A comprehensive automated computer-aided discovery pipeline from genomes to hit molecules. (31st August 2020)

• Record Type: Journal Article
• Authors: Bhat, Ruchika; Kaushik, Rahul; Singh, Ankita; DasGupta, Debarati; Jayaraj, Abhilash; Soni, Anjali; Shandilya, Ashutosh; Shekhar, Vandana; Shekhar, Shashank; Jayaram, B.
• Is Part Of: Chemical engineering science. Volume 222(2020)
• Publication Date: 2020-08-31
• Subjects: Genomics -- Computational structural proteomics -- Structure-based drug discovery -- Genome to hit pipeline -- Web suite; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2020.115711
• Languages: English
• ISSNs: 0009-2509

Abstract

Graphical abstract: Highlights: Dhanvantari is a comprehensive automatic drug design software suite. It would help in discovering new potential drug targets from genomic/proteomic data. Dhanvantari screens different molecular libraries to find novel hits . Tested on 111 FDA approved drugs against 33 diseases with ~90% accuracy. Entire protocol proposed in Dhanvantari requires ~6–12 h. Abstract: Big data generation through sequencing of genomes and proteomes has led to over thousands of whole genomes and millions of protein sequences. However, utilization of this data to generate drug-like molecules for curing diseases remains a challenge. We propose here, Dhanvantari, a comprehensive software suite which automates the journey from genomes to hit molecules via its various modules such as i) gene finding, ii) computational structural study of target proteins and iii) virtual screening/identification of hit molecules for computer aided drug discovery. The pipeline has five possible entry points. Validation of the protocol is performed on 10 major life-threatening diseases reported by WHO covering 33 different protein targets and 111 FDA approved drugs. Three complete case studies from genomes to hits are also performed using the pipeline where the reported FDA drugs against the pathogen have been successfully recovered. The proposed software suite promises to deliver some new opportunities and insights into "genome-based" drug discovery along with the classical structure-based approaches to discover novel potential drug-like molecules. The entire protocol requires ~6–12 h. Individual steps, however, get completed within a few minutes. The pipeline can be freely accessed at http://www.scfbio-iitd.res.in/software/dhanvantari_new/Home.html .