Workshop on Bioinformatics and Computational Drug Discovery

Workshop on Bioinformatics and Computational Drug Discovery
22-24 October, 2020

Training Location
Virtual Workshop 
Time: 1:30-4:30PM

Convener
Dr.C.N.Prashantha
Assistant Professor
Department of Biotechnology, 
School of Applied Sciences, 
REVA University, Bangalore-560064

COURSE OBJECTIVE

Department of Biotechnology, School of Physical, chemical and Biological Sciences, REVA University organized one day workshop on Computational Drug Discovery using Bioinformatics Approaches for M.Sc 1^st Year Biotechnology Students on 22-24, October, 2020. The modules included theoretical aspects and hands-on sessions to impart computational skills in the domains of drug discovery. The main focus were on bioinformatics and structure & ligand-based methods and their application in drug discovery.

 Dr.C.N.Prashantha, Assistant Professor, Department of Biotechnology was the resource person for the workshop. Students got hands on experience on basic bioinformatic techniques such as sequence Alignment, Pair wise sequence alignment, Multiple sequence alignment and Protein structure prediction. They were also exposed to drug discovery techniques such as Pharmacophore analysis, Pharmacokinetic analysis, Molecular Docking & Virtual Screening.

 Topics Covered in the training

• About the workshop and Welcome Address
• Introduction on Bioinformatics tools, software’s and Databases
• Sequence analysis (Theory & Practical)
• Phylogenetic Analysis using MEGA Software (Theory & Practical)
• Protein structure prediction & Homology Modeling
• Chemical structure design and physicochemical property prediction
• Pharmacophore & Pharmacokinetic Analysis
• Molecular docking and virtual screening

 Programming Skills

• Bioinformatics tools such as BLAST, FASTA, CLUSTAL OMEGA
• PROSITE, Pfam, Interproscan
• SwissPDB Viewer, Pymol
• AutoDock, Discovery Studio.

 Program Outcomes

• Students can understand the Bioinformatics tools and softwares
• Successfully can predict the protein structures and functions.
• Successfully can work with Computational drug discovery methods and softwares