Dr. Prashantha Karunakar obtained his Masters in Bioinformatics from Kuvempu University and Ph.D degree from PES Institute of Technology (Affiliated to Kuvempu University, Shankarghatta). He worked on the Ph.D research topic titled “Crystal structure and molecular docking analysis of furan derivatives having pharmaceutical significance and determination of assembly of chains in protein targets”. Prior to joining PESIT, he worked as Research Associate at Indgen Life Technologies, Bangalore and Research Assistant at Vittal Mallya Scientific Research Foundation, Bangalore where he contributed by performing target identification, validation and docking studies of different ligands for their pharmaceutical significance. He worked at two famous international synchrotron facilities like DESY, Hamburg, Germany and ESRF, Grenoble, France where he contributed on automating the number of monomers in the asymmetric unit of protein crystal and analysis of X-ray data and resulting structure from UV induced radiation damage phasing. He has published more than 20 articles in National and International Journals. Solved two protein crystal structures of Histidine kinases during the stay at Hamburg, Germany. He is the recipient of the prestigious EMBO Practical Course on Computational Structural Biology 07-11 April 2014, at the European Bioinformatics Institute, Hinxton, UK with complete travel support. He has completed a course on Symmetry in the Solid State conducted by Prof. T. N. Guru Row at Solid State Structural Chemistry Unit, Indian Institute of Science (IISc), Bangalore, India. He is also the Editor-in-chief for International Journal of Computational Biology and Bioinformatics, Strings Publications and Scientific Advisor for DNAskew Analytics Pvt Ltd.
- Guided several academic and research projects, many of them leading to research publications for UG and PG students.
- Delivered lectures on “Protein crystallography and hands on Proteomics tools” in the Department of Biotechnology, Garden City College, Bangalore, India on 5/3/2014.
- Organized a workshop on "Next Generation Sequencing (NGS) data analysis" in the Department of Biotechnology, PES University, Bangalore during 03-2015 & 10/2014
- Delivered lectures on “Protein-Ligand Docking" in the Department of Biotechnology, New Horizon College of Engineering, Bangalore, India on 4/14/2013.
- Delivered lectures on “Protein structure prediction (Secondary and tertiary) and Protein Docking" in National Bureau of Agriculturally Important Insect (NBAII), Bangalore, India on 11/29/2012.
Essential Bioinformatics, Chemoinformatics and Computational Medicinal Chemistry, Proteomics, Biomolecular Modeling & Simulation
Drug Design and Toxicology, Bioinformatics, Biochemistry, Bioenergetics & Metabolism, Structural Biology, Biopython (Special topic), Protein engineering and In silico drug design
Awards and Honors
EMBO fellowship to participate practical course on Computational Structural Biology - from data to structure to function”, EMBL-EBI, Hinxton, UK on 07-11, April 2014.
Scholarship Awarded by 'National Level Scholarship Program' during Master's studies
Industry and Journal Interactions
- Scientific Advisor - DNAskew Analytics Pvt Ltd (http://dnaskew.com/)
- Editor-in-chief, International Journal of Computational Biology and Bioinformatics (IJCOB) http://ijcob.stringsjournal.com/
Research areas of Interest: Bioinformatics, Computer Aided Drug Design, Molecular Modeling & Structural Bioinformatics, Crystallography
Journal Reviewer: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Asian Journal of Microbiology and Biotechnology, British Journal of Pharmaceutical Research, Chemical Science International Journal, Bioinformatics and Biology Insights
Current Research Projects
- Successfully completed the prototype development of TEQIP sponsored project on "ChemDetect: A microcontroller based detection method for identifying and storing chemicals in the stock room"
- Synthesis, molecular characterization and docking studies of schiff based organic compounds towards pharmaceutical significance
- Determining the Number of Molecules (chains) in the Asymmetric Unit of a Protein using machine learning