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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. in press (2021)    
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.Biomolecular Binding. J. Chem. Theory Comp. in press (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. in press (2021).    
Elucidation of cryptic and allosteric pockets within the SARS-CoV-2 proteaseSztain, T., R. Amaro, J.A. McCammonJ. Chem. Info. Model. in press (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. in press (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 in press (2021) Biorxiv    
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.
Lipoprotein-associated phospholipase A2: A paradigm for allosteric regulation by membranesMouchlis, V.D., D. Hayashi, A.M. Vasquez, J. Cao, J.A. McCammon, E.A. DennisProc. Natl. Acad. Sci. USA in press (2021).    
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. Chem. Theory Simul. in press (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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