IMPPAT 2.0: An Enhanced and Expanded Phytochemical Atlas of Indian Medicinal Plants.

Compilation, curation, digitization, and exploration of the phytochemical space of Indian medicinal plants can expedite ongoing efforts toward natural product and traditional knowledge based drug discovery. To this end, we present IMPPAT 2.0, an enhanced and expanded database compiling manually curated information on 4010 Indian medicinal plants, 17,967 phytochemicals, and 1095 therapeutic uses. Notably, IMPPAT 2.0 compiles associations at the level of plant parts and provides a FAIR-compliant nonredundant in silico stereo-aware library of 17,967 phytochemicals from Indian medicinal plants. The phytochemical library has been annotated with several useful properties to enable easier exploration of the chemical space. We have also filtered a subset of 1335 drug-like phytochemicals of which majority have no similarity to existing approved drugs. Using cheminformatics, we have characterized the molecular complexity and molecular scaffold based structural diversity of the phytochemical space of Indian medicinal plants and performed a comparative analysis with other chemical libraries. Altogether, IMPPAT 2.0 is a manually curated extensive phytochemical atlas of Indian medicinal plants that is accessible at https://cb.imsc.res.in/imppat/.

Virtual screening of phytochemicals from Indian medicinal plants against the endonuclease domain of SFTS virus L polymerase.

Severe fever with thrombocytopenia syndrome virus (SFTSV) causes a highly infectious disease with reported mortality in the range 2.8% to 47%. The replication and transcription of the SFTSV genome is performed by L polymerase, which has both an RNA dependent RNA polymerase domain and an N-terminal endonuclease (endoN) domain. Due to its crucial role in the cap-snatching mechanism required for initiation of viral RNA transcription, the endoN domain is an ideal antiviral drug target. In this virtual screening study for the identification of potential inhibitors of the endoN domain of SFTSV L polymerase, we have used molecular docking and molecular dynamics (MD) simulation to explore the natural product space of 14 011 phytochemicals from Indian medicinal plants. After generating a heterogeneous ensemble of endoN domain structures reflecting conformational diversity of the corresponding active site using MD simulations, ensemble docking of the phytochemicals was performed against the endoN domain structures. Apart from the ligand binding energy from docking, our virtual screening workflow imposes additional filters such as drug-likeness, non-covalent interactions with key active site residues, toxicity and chemical similarity with other hits, to identify top 5 potential phytochemical inhibitors of endoN domain of SFTSV L polymerase. Further, the stability of the protein-ligand docked complexes for the top 5 potential inhibitors was analyzed using MD simulations. The potential phytochemical inhibitors, predicted in this study using contemporary computational methods, are expected to serve as lead molecules in future experimental studies towards development of antiviral drugs against SFTSV.

Potential phytochemical inhibitors of SARS-CoV-2 helicase Nsp13: a molecular docking and dynamic simulation study.

The SARS-CoV-2 helicase Nsp13 is a promising target for developing anti-COVID drugs. In the present study, we have identified potential natural product inhibitors of SARS-CoV-2 Nsp13 targeting the ATP-binding site using molecular docking and molecular dynamics (MD) simulations. MD simulation of the prepared crystal structure of SARS-CoV-2 Nsp13 was performed to generate an ensemble of structures of helicase Nsp13 capturing the conformational diversity of the ATP-binding site. A natural product library of more than 14,000 phytochemicals from Indian medicinal plants was used to perform virtual screening against the ensemble of Nsp13 structures. Subsequently, a two-stage filter, first based on protein-ligand docking binding energy value and second based on protein residues in the ligand-binding site and non-covalent interactions between the protein residues and the ligand in the best-docked pose, was used to identify 368 phytochemicals as potential inhibitors of SARS-CoV-2 helicase Nsp13. MD simulations of the top inhibitors complexed with protein were performed to confirm stable binding, and to compute MM-PBSA based binding energy. From among the 368 potential phytochemical inhibitors, the top identified potential inhibitors of SARS-CoV-2 helicase Nsp13 namely, Picrasidine M, (+)-Epiexcelsin, Isorhoeadine, Euphorbetin and Picrasidine N, can be taken up initially for experimental studies.

MeFSAT: a curated natural product database specific to secondary metabolites of medicinal fungi.

Fungi are a rich source of secondary metabolites which constitutes a valuable and diverse chemical space of natural products. Medicinal fungi have been used in traditional medicine to treat human ailments for centuries. To date, there is no devoted resource on secondary metabolites and therapeutic uses of medicinal fungi. Such a dedicated resource compiling dispersed information on medicinal fungi across published literature will facilitate ongoing efforts towards natural product based drug discovery. Here, we present the first comprehensive manually curated database on Medicinal Fungi Secondary metabolites And Therapeutics (MeFSAT) that compiles information on 184 medicinal fungi, 1830 secondary metabolites and 149 therapeutics uses. Importantly, MeFSAT contains a non-redundant in silico natural product library of 1830 secondary metabolites along with information on their chemical structures, computed physicochemical properties, drug-likeness properties, predicted ADMET properties, molecular descriptors and predicted human target proteins. By comparing the physicochemical properties of secondary metabolites in MeFSAT with other small molecules collections, we find that fungal secondary metabolites have high stereochemical complexity and shape complexity similar to other natural product libraries. Based on multiple scoring schemes, we have filtered a subset of 228 drug-like secondary metabolites in MeFSAT database. By constructing and analyzing chemical similarity networks, we show that the chemical space of secondary metabolites in MeFSAT is highly diverse. The compiled information in MeFSAT database is openly accessible at: https://cb.imsc.res.in/mefsat/.

In Silico Identification of Potential Natural Product Inhibitors of Human Proteases Key to SARS-CoV-2 Infection.

Presently, there are no approved drugs or vaccines to treat COVID-19, which has spread to over 200 countries and at the time of writing was responsible for over 650,000 deaths worldwide. Recent studies have shown that two human proteases, TMPRSS2 and cathepsin L, play a key role in host cell entry of SARS-CoV-2. Importantly, inhibitors of these proteases were shown to block SARS-CoV-2 infection. Here, we perform virtual screening of 14,011 phytochemicals produced by Indian medicinal plants to identify natural product inhibitors of TMPRSS2 and cathepsin L. AutoDock Vina was used to perform molecular docking of phytochemicals against TMPRSS2 and cathepsin L. Potential phytochemical inhibitors were filtered by comparing their docked binding energies with those of known inhibitors of TMPRSS2 and cathepsin L. Further, the ligand binding site residues and non-covalent interactions between protein and ligand were used as an additional filter to identify phytochemical inhibitors that either bind to or form interactions with residues important for the specificity of the target proteases. This led to the identification of 96 inhibitors of TMPRSS2 and 9 inhibitors of cathepsin L among phytochemicals of Indian medicinal plants. Further, we have performed molecular dynamics (MD) simulations to analyze the stability of the protein-ligand complexes for the three top inhibitors of TMPRSS2 namely, qingdainone, edgeworoside C and adlumidine, and of cathepsin L namely, ararobinol, (+)-oxoturkiyenine and 3α,17α-cinchophylline. Interestingly, several herbal sources of identified phytochemical inhibitors have antiviral or anti-inflammatory use in traditional medicine. Further in vitro and in vivo testing is needed before clinical trials of the promising phytochemical inhibitors identified here.

IMPPAT: A curated database of Indian Medicinal Plants, Phytochemistry And Therapeutics.

Phytochemicals of medicinal plants encompass a diverse chemical space for drug discovery. India is rich with a flora of indigenous medicinal plants that have been used for centuries in traditional Indian medicine to treat human maladies. A comprehensive online database on the phytochemistry of Indian medicinal plants will enable computational approaches towards natural product based drug discovery. In this direction, we present, IMPPAT, a manually curated database of 1742 Indian Medicinal Plants, 9596 Phytochemicals, And 1124 Therapeutic uses spanning 27074 plant-phytochemical associations and 11514 plant-therapeutic associations. Notably, the curation effort led to a non-redundant in silico library of 9596 phytochemicals with standard chemical identifiers and structure information. Using cheminformatic approaches, we have computed the physicochemical, ADMET (absorption, distribution, metabolism, excretion, toxicity) and drug-likeliness properties of the IMPPAT phytochemicals. We show that the stereochemical complexity and shape complexity of IMPPAT phytochemicals differ from libraries of commercial compounds or diversity-oriented synthesis compounds while being similar to other libraries of natural products. Within IMPPAT, we have filtered a subset of 960 potential druggable phytochemicals, of which majority have no significant similarity to existing FDA approved drugs, and thus, rendering them as good candidates for prospective drugs. IMPPAT database is openly accessible at: https://cb.imsc.res.in/imppat .