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López CA, Zhang X, Aydin F, Shrestha R, Van QN, Stanley CB, Carpenter TS, Nguyen K, Patel LA, Chen D, Burns V, Hengartner NW, Reddy TJE, Bhatia H, Di Natale F, Tran TH, Chan AH, Simanshu DK, Nissley DV, Streitz FH, Stephen AG, Turbyville TJ, Lightstone FC, Gnanakaran S, Ingólfsson HI, Neale C. Asynchronous Reciprocal Coupling of Martini 2.2 Coarse-Grained and CHARMM36 All-Atom Simulations in an Automated Multiscale Framework. J Chem Theory Comput 2022; 18:5025-5045. [PMID: 35866871 DOI: 10.1021/acs.jctc.2c00168] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The appeal of multiscale modeling approaches is predicated on the promise of combinatorial synergy. However, this promise can only be realized when distinct scales are combined with reciprocal consistency. Here, we consider multiscale molecular dynamics (MD) simulations that combine the accuracy and macromolecular flexibility accessible to fixed-charge all-atom (AA) representations with the sampling speed accessible to reductive, coarse-grained (CG) representations. AA-to-CG conversions are relatively straightforward because deterministic routines with unique outcomes are achievable. Conversely, CG-to-AA conversions have many solutions due to a surge in the number of degrees of freedom. While automated tools for biomolecular CG-to-AA transformation exist, we find that one popular option, called Backward, is prone to stochastic failure and the AA models that it does generate frequently have compromised protein structure and incorrect stereochemistry. Although these shortcomings can likely be circumvented by human intervention in isolated instances, automated multiscale coupling requires reliable and robust scale conversion. Here, we detail an extension to Multiscale Machine-learned Modeling Infrastructure (MuMMI), including an improved CG-to-AA conversion tool called sinceCG. This tool is reliable (∼98% weakly correlated repeat success rate), automatable (no unrecoverable hangs), and yields AA models that generally preserve protein secondary structure and maintain correct stereochemistry. We describe how the MuMMI framework identifies CG system configurations of interest, converts them to AA representations, and simulates them at the AA scale while on-the-fly analyses provide feedback to update CG parameters. Application to systems containing the peripheral membrane protein RAS and proximal components of RAF kinase on complex eight-component lipid bilayers with ∼1.5 million atoms is discussed in the context of MuMMI.
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Affiliation(s)
- Cesar A López
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Xiaohua Zhang
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Fikret Aydin
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Rebika Shrestha
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Que N Van
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Christopher B Stanley
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Timothy S Carpenter
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Kien Nguyen
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Lara A Patel
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States.,Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - De Chen
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Violetta Burns
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Nicolas W Hengartner
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Tyler J E Reddy
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Harsh Bhatia
- Computing Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Francesco Di Natale
- Computing Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Timothy H Tran
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Albert H Chan
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Dhirendra K Simanshu
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Dwight V Nissley
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Frederick H Streitz
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Andrew G Stephen
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Thomas J Turbyville
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21701, United States
| | - Felice C Lightstone
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Sandrasegaram Gnanakaran
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Helgi I Ingólfsson
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States
| | - Chris Neale
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
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Jewel Y, Van Dinh Q, Liu J, Dutta P. Substrate-dependent transport mechanism in AcrB of multidrug resistant bacteria. Proteins 2020; 88:853-864. [PMID: 31998988 DOI: 10.1002/prot.25877] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 01/07/2020] [Accepted: 01/25/2020] [Indexed: 02/03/2023]
Abstract
The multidrug resistance (MDR) system effectively expels antibiotics out of bacteria causing serious issues during bacterial infection. In addition to drug, indole, a common metabolic waste of bacteria, is expelled by MDR system of gram-negative bacteria for their survival. Experimental results suggest that AcrB, one of the key components of MDR system, undergoes large scale conformation changes during the pumping due to proton-motive process. However, due to extremely short time scale, it is difficult to observe (experimentally) those changes in the AcrB, which might facilitate the pumping process. Molecular simulations can shed light to understand the conformational changes for transport of indole in AcrB. Examination of conformational changes using all-atom simulation is, however, impractical. Here, we develop a hybrid coarse-grained force field to study the conformational changes of AcrB in presence of indole in the porter domain of monomer II. Using the coarse-grained force field, we investigated the conformational changes of AcrB for a number of model systems considering the effect of protonation in aspartic acid (Asp) residues Asp407 and Asp408 in the transmembrane domain of monomer II. Our results show that in the presence of indole, protonation of Asp408 or Asp407 residue causes conformational changes from binding state to extrusion state in monomer II, while remaining two monomers (I and III) approach access state in AcrB protein. We also observed that all three AcrB monomers prefer to go back to access state in the absence of indole. Steered molecular dynamics simulations were performed to demonstrate the feasibility of indole transport mechanism for protonated systems. Identification of indole transport pathway through AcrB can be very helpful in understanding the drug efflux mechanism used by the MDR bacteria.
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Affiliation(s)
- Yead Jewel
- School of Mechanical and Materials Engineering, Washington State University, Pullman, Washington
| | - Quyen Van Dinh
- School of Mechanical and Materials Engineering, Washington State University, Pullman, Washington
| | - Jin Liu
- School of Mechanical and Materials Engineering, Washington State University, Pullman, Washington
| | - Prashanta Dutta
- School of Mechanical and Materials Engineering, Washington State University, Pullman, Washington
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Selvam B, Mittal S, Shukla D. Free Energy Landscape of the Complete Transport Cycle in a Key Bacterial Transporter. ACS CENTRAL SCIENCE 2018; 4:1146-1154. [PMID: 30276247 PMCID: PMC6161048 DOI: 10.1021/acscentsci.8b00330] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Indexed: 05/21/2023]
Abstract
PepTSo is a proton-coupled bacterial symporter, from the major facilitator superfamily (MFS), which transports di-/tripeptide molecules. The recently obtained crystal structure of PepTSo provides an unprecedented opportunity to gain an understanding of functional insights of the substrate transport mechanism. Binding of the proton and peptide molecule induces conformational changes into occluded (OC) and outward-facing (OF) states, which we are able to characterize using molecular dynamics (MD) simulations. The structural knowledge of the OC and OF state is important to fully understand the major energy barrier associated with the transport cycle. In order to gain functional insight into the interstate dynamics, we performed extensive all atom MD simulations. The Markov state model was constructed to identify the free energy barriers between the states, and kinetic information on intermediate pathways was obtained using the transition pathway theory (TPT). TPT shows that the OF state is obtained by the movement of TM1 and TM7 at the extracellular side approximately 12-16 Å away from each other, and the inward movement of TM4 and TM10 at the intracellular halves to 3-4 Å characterizes the OC state. Helix distance distributions obtained from MD simulations were compared with experimental double electron-electron resonance spectroscopy and were found to be in excellent agreement with previous studies. We also predicted the optimal positions for placement of methane thiosulfonate spin label probes to capture the slowest protein dynamics. Our finding sheds light on the conformational cycle of this key membrane transporter and the functional relationships between the multiple intermediate states.
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Affiliation(s)
- Balaji Selvam
- Department of Chemical and Biomolecular Engineering, Center for Biophysics and Quantitative
Biology, and Department
of Plant Biology, University of Illinois
at Urbana-Champaign, Urbana, Illinois, United States
| | - Shriyaa Mittal
- Department of Chemical and Biomolecular Engineering, Center for Biophysics and Quantitative
Biology, and Department
of Plant Biology, University of Illinois
at Urbana-Champaign, Urbana, Illinois, United States
| | - Diwakar Shukla
- Department of Chemical and Biomolecular Engineering, Center for Biophysics and Quantitative
Biology, and Department
of Plant Biology, University of Illinois
at Urbana-Champaign, Urbana, Illinois, United States
- E-mail:
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Jewel Y, Dutta P, Liu J. Exploration of conformational changes in lactose permease upon sugar binding and proton transfer through coarse-grained simulations. Proteins 2017. [PMID: 28639287 DOI: 10.1002/prot.25340] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Escherichia coli lactose permease (LacY) actively transports lactose and other galactosides across cell membranes through lactose/H+ symport process. Lactose/H+ symport is a highly complex process that involves sugar translocation, H+ transfer, and large-scale protein conformational changes. The complete picture of lactose/H+ symport is largely unclear due to the complexity and multiscale nature of the process. In this work, we develop the force field for sugar molecules compatible with PACE, a hybrid and coarse-grained force field that couples the united-atom protein models with the coarse-grained MARTINI water/lipid. After validation, we implement the new force field to investigate the binding of a β-d-galactopyranosyl-1-thio- β-d-galactopyranoside (TDG) molecule to a wild-type LacY. Results show that the local interactions between TDG and LacY at the binding pocket are consistent with the X-ray experiment. Transitions from inward-facing to outward-facing conformations upon TDG binding and protonation of Glu269 have been achieved from ∼5.5 µs simulations. Both the opening of the periplasmic side and closure of the cytoplasmic side of LacY are consistent with double electron-electron resonance and thiol cross-linking experiments. Our analysis suggests that the conformational changes of LacY are a cumulative consequence of interdomain H-bonds breaking at the periplasmic side, interdomain salt-bridge formation at the cytoplasmic side, and the TDG orientational changes during the transition.
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Affiliation(s)
- Yead Jewel
- School of Mechanical and Materials Engineering, Washington State University, Pullman, Washington, 99164
| | - Prashanta Dutta
- School of Mechanical and Materials Engineering, Washington State University, Pullman, Washington, 99164
| | - Jin Liu
- School of Mechanical and Materials Engineering, Washington State University, Pullman, Washington, 99164
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