phytochemdb: a platform for virtual screening and computer-aided drug designing.

The phytochemicals of medicinal plants are regarded as a rich source of diverse chemical spaces that have been used as supplements and alternative medicines in the millennium. Even in this era of combinatorial chemical drugs, phytomedicines account for a large share of the statistics of newly approved drugs. In the field of computational aided and rational drug design, there is an urgent need to develop and build a useful phytochemical database management system with a user-friendly interface that allows proper data storage, retrieval and management. We showed 'phytochemdb', a manually managed database that compiles 525 plants and their corresponding 8093 phytochemicals, aiming to incorporate the activities of phytochemicals from medicinal plants. The database collects molecular formula, three-dimensional/two-dimensional structure, canonical SMILES, molecular weight, no. of heavy atoms, no. of aromatic heavy atoms, fraction Csp3, no. of rotatable bonds, no. of H-bond acceptors, no. of H-bond donors, molar refractivity, topological polar surface area, gastrointestinal absorption, Blood-Brain Barrier (BBB) permeant, P-gp substrate, CYP1A2 inhibitor, CYP2C19 inhibitor, CYP2C9 inhibitor, CYP2D6 inhibitor, CYP3A4 inhibitor, Log Kp, Ghose, Veber, Egan, Muegge, bioavailability scores, pan-assay interference compounds, Brenk, Leadlikeness, synthetic accessibility, iLOGP and Lipinski rule of five with the number of violations for each compound. It provides open contribution functions for the researchers who screen phytochemicals in the laboratory and have released their data. 'phytochemdb' is a comprehensive database that gathers most of the information about medicinal plants in one platform, which is considered to be very beneficial to the work of researchers on medicinal plants. 'phytochemdb' is available for free at https://phytochemdb.com/.

Plant-Based Phytochemical Screening by Targeting Main Protease of SARS-CoV-2 to Design Effective Potent Inhibitors.

Currently, a worldwide pandemic has been declared in response to the spread of coronavirus disease 2019 (COVID-19), a fatal and fast-spreading viral infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The low availability of efficient vaccines and treatment options has resulted in a high mortality rate, bringing the world economy to its knees. Thus, mechanistic investigations of drugs capable of counteracting this disease are in high demand. The main protease (Mpro) expressed by SARS-CoV-2 has been targeted for the development of potential drug candidates due to the crucial role played by Mpro in viral replication and transcription. We generated a phytochemical library containing 1672 phytochemicals derived from 56 plants, which have been reported as having antiviral, antibacterial, and antifungal activity. A molecular docking program was used to screen the top three candidate compounds: epicatechin-3-O-gallate, psi-taraxasterol, and catechin gallate, which had respective binding affinities of -8.4, -8.5, and -8.8 kcal/mol. Several active sites in the targeted protein, including Cys145, His41, Met49, Glu66, and Met165, were found to interact with the top three candidate compounds. The multiple simulation profile, root-mean-square deviation, root-mean-square fluctuation, radius of gyration, and solvent-accessible surface area values supported the inflexible nature of the docked protein-compound complexes. The toxicity and carcinogenicity profiles were assessed, which showed that epicatechin-3-O-gallate, psi-taraxasterol, and catechin gallate had favorable pharmacological properties with no adverse effects. These findings suggest that these compounds could be developed as part of an effective drug development pathway to treat COVID-19.

Molecular docking and dynamics study to explore phytochemical ligand molecules against the main protease of SARS-CoV-2 from extensive phytochemical datasets.

BACKGROUND: The high transmission and pathogenicity of SARS-CoV-2 has led to a pandemic that has halted the world's economy and health. The newly evolved strains and scarcity of vaccines has worsened the situation. The main protease (Mpro) of SARS-CoV-2 can act as a potential target due to its role in viral replication and conservation level. METHODS: In this study, we have enlisted more than 1100 phytochemicals from Asian plants based on deep literature mining. The compounds library was screened against the Mpro of SARS-CoV-2. RESULTS: The selected three ligands, Flemichin, Delta-Oleanolic acid, and Emodin 1-O-beta-D-glucoside had a binding energy of -8.9, -8.9, -8.7 KJ/mol respectively. The compounds bind to the active groove of the main protease at; Cys145, Glu166, His41, Met49, Pro168, Met165, Gln189. The multiple descriptors from the simulation study; root mean square deviation, root mean square fluctuation, radius of gyration, hydrogen bond, solvent accessible surface area confirms the stable nature of the protein-ligand complexes. Furthermore, post-md analysis confirms the rigidness in the docked poses over the simulation trajectories. CONCLUSIONS: Our combinatorial drug design approaches may help researchers to identify suitable drug candidates against SARS-CoV-2.

Designing a multi-epitope vaccine candidate to combat MERS-CoV by employing an immunoinformatics approach.

Currently, no approved vaccine is available against the Middle East respiratory syndrome coronavirus (MERS-CoV), which causes severe respiratory disease. The spike glycoprotein is typically considered a suitable target for MERS-CoV vaccine candidates. A computational strategy can be used to design an antigenic vaccine against a pathogen. Therefore, we used immunoinformatics and computational approaches to design a multi-epitope vaccine that targets the spike glycoprotein of MERS-CoV. After using numerous immunoinformatics tools and applying several immune filters, a poly-epitope vaccine was constructed comprising cytotoxic T-cell lymphocyte (CTL)-, helper T-cell lymphocyte (HTL)-, and interferon-gamma (IFN-γ)-inducing epitopes. In addition, various physicochemical, allergenic, and antigenic profiles were evaluated to confirm the immunogenicity and safety of the vaccine. Molecular interactions, binding affinities, and the thermodynamic stability of the vaccine were examined through molecular docking and dynamic simulation approaches, during which we identified a stable and strong interaction with Toll-like receptors (TLRs). In silico immune simulations were performed to assess the immune-response triggering capabilities of the vaccine. This computational analysis suggested that the proposed vaccine candidate would be structurally stable and capable of generating an effective immune response to combat viral infections; however, experimental evaluations remain necessary to verify the exact safety and immunogenicity profile of this vaccine.

Prospective Role of Peptide-Based Antiviral Therapy Against the Main Protease of SARS-CoV-2.

The recently emerged coronavirus (SARS-CoV-2) has created a crisis in world health, and economic sectors as an effective treatment or vaccine candidates are still developing. Besides, negative results in clinical trials and effective cheap solution against this deadly virus have brought new challenges. The viral protein, the main protease from SARS-CoV-2, can be effectively targeted due to its viral replication and pathogenesis role. In this study, we have enlisted 88 peptides from the AVPdb database. The peptide molecules were modeled to carry out the docking interactions. The four peptides molecules, P14, P39, P41, and P74, had more binding energy than the rest of the peptides in multiple docking programs. Interestingly, the active points of the main protease from SARS-CoV-2, Cys145, Leu141, Ser139, Phe140, Leu167, and Gln189, showed nonbonded interaction with the peptide molecules. The molecular dynamics simulation study was carried out for 200 ns to find out the docked complex's stability where their stability index was proved to be positive compared to the apo and control complex. Our computational works based on peptide molecules may aid the future development of therapeutic options against SARS-CoV-2.

Virtual screening and molecular dynamics simulation study of plant-derived compounds to identify potential inhibitors of main protease from SARS-CoV-2.

The new coronavirus (SARS-CoV-2) halts the world economy and caused unbearable medical emergency due to high transmission rate and also no effective vaccine and drugs has been developed which brought the world pandemic situations. The main protease (Mpro) of SARS-CoV-2 may act as an effective target for drug development due to the conservation level. Herein, we have employed a rigorous literature review pipeline to enlist 3063 compounds from more than 200 plants from the Asian region. Therefore, the virtual screening procedure helps us to shortlist the total compounds into 19 based on their better binding energy. Moreover, the Prime MM-GBSA procedure screened the compound dataset further where curcumin, gartanin and robinetin had a score of (-59.439, -52.421 and - 47.544) kcal/mol, respectively. The top three ligands based on binding energy and MM-GBSA scores have most of the binding in the catalytic groove Cys145, His41, Met165, required for the target protein inhibition. The molecular dynamics simulation study confirms the docked complex rigidity and stability by exploring root mean square deviations, root mean square fluctuations, solvent accessible surface area, radius of gyration and hydrogen bond analysis from simulation trajectories. The post-molecular dynamics analysis also confirms the interactions of the curcumin, gartanin and robinetin in the similar binding pockets. Our computational drug designing approach may contribute to the development of drugs against SARS-CoV-2.

Screening of Potent Phytochemical Inhibitors Against SARS-CoV-2 Main Protease: An Integrative Computational Approach.

Coronavirus disease 2019 (COVID-19) is a potentially lethal and devastating disease that has quickly become a public health threat worldwide. Due to its high transmission rate, many countries were forced to implement lockdown protocols, wreaking havoc on the global economy and the medical crisis. The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus for COVID-19, represent an effective target for the development of a new drug/vaccine because it is well-conserved and plays a vital role in viral replication. Mpro inhibition can stop the replication, transcription as well as recombination of SARS-CoV-2 after the infection and thus can halt the formation of virus particles, making Mpro a viable therapeutic target. Here, we constructed a phytochemical dataset based on a rigorous literature review and explored the probability that various phytochemicals will bind with the main protease using a molecular docking approach. The top three hit compounds, medicagol, faradiol, and flavanthrin, had binding scores of -8.3, -8.6, and -8.8 kcal/mol, respectively, in the docking analysis. These three compounds bind to the active groove, consisting of His41, Cys45, Met165, Met49, Gln189, Thr24, and Thr190, resulting in main protease inhibition. Moreover, the multiple descriptors from the molecular dynamics simulation, including the root-mean-square deviation, root-mean-square fluctuation, solvent-accessible surface area, radius of gyration, and hydrogen bond analysis, confirmed the stable nature of the docked complexes. In addition, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis confirmed a lack of toxicity or carcinogenicity for the screened compounds. Our computational analysis may contribute toward the design of an effective drug against the main protease of SARS-CoV-2.