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Computational Research in Molecular Chemistry
Decoding allosteric regulation by the acyl carrier proteinSztain, T., T.G. Bartholow, D.J. Lee, L. Casalino, A. Mitchell, J. Wang, M.A. Young, J. A. McCammon, M.D. Burkart.Proc. Natl. Acad. Sci, April 20; 118 (16) e2025597118 (2021)    
Enzymes in multistep metabolic pathways utilize an array of regulatory mechanisms to maintain a delicate homeostasis [K. Magnuson, S. Jackowski, C. O. Rock, J. E. Cronan, Jr, Microbiol. Rev. 57, 522-542 (1993)]. Carrier proteins in particular play an essential role in shuttling substrates between appropriate enzymes in metabolic pathways. Although hypothesized [E. Płoskoń et al., Chem. Biol. 17, 776-785 (2010)], allosteric regulation of substrate delivery has never before been demonstrated for any acyl carrier protein (ACP)-dependent pathway. Studying these mechanisms has remained challenging due to the transient and dynamic nature of protein-protein interactions, the vast diversity of substrates, and substrate instability [K. Finzel, D. J. Lee, M. D. Burkart, ChemBioChem 16, 528-547 (2015)]. Here we demonstrate a unique communication mechanism between the ACP and partner enzymes using solution NMR spectroscopy and molecular dynamics to elucidate allostery that is dependent on fatty acid chain length. We demonstrate that partner enzymes can allosterically distinguish between chain lengths via protein-protein interactions as structural features of substrate sequestration are translated from within the ACP four-helical bundle to the protein surface, without the need for stochastic chain flipping. These results illuminate details of cargo communication by the ACP that can serve as a foundation for engineering carrier protein-dependent pathways for specific, desired products.
Coupling Monte Carlo, Variational Implicit Solvation, and Binary Level-Set for Simulations of Biomolecular BindingZhang, Z., C.G. Ricci, C. Fan, L.T. Cheng, B. Li, J.A. McCammon.J. Chem. Theory Comput. 17, 4, 2465–2478 (2021)    
We develop a hybrid approach that combines the Monte Carlo (MC) method, a variational implicit-solvent model (VISM), and a binary level-set method for the simulation of biomolecular binding in an aqueous solvent. The solvation free energy for the biomolecular complex is estimated by minimizing the VISM free-energy functional of all possible solute–solvent interfaces that are used as dielectric boundaries. This functional consists of the solute volumetric, solute–solvent interfacial, solute–solvent van der Waals interaction, and electrostatic free energy. A technique of shifting the dielectric boundary is used to accurately predict the electrostatic part of the solvation free energy. Minimizing such a functional in each MC move is made possible by our new and fast binary level-set method. This method is based on the approximation of surface area by the convolution of an indicator function with a compactly supported kernel and is implemented by simple flips of numerical grid cells locally around the solute–solvent interface. We apply our approach to the p53-MDM2 system for which the two molecules are approximated by rigid bodies. Our efficient approach captures some of the poses before the final bound state. All-atom molecular dynamics simulations with most of such poses quickly reach the final bound state. Our work is a new step toward realistic simulations of biomolecular interactions. With further improvement of coarse graining and MC sampling, and combined with other models, our hybrid approach can be used to study the free-energy landscape and kinetic pathways of ligand binding to proteins.
The Myosin II Coiled-Coil Domain Atomic Structure in its Native EnvironmentRahmani, H., W. Ma, Z. Hu, N. Daneshparvar, D.W. Taylor, J.A. McCammon, T.C. Irving, R.J. Edwards, K.A. Taylor.Proc. Natl. Acad. Sci. Apr 6; 118 (14) e2024151118 (2021)    
The atomic structure of the complete myosin tail within thick filaments isolated from Lethocerus indicus flight muscle is described and compared to crystal structures of recombinant, human cardiac myosin tail segments. Overall, the agreement is good with three exceptions: the proximal S2, in which the filament has heads attached but the crystal structure doesn't, and skip regions 2 and 4. At the head-tail junction, the tail α-helices are asymmetrically structured encompassing well-defined unfolding of 12 residues for one myosin tail, ∼4 residues of the other, and different degrees of α-helix unwinding for both tail α-helices, thereby providing an atomic resolution description of coiled-coil "uncoiling" at the head-tail junction. Asymmetry is observed in the nonhelical C termini; one C-terminal segment is intercalated between ribbons of myosin tails, the other apparently terminating at Skip 4 of another myosin tail. Between skip residues, crystal and filament structures agree well. Skips 1 and 3 also agree well and show the expected α-helix unwinding and coiled-coil untwisting in response to skip residue insertion. Skips 2 and 4 are different. Skip 2 is accommodated in an unusual manner through an increase in α-helix radius and corresponding reduction in rise/residue. Skip 4 remains helical in one chain, with the other chain unfolded, apparently influenced by the acidic myosin C terminus. The atomic model may shed some light on thick filament mechanosensing and is a step in understanding the complex roles that thick filaments of all species undergo during muscle contraction.
Elucidation of cryptic and allosteric pockets within the SARS-CoV-2 proteaseSztain, T., R. Amaro, J.A. McCammonJ. Chem. Inf. Model, 61, 7, 3495–3501 (2021)    
The SARS-CoV-2 pandemic has rapidly spread across the globe, posing an urgent health concern. Many quests to computationally identify treatments against the virus rely on in silico small molecule docking to experimentally determined structures of viral proteins. One limit to these approaches is that protein dynamics are often unaccounted for, leading to overlooking transient, druggable conformational states. Using Gaussian accelerated molecular dynamics to enhance sampling of conformational space, we identified cryptic pockets within the SARS-CoV-2 main protease, including some within regions far from the active site and assed their druggability. These pockets can aid in virtual screening efforts to identify a protease inhibitor for the treatment of COVID-19.
Characterizing protein kinase A (PKA) subunits as macromolecular regulators of PKA RIα liquid-liquid phase separationAhn, S.H., S. Qin, J.Z. Zhang, J.A. McCammon, J. Zhang, H.X. ZhouJ. Chem. Phys. 154, 221101 (2021)    
A glycan gate controls opening of the SARS-CoV-2 spike proteinSztain, T., S.H. Ahn, A.T. Bogetti, L. Casalino, J.A. Goldsmith, E. Seitz, R.S. McCool, F.L. Kearns, F. Acosta-Reyes, S. Maji, G. Mashayekhi, J.A. McCammon, A. Ourmazd, J. Frank, J.S. McLellan, L.T. Chong, R.E. AmaroNature Chemistry volume 13, pages 963–968 (2021)    
SARS-CoV-2 infection is controlled by the opening of the spike protein receptor binding domain (RBD), which transitions from a glycan-shielded “down” to an exposed “up” state in order to bind the human ACE2 receptor and infect cells. While snapshots of the “up” and “down” states have been obtained by cryoEM and cryoET, details of the RBD opening transition evade experimental characterization. Here, over 130 μs of weighted ensemble (WE) simulations of the fully glycosylated spike ectodomain allow us to characterize more than 300 continuous, kinetically unbiased RBD opening pathways. Together with ManifoldEM analysis of cryo-EM data and biolayer interferometry experiments, we reveal a gating role for the N-glycan at position N343, which facilitates RBD opening. Residues D405, R408, and D427 also participate. The atomic-level characterization of the glycosylated spike activation mechanism provided herein achieves a new high-water mark for ensemble pathway simulations and offers a foundation for understanding the fundamental mechanisms of SARS-CoV-2 viral entry and infection.
Data for molecular dynamics simulations of Escherichia coli cytochrome bd oxidase with the Amber force fieldAhn, S.H., C. Seitz, V.W.D. Cruzeiro, J.A. McCammon; A.W. GoetzData in Brief (Elsevier) 38, 107401 (2021).    
Cytochrome bd-type quinol oxidase is an important metalloenzyme that allows many bacteria to survive in low oxygen conditions. Since bd oxidase is found in many prokaryotes but not in eukaryotes, it has emerged as a promising bacterial drug target. Examples of organisms containing bd oxidases include the Mycobacterium tuberculosis (Mtb) bacterium that causes tuberculosis (TB) in humans, the Vibrio cholerae bacterium that causes cholera, the Pseudomonas aeruginosa bacterium that contributes to antibiotic resistance and sepsis, and the Campylobacter jejuni bacterium that causes food poisoning. Escherichia coli (E. coli) is another organism exhibiting the cytochrome bd oxidase. Since it has the highest sequence identity to Mtb (36%) and we are ultimately interested in finding drug targets for TB, we have built parameters for the E. coli bd oxidase (Protein Data Bank ID number: 6RKO) that are compatible with the all-atom Amber ff14SB force field for molecular dynamics (MD) simulations. Specifically, we built parameters for the three heme cofactors present in all species of bacterial cytochrome bd-type oxidases (heme b558, heme b595, and heme d) along with their axial ligands. This data report includes the parameter and library files that can be used with Amber’s LEaP program to generate input files for MD simulations using the Amber software package. We also provide the PDB data files of the initial model both by itself and solvated with TIP3P water molecules and counterions.
Gaussian accelerated molecular dynamics with the weighted ensemble method: a hybrid method improves thermodynamic and kinetic samplingAhn, S., A.A. Ojha, R.E. Amaro, J.A. McCammonJ. Che. Theory Comput. 17, 12, 7938-7951 (2021)    
Gaussian-accelerated molecular dynamics (GaMD) is a well-established enhanced sampling method for molecular dynamics simulations that effectively samples the potential energy landscape of the system by adding a boost potential, which smoothens the surface and lowers the energy barriers between states. GaMD is unable to give time-dependent properties such as kinetics directly. On the other hand, the weighted ensemble (WE) method can efficiently sample transitions between states with its many weighted trajectories, which directly yield rates and pathways. However, convergence to equilibrium conditions remains a challenge for the WE method. Hence, we have developed a hybrid method that combines the two methods, wherein GaMD is first used to sample the potential energy landscape of the system and WE is subsequently used to further sample the potential energy landscape and kinetic properties of interest. We show that the hybrid method can sample both thermodynamic and kinetic properties more accurately and quickly compared to using either method alone.
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