Subha Kalyaanamoorthy’s research is focused on developing and employing computational methods to address biological, health and environmental challenges.
She involves a hybrid scientific approach, where she and her research group make new novel hypothesis using in silico approaches and validate them in their wet lab.
Their research mainly engages multiple disciplines including molecular modeling and molecular dynamics simulations, Quantum modeling and simulations, protein biochemistry, machine learning, phylogenetic inference and bioinformatics to understand the structure, function, dynamics and evolution of proteins of interest. Drug discovery and synthetic biology are the key application areas of her research.
- Computational biology
- Structure- and ligand- based drug discovery
- Biomolecular simulations
- Membrane proteins
- Protein structure-function evolution
- Protein engineering
Subha Kalyaanamoorthy’s research interests encompass the following areas:
- Design/discovery of potential therapeutics to target various diseases
- Understanding the structure and pharmacology of membrane proteins
- Development of in silico methods/tools for sequence, structure and functional analysis
- Inferring the structure-function evolution of proteins
- Protein engineering for biotechnology and pharmaceutical applications
CHEM400 Biomolecular modeling: Principles and Practice
Recent publications include:
- Wong, T.K., Kalyaanamoorthy, S., Meusemann, K., Yeates, D.K., Misof, B. and Jermiin, L.S., 2020. A minimum reporting standard for multiple sequence alignments. Nucleic Acids Research: Genomics and Bioinformatics, 2020, 2(2), iqaa024.
- Feng T, Kalyaanamoorthy S, Ganesan A, Barakat KH, Atomistic modeling and molecular dynamics analysis of human CaV1. 2 channel using external electric field and ion pulling simulations. BBA: General Subjects, 2019, 1863(6), 1116-1126.
- Kalyaanamoorthy S, Barakat, KH, Binding modes of hERG blockers: An unsolved mystery in drug discovery arena. Expert opinion in drug discovery, 2018, 13(3), 207-210. [Invited article]
- Kalyaanamoorthy S, Barakat, KH. Development of safe drugs: The hERG challenge. Medicinal Research Reviews, 2018, 38(2), 525-555.
- Kalyaanamoorthy S, Minh BQ, Wong TFK, von Haeseler A, Jermiin LS. ModelFinder: A fast model selection method that greatly improves phylogenetic estimates. Nature Methods, 2017, 14, 587- 589.
- Wilding M, Peat TS, Kalyaanamoorthy S, Newman J, Scott S, Jermiin LS. Reverse engineering: transaminase biocatalyst development using ancestral sequence reconstruction. Green Chemistry, 2017, 19, 5375-5380.
Please see Subha Kalyaanamoorthy's Google Scholar profile for a current list of his peer-reviewed articles.
Awards and Distinctions
- NSERC Canada Post-Doctoral Fellowship Award, 2018-2020
- OCE Post-Doctoral Fellowship, 2013-2016
- LSCC PhD Top-up fellowship, 2012
- Travel fellowship from the Victorian Life Sciences Computation Initiative, 2011
- La Trobe University Postgraduate Research and Full Fee Remission Scholarships, 2010-2013
- Deakin University International Research Scholarships, 2009-2010
University of Waterloo Affiliations
Waterloo Artificial Intelligence Institute
2013 Ph.D., Computational Biology and Bioinformatics, La Trobe University, Australia
2007 M.Sc., Bioinformatics, Annamalai University, India