Pharmacophore-Based Virtual Screening, Quantum Mechanics Calculations, and Molecular Dynamics Simulation Approaches Identified Potential Natural Antiviral Drug Candidates against MERS-CoV S1-NTD

Antiviral Activity, Pharmacoinformatics, Molecular Docking, and Dynamics Studies of Azadirachta indica Against Nipah Virus by Targeting Envelope Glycoprotein: Emerging Strategies for Developing Antiviral Treatment

The Nipah virus (NiV) belongs to the Henipavirus genus is a serious public health concern causing numerous outbreaks with higher fatality rate. Unfortunately, there is no effective medication available for NiV. To investigate possible inhibitors of NiV infection, we used in silico techniques to discover treatment candidates in this work. As there are not any approved treatments for NiV infection, the NiV-enveloped attachment glycoprotein was set as target for our study, which is responsible for binding to and entering host cells. Our in silico drug design approach included molecular docking, post-docking molecular mechanism generalised born surface area (MM-GBSA), absorption, distribution, metabolism, excretion/toxicity (ADME/T), and molecular dynamics (MD) simulations. We retrieved 418 phytochemicals associated with the neem plant (Azadirachta indica) from the IMPPAT database, and molecular docking was used to ascertain the compounds' binding strength. The top 3 phytochemicals with binding affinities of -7.118, -7.074, and -6.894 kcal/mol for CIDs 5280343, 9064, and 5280863, respectively, were selected for additional study based on molecular docking. The post-docking MM-GBSA of those 3 compounds was -47.56, -47.3, and -43.15 kcal/mol, respectively. As evidence of their efficacy and safety, all the chosen drugs had favorable toxicological and pharmacokinetic (Pk) qualities. We also performed MD simulations to confirm the stability of the ligand-protein complex structures and determine whether the selected compounds are stable at the protein binding site. All 3 phytochemicals, Quercetin (CID: 5280343), Cianidanol (CID: 9064), and Kaempferol (CID: 5280863), appeared to have outstanding binding stability to the target protein than control ribavirin, according to the molecular docking, MM-GBSA, and MD simulation outcomes. Overall, this work offers a viable approach to developing novel medications for treating NiV infection.

Computational Exploration of Potential Pharmacological Inhibitors Targeting the Envelope Protein of the Kyasanur Forest Disease Virus

The limitations of the current vaccination strategy for the Kyasanur Forest Disease virus (KFDV) underscore the critical need for effective antiviral treatments, highlighting the crucial importance of exploring novel therapeutic approaches through in silico drug design. Kyasanur Forest Disease, caused by KFDV, is a tick-borne disease with a mortality of 3-5% and an annual incidence of 400 to 500 cases. In the early stage of infection, the envelope protein plays a crucial role by facilitating host-virus interactions. The objective of this research is to develop effective antivirals targeting the envelope protein to disrupt the virus-host interaction. In line with this, the 3D structure of the envelope protein was modeled and refined through molecular modeling techniques, and subsequently, ligands were designed via de novo design and pharmacophore screening, yielding 12 potential hits followed by ADMET analysis. The top five candidates underwent geometry optimization and molecular docking. Notably, compounds L4 (SA28) and L3 (CNP0247967) are predicted to have significant binding affinities of -8.91 and -7.58 kcal/mol, respectively, toward the envelope protein, based on computational models. Both compounds demonstrated stability during 200 ns molecular dynamics simulations, and the MM-GBSA binding free-energy values were -85.26 ± 4.63 kcal/mol and -66.60 ± 2.92 kcal/mol for the envelope protein L3 and L4 complexes, respectively. Based on the computational prediction, it is suggested that both compounds have potential as drug candidates for controlling host-virus interactions by targeting the envelope protein. Further validation through in-vitro assays would complement the findings of the present in silico investigations.

Coprisin/Compound K Conjugated Gold Nanoparticles Induced Cell Death through Apoptosis and Ferroptosis Pathway in Adenocarcinoma Gastric Cells

Ferroptosis and apoptosis are programmed cell death pathways with distinct characteristics. Sometimes, cancer cells are aided by the induction of a different pathway, such as ferroptosis, when they develop chemoresistance and avoid apoptosis. Identifying the nanomedicine that targets dual pathways is considered as one of the best strategies for diverse cancer types. In our previous work, we synthesized gold nanoparticles (GNP) utilizing Gluconacetobacter liquefaciens in conjunction with compound K (CK) and coprisin (CopA3), yielding GNP-CK-CopA3. Here, we assessed the inhibitory effect of GNP-CK-CopA3 on AGS cells and the induction of apoptosis using Hoechst and PI, Annexin V-FITC/PI, and qRT-PCR. Subsequently, we conducted downstream proteomic analysis and molecular dynamic stimulation to identify the underlying molecular mechanisms. Our investigation of cultured AGS cells treated with varying concentrations of GNP-CK-CopA3 demonstrated the anticancer properties of these nanoparticles. Penetration of GNP-CK-CopA3 into AGS cells was visualized using an enhanced dark field microscope. Apoptosis induction was initially confirmed by treating AGS cells with GNP-CK-CopA3, as evidenced by staining with dyes such as Hoechst and PI. Additionally, mitochondrial disruption and cellular localization induced by GNP-CK-CopA3 were validated through Mito-tracker staining and transmission electron microscopy images. Annexin V-FITC/PI staining was used to distinguish early and late-stage apoptosis or necrosis based on fluorescence patterns. The gene expression of apoptotic markers indicated the initiation of cellular apoptosis. Further, proteomic analysis suggested that the treatment of GNP-CK-CopA3 to AGS cells led to the suppression of 439 proteins and the stimulation of 832 proteins. Among these, ferroptosis emerged as a significant interconnected pathway where glutathione peroxidase 4 (GPX4) and glutathione synthetase (GSS) were significant interacting proteins. Molecular docking and dynamic simulation studies confirmed the binding affinity and stability between CopA3 and CK with GSS and GPX4 proteins, suggesting the role of GNP-CK-CopA3 in ferroptosis induction. Overall, our study showed GNP-CK-CopA3 could play a dual role by inducing apoptosis and ferroptosis to induce AGS cell death.

Molecular insights on the coronavirus MERS-CoV interaction with the CD26 receptor

The Middle East respiratory syndrome (MERS) is a severe respiratory disease with high fatality rates, caused by the Middle East respiratory syndrome coronavirus (MERS-CoV). The virus initiates infection by binding to the CD26 receptor (also known as dipeptidyl peptidase 4 or DPP4) via its spike protein. Although the receptor-binding domain (RBD) of the viral spike protein and the complex between RBD and the extracellular domain of CD26 have been studied using X-ray crystallography, conflicting studies exist regarding the importance of certain amino acids outside the resolved RBD-CD26 complex interaction interface. To gain atomic-level knowledge of the RBD-CD26 complex, we employed computational simulations to study the complex's dynamic behavior as it evolves from its crystal structure to a conformation stable in solution. Our study revealed previously unidentified interaction regions and interacting amino acids within the complex, determined a novel comprehensive RBD-binding domain of CD26, and by that expanded the current understanding of its structure. Additionally, we examined the impact of a single amino acid substitution, E513A, on the complex's stability. We discovered that this substitution disrupts the complex through an allosteric domino-like mechanism that affects other residues. Since MERS-CoV is a zoonotic virus, we evaluated its potential risk of human infection via animals, and suggest a low likelihood for possible infection by cats or dogs. The molecular structural information gleaned from our insights into the RBD-CD26 complex pre-dissociative states may be proved useful not only from a mechanistic view but also in assessing inter-species transmission and in developing anti-MERS-CoV antiviral therapeutics.

Neomangiferin, a Naturally Occurring Mangiferin Congener, Inhibits Sodium-Glucose Co-transporter-2: An In silico Approach

Type 2 diabetes is a major health concern contributing to most of diabetic cases worldwide. Mangiferin and its congeners are known for their diverse pharmacological properties. This study sought to investigate the inhibitory property of naturally occurring mangiferin congeners on sodium-glucose co-transporter 2 protein (SGLT-2) using comprehensive computational methods. The naturally occurring mangiferin congeners were subjected to molecular docking, molecular dynamics (MDs) simulation (100 ns), molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) binding free energy, density functional theory calculations (B3LYP 6-31G basis set), and ADMET approaches to identify potential SGLT-2 inhibitor. The molecular docking studies revealed neomangiferin (-9.0 kcal/mol) as the hit molecule compared with dapagliflozin (-8.3 kcal/mol). Root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) plots from the MD simulations established that neomangiferin stabilizes SGLT-2 better than the dapagliflozin, a standard drug. The MM-PBSA binding free energy calculations showed that neomangiferin (-26.05 kcal/mol) elicited better binding affinity than dapagliflozin (-17.42 kcal/mol). The electronic studies showed that neomangiferin (3.48 eV) elicited high electrophilicity index compared with mangiferin (3.31 eV) and dapagliflozin (2.11 eV). Also, the ADMET properties showed that the hit molecule is safe when administered to diabetic subjects. The current in silico studies suggest that neomangiferin could emerge as a promising lead molecule as a SGLT-2 inhibitor.

Identification of potential flavonoid compounds as antibacterial therapeutics against Klebsiella pneumoniae infection using structure-based virtual screening and molecular dynamics simulation

Klebsiella pneumoniae, which is among the top three pathogens on WHO's priority list, is one of the gram-negative bacteria that doctors and researchers around the world have fought for decades. Capsular polysaccharide (CPS) protein is extensively recognized as an important K. pneumoniae virulence factor. Thus, CPS has become the most characterized target for the discovery of novel drug candidates. The ineffectiveness of currently existing antibiotics urges the search for potent antimicrobial compounds. Flavonoids are a group of plant metabolites that have antibacterial potential and can enhance the present medications to elicit improved results against diverse diseases without adverse reactions. Henceforth, the present study aims to illustrate the inhibitory potential of flavonoids with varying pharmacological properties, targeting the CPS protein of K. pneumoniae by in silico approaches. The flavonoid compounds (n = 169) were retrieved from the PubChem database and screened using the structure-based virtual screening approach. Compounds with the highest binding score were estimated through their pharmacokinetic effects by ADMET descriptors. Finally, four potential inhibitors with PubChem CID: (4301534, 5213, 5481948, and 637080) were selected after molecular docking and drug-likeness analysis. All four lead compounds were employed for the MDS analysis of a 100 ns time period. Various studies were undertaken to assess the stability of the protein-ligand complexes. The binding free energy was computed using MM-PBSA, and the outcomes indicated that the molecules are having stable interactions with the binding site of the target protein. The results revealed that all four compounds can be employed as potential therapeutics against K. pneumoniae.

Integrated gene expression profiling and functional enrichment analyses to discover biomarkers and pathways associated with Guillain-Barré syndrome and autism spectrum disorder to identify new therapeutic targets

Guillain-Barré syndrome (GBS) is one of the most prominent and acute immune-mediated peripheral neuropathy, while autism spectrum disorders (ASD) are a group of heterogeneous neurodevelopmental disorders. The complete mechanism regarding the neuropathophysiology of these disorders is still ambiguous. Even after recent breakthroughs in molecular biology, the link between GBS and ASD remains a mystery. Therefore, we have implemented well-established bioinformatic techniques to identify potential biomarkers and drug candidates for GBS and ASD. 17 common differentially expressed genes (DEGs) were identified for these two disorders, which later guided the rest of the research. Common genes identified the protein-protein interaction (PPI) network and pathways associated with both disorders. Based on the PPI network, the constructed hub gene and module analysis network determined two common DEGs, namely CXCL9 and CXCL10, which are vital in predicting the top drug candidates. Furthermore, coregulatory networks of TF-gene and TF-miRNA were built to detect the regulatory biomolecules. Among drug candidates, imatinib had the highest docking and MM-GBSA score with the well-known chemokine receptor CXCR3 and remained stable during the 100 ns molecular dynamics simulation validated by the principal component analysis and the dynamic cross-correlation map. This study predicted the gene-based disease network for GBS and ASD and suggested prospective drug candidates. However, more in-depth research is required for clinical validation.Communicated by Ramaswamy H. Sarma.

Assessment of antidiabetic activity of three Phenylspirodrimanes from fungus Stachybotrys chartarum MUT 3308 by ADME, QSAR, molecular docking and molecular dynamics simulation studies against protein tyrosine phosphatase 1B (PTP1B)

Phenylspirodrimanes (PSD) are the sesquiterpene quinone type meroterpenoids found in nature. PSDs are found to exhibit inhibitory activity against immunocomplex diseases, and tyrosine kinase receptors. Three of the different PSDs C1, C2, and C3 that have been reported to be isolated from the sponge-associated fungus Stachybotrys chartarum MUT 3308 are selected for studying their possible inhibitory effect against type 2 diabetes mellitus. Mechanistically, blocking protein tyrosine phosphatase 1B (PTP1B) helps to reduce the insulin resistance induction caused by the high expression of PTP1B. The QSAR, ADME, toxicity (T) study was carried out to predict the pharmacokinetic properties and the biological activities of the PSDs. PASS prediction web tool was used to find and select the target proteins 1NNY, and 2HNP. According to the molecular docking simulations, C1 and C2 showed better binding affinity of -8.5 kcal/mol, and -8.1 kcal/mol respectively against 1NNY compared to the control ligand. RMSD, RMSF, Rg, and SASA analysis revealed that both C1, and C2 showed better stability, minor conformational changes, and minor fluctuation upon binding to PTP1B. Protein contact analysis was carried out to validate the residues that are in contact with the ligands according to molecular docking studies. Overall, C1, and C2 could be proposed as novel natural hits to be developed and small modifications of these PSDs could result in inducing the binding affinity significantly, although experimental validation is required for further evaluation of the work.Communicated by Ramaswamy H. Sarma.

Identification of 1,3,4-oxadiazoles as tubulin-targeted anticancer agents: a combined field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, molecular dynamics simulation, and density functional theory calculation approach

Cancer is one of the most prominent causes of death worldwide and tubulin is a crucial protein of cytoskeleton that maintains essential cellular functions including cell division as well as cell signalling, that makes an attractive drug target for cancer drug development. 1,3,4-oxadiazoles disrupt microtubule causing G2-M phase cell cycle arrest and provide anti-proliferative effect. In this study, field-based 3D-QSAR models were developed using 62 bioactive anti-tubulin 1,3,4-oxadiazoles. The best model characterized by PLS factor 7 was rigorously validated using various statistical parameters. Generated 3D-QSAR model having high degree of confidence showed favourable and unfavourable contours around 1,3,4-oxadiazole core that assisted in defining proper spatial positioning of desired functional groups for better bioactivity. A five featured pharmacophore model (AAHHR_1) was developed using same ligand library and validated through enrichment analysis (BEDROC160.9 value = 0.59, Average EF 1% = 27.05, and AUC = 0.74). Total 30,212 derivatives of 1,3,4-oxadiazole obtained from PubChem database was prefiltered through validated pharmacophore model and docked in XP mode on binding cavity of tubulin protein (PDB code: 1SA0) which led into the identification of 11 HITs having docking scores between -7.530 and -9.719 kcal/mol while the reference compound Colchicine exerted docking score of -7.046 kcal/mol. Following the analysis of MM-GBSA and ADME studies, HIT1 and HIT4 emerged as the two promising hits. To verify their thermodynamic stability at the target site, molecular dynamic simulations were carried out. Both HITs were further subjected to DFT analysis to determine their HOMO-LUMO energy gap for ensuring their biological feasibility. Finally, molecular docking based structural exploration for 1,3,4-oxadiazoles to set up a lead of Formula I for further advancements of tubulin polymerization inhibitors as anti-cancer agents.Communicated by Ramaswamy H. Sarma.

Computational formulation of a multiepitope vaccine unveils an exceptional prophylactic candidate against Merkel cell polyomavirus

Merkel cell carcinoma (MCC) is a rare neuroendocrine skin malignancy caused by human Merkel cell polyomavirus (MCV), leading to the most aggressive skin cancer in humans. MCV has been identified in approximately 43%-100% of MCC cases, contributing to the highly aggressive nature of primary cutaneous carcinoma and leading to a notable mortality rate. Currently, no existing vaccines or drug candidates have shown efficacy in addressing the ailment caused by this specific pathogen. Therefore, this study aimed to design a novel multiepitope vaccine candidate against the virus using integrated immunoinformatics and vaccinomics approaches. Initially, the highest antigenic, immunogenic, and non-allergenic epitopes of cytotoxic T lymphocytes, helper T lymphocytes, and linear B lymphocytes corresponding to the virus whole protein sequences were identified and retrieved for vaccine construction. Subsequently, the selected epitopes were linked with appropriate linkers and added an adjuvant in front of the construct to enhance the immunogenicity of the vaccine candidates. Additionally, molecular docking and dynamics simulations identified strong and stable binding interactions between vaccine candidates and human Toll-like receptor 4. Furthermore, computer-aided immune simulation found the real-life-like immune response of vaccine candidates upon administration to the human body. Finally, codon optimization was conducted on the vaccine candidates to facilitate the in silico cloning of the vaccine into the pET28+(a) cloning vector. In conclusion, the vaccine candidate developed in this study is anticipated to augment the immune response in humans and effectively combat the virus. Nevertheless, it is imperative to conduct in vitro and in vivo assays to evaluate the efficacy of these vaccine candidates thoroughly. These evaluations will provide critical insights into the vaccine's effectiveness and potential for further development.

Halting aberrant DNA methylation via in silico Identification of potent inhibitors of DNMT3B enzyme: Atomistic insights

To date, Cancer remains a global threat due to its impact on growing life expectancy. With the many efforts and methods of combating the disease, complete success remains a challenge owing to several limitations including cancer cells developing resistance through mutations, off-target effect of some cancer drugs resulting in toxicities, among many others. Aberrant DNA methylation is understood to be the primary reason for improper gene silence, which can result in neoplastic transformation, carcinogenesis, and tumour progression. DNA methyltransferase B (DNMT3B) enzyme is considered a potential target for the treatment of several cancers due to its important role in DNA methylation. However, only a few DNMT3B inhibitors have been reported to date. Herein, in silico molecular recognition techniques such as Molecular docking, Pharmacophore-based virtual screen and MD simulation were employed to identify potential inhibitors of DNMT3B that can halt aberrancy in DNA methylation. Findings initially identified 878 hit compounds based on a designed pharmacophore model from the reference compound Hypericin. Molecular docking was used to rank the hits by testing their efficiency when bound to the target enzyme and the top three (3) selected. All three (3) of the top hits showed excellent pharmacokinetic properties but two (2) (Zinc33330198 and Zinc77235130) were identified to be non-toxic. Molecular dynamic simulation of the final two hits showed good stability, flexibility, and structural rigidity of the compounds on DNMT3B. Finally, thermodynamic energy estimations show both compounds had favourable free energies comprising - 26.04 kcal/mol for Zinc77235130 and - 15.73 kcal/mol for Zinc33330198. Amongst the final two hits, Zinc77235130 showed consistency in favourable results across all the tested parameters and was thus selected as the lead compound for further experimental validation. The identification of this lead compound will form important basis for the inhibition of aberrant DNA methylation in cancer therapy.

Isolation and Characterization of an Unknown Process-Related Impurity in Furosemide and Validation of a New HPLC Method

Furosemide is a widely used loop diuretic in the treatment of congestive heart failure and edema. During the preparation of furosemide, a new process-related impurity G in the levels ranging from 0.08% to 0.13% was detected in pilot batches by a new high performance liquid chromatography (HPLC) method. The new impurity was isolated and characterized by comprehensive analysis of FT-IR, Q-TOF/LC-MS, 1D-NMR (¹H, ¹³C, and DEPT), and 2D-NMR (¹H-¹H-COSY, HSQC, and HMBC) spectroscopy data. The possible formation pathway of impurity G was also discussed in detail. Moreover, a novel HPLC method was developed and validated for the determination of impurity G and the other six known impurities registered in the European Pharmacopoeia as per ICH guidelines. The HPLC method was validated with respect to system suitability, linearity, the limit of quantitation, the limit of detection, precision, accuracy, and robustness. The characterization of impurity G and the validation of its quantitative HPLC method were reported for the first time in this paper. Finally, the toxicological properties of impurity G were predicted by the in silico webserver ProTox-II.

Potential Anti-SARS-CoV-2 Molecular Strategies

Finding effective antiviral molecular strategies was a main concern in the scientific community when the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged at the end of 2019 as an easily transmissible and potentially deadly β-coronavirus able to cause the coronavirus disease 19 (COVID-19), which famously led to one of the most worrying pandemics in recent times. Other members of this zoonotic pathogenic family were already known before 2019, but apart from the SARS-CoV, which was responsible of severe acute respiratory syndrome (SARS) pandemic in 2002/2003, and Middle East respiratory syndrome coronavirus (MERS-CoV), whose main impact on humans is geographically restricted to Middle Eastern countries, the other human β-coronaviruses known at that time were those typically associated with common cold symptoms which had not led to the development of any specific prophylactic or therapeutic measures. Although SARS-CoV-2 and its mutations are still causing illness in our communities, COVID-19 is less deadly than before and we are returning to normality. Overall, the main lesson learnt after the past few years of pandemic is that keeping our bodies healthy and immunity defenses strong using sport, nature-inspired measures, and using functional foods are powerful weapons for preventing the more severe forms of illness caused by SARS-CoV-2 and, from a more molecular perspective, that finding drugs with mechanisms of action involving biological targets conserved within the different mutations of SARS-CoV-2-and possibly within the entire family of β-coronaviruses-gives more therapeutic opportunities in the scenario of future pandemics based on these pathogens. In this regard, the main protease (M^pro), having no human homologues, offers a lower risk of off-target reactivity and represents a suitable therapeutic target in the search for efficacious, broad-spectrum anti-β-coronavirus drugs. Herein, we discuss on the above points and also report some molecular approaches presented in the past few years to counteract the effects of β-coronaviruses, with a special focus on SARS-CoV-2 but also MERS-CoV.

Integrative Ligand-Based Pharmacophore Modeling, Virtual Screening, and Molecular Docking Simulation Approaches Identified Potential Lead Compounds against Pancreatic Cancer by Targeting FAK1

Pancreatic cancer is a very deadly disease with a 5-year survival rate, making it one of the leading causes of cancer-related deaths globally. Focal adhesion kinase 1 (FAK1) is a ubiquitously expressed protein in pancreatic cancer. FAK, a tyrosine kinase that is overexpressed in cancer cells, is crucial for the development of tumors into malignant phenotypes. FAK functions in response to extracellular signals by triggering transmembrane receptor signaling, which enhances focal adhesion turnover, cell adhesion, cell migration, and gene expression. The ligand-based drug design approach was used to identify potential compounds against the target protein, which included molecular docking: ADME (absorption, distribution, metabolism, and excretion), toxicity, molecular dynamics (MD) simulation, and molecular mechanics generalized born surface area (MM-GBSA). Following the retrieval of twenty hits, four compounds were selected for further evaluation based on a molecular docking approach. Three newly discovered compounds, including PubChem CID24601203, CID1893370, and CID16355541, with binding scores of -10.4, -10.1, and -9.7 kcal/mol, respectively, may serve as lead compounds for the treatment of pancreatic cancer associated with FAK1. The ADME (absorption, distribution, metabolism, and excretion) and toxicity analyses demonstrated that the compounds were effective and nontoxic. However, further wet laboratory investigations are required to evaluate the activity of the drugs against the cancer.

In Vitro and In Silico Studies for the Identification of Potent Metabolites of Some High-Altitude Medicinal Plants from Nepal Inhibiting SARS-CoV-2 Spike Protein

Despite ongoing vaccination programs against COVID-19 around the world, cases of infection are still rising with new variants. This infers that an effective antiviral drug against COVID-19 is crucial along with vaccinations to decrease cases. A potential target of such antivirals could be the membrane components of the causative pathogen, SARS-CoV-2, for instance spike (S) protein. In our research, we have deployed in vitro screening of crude extracts of seven ethnomedicinal plants against the spike receptor-binding domain (S1-RBD) of SARS-CoV-2 using an enzyme-linked immunosorbent assay (ELISA). Following encouraging in vitro results for Tinospora cordifolia, in silico studies were conducted for the 14 reported antiviral secondary metabolites isolated from T. cordifolia-a species widely cultivated and used as an antiviral drug in the Himalayan country of Nepal-using Genetic Optimization for Ligand Docking (GOLD), Molecular Operating Environment (MOE), and BIOVIA Discovery Studio. The molecular docking and binding energy study revealed that cordifolioside-A had a higher binding affinity and was the most effective in binding to the competitive site of the spike protein. Molecular dynamics (MD) simulation studies using GROMACS 5.4.1 further assayed the interaction between the potent compound and binding sites of the spike protein. It revealed that cordifolioside-A demonstrated better binding affinity and stability, and resulted in a conformational change in S1-RBD, hence hindering the activities of the protein. In addition, ADMET analysis of the secondary metabolites from T. cordifolia revealed promising pharmacokinetic properties. Our study thus recommends that certain secondary metabolites of T. cordifolia are possible medicinal candidates against SARS-CoV-2.

Molecular Docking and Dynamics Simulation of Several Flavonoids Predict Cyanidin as an Effective Drug Candidate against SARS-CoV-2 Spike Protein

The in silico method has provided a versatile process of developing lead compounds from a large database in a short duration. Therefore, it is imperative to look for vaccinations and medications that can stop the havoc caused by SARS-CoV-2. The spike protein of SARS-CoV-2 is required for the viral entry into the host cells, hence inhibiting the virus from fusing and infecting the host. This study determined the binding interactions of 36 flavonoids along with two FDA-approved drugs against the spike protein receptor-binding domain of SARS-CoV-2 through molecular docking and molecular dynamics (MD) simulations. In addition, the molecular mechanics generalized Born surface area (MM/GBSA) approach was used to calculate the binding-free energy (BFE). Flavonoids were selected based on their in vitro assays on SARS-CoV and SARS-CoV-2. Our pharmacokinetics study revealed that cyanidin showed good drug-likeness, fulfilled Lipinski’s rule of five, and conferred favorable toxicity parameters. Furthermore, MD simulations showed that cyanidin interacts with spike protein and alters the conformation and binding-free energy suited. Finally, an in vitro assay indicated that about 50% reduction in the binding of hACE2 with S1-RBD in the presence of cyanidin-containing red grapes crude extract was achieved at approximately 1.25 mg/mL. Hence, cyanidin may be a promising adjuvant medication for the SARS-CoV-2 spike protein based on in silico and in vitro research.

Pharmacophore-Model-Based Virtual-Screening Approaches Identified Novel Natural Molecular Candidates for Treating Human Neuroblastoma

The mortality of cancer patients with neuroblastoma is increasing due to the limited availability of specific treatment options. Few drug candidates for combating neuroblastoma have been developed, and identifying novel therapeutic candidates against the disease is an urgent issue. It has been found that muc-N protein is amplified in one-third of human neuroblastomas and expressed as an attractive drug target against the disease. The myc-N protein interferes with the bromodomain and extraterminal (BET) family proteins. Pharmacologically inhibition of the protein potently depletes MYCN in neuroblastoma cells. BET inhibitors target MYCN transcription and show therapeutic efficacy against neuroblastoma. Therefore, the study aimed to identify potential inhibitors against the BET family protein, specifically Brd4 (brodamine-containing protein 4), to hinder the activity of neuroblastoma cells. To identify effective molecular candidates against the disease, a structure-based pharmacophore model was created for the binding site of the Brd4 protein. The pharmacophore model generated from the protein Brd4 was validated to screen potential natural active compounds. The compounds identified through the pharmacophore-model-based virtual-screening process were further screened through molecular docking, ADME (absorption, distribution, metabolism, and excretion), toxicity, and molecular dynamics (MD) simulation approach. The pharmacophore-model-based screening process initially identified 136 compounds, further evaluated based on molecular docking, ADME analysis, and toxicity approaches, identifying four compounds with good binding affinity and lower side effects. The stability of the selected compounds was also confirmed by dynamic simulation and molecular mechanics with generalized Born and surface area solvation (MM-GBSA) methods. Finally, the study identified four natural lead compounds, ZINC2509501, ZINC2566088, ZINC1615112, and ZINC4104882, that will potentially inhibit the activity of the desired protein and help to fight against neuroblastoma and related diseases. However, further evaluations through in vitro and in vivo assays are suggested to identify their efficacy against the desired protein and disease.

Identification of novel natural drug candidates against BRAF mutated carcinoma; An integrative in-silico structure-based pharmacophore modeling and virtual screening process

The BRAF gene is responsible for transferring signals from outside of the cell to inside of the nucleus by converting a protein namely B-Raf through the RAS/MAPK pathway. This pathway contribute to cell division, proliferation, migration, and apoptotic cell death of human and animal. Mutation in this gene may cause the development of several cancers, including lung, skin, colon, and neuroblastoma. Currently, a few available drugs are being used that has developed by targeting the BRAF mutated protein, and due to the toxic side effects, patients suffer a lot during their treatment. Therefore this study aimed to identify potentially lead compounds that can target and block the expression of BRAF and subsequently inhibit the cancer. The hits were generated through the pharmacophore model-based virtual screening, molecular docking, pharmacohore model validation, ADME (absorption, distribution, metabolism, and excretion) analysis molecular dynamics (MD) simulation to find more suitable candidate against the overexpress BRAF gene. The pharmacophore based screening initially identified 14 k possible hits from online database which were further screened by ligand scout advance software to get hit compound. Based on molecular docking score of ZINC70454679 (-10.6 kcal/mol), ZINC253500968 (-9.4 kcal/mol), ZINC106887736 (-8.6 kcal/mol), and ZINC107434492 (-8.1 kcal/mol), pharmacophore feature and toxicity evaluation, we selected four possible lead compounds. The dynamic simulation with Schrodinger Maestro software was used to determine the stability of the potential lead candidates with target protein (PDB ID: 5VAM). The results showed that the newly obtained four compounds were more stable than the control ligand (Pub Chem ID: 90408826). The current results showed that the ZINC70454679, ZINC253500968, ZINC106887736, and ZINC107434492 compounds may be able to work against several cancers through targeting the BRAF overexpressed gene. To develop a novel drug candidate, however the evaluation of the web lab based experimental work are necessary to evaluate the efficiency of the each compound against the BRAF target gene.

LY3041658/ interleukin-8 complex structure as targets for IL-8 small molecule inhibitors discovery using a combination of in silico methods

Since interleukin-8 (IL-8/CXCL8) and its receptor, CXCR1 and CXCR2, were known in the early 1990s, biological pathways related to these proteins were proven to have high clinical value in cancer and inflammatory/autoimmune conditions treatment. Recently, IL-8 has been identified as biomarker for severe COVID-19 patients and COVID-19 prognosis. Boyles et al. (mAbs 12 (2020), pp. 1831880) have published a high-resolution X-ray crystal structure of the LY3041658 Fab in a complex human CXCL8. They described the ability to bind to IL-8 and the blocking of IL-8/its receptors interaction by the LY3041658 monoclonal antibody. Therefore, the study has been designed to identify potential small molecules inhibiting interleukin-8 by targeting LY3041658/IL-8 complex structure using an in silico approach. A structure‑based pharmacophore and molecular docking models of the protein active site cavity were generated to identify possible candidates, followed by virtual screening with the ZINC database. ADME analysis of hit compounds was also conducted. Molecular dynamics simulations were then performed to survey the behaviour and stability of the ligand-protein complexes. Furthermore, the MM/PBSA technique has been utilized to evaluate the free binding energy. The final data confirmed that one newly obtained compound, ZINC21882765, may serve as the best potential inhibitor for IL-8.

Immune epitopes identification and designing of a multi-epitope vaccine against bovine leukemia virus: a molecular dynamics and immune simulation approaches

Background

Bovine leukemia virus (BLV) is an oncogenic delta-retrovirus causing bovine leucosis. Studies on BLV have shown the association with human breast cancer. However, the exact molecular mechanism is neither known nor their appropriate preventative measure to halt the disease initiation and progression. In this study, we designed a multi-epitope vaccine against BLV using a computational analyses.

Methods

Following a rigorous assessment, the vaccine was constructed using the T-cell epitopes from each BLV-derived protein with suitable adjuvant and linkers. Both physicochemistry and immunogenic potency as well as the safeness of the vaccine candidate were assessed. Population coverage was done to evaluate the vaccine probable efficiency in eliciting the immune response worldwide. After homology modeling, the three-dimensional structure was refined and validated to determine the quality of the designed vaccine. The vaccine protein was then subjected to molecular docking with Toll-like receptor 3 (TLR3) to evaluate the binding efficiency followed by dynamic simulation for stable interaction.

Results

Our vaccine construct has the potential immune response and good physicochemical properties. The vaccine is antigenic and immunogenic, and has no allergenic or toxic effect on the human body. This novel vaccine contains a significant interactions and binding affinity with the TLR3 receptor.

Conclusions

The proposed vaccine candidate would be structurally stable and capable of generating an effective immune response to combat BLV infections. However, experimental evaluations are essential to validate the exact safety and immunogenic profiling of this vaccine.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00262-022-03181-w.

Molecular docking study of various Enterovirus—A71 3C protease proteins and their potential inhibitors

Hand, foot, and mouth disease (HFMD) is a common infection that primarily affects children in preschool and kindergarten; however, there is yet no vaccination or therapy available. Despite the fact that current research is only focused on numerous strains of Enterovirus—A71 (EV-A71) 3C protease (3C^pro), these investigations are entirely separate and unrelated. Antiviral agents must therefore be tested on several EV strains or mutations. In total, 21 previously reported inhibitors were evaluated for inhibitory effects on eight EV-A71 3C^pro, including wild-type and mutant proteins in this study, and another 29 powerful candidates with inhibitory effects on EV-A71 were investigated using the molecular docking approach. This method is to determine the broad-spectrum of the antiviral agents on a range of strains or mutants because the virus frequently has mutations. Even though Rupintrivir is reported to pass phase I clinical trial, 4-iminooxazolidin-2-one moiety (FIOMC) was shown to have a broader anti-3C^pro spectrum than Rupintrivir. Meanwhile, Hesperidin possessed a better 3C^pro inhibitory capability than FIOMC. Thus, it could be considered the most promising candidate for inhibiting various strains of EV-A71 3C^pro proteins in the newly anti-EV compounds group. Furthermore, the mutation at E71A has the most significant impact on the docking results of all ligands evaluated. Future in vitro experiments on Hesperidin’s ability to inhibit 3C^pro activity should be conducted to compare with FIOMC’s in vitro results and validate the current in silico work.

Designing drugs when there is low data availability: one-shot learning and other approaches to face the issues of a long-term concern

INTRODUCTION

Modern drug discovery generally is accessed by useful information from previous large databases or uncovering novel data. The lack of biological and/or chemical data tends to slow the development of scientific research and innovation. Here, approaches that may help provide solutions to generate or obtain enough relevant data or improve/accelerate existing methods within the last five years were reviewed.

AREAS COVERED

One-shot learning (OSL) approaches, structural modeling, molecular docking, scoring function space (SFS), molecular dynamics (MD), and quantum mechanics (QM) may be used to amplify the amount of available data to drug design and discovery campaigns, presenting methods, their perspectives, and discussions to be employed in the near future.

EXPERT OPINION

Recent works have successfully used these techniques to solve a range of issues in the face of data scarcity, including complex problems such as the challenging scenario of drug design aimed at intrinsically disordered proteins and the evaluation of potential adverse effects in a clinical scenario. These examples show that it is possible to improve and kickstart research from scarce available data to design and discover new potential drugs.

Application of reverse vaccinology to design a multi-epitope subunit vaccine against a new strain of Aeromonas veronii

Background

Aeromonas veronii is one of the most common pathogens of freshwater fishes that cause sepsis and ulcers. There are increasing numbers of cases showing that it is a significant zoonotic and aquatic agent. Epidemiological studies have shown that A. veronii virulence and drug tolerance have both increased over the last few years as a result of epidemiological investigations. Cadaverine reverse transporter (CadB) and maltoporin (LamB protein) contribute to the virulence of A. veronii TH0426. TH0426 strain is currently showing severe cases on fish species, and its resistance against therapeutic has been increasing. Despite these devastating complications, there is still no effective cure or vaccine for this strain of A.veronii.

Results

In this regard, an immunoinformatic method was used to generate an epitope-based vaccine against this pathogen. The immunodominant epitopes were identified using the CadB and LamB protein of A. veronii. The final constructed vaccine sequence was developed to be immunogenic, non-allergenic as well as have better solubility. Molecular dynamic simulation revealed significant binding stability and structural compactness. Finally, using Escherichia coli K12 as a model, codon optimization yielded ideal GC content and a higher CAI value, which was then included in the cloning vector pET2+ (a).

Conclusion

Altogether, our outcomes imply that the proposed peptide vaccine might be a good option for A. veronii TH0426 prophylaxis.

The Current Perspectives in Clinical Research: Computer-Assisted Drug Designing, Ethics, and Good Clinical Practice

In the era of emerging microbial and non-communicable diseases and re-emerging microbial infections, the medical fraternity and the public are plagued by under-preparedness. It is evident by the severity of the Coronavirus disease (COVID-19) pandemic that novel microbial diseases are a challenge and are challenging to control. This is mainly attributed to the lack of complete knowledge of the novel microbe’s biology and pathogenesis and the unavailability of therapeutic drugs and vaccines to treat and control the disease. Clinical research is the only answer utilizing which can handle most of these circumstances. In this review, we highlight the importance of computer-assisted drug designing (CADD) and the aspects of molecular docking, molecular superimposition, 3D-pharmacophore technology, ethics, and good clinical practice (GCP) for the development of therapeutic drugs, devices, and vaccines.

25 (S)-Hydroxycholesterol acts as a possible dual enzymatic inhibitor of SARS-CoV-2 Mpro and RdRp-: an insight from molecular docking and dynamics simulation approaches

The coronavirus disease (COVID-19) pandemic has rapidly extended globally and killed approximately 5.83 million people all over the world. But, to date, no effective therapeutic against the disease has been developed. The disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and enters the host cell through the spike glycoprotein (S protein) of the virus. Subsequently, RNA-dependent RNA polymerase (RdRp) and main protease (M^pro) of the virus mediate viral transcription and replication. Mechanistically inhibition of these proteins can hinder the transcription as well as replication of the virus. Recently oxysterols and its derivative, such as 25 (S)-hydroxycholesterol (25-HC) has shown antiviral activity against SARS-CoV-2. But the exact mechanisms and their impact on RdRp and M^pro have not been explored yet. Therefore, the study aimed to identify the inhibitory activity of 25-HC against the viral enzymes RdRp and M^pro simultaneously. Initially, a molecular docking simulation was carried out to evaluate the binding activity of the compound against the two proteins. The pharmacokinetics (PK) and toxicity parameters were analyzed to observe the 'drug-likeness' properties of the compound. Additionally, molecular dynamics (MD) simulation was performed to confirm the binding stability of the compound to the targeted protein. Furthermore, molecular mechanics generalized Born surface area (MM-GBSA) was used to predict the binding free energies of the compound to the targeted protein. Molecular docking simulation identified low glide energy -51.0 kcal/mol and -35.0 kcal/mol score against the RdRp and M^pro, respectively, where MD simulation found good binding stability of the compound to the targeted proteins. In addition, the MM/GBSA approach identified a good value of binding free energies (ΔG bind) of the compound to the targeted proteins. Therefore, the study concludes that the compound 25-HC could be developed as a treatment and/or prevention option for SARS-CoV-2 disease-related complications. Although, experimental validation is suggested for further evaluation of the work.Communicated by Ramaswamy H. Sarma.

Review on the QM/MM Methodologies and Their Application to Metalloproteins

The multiscaling quantum mechanics/molecular mechanics (QM/MM) approach was introduced in 1976, while the extensive acceptance of this methodology started in the 1990s. The combination of QM/MM approach with molecular dynamics (MD) simulation, otherwise known as the QM/MM/MD approach, is a powerful and promising tool for the investigation of chemical reactions’ mechanism of complex molecular systems, drug delivery, properties of molecular devices, organic electronics, etc. In the present review, the main methodologies in the multiscaling approaches, i.e., density functional theory (DFT), semiempirical methodologies (SE), MD simulations, MM, and their new advances are discussed in short. Then, a review on calculations and reactions on metalloproteins is presented, where particular attention is given to nitrogenase that catalyzes the conversion of atmospheric nitrogen molecules N₂ into NH₃ through the process known as nitrogen fixation and the FeMo-cofactor.

Toward the Identification of Natural Antiviral Drug Candidates against Merkel Cell Polyomavirus: Computational Drug Design Approaches

Merkel cell carcinoma (MCC) is a rare form of aggressive skin cancer mainly caused by Merkel cell polyomavirus (MCPyV). Most MCC tumors express MCPyV large T (LT) antigens and play an important role in the growth-promoting activities of oncoproteins. Truncated LT promotes tumorigenicity as well as host cell proliferation by activating the viral replication machinery, and inhibition of this protein in humans drastically lowers cellular growth linked to the corresponding cancer. Our study was designed with the aim of identifying small molecular-like natural antiviral candidates that are able to inhibit the proliferation of malignant tumors, especially those that are aggressive, by blocking the activity of viral LT protein. To identify potential compounds against the target protein, a computational drug design including molecular docking, ADME (absorption, distribution, metabolism, and excretion), toxicity, molecular dynamics (MD) simulation, and molecular mechanics generalized Born surface area (MM-GBSA) approaches were applied in this study. Initially, a total of 2190 phytochemicals isolated from 104 medicinal plants were screened using the molecular docking simulation method, resulting in the identification of the top five compounds having the highest binding energy, ranging between −6.5 and −7.6 kcal/mol. The effectiveness and safety of the selected compounds were evaluated based on ADME and toxicity features. A 250 ns MD simulation confirmed the stability of the selected compounds bind to the active site (AS) of the target protein. Additionally, MM-GBSA analysis was used to determine the high values of binding free energy (ΔG bind) of the compounds binding to the target protein. The five compounds identified by computational approaches, Paulownin (CID: 3084131), Actaealactone (CID: 11537736), Epigallocatechin 3-O-cinnamate (CID: 21629801), Cirsilineol (CID: 162464), and Lycoricidine (CID: 73065), can be used in therapy as lead compounds to combat MCPyV-related cancer. However, further wet laboratory investigations are required to evaluate the activity of the drugs against the virus.

Designing a novel mRNA vaccine against Vibrio harveyi infection in fish: an immunoinformatics approach

Vibrio harveyi belongs to the family Vibrionaceae of class Gammaproteobacteria. Around 12 Vibrio species can cause gastroenteritis (gastrointestinal illness) in humans. A large number of bacterial particles can be found in the infected cells, which may cause death. Despite these devastating complications, there is still no cure or vaccine for the bacteria. As a result, we used an immunoinformatics approach to develop a multi-epitope vaccine against the most pathogenic hemolysin gene of V. harveyi. The immunodominant T- and B-cell epitopes were identified using the hemolysin protein. We developed a vaccine employing three possible epitopes: cytotoxic T-lymphocytes, helper T-lymphocytes, and linear B-lymphocyte epitopes, after thorough testing. The vaccine was developed to be antigenic, immunogenic, and non-allergenic, as well as have a better solubility. Molecular dynamics simulation revealed significant structural stiffness and binding stability. In addition, the immunological simulation generated by computers revealed that the vaccination might elicit immune reactions Escherichia coli K12 as a model, codon optimization yielded ideal GC content and a higher codon adaptation index value, which was then included in the cloning vector pET2+ (a). Altogether, our experiment implies that the proposed peptide vaccine might be a good option for vibriosis prophylaxis.

Scope of computational biology and bioinformatics towards the discovery of potential therapeutic agents against viral diseases

Tweetable abstract

Computational biology and bioinformatics resources provide a cutting-edge platform for the screening and development of novel therapeutic agents against probable targets of emerging viral diseases.

An Enhanced Hybrid Screening Approach to Identify Potent Inhibitors for the SARS-CoV-2 Main Protease From the NCI Compound Library

The emergence and rapid spread of SARS-CoV-2, the pathogen of COVID-19, have caused a worldwide public health crisis. The SARS-CoV-2 main protease (Mpro) is an essential enzyme for the virus and therefore an appealing target for the development of antivirals to treat COVID-19 patients. Recently, many in silico screenings have been performed against the main protease to discover novel hits. However, the actual hit rate of virtual screening is often low, and most of the predicted compounds are false positive hits. In this study, we developed a refined virtual screening strategy that incorporated molecular docking and post-docking filtering based on parameters including molecular weight and surface area, aiming to achieve predictions with fewer false positive hits. We applied this strategy to the NCI library containing 284,176 compounds against Mpro. In vitro potency analyses validated several potent inhibitors and thus confirmed the feasibility of our virtual screening strategy. Overall, The study resulted in several potent hit Mpro inhibitors, in which two inhibitors have IC50 values below 1 μM, that are worth being further optimized and explored. Meanwhile, the refined virtual screen strategy is also applicable to improve general in silico screening hit rates and is useful to accelerate drug discovery for treating COVID-19 and other viral infections.

Bioinformatics approaches identified dasatinib and bortezomib inhibit the activity of MCM7 protein as a potential treatment against human cancer

Minichromosome Maintenance Complex Component 7 (MCM7) is a key component of the DNA replication licensing factor and hexamer MCM (MCM2-7) complex that regulates the DNA replication process. The MCM7 protein is associated with tumor cell proliferation that plays an important role in different human cancer progression. As the protein is highly expressed during the cancer development process, therefore, inhibition of the protein can be utilized as a treatment option for different human cancer. However, the study aimed to identify potential small molecular drug candidates against the MCM7 protein that can utilize treatment options for human cancer. Initially, the compounds identified from protein-drugs network analysis have been retrieved from NetworkAnalyst v3.0 server and screened through molecular docking, MM-GBSA, DFT, pharmacokinetics, toxicity, and molecular dynamics (MD) simulation approach. Two compounds namely Dasatinib (CID_3062316) and Bortezomib (CID_387447) have been identified throughout the screening process, which have the highest negative binding affinity (Kcal/mol) and binding free energy (Kcal/mol). The pharmacokinetics and toxicity analysis identified drug-like properties and no toxicity properties of the compounds, where 500 ns MD simulation confirmed structural stability of the two compounds to the targeted proteins. Therefore, we can conclude that the compounds dasatinib and bortezomib can inhibit the activity of the MCM7 and can be developed as a treatment option against human cancer.

GC-MS analysis of phytoconstituents from Ruellia prostrata and Senna tora and identification of potential anti-viral activity against SARS-CoV-2

SARS-CoV-2 is an etiologic agent responsible for the coronavirus disease 2019 (COVID-19) pandemic. The virus has rapidly extended globally and taken millions of lives due to the unavailability of therapeutics candidates against the virus. Till now, no specific drug candidates have been developed that can prevent or treat infections caused by the pathogen. The main protease (M^pro) of the SARS-CoV-2 plays a pivotal role in mediating viral replication and mechanistically inhibition of the protein can hinder the replication and infection process of the virus. Therefore, the study aimed to identify the natural bioactive compounds against the virus that can block the activity of the M^pro and subsequently block viral infections. Initially, a total of 96 phytochemicals from Ruellia prostrata Poir. and Senna tora (L.) Roxb. plants were identified through the gas chromatography-mass spectrometry (GC-MS) analytical method. Subsequently, the compounds were screened through molecular docking, absorption, distribution, metabolism, excretion (ADME), toxicity (T), and molecular dynamics (MD) simulation approach. The molecular docking method initially identified four molecules having a PubChem CID: 70825, CID: 25247358, CID: 54685836 and, CID: 1983 with a binding affinity ranging between −6.067 to −6.53 kcal mol⁻¹ to the active site of the target protein. All the selected compounds exhibit good pharmacokinetics and toxicity properties. Finally, the four compounds were further evaluated based on the MD simulation methods that confirmed the binding stability of the compounds to the targeted protein. The computational approaches identified the best four compounds CID: 70825, CID: 25247358, CID: 54685836 and, CID: 1983 that can be developed as a treatment option of SARS-CoV-2 disease-related complications. Although, experimental validation is suggested for further evaluation of the work.

Protease (M^pro) of SARS-CoV-2 has been identified as being able to hinder the replication process of the virus. Using GC-MS analytical methods, phytochemicals were identified from different medicinal plants that resulted in inhibitory activity of the molecules against M^pro.