Abhishek Singharoy

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 Å 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 it’s 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.