Titles

• Assistant Professor, School of Molecular Sciences, College of Liberal Arts and Sciences

Biography

Abhishek Singharoy is an assistant professor in the School of Molecular Sciences at Arizona State University. His research is at the confluence of statistical mechanics, molecular biology, hybrid modeling and large-scale computer simulations.

The unified theme of Singharoy laboratory’s research is to combine rigorous statistical mechanical methodologies with state-of-the-art computational approaches for capturing cell-scale biological responses with atomic precision. Many of the high-throughput computations essential for approaching this grand challenge are pioneered in the group's past and ongoing work on molecular dynamics, free energy and kinetic modeling methods. Spanning multiple spatio-temporal scales ranging from that of single proteins to complexes up to the whole cell, these computations have led to discoveries in voltage-sensing and ion transport mechanisms of Ci-VSP and NRAMP proteins, ribosomal insertion pathways via YidC and holotranslocon complexes, allosteric networks controlling immunogenicity of Human Papilloma virus, and the bioenergetics of bacterial membranes. The laboratory's most recent endeavors focus on dissecting the evolutionary design principles of mitochondrial respiration, in particular, through investigation of an outer membrane-embedded supercomplex called the respirasome. This study brings to light a couple of cutting-edge biomedical applications, namely, determination of the molecular origins of cellular aging and programmed cell death, and creation of a novel computer-aided pipeline pertaining to intricate pathology of the respiratory network. To put together large-scale membrane systems in atomic detail requires theoretical advances in terms of fitting/refining structural data from experiments. To address this need, group members have been developing and applying an array of flexible-fitting tools that derive high-resolution molecular models from low-resolution experimental data, such as from X-ray crystallography, electron microscopy, quantitative mass-spectrometry and chemical cross-linking.