Glecaprevir and Maraviroc are high-affinity inhibitors of SARS-CoV-2 main protease: possible implication in COVID-19 therapy

Baicalein analogues as prospective SARS-CoV-2 main protease (Mpro) inhibitors: A dataset of molecular docking-based virtual screening hits

The global coronavirus disease 2019 (COVID-19) pandemic originating from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has exerted profound damage to millions of lives. Baicalein is a flavonoid that has gotten a lot of attention as a possible SARS-CoV-2 main protease (Mpro) inhibitor because it can fight off many different viruses. We prepared and screened three sets of databases, each containing 2563 baicalein analogues, against Mpro using molecular docking simulation. The data showed that several baicalein analogues exhibited stable binding energies relative to standard baicalein, indicating that they have some selectivity against Mpro. The binding properties of the top three stable analogues from each database were further analyzed with respect to their binding properties, such as binding mode, binding energy, and binding interaction of putative stable ligand confirmations at the target binding site region.

Breaking the Chain: Protease Inhibitors as Game Changers in Respiratory Viruses Management

Respiratory viral infections (VRTIs) rank among the leading causes of global morbidity and mortality, affecting millions of individuals each year across all age groups. These infections are caused by various pathogens, including rhinoviruses (RVs), adenoviruses (AdVs), and coronaviruses (CoVs), which are particularly prevalent during colder seasons. Although many VRTIs are self-limiting, their frequent recurrence and potential for severe health complications highlight the critical need for effective therapeutic strategies. Viral proteases are crucial for the maturation and replication of viruses, making them promising therapeutic targets. This review explores the pivotal role of viral proteases in the lifecycle of respiratory viruses and the development of protease inhibitors as a strategic response to these infections. Recent advances in antiviral therapy have highlighted the effectiveness of protease inhibitors in curtailing the spread and severity of viral diseases, especially during the ongoing COVID-19 pandemic. It also assesses the current efforts aimed at identifying and developing inhibitors targeting key proteases from major respiratory viruses, including human RVs, AdVs, and (severe acute respiratory syndrome coronavirus-2) SARS-CoV-2. Despite the recent identification of SARS-CoV-2, within the last five years, the scientific community has devoted considerable time and resources to investigate existing drugs and develop new inhibitors targeting the virus's main protease. However, research efforts in identifying inhibitors of the proteases of RVs and AdVs are limited. Therefore, herein, it is proposed to utilize this knowledge to develop new inhibitors for the proteases of other viruses affecting the respiratory tract or to develop dual inhibitors. Finally, by detailing the mechanisms of action and therapeutic potentials of these inhibitors, this review aims to demonstrate their significant role in transforming the management of respiratory viral diseases and to offer insights into future research directions.

Rational Approach toward COVID-19's Main Protease Inhibitors: A Hierarchical Biochemoinformatics Analysis

This study investigated the potential of selected compounds as inhibitors of SARS-CoV-2 Mpro through pharmacokinetic and toxicological analyses, molecular docking, and molecular dynamics simulations. In silico molecular docking simulations revealed promising ligands with favorable binding affinities for Mpro, ranging from -6.2 to -9.5 kcal/mol. Moreover, molecular dynamics simulations demonstrated the stability of protein-ligand complexes over 200 ns, maintaining protein secondary structures. MM-PBSA analysis revealed favorable interactions between ligands and Mpro, with negative binding energy values. Hydrogen bond formation capacity during molecular dynamics was confirmed, indicating consistent interactions with Mpro catalytic residues. Based on these findings, selected ligands show promise for future studies in developing COVID-19 treatments.

Fluorine in the pharmaceutical industry: Synthetic approaches and application of clinically approved fluorine-enriched anti-infectious medications

The strategic integration of fluorine atoms into anti-infectious agents has become a cornerstone in the field of medicinal chemistry, owing to the unique influence of fluorine on the chemical and biological properties of pharmaceuticals. This review examines the synthetic methodologies that enable the incorporation of fluorine into anti-infectious drugs, and the resultant clinical applications of these fluorine-enriched compounds. With a focus on clinically approved medications, the discussion extends to the molecular mechanisms. It further outlines the specific effects of fluorination, which contribute to the heightened efficacy of anti-infective therapies. By presenting a comprehensive analysis of current drugs and their developmental pathways, this review underscores the continuing evolution and significance of fluorine in advancing anti-infectious treatment options. The insights offered extend valuable guidance for future drug design and the development of next-generation anti-infectious agents.

Identification of novel peptide inhibitors of Plasmodium falciparum dihydrofolate reductase (PfDHFR): molecular docking and MD simulation studies

The presence of drug-resistant variants of Plasmodium parasites within the population has presented a substantial obstacle to the eradication of Malaria. As a result, numerous research groups have directed their efforts towards creating new medication candidates that specifically target parasites. In this study, our main objective was to identify tri-peptide inhibitors for Plasmodium falciparum Dihydrofolate Reductase (PfDHFR) with the aim of finding a new peptide that exhibits superior binding properties compared to the current inhibitor, WR99210. In order to achieve this objective, a virtual library consisting of 8000 tripeptides was generated and subjected to computational screening against wild-type PfDHFR. The purpose of this screening was to discover the most effective binders at the active site. The four most optimal tripeptides identified (Trp-Trp-Glu, Trp-Phe-Tyr, Phe-Trp-Trp, Tyr-Trp-Trp) exhibited significant non-covalent interactions inside the active site of PfDHFR and had binding energies ranging from -9.5 to -9.0 kcal/mol and WR99210 had a binding energy of -6.2 kcal/mol. A 250 ns Molecular Dynamics (MD) simulation was performed to investigate the kinetic and thermodynamic characteristics of the protein-ligand complexes. The Root Mean Square Deviation (RMSD) values for the optimal tripeptides fell within the allowed range, indicating the stability of the ligands inside the protein complex. The Ki value for the most effective tripeptide was 0.3482 µM, whereas WR99210 had a Ki value of 1.02 µM. This article presents the initial discovery of peptide inhibitors targeting PfDHFR. In this text, we provide a comprehensive explanation of the interactions that occur between peptides and the enzyme.Communicated by Ramaswamy H. Sarma.

Understanding the Modulation of α-Synuclein Fibrillation by N-Acetyl Aspartate: A Brain Metabolite

α-Synuclein (α-Syn) fibrillation is a prominent contributor to neuronal deterioration and plays a significant role in the advancement of Parkinson's Disease (PD). Considering this, the exploration of novel compounds that can inhibit or modulate the aggregation of α-Syn is a topic of significant research. This study, for the first time, elucidated the effect of N-acetyl aspartate (NAA), a brain osmolyte, on α-Syn aggregation using spectroscopic and microscopic approaches. Thioflavin T (ThT) assay revealed that a lower concentration of NAA inhibits α-Syn aggregation, whereas higher concentrations of NAA accelerate the aggregation. Further, this paradoxical effect of NAA was complemented by ANS, RLS, and the turbidity assay. The secondary structure transition was more pronounced at higher concentrations of NAA by circular dichroism, corroborating the fluorescence spectroscopic observations. Confocal microscopy also confirmed the paradoxical effect of NAA on α-Syn aggregation. Interaction studies including fluorescence quenching and molecular docking were employed to determine the binding affinity and critical residues involved in the α-Syn-NAA interaction. The explanation for this paradoxical nature of NAA could be a solvophobic effect. The results offer a profound understanding of the modulatory mechanism of α-Syn aggregation by NAA, thereby suggesting the potential role of NAA at lower concentrations in therapeutics against α-Syn aggregation-related disorders.

Biophysical Analysis of Potential Inhibitors of SARS-CoV-2 Cell Recognition and Their Effect on Viral Dynamics in Different Cell Types: A Computational Prediction from In Vitro Experimental Data

Recent reports have suggested that the susceptibility of cells to SARS-CoV-2 infection can be influenced by various proteins that potentially act as receptors for the virus. To investigate this further, we conducted simulations of viral dynamics using different cellular systems (Vero E6, HeLa, HEK293, and CaLu3) in the presence and absence of drugs (anthelmintic, ARBs, anticoagulant, serine protease inhibitor, antimalarials, and NSAID) that have been shown to impact cellular recognition by the spike protein based on experimental data. Our simulations revealed that the susceptibility of the simulated cell systems to SARS-CoV-2 infection was similar across all tested systems. Notably, CaLu3 cells exhibited the highest susceptibility to SARS-CoV-2 infection, potentially due to the presence of receptors other than ACE2, which may account for a significant portion of the observed susceptibility. Throughout the study, all tested compounds showed thermodynamically favorable and stable binding to the spike protein. Among the tested compounds, the anticoagulant nafamostat demonstrated the most favorable characteristics in terms of thermodynamics, kinetics, theoretical antiviral activity, and potential safety (toxicity) in relation to SARS-CoV-2 spike protein-mediated infections in the tested cell lines. This study provides mathematical and bioinformatic models that can aid in the identification of optimal cell lines for compound evaluation and detection, particularly in studies focused on repurposed drugs and their mechanisms of action. It is important to note that these observations should be experimentally validated, and this research is expected to inspire future quantitative experiments.

CCR5/CXCR3 antagonist TAK-779 prevents diffuse alveolar damage of the lung in the murine model of the acute respiratory distress syndrome

Introduction: The acute respiratory distress syndrome (ARDS), secondary to viral pneumonitis, is one of the main causes of high mortality in patients with COVID-19 (novel coronavirus disease 2019)-ongoing SARS-CoV-2 infection- reached more than 0.7 billion registered cases. Methods: Recently, we elaborated a non-surgical and reproducible method of the unilateral total diffuse alveolar damage (DAD) of the left lung in ICR mice-a publicly available imitation of the ARDS caused by SARS-CoV-2. Our data read that two C-C chemokine receptor 5 (CCR5) ligands, macrophage inflammatory proteins (MIPs) MIP-1α/CCL3 and MIP-1β/CCL4, are upregulated in this DAD model up to three orders of magnitude compared to the background level. Results: Here, we showed that a nonpeptide compound TAK-779, an antagonist of CCR5/CXCR3, readily prevents DAD in the lung with a single injection of 2.5 mg/kg. Histological analysis revealed reduced peribronchial and perivascular mononuclear infiltration in the lung and mononuclear infiltration of the wall and lumen of the alveoli in the TAK-779-treated animals. Administration of TAK-779 decreased the 3-5-fold level of serum cytokines and chemokines in animals with DAD, including CCR5 ligands MIP-1α/β, MCP-1, and CCL5. Computed tomography revealed rapid recovery of the density and volume of the affected lung in TAK-779-treated animals. Discussion: Our pre-clinical data suggest that TAK-779 is more effective than the administration of dexamethasone or the anti-IL6R therapeutic antibody tocilizumab, which brings novel therapeutic modality to TAK-779 and other CCR5 inhibitors for the treatment of virus-induced hyperinflammation syndromes, including COVID-19.

Identifying repurposed drugs as potential inhibitors of Apolipoprotein E: A bioinformatics approach to target complex diseases associated with lipid metabolism and neurodegeneration

Apolipoprotein E (ApoE), a pivotal contributor to lipid metabolism and neurodegenerative disorders, emerges as an attractive target for therapeutic intervention. Within this study, we deployed an integrated in-silico strategy, harnessing structure-based virtual screening, to identify potential compounds from DrugBank database. Employing molecular docking, we unveil initial hits by evaluating their binding efficiency with ApoE. This first tier of screening narrows our focus to compounds that exhibit a strong propensity to bind with ApoE. Further, a detailed interaction analysis was carried out to explore the binding patterns of the selected hits towards the ApoE binding site. The selected compounds were then evaluated for the biological properties in PASS analysis, which showed anti-neurodegenerative properties. Building upon this foundation, we delve deeper, employing all-atom molecular dynamics (MD) simulations extending over an extensive 500 ns. In particular, Ergotamine and Dihydroergocristine emerge as noteworthy candidates, binding to ApoE in a competitive mode. This intriguing binding behavior positions these compounds as potential candidates warranting further analysis in the pursuit of novel therapeutics targeting complex diseases associated with lipid metabolism and neurodegeneration. This approach holds the promise of catalyzing advancements in therapeutic intervention for complex disorders, thereby reporting a meaningful pace towards improved healthcare outcomes.

Inhibition of respiratory syncytial virus by Daclatasvir and its derivatives: synthesis of computational derivatives as a new drug development

The most common cause of respiratory tract illness in newborns and young children is the respiratory syncytial virus (RSV). There is no approved vaccination or specific antiviral medication for RSV infections. Here, an attempt has been made to explore the potential of currently marketed drugs as well as their probable derivatives to improve the possibility of developing stronger medications against RSV. From the 100 synthetic drug compounds library, the best drug molecule was identified through drug-likeness properties, toxicity, molecular docking and molecular dynamics simulations. Molecular Mechanics Generalized Born Surface Area (MM-GBSA) was also a method that was applied in this study. Daclatasvir showed the highest binding energy and appeared as the best drug to inhibit matrix protein and a fusion protein of RSV. Based on Daclatasvir, 40 computational derivatives were made. D28, D34 and D40 showed far better results than the actual drug. Changes in lipophilicity character increase the binding energy of derivatives. Molecular dynamic simulations showed their non-deviated, non-fluctuated and stable complex formation with target proteins. The high number of amino acid contacts throughout the trajectory increases the stability and effectiveness of derivatives. The key to producing a novel medicine to eradicate RSV is provided by derivatives. Daclatasvir will be employed as a potential RSV inhibitor up until that point.Communicated by Ramaswamy H. Sarma.

Computational Screening of Repurposed Drugs for HMG-CoA Synthase 2 in Alzheimer's Disease

Background

HMGCS2 (mitochondrial 3-hydroxy-3-methylglutaryl-COA synthase 2) plays a pivotal role as a control enzyme in ketogenesis, and its association with the amyloid-β protein precursor (AβPP) in mitochondria implicates a potential involvement in Alzheimer's disease (AD) pathophysiology.

Objective

Our study aimed at identifying repurposed drugs using the DrugBank database capable of inhibiting HMGCS2 activity.

Methods

Exploiting the power of drug repurposing in conjunction with virtual screening and molecular dynamic (MD) simulations against 'HMGCS2', we present new in-silico insight into structure-based drug repurposing.

Results

The initial molecules were screened for their binding affinity to HMGCS2. Subsequent interaction analyses and extensive 300 ns MD simulations were conducted to explore the conformational dynamics and stability of HMGCS2 in complex with the screened molecules, particularly Penfluridol and Lurasidone.

Conclusions

The study revealed that HMGCS2 forms stable protein-ligand complexes with Penfluridol and Lurasidone. Our findings indicate that Penfluridol and Lurasidone competitively bind to HMGCS2 and warrant their further exploration as potential repurposed molecules for anti-Alzheimer's drug development.

Synthesis, Docking Study of Some Novel Chromeno[4',3'-b]Pyrano [6,5-d]Pyrimidine Derivatives Against COVID-19 Main Protease (Mpro) (6LU7, 6M03)

AIMS

In this work, some new chromeno[4',3'-b]pyrano[6,5-d]pyrimidines,3-amino and 3-methyl-5-aryl-4-imino-5(H)-chromeno[4',3'-b]pyrano[6,5-d]pyrimidine-6-ones derivatives were synthesized.

BACKGROUND

Chromenopyrimidines have attracted significant attention recently because of their activities, such as antiviral and cytotoxic activity.

OBJECTIVE

All synthesized compounds were characterized using IR, 1H-NMR, Mass Spectroscopy, and elemental analysis data.

METHODS

Molecular docking studies were carried out to determine the inhibitory action of studied ligands against the Main Protease (6LU7, 6m03) of coronavirus (COVID-19). Moreover, the Lipinski Rule parameters were calculated for the synthesized compounds.

RESULTS

The result of the docking studies showed a significant inhibitory action against the Main protease (Mpro) of SARS-CoV-2, and the binding energy (ΔG) values of the ligands against the protein (6LU7, 6M03) are -7.8 to -9.9 Kcal/mole.

CONCLUSION

It may conclude that some ligands were likely to be considered lead-like against the main protease of SARS-CoV-2.

Multi-dimensional search for drug-target interaction prediction by preserving the consistency of attention distribution

Predicting drug-target interaction (DTI) is a crucial step in the process of drug repurposing and new drug development. Although the attention mechanism has been widely used to capture the interactions between drugs and targets, it mainly uses the Simplified Molecular Input Line Entry System (SMILES) and two-dimensional (2D) molecular graph features of drugs. In this paper, we propose a neural network model called MdDTI for DTI prediction. The model searches for binding sites that may interact with the target from the multiple dimensions of drug structure, namely the 2D substructures and the three-dimensional (3D) spatial structure. For the 2D substructures, we have developed a novel substructure decomposition strategy based on drug molecular graphs and compared its performance with the SMILES-based decomposition method. For the 3D spatial structure of drugs, we constructed spatial feature representation matrices for drugs based on the Cartesian coordinates of heavy atoms (without hydrogen atoms) in each drug. Finally, to ensure the search results of the model are consistent across multiple dimensions, we construct a consistency loss function. We evaluate MdDTI on four drug-target interaction datasets and three independent compound-protein affinity test sets. The results indicate that our model surpasses a series of state-of-the-art models. Case studies demonstrate that our model is capable of capturing the potential binding regions between drugs and targets, and it shows efficacy in drug repurposing. Our code is available at https://github.com/lhhu1999/MdDTI.

A review: FDA-approved fluorine-containing small molecules from 2015 to 2022

Fluorine-containing small molecules have occupied a special position in drug discovery research. The successful clinical use of fluorinated corticosteroids in the 1950s and fluoroquinolones in the 1980s led to an ever-increasing number of approved fluorinated compounds over the last 50 years. They have shown various biological properties such as antitumor, antimicrobial, and anti-inflammatory activities. Fluoro-pharmaceuticals have been considered a strong and practical tool in the rational drug design approach due to their benefits from potency and ADME (absorption, distribution, metabolism, and excretion) points of view. Herein, approved fluorinated drugs from 2015 to 2022 were reviewed.

Phytoconstituents as potential therapeutic agents against COVID-19: a computational study on inhibition of SARS-CoV-2 main protease

The Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) has become a global health crisis, and the urgent need for effective treatments is evident. One potential target for COVID-19 therapeutics is the main protease (Mpro) of SARS‑CoV‑2, an essential enzyme for viral replication. Natural compounds have been explored as a source of potential inhibitors for Mpro due to their safety and availability. In this study, we employed a computational approach to screen a library of phytoconstituents and identified potential Mpro inhibitors based on their binding affinities and molecular interactions. The top-ranking compounds were further validated through molecular dynamics simulations (MDS) and free energy calculations. As a result of the above procedures, we identified two phytoconstituents, Khelmarin B and Neogitogenin, with appreciable binding affinity and specificity towards the Mpro binding pocket. Our results suggest that Khelmarin B and Neogitogenin could potentially serve as Mpro inhibitors and have the potential to be developed as COVID-19 therapeutics. Further experimental studies are required to confirm the efficacy and safety of these compounds.Communicated by Ramaswamy H. Sarma.

Deciphering the role of fucoidan from brown macroalgae in inhibiting SARS-CoV-2 by targeting its main protease and receptor binding domain: Invitro and insilico approach

The current study investigated the role of fucoidan from Padina tetrastromatica and Turbinaria conoides against 3-chymotrypsin like protease (3CLpro) and receptor binding domain (RBD) spike protein of SARS-CoV-2 using an invitro and computational approach. The 3CLpro and RBD genes were successfully cloned in pET28a vector, expressed in BL-21DE3 E. coli rosetta cells and purified by ion exchange affinity and size exclusion chromatography. Fucoidan extracted from both biomass using green approach, subcritical water, was found to inhibit 3CLpro of SARS-CoV-2 with an IC50 value of up to 0.35 mg mL-1. However, fucoidan was found to be inactive against the RBD protein. Molecular docking studies demonstrated that fucoidan binds to the active sites of 3CLpro with an affinity of -5.0 kcal mol-1. In addition, molecular dynamic simulations recorded stabilized interactions of protein-ligand complexes in terms of root mean square deviation, root mean square fluctuation, the radius of gyration, solvent accessible surface area and hydrogen bond interaction. The binding energy of fucoidan with 3CLpro was determined to be -101.821 ± 12.966 kJ mol-1 using Molecular Mechanic/Poisson-Bolt-Boltzmann Surface Area analysis. Fucoidan satisfies the Absorption, Distribution, Metabolism, and Excretion (ADME) properties, including Lipinski's rule of five, which play an essential role in drug design. According to the toxicity parameters, fucoidan does not exhibit skin sensitivity, hepatotoxicity, or AMES toxicity. Therefore, this work reveals that fucoidan from brown macroalgae could act as possible inhibitors in regulating the function of the 3CLpro protein, hence inhibiting viral replication and being effective against COVID-19.

Insights into targeting SARS-CoV-2: design, synthesis, in silico studies and antiviral evaluation of new dimethylxanthine derivatives

Aiming to achieve efficient activity against severe acute respiratory syndrome coronavirus (SARS-CoV-2), the expansion of the structure- and ligand-based drug design approaches was adopted, which has been recently reported by our research group. Purine ring is a corner stone in the development of SARS-CoV-2 main protease (Mpro) inhibitors. The privileged purine scaffold was elaborated to achieve additional affinity based on hybridization and fragment-based approaches. Thus, the characteristic pharmacophoric features that are required for the inhibition of Mpro and RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 were utilized along with the crystal structure information of both targets. The designed pathways involved rationalized hybridization with large sulfonamide moieties and a carboxamide fragment for the synthesis of ten new dimethylxanthine derivatives. The synthesis was performed under diverse conditions to afford N-alkylated xanthine derivatives, and cyclization afforded tricyclic compounds. Molecular modeling simulations were used to confirm and gain insights into the binding interactions at both targets' active sites. The merit of designed compounds and the in silico studies resulted in the selection of three compounds that were evaluated in vitro to estimate their antiviral activity against SARS-CoV-2 (compounds 5, 9a and 19 with IC50 values of 38.39, 8.86 and 16.01 μM, respectively). Furthermore, oral toxicity of the selected antiviral candidates was predicted, in addition to cytotoxicity investigations. Compound 9a showed IC50 values of 8.06 and 3.22 μM against Mpro and RdRp of SARS-CoV-2, respectively, in addition to promising molecular dynamics stability in both target active sites. The current findings encourage further specificity evaluations of the promising compounds for confirming their specific protein targeting.

Vitamin D, Albumin, and D-Dimer as Significant Prognostic Markers in Early Hospitalization in Patients with COVID-19

SARS-CoV-2 continues to pose a major challenge to scientists and clinicians. We examined the significance of the serum concentrations of vitamin D, albumin, and D-dimer for the severity of the clinical picture and mortality in COVID-19.

MATERIALS AND METHODS

A total of 288 patients treated for COVID-19 infection participated in the research. The patients were treated in the period from May 2020 to January 2021. All patients were divided based on the need for oxygen therapy (Sat > 94%) into patients with mild or severe clinical pictures. The biochemical and radiographic parameters of the patients were analyzed. Appropriate statistical methods were used in the statistical analysis.

RESULTS

In patients with COVID-19 with confirmed severe clinical pictures, lower values of serum albumin (p < 0.0005) and vitamin D (p = 0.004) were recorded, as opposed to elevated values of D-dimer (p < 0.0005). Accordingly, the patients with fatal disease outcomes had lower levels of albumin (p < 0.0005) and vitamin D (p = 0.002), while their D-dimer (p < 0.0005) levels were elevated. An increase in the radiographic score, as a parameter for assessing the severity of the clinical picture, was accompanied by a decrease in serum albumin (p < 0.0005) and a simultaneous increase in D-dimer (p < 0.0005), without a change in the vitamin D concentration (p = 0.261). We also demonstrated the interrelations of the serum levels of vitamin D, albumin, and D-dimer in patients with COVID-19 as well as their significance as predictors of the outcome of the disease.

CONCLUSION

The significance of the predictive parameters in our study indicates the existence of an important combined role of vitamin D, albumin, and D-dimer in the early diagnosis of the most severe patients suffering from COVID-19. Reduced values of vitamin D and albumin, in combination with elevated values of D-dimer, can be timely indicators of the development of a severe clinical picture and death due to COVID-19.

Enhanced compound-protein binding affinity prediction by representing protein multimodal information via a coevolutionary strategy

Due to the lack of a method to efficiently represent the multimodal information of a protein, including its structure and sequence information, predicting compound-protein binding affinity (CPA) still suffers from low accuracy when applying machine-learning methods. To overcome this limitation, in a novel end-to-end architecture (named FeatNN), we develop a coevolutionary strategy to jointly represent the structure and sequence features of proteins and ultimately optimize the mathematical models for predicting CPA. Furthermore, from the perspective of data-driven approach, we proposed a rational method that can utilize both high- and low-quality databases to optimize the accuracy and generalization ability of FeatNN in CPA prediction tasks. Notably, we visually interpret the feature interaction process between sequence and structure in the rationally designed architecture. As a result, FeatNN considerably outperforms the state-of-the-art (SOTA) baseline in virtual drug evaluation tasks, indicating the feasibility of this approach for practical use. FeatNN provides an outstanding method for higher CPA prediction accuracy and better generalization ability by efficiently representing multimodal information of proteins via a coevolutionary strategy.

Linagliptin and Empagliflozin Inhibit Microtubule Affinity Regulatory Kinase 4: Repurposing Anti-Diabetic Drugs in Neurodegenerative Disorders Using In Silico and In Vitro Approaches

Type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) are significant public health burdens. Many studies have revealed the possibility of common pathophysiology between T2DM and AD. Thus, in recent years, studies deciphering the action mechanism of anti-diabetic drugs with their future use in AD and related pathologies are on high demand. Drug repurposing is a safe and effective approach owing to its low cost and time-saving attributes. Microtubule affinity regulating kinase 4 (MARK4) is a druggable target for various diseases and is found to be linked with AD and diabetes mellitus. MARK4 plays a vital role in energy metabolism and regulation and thus serves as an irrefutable target to treat T2DM. The present study was intended to identify the potent MARK4 inhibitors among FDA-approved anti-diabetic drugs. We performed structure-based virtual screening of FDA-approved drugs to identify the top hits against MARK4. We identified five FDA-approved drugs having an appreciable affinity and specificity toward the binding pocket of MARK4. Among these identified hits, two drugs, linagliptin, and empagliflozin, favorably bind to the MARK4 binding pocket, interacting with its critical residues and thus subjected to detailed analysis. All-atom detailed molecular dynamics (MD) simulations revealed the dynamics of binding of linagliptin and empagliflozin with MARK4. Kinase assay showed significant inhibition of MARK4 kinase activity in the presence of these drugs, implying them as potent MARK4 inhibitors. In conclusion, linagliptin and empagliflozin may be promising MARK4 inhibitors, which can further be exploited as potential lead molecules against MARK4-directed neurodegenerative diseases.

In silico analysis of dietary polyphenols and their gut microbial metabolites suggest inhibition of SARS-CoV-2 infection, replication, and host inflammatory mediators

The outcome of SARS-CoV-2 infection ranges from asymptomatic to severe COVID-19 and death resulting from an exaggerated immune response termed cytokine storm. Epidemiological data have associated consumption of a high-quality plant-based diet with decreased incidence and severity of COVID-19. Dietary polyphenols and their microbial metabolites (MMs) have anti-viral and anti-inflammatory activities. Autodock Vina and Yasara were used in molecular docking and dynamics studies to investigate potential interactions of 7 parent polyphenols (PPs) and 11 MMs with the α- and Omicron variants of the SARS-CoV-2 spike glycoprotein (SGP), papain-like pro-tease (PLpro) and 3 chymotrypsin-like protease (3CLpro), as well as host inflammatory mediators including complement component 5a (C5a), C5a receptor (C5aR), and C-C chemokine receptor type 5 (CCR5). PPs and MMs interacted to varying degrees with residues on target viral and host inflammatory proteins showing potential as competitive inhibitors. Based on these in silico findings, PPs and MMs may inhibit SARS-CoV-2 infection, replication, and/or modulate host immunity in the gut or periphery. Such inhibition may explain why people that consume a high-quality plant-based diet have less incidence and severity of COVID-19.Communicated by Ramaswamy H. Sarma.

In silico prediction of potential inhibitors for SARS-CoV-2 Omicron variant using molecular docking and dynamics simulation-based drug repurposing

BACKGROUND

In November 2021, variant B.1.1.529 of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified by the World Health Organization (WHO) and designated Omicron. Omicron is characterized by a high number of mutations, thirty-two in total, making it more transmissible than the original virus. More than half of those mutations were found in the receptor-binding domain (RBD) that directly interacts with human angiotensin-converting enzyme 2 (ACE2). This study aimed to discover potent drugs against Omicron, which were previously repurposed for coronavirus disease 2019 (COVID-19). All repurposed anti-COVID-19 drugs were compiled from previous studies and tested against the RBD of SARS-CoV-2 Omicron.

METHODS

As a preliminary step, a molecular docking study was performed to investigate the potency of seventy-one compounds from four classes of inhibitors. The molecular characteristics of the best-performing five compounds were predicted by estimating the drug-likeness and drug score. Molecular dynamics simulations (MD) over 100 ns were performed to inspect the relative stability of the best compound within the Omicron receptor-binding site.

RESULTS

The current findings point out the crucial roles of Q493R, G496S, Q498R, N501Y, and Y505H in the RBD region of SARS-CoV-2 Omicron. Raltegravir, hesperidin, pyronaridine, and difloxacin achieved the highest drug scores compared with the other compounds in the four classes, with values of 81%, 57%, 18%, and 71%, respectively. The calculated results showed that raltegravir and hesperidin had high binding affinities and stabilities to Omicron with ΔGbinding of - 75.7304 ± 0.98324 and - 42.693536 ± 0.979056 kJ/mol, respectively. Further clinical studies should be performed for the two best compounds from this study.

Elucidating the role of N440K mutation in SARS-CoV-2 spike - ACE-2 binding affinity and COVID-19 severity by virtual screening, molecular docking and dynamics approach

COVID-19 has become a public health concern around the world. The frequency of N440K variant was higher during the second wave in South India. The mutation was observed in the Receptor Binding Domain region (RBD) of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) spike (S) protein. The binding affinity of SARS-CoV-2-Angiotensin-Converting Enzyme-2 (ACE-2) plays a major role in the transmission and severity of the disease. To understand the binding affinity of the wild and mutant SARS-CoV-2 S with ACE2, molecular modeling studies were carried out. We discovered that the wild SARS-CoV-2 S RBD-ACE-2 complex has a high binding affinity and stability than that of the mutant. The N440K strain escapes from antibody neutralization, which might increase reinfection and decrease vaccine efficiency. To find a potential inhibitor against mutant N440K SARS-CoV-2, a virtual screening process was carried out and found ZINC169293961, ZINC409421825 and ZINC22060839 as the best binding energy compounds. Communicated by Ramaswamy H. Sarma.

Current Insights and Molecular Docking Studies of the Drugs under Clinical Trial as RdRp Inhibitors in COVID-19 Treatment

Study Background & Objective: After the influenza pandemic (1918), COVID-19 was declared a Vth pandemic by the WHO in 2020. SARS-CoV-2 is an RNA-enveloped single-stranded virus. Based on the structure and life cycle, Protease (3CLpro), RdRp, ACE2, IL-6, and TMPRSS2 are the major targets for drug development against COVID-19. Pre-existing several drugs (FDA-approved) are used to inhibit the above targets in different diseases. In coronavirus treatment, these drugs are also in different clinical trial stages. Remdesivir (RdRp inhibitor) is the only FDA-approved medicine for coronavirus treatment. In the present study, by using the drug repurposing strategy, 70 preexisting clinical or under clinical trial molecules were used in scrutiny for RdRp inhibitor potent molecules in coronavirus treatment being surveyed via docking studies. Molecular simulation studies further confirmed the binding mechanism and stability of the most potent compounds.

MATERIAL AND METHODS

Docking studies were performed using the Maestro 12.9 module of Schrodinger software over 70 molecules with RdRp as the target and remdesivir as the standard drug and further confirmed by simulation studies.

RESULTS

The docking studies showed that many HIV protease inhibitors demonstrated remarkable binding interactions with the target RdRp. Protease inhibitors such as lopinavir and ritonavir are effective. Along with these, AT-527, ledipasvir, bicalutamide, and cobicistat showed improved docking scores. RMSD and RMSF were further analyzed for potent ledipasvir and ritonavir by simulation studies and were identified as potential candidates for corona disease.

CONCLUSION

The drug repurposing approach provides a new avenue in COVID-19 treatment.

Potential of plant extracts in targeting SARS-CoV-2 main protease: an in vitro and in silico study

The deaths caused by the covid-19 pandemic have recently decreased due to a worldwide effort in vaccination campaigns. However, even vaccinated people can develop a severe form of the disease that requires ICU admission. As a result, the search for antiviral drugs to treat these severe cases has become a necessity. In this context, natural products are an interesting alternative to synthetic medicines used in drug repositioning, as they have been consumed for a long time through traditional medicine. Many natural compounds found in plant extracts have already been shown to be effective in treating viral and bacterial diseases, making them possible hits to exploit against covid-19. The objective of this work was to evaluate the antiviral activity of different plant extracts available in the library of natural products of the Universidade Estadual de Maringá, by inhibiting the SARS-CoV-2 main protease (Mpro), and by preventing viral infection in a cellular model. As a result, the extract of Cytinus hypocistis, obtained by ultrasound, showed a Mpro inhibition capacity greater than 90%. In the infection model assays using Vero cells, an inhibition of 99.6% was observed, with a selectivity index of 42.7. The in silico molecular docking simulations using the extract compounds against Mpro, suggested Tellimagrandin II as the component of C. hypocistis extract most likely to inhibit the viral enzyme. These results demonstrate the potential of C. hypocistis extract as a promising source of natural compounds with antiviral activity against covid-19.Communicated by Ramaswamy H. Sarma.

Influence of SARS-CoV-2 on Adult Human Neurogenesis

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with the onset of neurological and psychiatric symptoms during and after the acute phase of illness. Inflammation and hypoxia induced by SARS-CoV-2 affect brain regions essential for fine motor function, learning, memory, and emotional responses. The mechanisms of these central nervous system symptoms remain largely unknown. While looking for the causes of neurological deficits, we conducted a study on how SARS-CoV-2 affects neurogenesis. In this study, we compared a control group with a group of patients diagnosed with COVID-19. Analysis of the expression of neurogenesis markers showed a decrease in the density of neuronal progenitor cells and newborn neurons in the SARS-CoV-2 group. Analysis of COVID-19 patients revealed increased microglial activation compared with the control group. The unfavorable effect of the inflammatory process in the brain associated with COVID-19 disease increases the concentration of cytokines that negatively affect adult human neurogenesis.

Potential PDE4B inhibitors as promising candidates against SARS-CoV-2 infection

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is an RNA virus belonging to the coronavirus family responsible for coronavirus disease 2019 (COVID-19). It primarily affects the pulmonary system, which is the target of chronic obstructive pulmonary disease (COPD), for which many new compounds have been developed. In this study, phosphodiesterase 4 (PDE4) inhibitors are being investigated. The inhibition of PDE4 enzyme produces anti-inflammatory and bronchodilator effects in the lung by inducing an increase in cAMP concentrations. Piclamilast and rolipram are known selective inhibitors of PDE4, which are unfortunately endowed with common side effects, such as nausea and emesis. The selective inhibition of the phosphodiesterase 4B (PDE4B) subtype may represent an intriguing technique for combating this highly contagious disease with fewer side effects. In this article, molecular docking studies for the selective inhibition of the PDE4B enzyme have been carried out on 21 in-house compounds. The compounds were docked into the pocket of the PDE4B catalytic site, and in most cases, they were almost completely superimposed onto piclamilast. Then, in order to enlarge our study, drug-likeness prediction studies were performed on the compounds under study.

Potential inhibitory properties of structurally modified quercetin/isohamnetin glucosides against SARS-CoV-2 Mpro; molecular docking and dynamics simulation strategies

Concerned organizations and individuals are fully engaged in seeking appropriate measures towards managing Severe Acute Respiratory Syndrome Coronavirus 2 (SAR-CoV-2) infection because of the unprecedented economic and health impact. SAR-CoV-2 Main protease (SARS-CoV-2 Mpro) is unique to the survival and viability of the virus. Therefore, inhibition of Mpro can block the viral propagation. Thirty (30) derivatives were built by changing the glucosides in the Meta and para position of quercetin and isohamnetin. Molecular docking analysis was used for the screening of the compounds. Dynamics simulation was performed to assess the stability of the best pose docked complex. Molecular mechanics binding free energy calculation was done by Molecular Mechanics/Poisson-Boltzmann Surface Area (MMPBSA). Overall analysis showed that the compounds are allosteric inhibitors of SARS-CoV-2 Mpro. Dynamic simulation analysis established the stability of Mpro-ISM-1, Mpro-ISD-3, Mpro-IST-2, Mpro-QM-2, and Mpro-QD-6 complexes with a maximum of 7 hydrogen bonds involved in their interaction. The MMPBSA binding free energies for ISM-1, ISD-3, IST-2, QM-2, and QD-6 were -92.47 ± 9.06, -222.27 ± 32.5, 180.72 ± 47.92, 156.46 ± 49.88 and -93.52 ± 48.75 kcal/mol respectively. All the compounds showed good pharmacokinetic properties, while only ISM-1 inhibits hERG and might be cardio-toxic. Observations in this study established that the glucoside position indeed influenced the affinity for SARS-CoV-2 Mpro. The study also suggested the potentials of ISD-3, QM-2 and QD-6 as potent inhibitors of the main protease, further experimental and clinical studies are however necessary to validate and establish the need for further drug development processes. Therefore, future studies will be on the chemical synthesis of the compounds and investigation of the in-vitro inhibition of SARS-CoV-2.

Disruption of 3CLpro protease self-association by short peptides as a potential route to broad spectrum coronavirus inhibitors

Coronaviruses have posed a persistent threat to human health over the last two decades. Despite the accumulated knowledge about coronavirus-related pathogens, development of an effective treatment for its new variant COVID-19 is highly challenging. For the highly-conserved and main coronavirus protease 3CLpro, dimerization is known to be essential for its catalytic activity and thereby for virus proliferation. Here, we assess the potential of short peptide segments to disrupt dimerization of the 3CLpro protease as a route to block COVID-19 proliferation. Based on the X-ray structure of the 3CLpro dimer, we identified the SPSGVY₁₂₆QCAMRP dodecapeptide segment as overlapping the hotspot regions on the 3CLpro dimer interface. Using computational blind docking of the peptide to the 3CLpro monomer, we found that the SPSGVY₁₂₆QCAMRP peptide has favourable thermodynamic binding (ΔG= -5.93 kcal/mol) to the hotspot regions at the 3CLpro dimer interface. Importantly, the peptide was also found to preferentially bind to the hotspot regions compared to other potential binding sites lying away from the dimer interface (ΔΔG=-1.31 kcal/mol). Docking of peptides corresponding to systematic mutation of the V125 and Y126 residues led to the identification of seven peptides, SPSGHAQCAMRP, SPSGVTQCAMRP, SPSGKPQCAMRP, SPSGATQCAMRP, SPSGWLQCAMRP, SPSGAPQCAMRP and SPSGHPQCAMRP, that outperform the wild-type SPSGVY₁₂₆QCAMRP peptide in terms of preferential binding to the 3CLpro dimer interface. These peptides have the potential to disrupt 3CLpro dimerization and therefore could provide lead structures for the development of broad spectrum COVID-19 inhibitors.Communicated by Ramaswamy H. Sarma.

Interaction of the renin inhibitor aliskiren with the SARS-CoV-2 main protease: a molecular docking study

The renin protein is an upstream enzymatic regulator of the renin-aldosterone-angiotensin system (RAAS) essential for the maintenance of blood pressure. The angiotensin-converting enzyme-2 (ACE2) is a major component of the RAAS and a cell surface receptor exploited by the SARS-CoV-2 virus to enter host cells. A recent molecular modeling study has revealed that the direct renin peptide inhibitor remikiren can bind to the catalytic site of SARS-CoV-2 main protease (M^pro). By analogy, we postulated that the non-peptidic drug aliskiren, a more potent renin inhibitor than remikiren and a drug routinely used to treat hypertension, may also be able to interact with M^pro. An in silico comparison of the binding of the two compounds to M^pro indicates that aliskiren (ΔE = -75.9 kcal/mol) can form stable complexes with the main viral protease, binding to the active site, as remikiren (ΔE = -83.2 kcal/mol). The comparison with a panoply of 30 references compounds (mainly antiviral drugs) indicated that remikiren is a potent M^pro binder comparable to drugs like glecaprevir and pibrentasvir (ΔE = -96.5 kcal/mol). The energy of interaction (ΔE) of aliskiren with M^pro is about 10% lower than with remikiren, comparable to that calculated with drugs like velpatasvir and sofosbuvir. A model is proposed to define the drug binding site, with the best binders (including remikiren) penetrating deeply into the site, whereas the less potent binders (including aliskiren) interact more superficially with the protein.Communicated by Ramaswamy H. Sarma.

Design and in silico investigation of novel Maraviroc analogues as dual inhibition of CCR-5/SARS-CoV-2 Mpro

A sudden increase in life-threatening COVID-19 infections around the world inflicts global crisis and emotional trauma. In current study two druggable targets, namely SARS-COV-2 M^pro and CCR-5 were selected due to their significant nature in the viral life cycle and cytokine molecular storm respectively. The systematic drug repurposing strategy has been utilized to recognize inhibitory mechanism through extensive in silico investigation of novel Maraviroc analogues as promising inhibitors against SARS-CoV-2 M^pro and CCR-5. The dual inhibition specificity approach implemented in present study using molecular docking, molecular dynamics (MD), principal component analysis (PCA), free energy landscape (FEL) and MM/PBSA binding energy studies. The proposed Maraviroc analogues obtained from in silico investigation could be easily synthesized and constructive in developing significant drug against COVID-19 pandemic, with essentiality of their in vivo/in vitro evaluation to affirm the conclusions of this study. This will further fortify the concept of single drug targeting dual inhibition mechanism for treatment of COVID-19 infection and complications.

Identification of plant-based hexokinase 2 inhibitors: combined molecular docking and dynamics simulation studies

Cancer cells ferment glucose, even under aerobic conditions, following a phenomenon known as the 'Warburg effect.' Hexokinase 2 (HK2) catalyzes the crucial step of phosphorylation of glucose for subsequent utilization in glycolysis and other pathways. HK2 has been proposed as a potential therapeutic target for anti-cancer therapy because of its enhanced expression in glucose-dependent tumors. Here, we have employed structure-based virtual screening using in-house library to identify potential phytoconstituents which could inhibit the HK2 activity. The initial hits were selected based on their binding affinity towards HK2 using the molecular docking approach. Subsequently, the filters for physicochemical properties, PAINS patterns and PASS evaluation were applied to find potential hits against HK2. Finally, we have identified epigallocatechin gallate (EGCG) and quercitrin, two natural compounds with appreciable binding affinity, efficiency and specificity towards the HK2 binding pocket. Both compounds were found to be binding preferentially to the HK2 active site and showed a decent set of drug-like properties. All-atom molecular dynamics (MD) simulations for 100 ns were carried out to see the conformational dynamics, complexes stability and interaction mechanism of HK2 with EGCG and quercitrin. MD simulation results showed that HK2 forms stable protein-ligand complexes with EGCG and quercitrin with consistency throughout the trajectory. Overall, these findings suggest that EGCG and quercitrin might be further exploited as promising scaffolds in the drug development process against HK2..Communicated by Ramaswamy H. Sarma.

Targeting SARS-CoV-2 nsp13 Helicase and Assessment of Druggability Pockets: Identification of Two Potent Inhibitors by a Multi-Site In Silico Drug Repurposing Approach

The SARS-CoV-2 non-structural protein 13 (nsp13) helicase is an essential enzyme for viral replication and has been identified as an attractive target for the development of new antiviral drugs. In detail, the helicase catalyzes the unwinding of double-stranded DNA or RNA in a 5' to 3' direction and acts in concert with the replication-transcription complex (nsp7/nsp8/nsp12). In this work, bioinformatics and computational tools allowed us to perform a detailed conservation analysis of the SARS-CoV-2 helicase genome and to further predict the druggable enzyme's binding pockets. Thus, a structure-based virtual screening was used to identify valuable compounds that are capable of recognizing multiple nsp13 pockets. Starting from a database of around 4000 drugs already approved by the Food and Drug Administration (FDA), we chose 14 shared compounds capable of recognizing three out of four sites. Finally, by means of visual inspection analysis and based on their commercial availability, five promising compounds were submitted to in vitro assays. Among them, PF-03715455 was able to block both the unwinding and NTPase activities of nsp13 in a micromolar range.

A Comprehensive In Silico Study of New Metabolites from Heteroxenia fuscescens with SARS-CoV-2 Inhibitory Activity

Chemical investigation of the total extract of the Egyptian soft coral Heteroxenia fuscescens, led to the isolation of eight compounds, including two new metabolites, sesquiterpene fusceterpene A (1) and a sterol fuscesterol A (4), along with six known compounds. The structures of 1–8 were elucidated via intensive studies of their 1D, 2D-NMR, and HR-MS analyses, as well as a comparison of their spectral data with those mentioned in the literature. Subsequent comprehensive in-silico-based investigations against almost all viral proteins, including those of the new variants, e.g., Omicron, revealed the most probable target for these isolated compounds, which was found to be M^pro. Additionally, the dynamic modes of interaction of the putatively active compounds were highlighted, depending on 50-ns-long MDS. In conclusion, the structural information provided in the current investigation highlights the antiviral potential of H. fuscescens metabolites with 3β,5α,6β-trihydroxy steroids with different nuclei against SARS-CoV-2, including newly widespread variants.

Effectiveness of Remdesivir in Comparison with Five Approved Antiviral Drugs for Inhibition of RdRp in Combat with SARS-CoV-2

The treatment of COVID-19 disease has been one of the most critical essential concerns of researchers in recent years. One of the most exciting and potential therapeutic targets for SARS-CoV-2 therapy progression is RNA-dependent RNA polymerase (RdRP), a viral enzyme for viral RNA replication throughout host cells. According to some research, Remdesivir suppresses RdRp. The nucleoside medication remdesivir has been authorized under an Emergency Use Authorization to treat COVID-19. Given the role of this enzyme in virus replication, our scientific question is whether Remdesivir is the most appropriate antiviral drug to inhibit this enzyme or not. Accordingly, this study aimed to repurpose antiviral drugs to inhibition of RdRp using virtual screening and Molecular Dynamics simulation methods. Five FDA-approved antiviral medications, including Elbasvir, Glecaprevir, Ledipasvir, Paritaprevir, and Simeprevir, had good interaction potential with RdRp. Also, the results show that the number of H-bonds and contacts and ∆G interactions between the protein and ligand in the Remdesivir complex is less than those of other complexes. According to the given data which shows the tendency of binding with RdRp for Paritaprevir, Simeprevir, Glecaprevir, and Ledipasvir and Elbasvir is more than Remdesivir and due to the fact that these five drugs have a high tendency to bind to other targets in the SARS-CoV-2, the use of Remdesivir as an antiviral drug in the treatment of COVID-19 should be considered more sensitively.

Therapeutic implications and clinical manifestations of thymoquinone

Thymoquinone (TQ), a natural phytochemical predominantly found in Nigella sativa, has been investigated for its numerous health benefits. TQ showed anti-cancer, anti-oxidant, and anti-inflammatory properties, validated in various disease models. The anti-cancer potential of TQ is goverened by anti-proliferation, cell cycle arrest, apoptosis induction, ROS production, anti-metastasis and anti-angiogenesis, inhibition of cell migration and invasion action. Additionally, TQ exhibited antitumor activity via the modulation of multiple pathways and molecular targets, including Akt, ERK1/2, STAT3, and NF-κB. The present review highlighted the anticancer potential of TQ . We summarize the anti-cancer, anti-oxidant, and anti-inflammatory properties of TQ, focusing on its molecular targets and its promising action in cancer therapy. We further described the molecular mechanisms by which TQ prevents signaling pathways that mediate cancer progression, invasion, and metastasis.

Evaluation for substitution of stem bark with small branches of Cassia fistula Linn for traditional medicinal uses: A comparative chemical profiling studies by HPLC, LC-MS, GC-MS

Background

The Aim of the present research article is to proposing a conservative approach for the Cassia fistula by using of small branches instead of stem bark because of plant has many important chemical constituents which show different medicinal activity so consumption of plant is high. We studied here Comparative preliminary phytochemical screening test of the ethanol extract and aqueous extract of the stem bark and small branches of Cassia fistula obtained by cold maceration process. Physicochemical analysis of Cassia fistula was done to ascertain the quality of the raw material used in the study. Successive soxhlet extraction method used for the successive extraction of stem bark and small branches with different solvents for comparative chemical profile study by HPLC, LCMS, and GCMS. Molecular Docking Interaction of Abundant Medicinal Phytochemicals in the Liquid Chromatography−Mass Spectrometry (LC−MS) Analysis Data of C. fistula with the L. donovani Drug Target Proteins and Pancreatic lipase colipase target protein.

Result

The pH of the small branches was found slightly higher as compared to stem bark and the percentage of other parameters like total ash content, acid insoluble ash, loss on drying at 105 °C, water soluble extractive and alcohol soluble extractive values were found fewer in the small branches as compare to stem bark of the plant. It was observed that the number of peaks in stem bark and small branches of the plant sample were almost similar and the retention time of each peak in stem bark was coincide with the retention of small branches of the sample. Therefore, similarity was observed in stem bark and small branches of the Cassia fistula plant in HPLC, LC-MS and GC-MS. The results obtained from HPLC analysis shows that stem bark contains 0.0084% and small branches having 0.0257% of rhein in Cassia fistula. Compounds 3, 9 and 12 are present in Stem bark as well as small branches of C. fistula and Compounds 22, 32 and 37 are present in small branches only. All the compounds have very good binding energy (Kcal/mol) with the respective target proteins.

Conclusion

The small branches have more active chemical constituents than stem bark against particular target proteins.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Drug repurposing against main protease and RNA-dependent RNA polymerase of SARS-CoV-2 using molecular docking, MM-GBSA calculations and molecular dynamics

A virus called severe acute respiratory distress syndrome coronavirus type 2 (SARS‐CoV‐2) is the causing organism of coronavirus disease 2019 (COVID-19), which has severely affected human life and threatened public health. The pandemic took millions of lives worldwide and caused serious negative effects on human society and the economy. SARS-CoV-2 main protease (Mpro) and RNA-dependent RNA polymerase (RdRp) are interesting targets due to their crucial role in viral replication and growth. Since there is only one approved therapy for COVID-19, drug repurposing is a promising approach to finding molecules with potential activity against COVID-19 in a short time and at minimal cost. In this study, virtual screening was performed on the ChEMBL library containing 9923 FDA-approved drugs, using various docking filters with different accuracy. The best drugs with the highest docking scores were further examined for molecular dynamics (MD) studies and MM-GBSA calculations. The results of this study suggest that nadide, cangrelor and denufosol are promising potential candidates against COVID-19. Further in vitro, preclinical and clinical studies of these candidates would help to discover safe and effective anti-COVID-19 drugs.

Molecular dynamics simulation approach for discovering potential inhibitors against SARS-CoV-2: A structural review

Since the commencement of the novel Coronavirus, the disease has quickly turned into a worldwide crisis so that there has been growing attention in discovering possible hit compounds for tackling this pandemic. Discovering standard treatment strategies is a serious challenge because little information is available about this emerged infectious virus. Regarding the high impact of time, applying computational procedures to choose promising drugs from a catalog of licensed medications provides a precious chance for combat against the life-threatening disorder of COVID-19. Molecular dynamics (MD) simulation is a promising approach for assessing the binding affinity of ligand-receptor as well as observing the conformational trajectory of docked complexes over time. Given that many computational studies are performed using MD along with the molecular docking on various candidates as antiviral inhibitors of COVID-19 protease, there is a demand to conduct a comprehensive review of the most important studies to reveal and compare the potential introduced agents that this study covers this defect. In this context, the present review intends to prepare an overview of these studies by considering RMSD, RMSF, radius of gyration, binding free energy, and Solvent-Accessible Surface Area (SASA) as effective parameters for evaluation. The outcomes will offer a road map for adjusting antiviral inhibitors, which can facilitate the selection and development of drug candidates for use in the medical therapy. Finally, the molecular modeling approaches rendered by this study may be valuable for future computational studies.

Structure-based identification of potential SARS-CoV-2 main protease inhibitors

To address coronavirus disease (COVID-19), currently, no effective drug or vaccine is available. In this regard, molecular modeling approaches are highly useful to discover potential inhibitors of the main protease (Mpro) enzyme of SARS-CoV-2. Since, the Mpro enzyme plays key roles in mediating viral replication and transcription; therefore, it is considered as an attractive drug target to control SARS-CoV-2 infection. By using structure-based drug design, pharmacophore modeling, and virtual high throughput drug screening combined with docking and all-atom molecular dynamics simulation approach, we have identified five potential inhibitors of SARS-CoV-2 Mpro. MD simulation studies revealed that compound 54035018 binds to the Mpro with high affinity (ΔGbind -37.40 kcal/mol), and the complex is more stable in comparison with other protein-ligand complexes. We have identified promising leads to fight COVID-19 infection as these compounds fulfill all drug-likeness properties. However, experimental and clinical validations are required for COVID-19 therapy.Communicated by Ramaswamy H. Sarma.

Identification of intrinsically disorder regions in non-structural proteins of SARS-CoV-2: New insights into drug and vaccine resistance

The outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emerged in December 2019 and caused coronavirus disease 2019 (COVID-19), which causes pneumonia and severe acute respiratory distress syndrome. It is a highly infectious pathogen that promptly spread. Like other beta coronaviruses, SARS-CoV-2 encodes some non-structural proteins (NSPs), playing crucial roles in viral transcription and replication. NSPs likely have essential roles in viral pathogenesis by manipulating many cellular processes. We performed a sequence-based analysis of NSPs to get insights into their intrinsic disorders, and their functions in viral replication were annotated and discussed in detail. Here, we provide newer insights into the structurally disordered regions of SARS-CoV-2 NSPs. Our analysis reveals that the SARS-CoV-2 proteome has a chunk of the disordered region that might be responsible for increasing its virulence. In addition, mutations in these regions are presumably responsible for drug and vaccine resistance. These findings suggested that the structurally disordered regions of SARS-CoV-2 NSPs might be invulnerable in COVID-19.

Resilience of Spike-Specific Immunity Induced by COVID-19 Vaccines against SARS-CoV-2 Variants

The outbreak of SARS-CoV-2 leading to the declaration of the COVID-19 global pandemic has led to the urgent development and deployment of several COVID-19 vaccines. Many of these new vaccines, including those based on mRNA and adenoviruses, are aimed to generate neutralizing antibodies against the spike glycoprotein, which is known to bind to the receptor angiotensin converting enzyme 2 (ACE2) in host cells via the receptor-binding domain (RBD). Antibodies binding to this domain can block the interaction with the receptor and prevent viral entry into the cells. Additionally, these vaccines can also induce spike-specific T cells which could contribute to providing protection against the virus. However, the emergence of new SARS-CoV-2 variants can impair the immunity generated by COVID-19 vaccines if mutations occur in cognate epitopes, precluding immune recognition. Here, we evaluated the chance of five SARS-CoV-2 variants of concern (VOCs), Alpha, Beta, Gamma, Delta and Omicron, to escape spike-specific immunity induced by vaccines. To that end, we examined the impact of the SARS-CoV-2 variant mutations on residues located on experimentally verified spike-specific epitopes, deposited at the Immune Epitope Database, that are targeted by neutralizing antibodies or recognized by T cells. We found about 300 of such B cell epitopes, which were largely overlapping, and could be grouped into 54 B cell epitope clusters sharing ≥ 7 residues. Most of the B cell epitope clusters map in the RBD domain (39 out of 54) and 20%, 50%, 37%, 44% and 57% of the total are mutated in SARS-CoV-2 Alpha, Beta, Gamma, Delta and Omicron variants, respectively. We also found 234 experimentally verified CD8 and CD4 T cell epitopes that were distributed evenly throughout the spike protein. Interestingly, in each SARS-CoV-2 VOC, over 87% and 79% of CD8 and CD4 T cell epitopes, respectively, are not mutated. These observations suggest that SARS-CoV-2 VOCs—particularly the Omicron variant—may be prone to escape spike-specific antibody immunity, but not cellular immunity, elicited by COVID-19 vaccines.

Plant Source Derived Compound Exhibited In Silico Inhibition of Membrane Glycoprotein In SARS-CoV-2: Paving the Way to Discover a New Class of Compound For Treatment of COVID-19

SARS-CoV-2 is the virus responsible for causing COVID-19 disease in humans, creating the recent pandemic across the world, where lower production of Type I Interferon (IFN-I) is associated with the deadly form of the disease. Membrane protein or SARS-CoV-2 M proteins are known to be the major reason behind the lower production of human IFN-I by suppressing the expression of IFNβ and Interferon Stimulated Genes. In this study, 7,832 compounds from 32 medicinal plants of India possessing traditional knowledge linkage with pneumonia-like disease treatment, were screened against the Homology-Modelled structure of SARS-CoV-2 M protein with the objective of identifying some active phytochemicals as inhibitors. The entire study was carried out using different modules of Schrodinger Suite 2020-3. During the docking of the phytochemicals against the SARS-CoV-2 M protein, a compound, ZIN1722 from Zingiber officinale showed the best binding affinity with the receptor with a Glide Docking Score of −5.752 and Glide gscore of −5.789. In order to study the binding stability, the complex between the SARS-CoV-2 M protein and ZIN1722 was subjected to 50 ns Molecular Dynamics simulation using Desmond module of Schrodinger suite 2020-3, during which the receptor-ligand complex showed substantial stability after 32 ns of MD Simulation. The molecule ZIN1722 also showed promising results during ADME-Tox analysis performed using Swiss ADME and pkCSM. With all the findings of this extensive computational study, the compound ZIN1722 is proposed as a potential inhibitor to the SARS-CoV-2 M protein, which may subsequently prevent the immunosuppression mechanism in the human body during the SARS-CoV-2 virus infection. Further studies based on this work would pave the way towards the identification of an effective therapeutic regime for the treatment and management of SARS-CoV-2 infection in a precise and sustainable manner.

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.

BACPI: a bi-directional attention neural network for compound-protein interaction and binding affinity prediction

MOTIVATION

The identification of compound-protein interactions (CPIs) is an essential step in the process of drug discovery. The experimental determination of CPIs is known for a large amount of funds and time it consumes. Computational model has therefore become a promising and efficient alternative for predicting novel interactions between compounds and proteins on a large scale. Most supervised machine learning prediction models are approached as a binary classification problem, which aim to predict whether there is an interaction between the compound and the protein or not. However, CPI is not a simple binary on-off relationship, but a continuous value reflects how tightly the compound binds to a particular target protein, also called binding affinity.

RESULTS

In this study, we propose an end-to-end neural network model, called BACPI, to predict CPI and binding affinity. We employ graph attention network and convolutional neural network (CNN) to learn the representations of compounds and proteins and develop a bi-directional attention neural network model to integrate the representations. To evaluate the performance of BACPI, we use three CPI datasets and four binding affinity datasets in our experiments. The results show that, when predicting CPIs, BACPI significantly outperforms other available machine learning methods on both balanced and unbalanced datasets. This suggests that the end-to-end neural network model that predicts CPIs directly from low-level representations is more robust than traditional machine learning-based methods. And when predicting binding affinities, BACPI achieves higher performance on large datasets compared to other state-of-the-art deep learning methods. This comparison result suggests that the proposed method with bi-directional attention neural network can capture the important regions of compounds and proteins for binding affinity prediction.

AVAILABILITY AND IMPLEMENTATION

Data and source codes are available at https://github.com/CSUBioGroup/BACPI.

In Silico Insights towards the Identification of SARS-CoV-2 NSP13 Helicase Druggable Pockets

The merging of distinct computational approaches has become a powerful strategy for discovering new biologically active compounds. By using molecular modeling, significant efforts have recently resulted in the development of new molecules, demonstrating high efficiency in reducing the replication of severe acute respiratory coronavirus 2 (SARS-CoV-2), the agent responsible for the COVID-19 pandemic. We have focused our interest on non-structural protein Nsp13 (NTPase/helicase), as a crucial protein, embedded in the replication–transcription complex (RTC), that controls the virus life cycle. To assist in the identification of the most druggable surfaces of Nsps13, we applied a combination of four computational tools: FTMap, SiteMap, Fpocket and LigandScout. These software packages explored the binding sites for different three-dimensional structures of RTC complexes (PDB codes: 6XEZ, 7CXM, 7CXN), thus, detecting several hot spots, that were clustered to obtain ensemble consensus sites, through a combination of four different approaches. The comparison of data provided new insights about putative druggable sites that might be employed for further docking simulations on druggable surfaces of Nsps13, in a scenario of repurposing drugs.

Natural products can be used in therapeutic management of COVID-19: Probable mechanistic insights

The unexpected emergence of the new Coronavirus disease (COVID-19) has affected more than three hundred million individuals and resulted in more than five million deaths worldwide. The ongoing pandemic has underscored the urgent need for effective preventive and therapeutic measures to develop anti-viral therapy. The natural compounds possess various pharmaceutical properties and are reported as effective anti-virals. The interest to develop an anti-viral drug against the novel severe acute respiratory syndrome Coronavirus (SARS-CoV-2) from natural compounds has increased globally. Here, we investigated the anti-viral potential of selected promising natural products. Sources of data for this paper are current literature published in the context of therapeutic uses of phytoconstituents and their mechanism of action published in various reputed peer-reviewed journals. An extensive literature survey was done and data were critically analyzed to get deeper insights into the mechanism of action of a few important phytoconstituents. The consumption of natural products such as thymoquinone, quercetin, caffeic acid, ursolic acid, ellagic acid, vanillin, thymol, and rosmarinic acid could improve our immune response and thus possesses excellent therapeutic potential. This review focuses on the anti-viral functions of various phytoconstituent and alkaloids and their potential therapeutic implications against SARS-CoV-2. Our comprehensive analysis provides mechanistic insights into phytoconstituents to restrain viral infection and provide a better solution through natural, therapeutically active agents.

Baicalin Targets HSP70/90 to Regulate PKR/PI3K/AKT/eNOS Signaling Pathways

Baicalin is a major active ingredient of traditional Chinese medicine Scutellaria baicalensis, and has been shown to have antiviral, anti-inflammatory, and antitumor activities. However, the protein targets of baicalin have remained unclear. Herein, a chemical proteomics strategy was developed by combining baicalin-functionalized magnetic nanoparticles (BCL-N3@MNPs) and quantitative mass spectrometry to identify the target proteins of baicalin. Bioinformatics analysis with the use of Gene Ontology, STRING and Ingenuity Pathway Analysis, was performed to annotate the biological functions and the associated signaling pathways of the baicalin targeting proteins. Fourteen proteins in human embryonic kidney cells were identified to interact with baicalin with various binding affinities. Bioinformatics analysis revealed these proteins are mainly ATP-binding and/or ATPase activity proteins, such as CKB, HSP86, HSP70-1, HSP90, ATPSF1β and ACTG1, and highly associated with the regulation of the role of PKR in interferon induction and the antiviral response signaling pathway (P = 10-6), PI3K/AKT signaling pathway (P = 10-5) and eNOS signaling pathway (P = 10-4). The results show that baicalin exerts multiply pharmacological functions, such as antiviral, anti-inflammatory, antitumor, and antioxidant functions, through regulating the PKR and PI3K/AKT/eNOS signaling pathways by targeting ATP-binding and ATPase activity proteins. These findings provide a fundamental insight into further studies on the mechanism of action of baicalin.

Discovery of compounds inhibiting SARS-COV-2 multi-targets

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pandemic that has devastated the lives of millions. Researchers around the world are relentlessly working in hopes of finding a cure. Even though the virus shares similarities with reported SARS-CoV and MERS-CoV at the genomic and proteomic level, efforts to repurpose already known drugs against SARS-CoV-2 have resulted ineffective. In this succinct review, we discuss the different potential targets in SARS-CoV-2 at both the genomic and proteomic levels. In addition, we analyze the compounds inhibiting individual target protein as well as multiple targets of SARS-CoV-2. ACE-2 receptor in humans has also been considered a target, keeping the role of the receptor in mind. The mechanism of action of these compounds has also been highlighted along with their clinical manifestation. Towards the end of the review, a brief note on the drugs currently in clinical trials and the current status of the vaccines are also examined. In conclusion, compounds targeting multiple targets of the virus hold the key in putting an end to the coronavirus malady.Communicated by Ramaswamy H. Sarma.