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. 2014 Oct 11;6(1):46.
doi: 10.1186/s13321-014-0046-2. eCollection 2014 Dec.

BioPhytMol: a drug discovery community resource on anti-mycobacterial phytomolecules and plant extracts

Affiliations

BioPhytMol: a drug discovery community resource on anti-mycobacterial phytomolecules and plant extracts

Arun Sharma et al. J Cheminform. .

Abstract

Background: Tuberculosis (TB) is the second leading cause of death from a single infectious organism, demanding attention towards discovery of novel anti-tubercular compounds. Natural products or their derivatives have provided more than 50% of all existing drugs, offering a chemically diverse space for discovery of novel drugs.

Description: BioPhytMol has been designed to systematically curate and analyze the anti-mycobacterial natural product chemical space. BioPhytMol is developed as a drug-discovery community resource with anti-mycobacterial phytomolecules and plant extracts. Currently, it holds 2582 entries including 188 plant families (692 genera and 808 species) from global flora, manually curated from literature. In total, there are 633 phytomolecules (with structures) curated against 25 target mycobacteria. Multiple analysis approaches have been used to prioritize the library for drug-like compounds, for both whole cell screening and target-based approaches. In order to represent the multidimensional data on chemical diversity, physiochemical properties and biological activity data of the compound library, novel approaches such as the use of circular graphs have been employed.

Conclusion: BioPhytMol has been designed to systematically represent and search for anti-mycobacterial phytochemical information. Extensive compound analyses can also be performed through web-application for prioritizing drug-like compounds. The resource is freely available online at http://ab-openlab.csir.res.in/biophytmol/. Graphical AbstractBioPhytMol: a drug discovery community resource on anti-mycobacterial phytomolecules and plant extracts generated using Crowdsourcing. The platform comprises of manually curated data on antimycobacterial natural products along with tools to perform structure similarity and visualization. The platform allows for prioritization of drug like natural products for antimycobacterial drug discovery.

Keywords: Anti-TB; Anti-mycobacterial; Anti-tubercular; BioPhytMol; Crowdsourcing; Drug discovery; TB; Tuberculosis.

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Figures

Graphical Abstract
Graphical Abstract
BioPhytMol: a drug discovery community resource on anti-mycobacterial phytomolecules and plant extracts generated using Crowdsourcing. The platform comprises of manually curated data on antimycobacterial natural products along with tools to perform structure similarity and visualization. The platform allows for prioritization of drug like natural products for antimycobacterial drug discovery.
Figure 1
Figure 1
BioPhytMol database architecture showing its various components with ‘Search’ options, ‘Browse by’ options and structural ‘similarity’ between BioPhytMol compounds and Anti-TB drugs, FDA approved small molecule drugs and Nutraceuticals.
Figure 2
Figure 2
Overall distribution of chemical, biological and physicochemical properties of 623 BioPhytMol phytomolecules. The outermost circle represents the broad chemical structure of compounds i.e., they are cyclic or aliphatic. The next ring depicts the biological activity of the compounds in terms of MIC ≤ 50 μg/ml and mycobacterial growth % inhibition > 90. The subsequent rings represent six graphs of calculated physicochemical properties. All the compounds are sorted in the increasing order of their molecular weight. The innermost graph is the representation of near neighbours (NN) amongst B_mols. The four compounds: T-cadinol, Maniladiol, Faradiol and Erythrodiol are nearest neighbours with difference in molecular weight between T-cadinol and the rest of the three compounds. Important structural differences may be the reason behind different MICs.
Figure 3
Figure 3
Drug-likeness study of BioPhytMol compounds. (A) Compound distribution graph based on the number of compounds screened against DruLiTo (Drug-likeness Tool) filter with 6 compounds passing all 8 filters. (B) Structure of BioPhytMol compounds crossing all the filters of DruLiTo: (1) 4-((Z)-2-(3-(3,4-dimethoxystyryl)isoxazol-5-yl)vinyl)-2-methoxyphenol (2) 4-((E)-2-(5-(3,4-dimethoxystyryl)isoxazol-3-yl)vinyl)-2-methoxyphenol (3) 2-(3,4-dimethoxyphenethyl)-4-methoxyquinoline (4) (2S,3R)-6-oxo-2-((2S,3R)-3-phenyloxiran-2-yl)-3,6-dihydro-2H-pyran-3-yl cinnamate (5) (2Z,4Z,8E)-9-(benzo[d][1,3]dioxol-5-yl)-1-(pyrrolidin-1-yl)nona-2,4,8-trien-1-one (6) (2Z,6Z)-7-(benzo[d][1,3]dioxol-5-yl)-1-(pyrrolidin-1-yl)hepta-2,6-dien-1-one. The dotted circle shows the presence of a Michael acceptor group (toxicophore).

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