What role do surfaces play in GB models? A new‐generation of surface‐generalized born model based on a novel gaussian surface for biomolecules

Yu, Zhiyun; Jacobson, Matthew P.; Friesner, Richard A.

doi:10.1002/jcc.20307

Cited by 89 publications

(88 citation statements)

References 56 publications

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“…Following the MTS-MC derivation, 35 the probability of selecting state j from state i is given by the following: (33) where the above transition probability is the product of the individual transition probabilities of the inner loop (34) In the short-range, or inner loop of sampling, neither the switching function nor the Born radii are updated, so that each step obeys the following detailed balance relation: (35) The transition between outer states j and i obeys the following detailed balance relation: (36) Combining eqs 32-35 and solving for the ratio of acceptance probabilities gives the following: (37) Protocols A and B follow the same updating scheme for the switching functions. The acceptance probability for protocol A is expressed in eq 17 as follows: (38) The ratio of eqs 37 and 38 is unity (39) and therefore, the sampling scheme described by eqs 37 and 38 rigorously obeys detailed balance. For all equations in the body of the text, the state of the switching function is not shown, but is updated according to the scheme described.…”

Section: Discussionmentioning

confidence: 99%

Multiscale Monte Carlo Sampling of Protein Sidechains: Application to Binding Pocket Flexibility

Nilmeier

Jacobson

2008

J. Chem. Theory Comput.

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We present a Monte Carlo sidechain sampling procedure and apply it to assessing the flexibility of protein binding pockets. We implemented a multiple "time step" Monte Carlo algorithm to optimize sidechain sampling with a surface generalized Born implicit solvent model. In this approach, certain forces (those due to long-range electrostatics and the implicit solvent model) are updated infrequently, in "outer steps", while short-range forces (covalent, local nonbonded interactions) are updated at every "inner step". Two multistep protocols were studied. The first protocol rigorously obeys detailed balance, and the second protocol introduces an approximation to the solvation term that increases the acceptance ratio. The first protocol gives a 10-fold improvement over a protocol that does not use multiple time steps, while the second protocol generates comparable ensembles and gives a 15-fold improvement. A range of 50-200 inner steps per outer step was found to give optimal performance for both protocols. The resultant method is a practical means to assess sidechain flexibility in ligand binding pockets, as we illustrate with proof-of-principle calculations on six proteins: DB3 antibody, thermolysin, estrogen receptor, PPAR-γ, PI3 kinase, and CDK2. The resulting sidechain ensembles of the apo binding sites correlate well with known induced fit conformational changes and provide insights into binding pocket flexibility.

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Section: Discussionmentioning

confidence: 99%

Multiscale Monte Carlo Sampling of Protein Sidechains: Application to Binding Pocket Flexibility

Nilmeier

Jacobson

2008

J. Chem. Theory Comput.

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“…The VDW surface, SAS and SES can be approximated well by the Gaussian surface with proper parameter selection [6,7]. The Gaussian surface has been widely used in many problems in computational biology, such as docking problem [8], molecular shape comparison [9], calculating SAS area [10] and the generalized Born models [11]. With various definitions of molecular surface that has been proposed, numerous works have been devoted to the computation of molecular surface.…”

Section: Some Definitions and Meshing Methods For Molecular Surfacementioning

confidence: 99%

Advances in biomolecular surface meshing and its applications to mathematical modeling

Chen

2013

Chin. Sci. Bull.

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In the field of molecular modeling and simulation, molecular surface meshes are necessary for many problems, such as molecular structure visualization and analysis, docking problem and implicit solvent modeling and simulation. Recently, with the developments of advanced mathematical modeling in the field of implicit solvent modeling and simulation, providing surface meshes with good qualities efficiently for large real biomolecular systems becomes an urgent issue beyond its traditional purposes for visualization and geometry analyses for molecular structure. In this review, we summarize recent works on this issue. First, various definitions of molecular surfaces and corresponding meshing methods are introduced. Second, our recent meshing tool, TMSmesh, and its performances are presented. Finally, we show the applications of the molecular surface mesh in implicit solvent modeling and simulations using boundary element method (BEM) and finite element method (FEM). molecular surface meshing, manifold mesh, mathematical modeling, TMSmeshCitation: Chen M X, Lu B Z. Advances in biomolecular surface meshing and its applications to mathematical modeling. Chin Sci Bull, 2013Bull, , 58: 1843Bull, -1849 10.1007/s11434-013-5829-8One main goal of computational structural biology/chemistry is to understand the functions and mechanisms of biomolecular systems and their relations to molecular structures with a wide range of computational approaches. To achieve this, proper and correct representation of the interface between biomolecule and solvent, molecular surface, is a primary task. In the field of implicit solvent modeling and continuum modeling, the molecular surface is used to model the dielectric interface which is the transition from the low-dielectric solute region to the high-dielectric solvent region. It is also important and useful in materials science and surface science [1]. Meshing molecular surface is a prerequisite for using boundary element method (BEM) and finite element method (FEM) in the implicit solvent models, and it is a more demanding task than for the only purposes of visualization and/or geometry analyses of molecular structure. So far, due to the highly complex and irregular shape of the molecular surface, *Corresponding author (email: bzlu@lsec.cc.ac.cn) efficient meshing of molecular surface for large real biomolecule with high quality remains a challenging problem. Actually, it was historically a great impediment to use BEM/FEM in continuum modeling of large molecular systems.The main purpose of this paper is to review the various definitions and meshing methods for molecular surface, including our recent work, and introduce their applications in implicit solvent modeling and simulation. Following this introduction section, in Section 1, various definitions of molecular surfaces and corresponding meshing methods are introduced. In Section 2, our recent algorithm and software, TMSmesh, are focused. We also made comparisons with some other methods. In Section 3, a closely related topic, volume me...

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“…The VDW surface, SAS and SES can be approximated well by the Gaussian surface with proper parameter selection [25,26]. The Gaussian surface has been widely used in many problems in computational biology, such as docking problem [27], molecular shape comparison [28], calculating SAS area [29] and the generalized Born models [30]. TMSmesh contains two main steps.…”

Section: Previous Algorithms In Tmsmeshmentioning

confidence: 99%

Triangulated manifold meshing method preserving molecular surface topology

Chen

2012

Journal of Molecular Graphics and Modelling

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What role do surfaces play in GB models? A new‐generation of surface‐generalized born model based on a novel gaussian surface for biomolecules

Cited by 89 publications

References 56 publications

Multiscale Monte Carlo Sampling of Protein Sidechains: Application to Binding Pocket Flexibility

Multiscale Monte Carlo Sampling of Protein Sidechains: Application to Binding Pocket Flexibility

Advances in biomolecular surface meshing and its applications to mathematical modeling

Triangulated manifold meshing method preserving molecular surface topology

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