Building a macro-mixing dual‑basin Gō model using the Multistate Bennett Acceptance Ratio

Shinobu, Ai; Kobayashi, Chigusa; Matsunaga, Yasuhiro; Sugita, Yuji

doi:10.2142/biophysico.16.0_310

Cited by 4 publications

(19 citation statements)

References 71 publications

(78 reference statements)

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“…Initial MD simulation time was set to 0.5 μs. t converge was set to 8 μs and refers to a sampling time sufficient for obtaining a converged energy landscape (this time was set following our previous work 62 in which convergence was ensured for a system of similar size). t short was set to 2 μs (one-fourth the length of t converge ), and simulations were elongated by a factor of 2 in stages C → G and F → A in Figure 2.…”

Section: Resultsmentioning

confidence: 99%

“…Out of the 2035 pairs of protein motions currently in the database, two-domain movements were further classified according to the pattern of contact changes during the movement. 119 Examination of the database reveals that 75% of the target systems can be treated using our original DB potential 62 (there is a difference in the contact lists of the two reference structures). Among those targets, there are also proteins with three or more domains, which require the newly introduced MBGo ̅ potential to describe intermediate states.…”

Section: Resultsmentioning

confidence: 99%

“…Three single-basin potentials are mixed exponentially to form the triple-basin potential. The macro-mixing exponential mixing scheme 43,59 is used here, as done in our previous work: 62 k T…”

Section: Theory and Methodsmentioning

confidence: 99%

“…The procedure is similar to the one used in our previous work. 62 At each round, we perform a series of simulations with different sets of parameters and initiate simulations from both the Open and the Closed forms. At each round, one parameter is varied across the set of simulations while the other two are held fixed.…”

Section: Theory and Methodsmentioning

confidence: 99%

“…The details of the method are described in the Supporting Information (Eqs. S2−S4 and text) as well as in the original work 63 and in our previous work 62 in which we applied it for tuning mixing parameters for DB potentials.…”

Section: Theory and Methodsmentioning

confidence: 99%

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Coarse-Grained Modeling of Multiple Pathways in Conformational Transitions of Multi-Domain Proteins

Shinobu

Kobayashi

Matsunaga

et al. 2021

J. Chem. Inf. Model.

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Large-scale conformational transitions in multi-domain proteins are often essential for their functions. To investigate the transitions, it is necessary to explore multiple potential pathways, which involve different intermediate structures. Here, we present a multi-basin (MB) coarse-grained (CG) structure-based Go̅ model for describing transitions in proteins with more than two moving domains. This model is an extension of our dual-basin Go̅ model in which system-dependent parameters are determined systematically using the multistate Bennett acceptance ratio method. In the MB Go̅ model for multi-domain proteins, we assume that intermediate structures may have partial inter-domain native contacts. This approach allows us to search multiple transition pathways that involve distinct intermediate structures using the CG molecular dynamics (MD) simulations. We apply this scheme to an enzyme, adenylate kinase (AdK), which has three major domains and can move along two different pathways. Using the optimized mixing parameters for each pathway, AdK shows frequent transitions between the Open, Closed, and the intermediate basins and samples a wide variety of conformations within each basin. The explored multiple transition pathways could be compared with experimental data and examined in more detail by atomistic MD simulations.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Theory and Methodsmentioning

confidence: 99%

Section: Theory and Methodsmentioning

confidence: 99%

Section: Theory and Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Coarse-Grained Modeling of Multiple Pathways in Conformational Transitions of Multi-Domain Proteins

Shinobu

Kobayashi

Matsunaga

et al. 2021

J. Chem. Inf. Model.

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Use of multistate Bennett acceptance ratio method for free-energy calculations from enhanced sampling and free-energy perturbation

et al. 2022

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Multistate Bennett acceptance ratio (MBAR) works as a method to analyze molecular dynamics (MD) simulation data after the simulations have been finished. It is widely used to estimate free-energy changes between different states and averaged properties at the states of interest. MBAR allows us to treat a wide range of states from those at different temperature/pressure to those with different model parameters. Due to the broad applicability, the MBAR equations are rather difficult to apply for free-energy calculations using different types of MD simulations including enhanced conformational sampling methods and free-energy perturbation. In this review, we first summarize the basic theory of the MBAR equations and categorize the representative usages into the following four: (i) perturbation, (ii) scaling, (iii) accumulation, and (iv) full potential energy. For each, we explain how to prepare input data using MD simulation trajectories for solving the MBAR equations. MBAR is also useful to estimate reliable free-energy differences using MD trajectories based on a semi-empirical quantum mechanics/molecular mechanics (QM/MM) model and ab initio QM/MM energy calculations on the MD snapshots. We also explain how to use the MBAR software in the GENESIS package, which we call mbar_analysis, for the four representative cases. The proposed estimations of free-energy changes and thermodynamic averages are effective and useful for various biomolecular systems.

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Unraveling the Coupling between Conformational Changes and Ligand Binding in Ribose Binding Protein Using Multiscale Molecular Dynamics and Free-Energy Calculations

et al. 2021

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Conformational changes of proteins upon ligand binding are usually explained in terms of several mechanisms including the induced fit, conformational selection, or their mixtures. Due to the slow time scales, conventional molecular dynamics (cMD) simulations based on the atomistic models cannot easily simulate the open-to-closed conformational transition in proteins. In our previous study, we have developed an enhanced sampling scheme (generalized replica exchange with solute tempering selected surface charged residues: gREST_SSCR) for multidomain proteins and applied it to ligand-mediated conformational changes in the G134R mutant of ribose-binding protein (RBPG134R) in solution. The free-energy landscape (FEL) of RBPG134R in the presence of a ribose at the binding site included the open and closed states and two intermediates, open-like and closed-like forms. Only the open and open-like forms existed in the FEL without a ribose. In the current study, the coupling between the conformational changes and ligand binding is further investigated using coarse-grained MD, multiple atomistic cMD, and free-energy calculations. The ribose is easily dissociated from the binding site of wild-type RBP and RBPG134R in the cMD simulations starting from the open and open-like forms. In contrast, it is stable at the binding site in the simulations from the closed and closed-like forms. The free-energy calculations provide the binding affinities of different structures, supporting the results of cMD simulations. Importantly, cMD simulations from the closed-like structures reveal transitions toward the closed one in the presence of a bound ribose. On the basis of the computational results, we propose a molecular mechanism in which conformational selection and induced fit happen in the first and second halves of the open-to-closed transition in RBP, respectively.

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Building a macro-mixing dual‑basin Gō model using the Multistate Bennett Acceptance Ratio

Cited by 4 publications

References 71 publications

Coarse-Grained Modeling of Multiple Pathways in Conformational Transitions of Multi-Domain Proteins

Coarse-Grained Modeling of Multiple Pathways in Conformational Transitions of Multi-Domain Proteins

Use of multistate Bennett acceptance ratio method for free-energy calculations from enhanced sampling and free-energy perturbation

Unraveling the Coupling between Conformational Changes and Ligand Binding in Ribose Binding Protein Using Multiscale Molecular Dynamics and Free-Energy Calculations

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