Big data generation through sequencing of genomes and proteomes has led to over 2800 whole genomes and ~84 million protein sequences, however utilization of this data to generate lead molecules for curing diseases remains a challenge. We propose here, Dhanvantari, a comprehensive software suite which automates the computational journey from genome to hit molecules via its various genomics, proteomics and drug designing modules with possible entry at any module. The proposed software suite offers new opportunities and insights to “genome-based” drug discovery along with classical structure-based approaches to discover new drug-like molecules. The pipeline helps in exploring new potential drug targets from genomic/proteomic data which were earlier inaccessible and helps to find novel hits via screening against million compounds or natural products or FDA approved drugs or even customized molecule libraries. Case studies on Hepatitis B Virus and Hepatitis A Virus against their druggable proteins via this pipeline have led to potent and novel inhibitors with low micro molar range inhibitions in in vitro studies. The entire protocol proposed in Dhanvantari requires ~ 6 to12 hours, however individual steps get completed within few minutes. The software suite is made freely accessible as an online resource at

http://www.scfbio-iitd.res.in/software/dhanvantari_new/Home.html


with no additional dependencies. Presently, there is no fully-automated open source similar to Dhanvantari which can mine the information about the potential drug like molecules from the genome as well as proteome information.






References
Soni, A. et al. (2013). Genomes to Hits In Silico - A Country Path Today, A Highway Tomorrow: A Case Study of Chikungunya. Curr. Pharma. Des. 19, 4687 – 4700.