My group performs research to understand, through multiscale modelling, how organismal metagenomes specify their behavior and characteristics in conjunction with their environments. We accomplish this by developing novel computational biology and bioinformatics algorithms for predicting protein and proteome structure, function, interaction, design and evolution. We apply these basic science techniques to important practical problems in medicine, genetic and genomic engineering and nanobiotechnology.

I received the 2010 National Institutes of Health (NIH) Director‘s Pioneer Award to develop the Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando/) for multiscale therapeutic drug discovery, repurposing, and design. Our integrated informatics platform determines interactions between and among all drugs/compounds and higher scale entities (proteins, RNA, pathways, cells, tissues, etc.) to generate multiscale interaction signatures. The multiscale signatures are weighted using pharmacological, physiological and chemoinformatics data and compared and analyzed to predict the likelihood of the corresponding compounds being efficacious for any indication, in effect inferring homology of drug/compound behavior at proteomic/interactomic scales.

Using this approach, we made predictions for all the indications that our library of drugs maps to, with benchmarking accuracies that are orders of magnitude better than what is observed when using random controls. We have performed prospective validations of our predictions, demonstrating comparable or better in vitro inhibition than existing drugs approved for clinical use in indications such as COVID-19, dengue, dental caries, diabetes, hepatitis B, herpes, lupus, malaria and tuberculosis. We have implemented drug design capabilities in our platform to generate compounds beyond what is already known for indications such as opioid use disorder and overdose and non-small cell lunger cancer. We have further extended our platform to incorporate genotypic and phenotypic variations to enable precision medicine.

We also applied our computational techniques to design peptides for vaccines, antibacterial activity and inorganic substrate adhesion and model the structures, functions and interactions of all tractable proteins encoded by several rice genomes. A consistent theme in our research is the combination of in virtuale simulation and homology inference, followed by in vitro and in vivo verification and application, directed toward holistic multiscale modelling of complex biological systems. All this is accomplished in close collaboration with researchers across the world and primarily with Dr. Zackary Falls, also a faculty in the Bioinformatics Division.