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 ageing 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.
Some recent research highlights are provided here:
Flexible-fitting tools for refining low-resolution crystallographic and electron microscopy (EM) data. X-ray crystallography remains the most dominant method for solving atomic structures. However, for relatively large systems, the availability of only medium-to-low-resolution diffraction data often limits the determination of all-atom details. We have developed a flexible fitting-based real space refinement approach, xMDFF, for determining structures from such low-resolution crystallographic data. Even during the testing phases, xMDFF solved the structure of a voltage sensor protein, Ci-VSP. The refinement enabled resolution of search models 6 angstrom away from the target data even with maps as coarse as 7 angstrom, a feat very rare in the 100 years of X-ray crystallography. Resorting to the application of chemically accurate force fields, xMDFF allows uniquely the use of macromolecular structure determination strategies for resolving small molecule crystals. Finally, since xMDFF very naturally addresses whole-molecule disorder, we are currently employing it with to decrypt low-resolution diffraction patterns from X-ray free electron laser data of membrane proteins. In recent years, however, cryo-EM has evolved into one of the most effective structure determination tools rivaling X-ray crystallography, and also reaching 3-5 angstrom resolutions. Taking advantage of this overlapping resolution limits, we have successfully modified our low-resolution crystallographic tools into ones for addressing high-resolution cryo-EM data. Termed resolution-exchange MDFF, these novel cryo-EM tools have applied to validate the structure of TRP channels, and determine the latest human proteasome model.
Structural systems biology of photosynthetic and respiratory membranes. Bioenergetic membranes compose key cellular apparatus in many life forms that carry out a series of interlinked energy conversion processes, providing ATP and other metabolites to a cell. The individual processes and their underlying membrane proteins have been investigated intensively, but rarely have these processes been studied together, in particular on a system-scale covering all the dynamical steps. The reasons are both lack of whole membrane atomic resolution models, and huge complexity. Combining MD and Brownian Dynamics simulations, and GPU-accelerated molecular visualization, we have constructed the first all-atom model of an entire cell-organelle, namely that of the chromatophore of a purple bacteria. Thereafter, we have recognized the role of protein-imposed membrane curvature in chromatophore vesicle budding – a phenomenon that has been hypothesized by AFM experiments, now confirmed using our simulations. The study delivers further a systems-scale functional model that connects fast electronic processes with slow diffusive and conformational transition steps to identify key rate-determining bottlenecks that affect the ATP yield. These rate-determining energy conversion steps are evolutionarily conserved and surprisingly, contribute to pathways of cellular ageing across multiple life forms. Finally, we have accessed the millisecond-scales dynamics of the ubiquitous motor protein ATP synthase to showcase how it’s protein-protein interface conformations directly mediate the ~100% efficiency of ATP turnover – a processes indispensible sustaining all the cellular activities.
Singharoy A, Barragan AM, Thangapandian S, Tajkhorshid E, Schulten K. Binding Site Recognition and Docking Dynamics of a Single Electron Transport Protein: Cytochrome c2. J Am Chem Soc. 2016 Sep 21;138(37):12077-89. PubMed PMID: 27508459.
2005-2006 Burjor Godrej Fellowship, Indian Institute of Technology Bombay
2010 Best Poster award at the Midwest Theoretical Chemistry Conference, Purdue University
2011-2012 McCormick Science Grant by the College of Arts and Sciences, Indiana University
2012-2013 David A. Rothrock. Jr. Scholarship by the Department of Chemistry, Indiana University
2013-2016 Beckman Postdoctoral Fellowship, University of Illinois at Urbana Champaign
2014 Best Visualization and Data Analytics Showcase at the International Conference for High
Performance Computing, Networking, Storage, and Analysis, New Orleans
2016-2017 NSF Center for the Physics of Living Cells Postdoctoral Fellow
2017-2019 INCITE Leadership Computing Award, U.S. Depart of Energy
2017-2020 Executive member of Oakridge Leadeship Computing Facility (OLCF) Users Board
2018 Faculty Sponsor of Biophysical Society's Arizona Student Chapter
2018 Scialog Fellow for "Chemical Machinery of Cells" by Research Corporation
and the Gordon and Betty Moore Foundation