More information about Databses and Tools
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A Database of Plants based Aroma Molecules
AROMA database (http://bioinfo.cimap.res.in/aroma/) is a comprehensive electronic library of aroma molecules of medicinal and aromatic plants of Indian origin, as well as foreign and include detail information about aroma plants, description, plants varieties, plants accessions, chemotypes, essential oils, oil yields and constituents, chromatograms, major and minor compounds, structural elucidation data, structural data (2D and 3D) of very small size volatile molecules (< 300 molecular weight) and medium size molecules (< 500 molecular weight), physico-chemical properties, biological pathways information and cross references. Here, aroma compounds classified by structure as esters, linear terpenes, cyclic terpenes, aromatic, amines, alcohols, aldehydes, ketones, lactones, thiols and miscellaneous compounds. Publication: Kumar Y, Prakash O, Tripathi H, Tandon S, Gupta MM, Rahman LU, Lal RK, Semwal M, Darokar MP, Khan F. AromaDb: A Database of Medicinal and Aromatic Plant's Aroma Molecules With Phytochemistry and Therapeutic Potentials. Frontiers in plant science. 2018;9. (PMID: 30150996) |
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A QSAR Modeling based Screening Tool for Active Leads Prediction.
Summary: The Q-Lead (http://bioinfo.cimap.res.in/qlead/) is a software tool for predicting biological activity of untested natural molecules and it's derivatives/analogues, to provide molecular insight into relevant 2D & 3D chemical descriptors responsible for certain biological activity. For this, Q-Lead uses various in-house developed local and global Quantitative Structure-Activity Relationship (QSAR) models based on different natural chemical series. The Q-Lead models quantitatively correlate chemical descriptors (structural properties) with biological activities for a set of similar compounds by using statistical modeling such as Multiple linear Regression (MLR) or PLS. The Q-Lead tool covers 2D QSAR models, which mimicks the bioactivity evaluation through in vitro studies, including both cell line and target based screening assays. The QSAR models included chemical series of following natural compounds e.g., 18ß-Glycyrrhetinic acid (GA), Ursolic acid (UA), Camptothecin (CPT), Chalcone, artemisinin, vaniloids (capsaicin and capsazepine), and Xanthone derivatives for anticancer, antibacterial, antimalarial and immunomodulatory/antiinflammamtrory activities, both cell line and target enzyme specific. The Q-Lead tool could be more useful in early identification of potential drug-like leads.
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A Tool for Motif Prediction and Weight Matrix Construction
D-Matrix (http://bioinfo.cimap.res.in/dmatrix/). D-Matrix is a tool for the construction of the conserved motif/pattern alignment, consensus sequence generation, alignment, frequency and weight matrix construction along with their possible regular expression signature or degenerate sequence of the motif with help of conserved sites/motif. D-Matrix program is based on heuristic algorithm to construct the position specific scoring matrix (PSSM) for DNA pattern set (Khan et al., 2008). These matrices can be useful in the identification of genome wide unexplored conserved motifs through established weight matrix based motif discovery tools such as RSAT (Patser), PossuMsearch etc. Publication: Sen N, Mishra M, Khan F, Meena A, Sharma A. D-MATRIX: a web tool for constructing weight matrix of conserved DNA motifs. Bioinformation. 2009 Jul 27;3(10):415-8. (PMID: 19759861)
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DbMDR: A database of multi drug resistance genes
DbMDR (http://bioinfo.cimap.res.in/dbmdr/index.aspx).A comprehensive reference database of multi-drug resistance genes found in all forms of life such as archaea, eubacteria, fungi, plants and animals and even viruses. DbMDR is a non-redundant reference database of MDR genes that contains experimentally verified data curated from the scientific literature. DbMDR database covers information of MDR genes & their phylogenetic distribution, Human Diseases caused by antibiotics resistant bacterial strains and references. Besides experimentally elucidated data, it also covers predicted data such as potential orthologs of MDR genes, protein motifs and domains of MDR, which made DbMDR a unique and valuable resource for drug discovery research. Publication: Gupta S, Mishra M, Sen N, Parihar R, Dwivedi GR, Khan F, Sharma A. DbMDR: a relational database for multidrug resistance genes as potential drug targets. Chem Biol Drug Des. 2011 Oct;78(4):734-8. (PMID: 21781283) |