
Department of Bioinformatics
Bioinformatics in drug discovery spans the varied yet interconnected fields of cheminformatics, network biology, network pharmacology, computational biology, in-silico modelling and more. One common aspect of these fields is the mimicry of a biological environment by a computer. Bioinformatics is a constant effort to accurately and effectively simulate nature, from a simple biochemical reaction to the advanced creation of virtual organs or entire organisms.
By and large, biochemical reactions follow predictable rules of chemistry allowing relevant algorithms to be written that can mimic and predict chemical reactions in a virtual environment. If one can mimic a biochemical reaction, obviously the scope can extend to physiology and pathology, especially their investigation using virtual reality and, in the future, artificial intelligence.
Being the pioneer in medicinal plant research Atrimed has a curated plant molecules database that has been constructed via literature mining followed by manual curation of information gathered from books on traditional Indian medicine, published research articles, and other existing database resources. The phytochemicals/phytomolecules curated are systematically organized on the basis of drug likeliness properties. The information over physicochemical parameters and ADME is also covered in the database. The database is subjected to periodic testing and updates to make it more robust and accurate.

We at Atrimed are pioneers in using cutting-edge bioinformatics tools in drug discovery. Our primary field of focus is inflammation in the skin, in order to treat and manage diseases like Psoriasis, Eczema, Acne, Lichen planus, Nonhealing ulcers, Hyperpigmentation, etc. So we have established a Bioinformatics lab, with highly advanced software to conduct molecular docking and study ligand-protein and protein-protein interactions. We have a twin library of around 10,000 natural product extracts and a virtual library of their secondary metabolites. This library has all active molecular structures reported so far. We first scan this library against desired disease targets and then confirm the hits in in-vitro studies. In addition, our virtual skin model, which is constantly improving, helps in exploring possible outcomes of polypharmacology, which can be verified through structured experiments.
