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Bioactivity of Indian Medicinal Plants
Database of Phytochemicals
SCFBio, IIT Delhi
The creation of a comprehensive databank on bioactivities of compounds in Indian medicinal plants involves the systematic collection, curation, and organization of data from various sources. This databank aims to consolidate information on the chemical constituents of medicinal plants, their bioactive properties, and their potential applications in the treatment of various diseases.
The compilation of this information in a structured and accessible format offers several advantages. Researchers, scientists, and pharmaceutical companies can use the databank as a valuable resource to identify potential leads for drug discovery and development. It facilitates the exploration of bioactive compounds that may exhibit specific therapeutic effects, thereby accelerating the process of finding new drug candidates from natural sources.
The data provided showcases a diverse array of organic compound Super Classes predicted by Classifire along with their respective counts. From smaller categories like "Acetylides" and "Organic 1,3-dipolar compounds" to broader classifications such as "Hydrocarbons" and "Organic oxygen compounds," each category represents a distinct subset of organic chemistry. Particularly noteworthy is the high count of compounds in categories like "Organoheterocyclic compounds" and "Phenylpropanoids and polyketides," indicating their significant presence in organic compound databases. Moreover, the substantial count of "Lipids and lipid-like molecules" highlights the importance of these compounds in biological and chemical systems.
The data provided includes counts for compounds adhering to various drug-likeness rules, such as Lipinski, Ghose, Veber, Egan, and Muegge. These rules are often used in drug discovery to assess the likelihood of a compound's success as a drug candidate. Among the compounds evaluated, Lipinski's rule appears to be the most prevalent, with 52,058 compounds meeting its criteria, followed by Veber's rule with 66,020 compounds. In total, 33,031 compounds adhere to all of these rules out of a total of 105,909 compounds evaluated.
The data provided represents the distribution of compounds based on their molecular weight (MW). A significant portion, 71,202 compounds, falls within the range of 0-500 MW, indicating a prevalence of smaller molecules. Additionally, 29,595 compounds have MW between 500 and 1000, while a smaller subset of 5,058 compounds has a MW exceeding 1000. This breakdown suggests a diverse range of molecular sizes among the evaluated compounds, with the majority falling within the lower MW range.
The data provided includes counts for compounds adhering to various WLogP Ranges.
The data provided represents the distribution of compounds based on their Hydrogen Bond Acceptors (HBA) and Donars (HBD).