Forthcoming
Roh SH, Shekhar M, Pintilie G, Chipot C, Wilkens S, Singharoy A, Chiu W. CryoEM and MD Infer Water-Mediated Proton Transport and Autoinhibition Mechanisms of Vo Complex. Science Advances. Forthcoming.
Dashti A, Shekhar M, Ben Hail B, Mashayekhi G, Schwander P, des Georges A, Frank J, Singharoy A, Ourmazd A. Functional Pathways of Biomolecules Retrieved from Single-particle Snapshots. Nature Communications. Forthcoming.
2020
Phillips et al JC. Scalable molecular dynamics on CPU and GPU architectures with NAMD. The Journal of Chemical Physics [Internet]. 2020;153 :044130 . Publisher's Version
Vant JW, Sarkar D, Fiorin G, Skeel R, Vermaas JV, Singharoy A. Data-guided Multi-Map variables for ensemble refinement of molecular movies. biorxiv [Internet]. 2020. Publisher's Version
Vant JW, Sarkar D, Gupta C, Shekhar MS, Mittal S, Singharoy A. Molecular Dynamics Flexible Fitting: All You Want to Know About Resolution Exchange. In: Methods in Molecular Biology. Vol. 2165. ; 2020. pp. 301-315. Publisher's Version
Khaniya U, Gupta C, Cai X, Mao J, Kaur D, Zhang Y, Singharoy A, Gunner MR. Hydrogen bond network analysis reveals the pathway for the proton transfer in the E-channel of T. thermophilus Complex I. BBA Bioenergetics. 2020;1861 (10) :148240.
Mittal S, Vant JW, Shekhar M, Rowley C, Singharoy A. Flexible fitting of small-molecules into electron microscopy maps using molecular dynamics simulations with Neural Network Potentials. Journal of Chemical Information and Modeling. 2020;60 :2591.
Gupta C, Khaniya U, Chan CK, Dehez F, Dehez F, Gunner MR, Sazanov L, Chipot C, Singharoy A. Charge Transfer and Chemo-Mechanical Coupling in Respiratory Complex I. Journal of the American Chemical Society. 2020;142 :9220-9230.
Zook J, Shekhar M, Hansen D, Conrad C, Grant T, Gupta C, White T, Barty A, Basu S, Zhao Y. XFEL and NMR structures of Francisella lipoprotein reveal conformational space of drug target against tularemia. Structure. 2020;28 :1-8.
2019
Singharoy A, Maffeo C, Delgado-Magnero KH, Swainsbury DJK, Sener M, Kleinekathofer U, Vant JW, Nguyen J, Hitchcock A, Isralewitz B, et al. Atoms to Phenotypes: Molecular Design Principles of Cellular Energy Metabolism. Cell. 2019;179 (5) :1098-1111.e23.Abstract
We report a 100-million atom-scale model of an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium, that reveals the cascade of energy conversion steps culminating in the generation of ATP from sunlight. Molecular dynamics simulations of this vesicle elucidate how the integral membrane complexes influence local curvature to tune photoexcitation of pigments. Brownian dynamics of small molecules within the chromatophore probe the mechanisms of directional charge transport under various pH and salinity conditions. Reproducing phenotypic properties from atomistic details, a kinetic model evinces that low-light adaptations of the bacterium emerge as a spontaneous outcome of optimizing the balance between the chromatophore’s structural integrity and robust energy conversion. Parallels are drawn with the more universal mitochondrial bioenergetic machinery, from whence molecular-scale insights into the mechanism of cellular aging are inferred. Together, our integrative method and spectroscopic experiments pave the way to first-principles modeling of whole living cells.
2018
Wang Y, Shekhar M, Thifault D, Williams CJ, Mcgreevy R, Richardson J, Tajkhorshid E, Singharoy A. Constructing Atomic Structural Models into Cryo-EM densities using Molecular Dynamics - Pros and Cons. Journal of Structural Biology. 2018;Accepted.Abstract

Accurate structure determination from electron density maps at 3-5 Angstrom resolution necessitates a balance between extensive global and local sampling of atomistic models, yet with stereochemical correctness of backbone and sidechain geometries. Molecular Dynamics Flexible Fitting (MDFF), particularly through a resolution-exchange scheme, ReMDFF, provides a robust way of achieving this balance for hybrid structure determination. Employing two high-resolution density maps, namely that of beta-galactosidase at 3.2 Angstrom and TRPV1 at 3.4 Angstrom, we showcase the quality of ReMDFF-generated models, comparing them against ones submitted by independent research groups for the 2015-2016 Cryo-EM Model Challenge. This comparison offers a clear evaluation of ReMDFF's strengths and shortcomings, and those of data-guided real-space refinements in general. ReMDFF results scored highly on the various metric for judging the quality-of-fit and quality-of-model. However, some systematic discrepancies are also noted employing a Molprobity analysis, that are reproducible across multiple competition entries. A space of key refinement
parameters is explored within ReMDFF to observe their impact within the final model. Choice of force eld parameters and initial model seem to have the most significant impact on ReMDFF model-quality. To this end, very recently developed CHARMM36m force field parameters provide now more rened ReMDFF models than the ones originally submitted to the Cryo-EM challenge. Finally, a set of good-practices is prescribed for the community to benet from the MDFF developments.

Benson CR, Maffeo C, Fatila EM, Liu Y, Sheetz EG, Aksimentiev A, Singharoy A, Flood AH. Inchworm movement of two rings switching onto a thread by biased Brownian diffusion represent a three-body problem. Proceedings of the National Academy of Sciences [Internet]. 2018;Accepted (Special volume commemorating 2016 Nobel Prize in Chemistry). Publisher's VersionAbstract
The coordinated motion of many individual components underpins the operation of all machines. However, despite generations of experience in engineering, understanding the motion of three or more coupled components remains a challenge, known since the time of Newton as the “three-body problem.” Here, we describe, quantify, and simulate a molecular three-body problem of threading two molecular rings onto a linear molecular thread. Specifically, we use voltage-triggered reduction of a tetrazine-based thread to capture two cyanostar macrocycles and form a [3]pseudorotaxane product. As a consequence of the noncovalent coupling between the cyanostar rings, we find the threading occurs by an unexpected and rare inchworm-like motion where one ring follows the other. The mechanism was derived from controls, analysis of cyclic voltammetry (CV) traces, and Brownian dynamics simulations. CVs from two noncovalently interacting rings match that of two covalently linked rings designed to thread via the inchworm pathway, and they deviate considerably from the CV of a macrocycle designed to thread via a stepwise pathway. Time-dependent electrochemistry provides estimates of rate constants for threading. Experimentally derived parameters (energy wells, barriers, diffusion coefficients) helped determine likely pathways of motion with rate-kinetics and Brownian dynamics simulations. Simulations verified intercomponent coupling could be separated into ring–thread interactions for kinetics, and ring–ring interactions for thermodynamics to reduce the three-body problem to a two-body one. Our findings provide a basis for high-throughput design of molecular machinery with multiple components undergoing coupled motion.
2017
Singharoy A, Chipot C. Methodology for the simulation of molecular motors at different scales. The Journal of Physical Chemistry B [Internet]. 2017;121 (15) :3502-3514. Publisher's VersionAbstract
Millisecond-scale conformational transitions represent a seminal challenge for traditional molecular dynamics simulations, even with the help of high-end supercomputer architectures. Such events are particularly relevant to the study of molecular motors—proteins or abiological constructs that convert chemical energy into mechanical work. Here, we present a hybrid-simulation scheme combining an array of methods including elastic network models, transition path sampling, and advanced free-energy methods, possibly in conjunction with generalized-ensemble schemes to deliver a viable option for capturing the millisecond-scale motor steps of biological motors. The methodology is already implemented in large measure in popular molecular dynamics programs, and it can leverage the massively parallel capabilities of petascale computers. The applicability of the hybrid method is demonstrated with two examples, namely cyclodextrin-based motors and V-type ATPases.
Singharoy A, Chipot C, Moradi M, Schulten K. Chemomechanical coupling in hexameric protein–protein interfaces harnesses energy within V-Type ATPases. Journal of the American Chemical Society [Internet]. 2017;139 (1) :293-310. Publisher's VersionAbstract
ATP synthase is the most prominent bioenergetic macromolecular motor in all life forms, utilizing the proton gradient across the cell membrane to fuel the synthesis of ATP. Notwithstanding the wealth of available biochemical and structural information inferred from years of experiments, the precise molecular mechanism whereby vacuolar (V-type) ATP synthase fulfills its biological function remains largely fragmentary. Recently, crystallographers provided the first high-resolution view of ATP activity in Enterococcus hirae V1-ATPase. Employing a combination of transition-path sampling and high-performance free-energy methods, the sequence of conformational transitions involved in a functional cycle accompanying ATP hydrolysis has been investigated in unprecedented detail over an aggregate simulation time of 65 μs. Our simulated pathways reveal that the chemical energy produced by ATP hydrolysis is harnessed via the concerted motion of the protein–protein interfaces in the V1-ring, and is nearly entirely consumed in the rotation of the central stalk. Surprisingly, in an ATPase devoid of a central stalk, the interfaces of this ring are perfectly designed for inducing ATP hydrolysis. However, in a complete V1-ATPase, the mechanical property of the central stalk is a key determinant of the rate of ATP turnover. The simulations further unveil a sequence of events, whereby unbinding of the hydrolysis product (ADP + Pi) is followed by ATP uptake, which, in turn, leads to the torque generation step and rotation of the center stalk. Molecular trajectories also bring to light multiple intermediates, two of which have been isolated in independent crystallography experiments.
Gaudet R, Bozzi AT, Zimanyi CM, Bane LB, Singharoy A. Panning for precious metals: mechanics of a transition metal transporter. Foundations of Crystallography. 2017;70 :C149.Abstract
The Nramp (natural resistance associated macrophage protein) family, found in all kingdoms of life, is an important class of transporters for transition metal homeostasis. Two mammalian Nramp paralogs are required for the dietary uptake and endosomal recycling of non-heme iron, as well as in the innate immune response to intracellular pathogens. We have determined structures of a bacterial Nramp homolog. Using these structures, and other results from computational approaches and biochemical and cell-based functional assays, we arrive at a working model for the conformational change mechanism and metal selectivity of Nramps [1-2]. Our results explain how Nramps specifically discriminate against the highly abundant divalent metals calcium and magnesium, and yet at the same time remain promiscuous in their ability to transport other divalent metals including the toxic metal cadmium. We also describe the molecular mechanism for disease-causing missense mutations in mammalian Nramps.
Qi Y, Lee J, Singharoy A, Mcgreevy R, Schulten K, Im W. Charmm-gui mdff/xmdff utilizer for molecular dynamics flexible fitting simulations in various environments. The Journal of Physical Chemistry B [Internet]. 2017;121 (15) :3718-3723. Publisher's VersionAbstract
X-ray crystallography and cryo-electron microscopy are two popular methods for the structure determination of biological molecules. Atomic structures are derived through the fitting and refinement of an initial model into electron density maps constructed by both experiments. Two computational approaches, MDFF and xMDFF, have been developed to facilitate this process by integrating the experimental data with molecular dynamics simulation. However, the setup of an MDFF/xMDFF simulation requires knowledge of both experimental and computational methods, which is not straightforward for nonexpert users. In addition, sometimes it is desirable to include realistic environments, such as explicit solvent and lipid bilayers during the simulation, which poses another challenge even for expert users. To alleviate these difficulties, we have developed MDFF/xMDFF Utilizer in CHARMM-GUI that helps users to set up an MDFF/xMDFF simulation. The capability of MDFF/xMDFF Utilizer is greatly enhanced by integration with other CHARMM-GUI modules, including protein structure manipulation, a diverse set of lipid types, and all-atom CHARMM and coarse-grained PACE force fields. With this integration, various simulation environments are available for MDFF Utilizer (vacuum, implicit/explicit solvent, and bilayers) and xMDFF Utilizer (vacuum and solution). In this work, three examples are shown to demonstrate the usage of MDFF/xMDFF Utilizer.
2016
Singharoy A, Liu Y, Mayne CG, Sengupta A, Raghavachari K, Schulten K, Flood AH. Flexibility coexists with shape-persistence in cyanostar macrocycles. Journal of the American Chemical Society [Internet]. 2016;138 (14) :4843-4851. Publisher's VersionAbstract
Shape-persistent macrocycles are attractive functional targets for synthesis, molecular recognition, and hierarchical self-assembly. Such macrocycles are non-collapsible and geometrically well-defined, and they are traditionally characterized by having repeat units and low conformational flexibility. Here, we find it necessary to refine these ideas in the face of a highly flexible yet shape-persistent macrocycles. A molecule is shape-persistent if it has a small change in shape when perturbed by external stimuli (e.g., heat, light, and redox chemistry). In support of this idea we provide the first examination of the relationships between a macrocycle’s shape persistence, its conformational space, and the resulting functions. We do this with a star-shaped macrocycle called cyanostar that is flexible as well as being shape-persistent. We employed molecular dynamics (MD), density functional theory (DFT), and NMR experiments. Considering a thermal bath as a stimulus we found a single macrocycle has 332 accessible conformers with olefins undergoing rapid interconversion by up-down and in-out motions on short time scales (0.2 ns). These many interconverting conformations classify single cyanostars as flexible. To determine and confirm that cyanostars are shape-persistent, we show that it has a high 87% shape similarity across these conformations. To further test the idea, we use the binding of diglyme to the single macrocycle as guest-induced stimulation. This guest has almost no effect on the conformational space. However, formation of a 2:1 sandwich complex involving two macrocycles enhances rigidity and dramatically shifts the conformer distribution towards perfect bowls. Overall, the present study expands the scope of shape-persistent macrocycles to include flexible macrocycles if and only if their conformers have similar shapes.
Mcgreevy R, Teo I, Singharoy A, Schulten K. Advances in the molecular dynamics flexible fitting method for cryo-EM modeling. Methods [Internet]. 2016;Methods :50-60. Publisher's VersionAbstract
Molecular Dynamics Flexible Fitting (MDFF) is an established technique for fitting all-atom structures of molecules into corresponding cryo-electron microscopy (cryo-EM) densities. The practical application of MDFF is simple but requires a user to be aware of and take measures against a variety of possible challenges presented by each individual case. Some of these challenges arise from the complexity of a molecular structure or the limited quality of available structural models and densities to be interpreted, while others stem from the intricacies of MDFF itself. The current article serves as an overview of the strategies that have been developed since MDFF’s inception to overcome common challenges and successfully perform MDFF simulations.
Goh BC, Hadden JA, Bernardi RC, Singharoy A, Mcgreevy R, Rudack T, Cassidy KC, Schulten K. Computational methodologies for real-space structural refinement of large macromolecular complexes. Annual review of biophysics [Internet]. 2016;45 :253-278. Publisher's VersionAbstract
The rise of the computer as a powerful tool for model building and refinement has revolutionized the field of structure determination for large biomolecular systems. Despite the wide availability of robust experimental methods capable of resolving structural details across a range of spatiotemporal resolutions, computational hybrid methods have the unique ability to integrate the diverse data from multimodal techniques such as X-ray crystallography and electron microscopy into consistent, fully atomistic structures. Here, commonly employed strategies for computational real-space structural refinement are reviewed, and their specific applications are illustrated for several large macromolecular complexes: ribosome, virus capsids, chemosensory array, and photosynthetic chromatophore. The increasingly important role of computational methods in large-scale structural refinement, along with current and future challenges, is discussed.
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 [Internet]. 2016;5 :e16105. Publisher's VersionAbstract
Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 A˚ cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 A˚ demonstrated with the accurate modeling of b-galactosidase and TRPV1 proteins at 3.2 A˚ and 3.4 A˚ resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services

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