Abhishek Singharoy

Assistant Professor
Faculty
TEMPE Campus
Mailcode
1604

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 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:  

http://ascr-discovery.science.doe.gov/2018/06/cellular-energy-crisis/

https://www.olcf.ornl.gov/2017/05/09/assembling-lifes-molecular-motor/

https://www.olcf.ornl.gov/2017/06/27/annual-user-meeting-spotlights-titan-summit-and-deep-learning/

https://beckman.illinois.edu/news/2016/08/singharoy

https://beckman.illinois.edu/news/2015/08/cyanostar-atomic-structure

https://www.olcf.ornl.gov/2018/02/07/new-discoveries-within-sight/

Videos

Google Scholar

Research Interests

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.

  1. Li Q, Wanderling S, Paduch M, Medovoy D, Singharoy A, McGreevy R, Villalba-Galea CA, Hulse RE, Roux B, Schulten K, Kossiakoff A, Perozo E. Structural mechanism of voltage-dependent gating in an isolated voltage-sensing domain. Nat Struct Mol Biol. 2014 Mar;21(3):244-52. PubMed PMID: 24487958; PubMed Central PMCID: PMC4116111.
  2. McGreevy R, Singharoy A, Li Q, Zhang J, Xu D, Perozo E, Schulten K. xMDFF: molecular dynamics flexible fitting of low-resolution X-ray structures. Acta Crystallogr D Biol Crystallogr. 2014 Sep;70(Pt 9):2344-55. PubMed PMID: 25195748; PubMed Central PMCID: PMC4157446.
  3. Singharoy A, Venkatakrishnan B, Liu Y, Mayne CG, Lee S, Chen CH, Zlotnick A, Schulten K, Flood AH. Macromolecular Crystallography for Synthetic Abiological Molecules: Combining xMDFF and PHENIX for Structure Determination of Cyanostar Macrocycles. J Am Chem Soc. 2015 Jul 15;137(27):8810-8. PubMed PMID: 26121416; PubMed Central PMCID: PMC4504762.
  4. Singharoy A, Teo I, McGreevy R, Stone JE, Zhao J, Schulten K. Molecular dynamics-based refinement and validation for sub-5 � cryo-electron microscopy maps. Elife. 2016 Jul 7;5. pii: e16105. PubMed PMID: 27383269; PubMed Central PMCID: PMC4990421.

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 its protein-protein interface conformations directly mediate the ~100% efficiency of ATP turnover  a processes indispensible sustaining all the cellular activities.

  1. 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.

  2. Sener M, Strumpfer J, Singharoy A, Hunter CN, Schulten K. Overall energy conversion efficiency of a photosynthetic vesicle. Elife. 2016 Aug 26;5. pii: e09541. PubMed PMID: 27564854; PubMed Central PMCID: PMC5001839.
  3. Singharoy A, Chipot C. Methodology for the simulation of molecular motors at different scales. J Phys Chem B. 2016 Nov;121(15): 3502-3514.
  4. Singharoy A, Chipot C, Moradi M, Schulten K. Chemomechanical Coupling in Hexameric Protein-Protein Interfaces Harnesses Energy within V-Type ATPases. J Am Chem Soc. 2017 Jan 11;139(1):293-310. PubMed PMID: 27936329.

Publications

  • Ali, Md. E.; Singharoy, A.; Datta, S.N. Molecular Tailoring and Prediction of Strongly Ferromagnetically Coupled Trimethylenemethane-Based Nitroxide Diradicals J. Phys. Chem. A 2007, 111, 5523.
  • Singharoy, A.; Yesnik, A.; Ortoleva, P. J. Multiscale Analytic Continuation Approach to Nanosystem Simulation: Applications to Virus Electrostatics J.Chem. Phys. 2010, 132, 174112 (Reviewed in Virtual Journals in Science and Technology).
  • Singharoy, A.; Cheluvaraja, S.; Ortoleva, P. J. Order Parameters for Macromolecules: Application to Multiscale Simulation J. Chem. Phys. 2011, 134, 044104 (Reviewed in Virtual Journals in Science and Technology).
  • Joshi, H.; Singharoy, A.; Sereda, Y.; Cheluvaraja, S.; Ortoleva, P. J. Multiscale Simulation of Microbe Structure and Dynamics Prog. Biophys. Mol. Biol. 2011, 107, 200.
  • Singharoy, A. ; Joshi, H.; Ortoleva, P.J.; Miao, Y. Space Warping Order Parameters and Symmetry: Application to Multiscale Simulation of Macromolecular Assemblies J. Phys. Chem. B 2012, 116, 8423 .
  • Singharoy, A.; Sereda, Y.; Ortoleva, P. J. Hierarchical Order Parameters for Macromolecular Assembly Simulation I: Construction and Dynamical Properties of Order Parameters J. Chem. Theor. Comput. 2012, 8, 1379 .
  • Pankavich, S.; Singharoy, A. ; Ortoleva, P.J. Hierarchical Multiscale Modeling of Macromolecules and their Assemblies Soft Matter 2013, 9, 4319.
  • Joshi, H.; Lewis, K.; Singharoy, A. ; Ortoleva, P.J. Epitope Engineering and Molecular Metrics of Immunogenicity: A Computational Approach to VLP-based Vaccine DesignVaccine 2013, 31, 4841.
  • Singharoy, A.* ; Polavarapu, A.*; Joshi, H.; Baik, M.; Ortoleva, P. J. Epitope Fluctuation in the Human Papillomavirus are under Dynamic Allosteric Control:a Computational Evaluation of a New Vaccine Design Strategy J. Am. Chem. Soc. 2013, 135, 18458.
  • Li, Q.; Wanderling, S.; Paduch, M.; Medovoy, D.; Singharoy, A. ; Mcgreevy, R.; Villalba-Galea, C.; Hulse, R.E.; Roux, B.; Schulten, K.; Kossaikoff, A.; Perozo, E. Structural mechanism of Voltage-dependent Gating in an Isolated Voltage-sensing Domain Nat. Struct. Chem. Biol. 2014, 21, 244.
  • Wickles, S.; Singharoy, A. ; Andreani, J.; Seemayer, S.; Bischoff, L.; Berninghausen, O.; Soeding, J.; Schulten, K.; Van der Sluis, E. O.; Beckmann, R. A Structural Model of the Active Ribosome-bound Membrane Protein Insertase YidCi eLife 2014, 3, e03035 .
  • Mcgreevy, R.*, Singharoy, A.* ; Li, Q.; Zhang, J.; Xu, D.; Perozo, E.; Schulten, K. xMDFF: Molecular dynamics flexible fitting of low-resolution X-Ray structures Acta. Cryst. D 2014, 70, 2344.
  •  Singharoy, A.* ; Venkatakrishnan, B.*; Liu, Y.*; Mayne, C.; Lee, S.; Chen, C.; Zlotnick, A.; Schulten, K.; Flood, A. Macromolecular Crystallography for Synthetic Abiological Molecules: Combining xMDFF and PHENIX for Structure Determination of Cyanostar Macrocycles J. Am. Chem. Soc. 2015, 137, 8810.
  • Singharoy, A.* ; Liu, Y.*; Mayne, C.*; Sengupta, A.; Raghavachari, A.; Schulten, K.; Flood, A. Flexibility Coexists with Shape-Persistence in Cyanostar Macrocycles J. Am. Chem. Soc. 2016, 138, 4843.
  • Sener, M.; Strumpher, J.; Singharoy, A. ; Hunter, N.; Schulten, K. Overall energy conversion efficiency of a photosynthetic vesicle eLife 2016, 5, e09541.
  • Singharoy, A. ; Teo, I.; Mcgreevy, R.; Stone, J.; Jhao, J.; Schulten, K. Molecular dynamics-based refinement and validation with Resolution Exchange MDFF for sub-5 Å cryo-electron microscopy maps eLife 2016, 5, e16105.
  • Bozzi, A.; Bane, L.; Singharoy, A. ; Chipot, C.; Schulten, K.; Gaudet, R. Conserved methionine dictates substrate preference in Nramp-family divalent metal transporters PNAS 2016, 113, 10310.
  • Singharoy, A. ; Barragan, A.; Thangapandian, S.; Tajkhorshid, E.; Schulten, K. Binding site recognition and docking dynamics of a single electron transport protein: revisiting cytochrome c2 J. Am. Chem. Soc. 2016, 138, 12077.
  • 24. Singharoy, A. ; Moradi, M.; Chipot, C.; Schulten, K. Chemomechanical coupling in hexameric protein-protein interfaces harness energy within V- type ATPases J. Am. Chem. Soc 2017, 139, 293.

Courses

Fall 2018
Course NumberCourse Title
CHM 113General Chemistry I
Spring 2018
Course NumberCourse Title
CHM 113General Chemistry I

Honors/Awards

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