and discuss the technological advances that have created a new landscape of opportunities.

Drugs can be repurposed for new therapeutic indications. In this Review, Mercola and colleagues summarize the latest techniques for systematic drug repurposing and re-engineering, which could increase the pace, efficiency and cost-effectiveness of drug discovery for the treatment of cardiovascular disease.

Contemporary technologies are expected to make drug repurposing large-scale, systematic and deliberate rather than opportunistic.

New experimental and computational tools harness patient genomics for drug repurposing.

Discovery of repurposed drugs on the basis of patient genomics has implications for precision prescribing of medicines to treat individual patients.

The treatment of rare, monogenic diseases, which often provide too little return on investment to incentivize conventional drug discovery, might benefit because the molecular aetiologies of these diseases are well suited to the discovery of drug repurposing candidates.

Molecular Docking as a Potential Approach in Repurposing Drugs Against COVID-19: a Systematic Review and Novel Pharmacophore Models

Purpose of Review

This article provides a review of the recent literature related to the FDA-approved drugs that had been repurposed as potential drug candidates against COVID-19. Moreover, we performed a quality pharmacophore study for frequently studied targets, namely, the main protease, RNA-dependent RNA polymerase, and spike protein.

Recent Findings

Ever since the COVID-19 pandemic, the whole spectrum of scientific community is still unable to invent an absolute therapeutic agent for COVID-19. Considering such a fact, drug repurposing strategies seem a truly viable approach to develop novel therapeutic interventions.

Summery

Drug repurposing explores previously approved drugs of known safety and pharmacokinetics profile for possible new effects, reducing the cost, time, and predicting prospective side effects and drug interactions. COVID-19 virulent machinery appeared similar to other viruses, making antiviral agents widely repurposed in pursuit for curative candidates. Our main protease pharmacophoric study revealed multiple features and could be a probable starting point for upcoming research.

Potential inhibitors of SARS-CoV-2 (COVID 19) proteases PLpro and Mpro/ 3CLpro: molecular docking and simulation studies of three pertinent medicinal plant natural components

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) - coronavirus disease 2019 (COVID-19) has raised a severe global public health issue and creates a pandemic situation. The present work aims to study the molecular -docking and dynamic of three pertinent medicinal plants i.e. Eurycoma harmandiana, Sophora flavescens and Andrographis paniculata phyto-compounds against SARS-COV-2 papain-like protease (PL^pro) and main protease (M^pro)/3-chymotrypsin-like protease (3CL^pro). The interaction of protein targets and ligands was performed through AutoDock-Vina visualized using PyMOL and BIOVIA-Discovery Studio 2020. Molecular docking with canthin-6-one 9-O-beta-glucopyranoside showed highest binding affinity and less binding energy with both PL^pro and M^pro/3CL^pro proteases and was subjected to molecular dynamic (MD) simulations for a period of 100ns. Stability of the protein-ligand complexes was evaluated by different analyses. The binding free energy calculated using MM-PBSA and the results showed that the molecule must have stable interactions with the protein binding site. ADMET analysis of the compounds suggested that it is having drug-like properties like high gastrointestinal (GI) absorption, no blood-brain barrier permeability and high lipophilicity. The outcome revealed that canthin-6-one 9-O-beta-glucopyranoside can be used as a potential natural drug against COVID-19 protease.

Comparative molecular docking and simulation analysis of molnupiravir and remdesivir with SARS-CoV-2 RNA dependent RNA polymerase (RdRp)

Treatment of SARS-CoV-2 targeting its RNA dependent RNA polymerase (RdRp) is of current interest. Remdesivir has been approved for the treatment of COVID-19 around the world. However, the drug has been linked with pharmacological limitations like adverse effects and reduced efficiency. Nevertheless, recent advancements have depicted molnupiravir as an effective therapeutic agent to target the SARS-CoV-2 RdRp. The drug has cleared both in vitro and in vivo screening. It is in phase-III clinical trial. Nonetheless, there are no data on themolecular binding interaction of molnupiravir with RdRp. Therefore, it is of interest to report the binding interaction of molnupiravir using molecular docking. It is also of interest to show its stability during interaction using molecular dynamics and binding free energy calculations along with drug likeliness and pharmacokinetic properties in comparison with remdesivir.

A Drug Repurposing Approach for Antimalarials Interfering with SARS-CoV-2 Spike Protein Receptor Binding Domain (RBD) and Human Angiotensin-Converting Enzyme 2 (ACE2)

Host cell invasion by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is mediated by the interaction of the viral spike protein (S) with human angiotensin-converting enzyme 2 (ACE2) through the receptor-binding domain (RBD). In this work, computational and experimental techniques were combined to screen antimalarial compounds from different chemical classes, with the aim of identifying small molecules interfering with the RBD-ACE2 interaction and, consequently, with cell invasion. Docking studies showed that the compounds interfere with the same region of the RBD, but different interaction patterns were noted for ACE2. Virtual screening indicated pyronaridine as the most promising RBD and ACE2 ligand, and molecular dynamics simulations confirmed the stability of the predicted complex with the RBD. Bio-layer interferometry showed that artemisone and methylene blue have a strong binding affinity for RBD (KD = 0.363 and 0.226 μM). Pyronaridine also binds RBD and ACE2 in vitro (KD = 56.8 and 51.3 μM). Overall, these three compounds inhibit the binding of RBD to ACE2 in the μM range, supporting the in silico data.

Dynamic properties of SARS-CoV and SARS-CoV-2 RNA-dependent RNA polymerases studied by molecular dynamics simulations

One of the promising drug targets against COVID-19 is an RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. The tertiary structures of the SARS-CoV-2 and SARS-CoV RdRps are almost the same. However, the RNA-synthesizing activity of the SARS-CoV RdRp is higher than that of the SARS-CoV-2 RdRp. We performed molecular dynamics simulations and found differences in their dynamic properties. In the SARS-CoV RdRp, motifs A-G, which form the active site, are up to 63% closer to each other. We also observed cooperative domain motion in the SARS-CoV RdRp. Such dynamic differences may cause the activity differences between the two RdRps.

Computational drug repurposing study of antiviral drugs against main protease, RNA polymerase, and spike proteins of SARS-CoV-2 using molecular docking method

OBJECTIVES

The new Coronavirus (SARS-CoV-2) created a pandemic in the world in late 2019 and early 2020. Unfortunately, despite the increasing prevalence of the disease, there is no effective drug for the treatment. A computational drug repurposing study would be an appropriate and rapid way to provide an effective drug in the treatment of the coronavirus disease of 2019 (COVID-19) pandemic. In this study, the inhibitory potential of more than 50 antiviral drugs on three important proteins of SARS-CoV-2, was investigated using the molecular docking method.

METHODS

By literature review, three important proteins, including main protease, RNA-dependent RNA polymerase (RdRp), and spike, were selected as the drug targets. The three-dimensional (3D) structure of protease, spike, and RdRp proteins was obtained from the Protein Data Bank. Proteins were energy minimized. More than 50 antiviral drugs were considered as candidates for protein inhibition, and their 3D structure was obtained from Drug Bank. Molecular docking settings were defined using Autodock 4.2 software and the algorithm was executed.

RESULTS

Based on the estimated binding energy of docking and hydrogen bond analysis and the position of drug binding, five drugs including, indinavir, lopinavir, saquinavir, nelfinavir, and remdesivir, had the highest inhibitory potential for all three proteins.

CONCLUSIONS

According to the results, among the mentioned drugs, saquinavir and lopinavir showed the highest inhibitory potential for all three proteins compared to the other drugs. This study suggests that saquinavir and lopinavir could be included in the laboratory phase studies as a two-drug treatment for SARS-CoV-2 inhibition.

Insight into the LFA-1/SARS-CoV-2 Orf7a Complex by Protein-Protein Docking, Molecular Dynamics, and MM-GBSA Calculations

In the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) genome, open reading frames (ORFs) encode for viral accessory proteins. Among these, Orf7a structurally resembles the members of the immunoglobulin (Ig) superfamily and intracellular adhesion molecules (ICAMs), in particular. ICAMs are involved in integrin binding through lymphocyte function-associated antigen 1 (LFA-1). Based on such considerations and on previous findings on SARS-CoV, it has been postulated that the formation of the LFA-1/Orf7a complex could contribute to SARS-CoV-2 infectivity and pathogenicity. With the current work, we aim at providing insight into this macromolecular assembly, taking advantage of the recently reported SARS-CoV-2 Orf7a structure. Protein-protein docking, molecular dynamics (MD) simulations, and a Molecular Mechanical-Generalized Born Surface Area (MM-GBSA)-based stage were enrolled to provide refined models.

A COVID-19 Drug Repurposing Strategy through Quantitative Homological Similarities Using a Topological Data Analysis-Based Framework

Since its emergence in March 2020, the SARS-CoV-2 global pandemic has produced more than 116 million cases and 2.5 million deaths worldwide. Despite the enormous efforts carried out by the scientific community, no effective treatments have been developed to date. We applied a novel computational pipeline aimed to accelerate the process of identifying drug repurposing candidates which allows us to compare three-dimensional protein structures. Its use in conjunction with two in silico validation strategies (molecular docking and transcriptomic analyses) allowed us to identify a set of potential drug repurposing candidates targeting three viral proteins (3CL viral protease, NSP15 endoribonuclease, and NSP12 RNA-dependent RNA polymerase), which included rutin, dexamethasone, and vemurafenib. This is the first time that a topological data analysis (TDA)-based strategy has been used to compare a massive number of protein structures with the final objective of performing drug repurposing to treat SARS-CoV-2 infection.

Identifying and repurposing antiviral drugs against severe acute respiratory syndrome coronavirus 2 with in silico and in vitro approaches

Coronavirus infectious diseases 2019 (COVID-19), a global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been a serious public health threat worldwide. So far, there are no drugs and vaccines whose efficacy has been well-proven. After the outbreak, there has been a massive search for anti-SARS-CoV-2 medications, focusing on approved drugs because repurposing approved drugs will take less time to reach clinical usage than new drugs. This article summarizes the studies using in silico and in vitro approaches to identify therapeutic candidates among approved drugs that target the SARS-CoV-2 life cycle.

Chalcogen-Nitrogen Bond: Insights into a Key Chemical Motif

Chalcogen-nitrogen chemistry deals with systems in which sulfur, selenium, or tellurium is linked to a nitrogen nucleus. This chemical motif is a key component of different functional structures, ranging from inorganic materials and polymers, to rationally designed catalysts, to bioinspired molecules and enzymes. The formation of a selenium–nitrogen bond, typically occurring upon condensation of an amine and the unstable selenenic acid, often leading to intramolecular cyclizations, and its disruption, mainly promoted by thiols, are rather common events in organic Se-catalyzed processes. In this work, focusing on examples taken from selenium organic chemistry and biochemistry, the selenium–nitrogen bond is described, and its strength and reactivity are quantified using accurate computational methods applied to model molecular systems. The intermediate strength of the Se–N bond, which can be tuned to necessity, gives rise to significant trends when comparing it to the stronger S– and weaker Te–N bonds, reaffirming also in this context the peculiar and valuable role of selenium in chemistry and life.