1
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Fossat MJ, Pappu RV. q-Canonical Monte Carlo Sampling for Modeling the Linkage between Charge Regulation and Conformational Equilibria of Peptides. J Phys Chem B 2019; 123:6952-6967. [PMID: 31362509 PMCID: PMC10785832 DOI: 10.1021/acs.jpcb.9b05206] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The overall charge content and the patterning of charged residues have a profound impact on the conformational ensembles adopted by intrinsically disordered proteins. These parameters can be altered by charge regulation, which refers to the effects of post-translational modifications, pH-dependent changes to charge, and conformational fluctuations that modify the pKa values of ionizable residues. Although atomistic simulations have played a prominent role in uncovering the major sequence-ensemble relationships of IDPs, most simulations assume fixed charge states for ionizable residues. This may lead to erroneous estimates for conformational equilibria if they are linked to charge regulation. Here, we report the development of a new method we term q-canonical Monte Carlo sampling for modeling the linkage between charge regulation and conformational equilibria. The method, which is designed to be interoperable with the ABSINTH implicit solvation model, operates as follows: For a protein sequence with n ionizable residues, we start with all 2n charge microstates and use a criterion based on model compound pKa values to prune down to a subset of thermodynamically relevant charge microstates. This subset is then grouped into mesostates, where all microstates that belong to a mesostate have the same net charge. Conformational distributions, drawn from a canonical ensemble, are generated for each of the charge microstates that make up a mesostate using a method we designate as proton walk sampling. This method combines Metropolis Monte Carlo sampling in conformational space with an auxiliary Markov process that enables interconversions between charge microstates along a mesostate. Proton walk sampling helps identify the most likely charge microstate per mesostate. We then use thermodynamic integration aided by the multistate Bennett acceptance ratio method to estimate the free energies for converting between mesostates. These free energies are then combined with the per-microstate weights along each mesostate to estimate standard state free energies and pH-dependent free energies for all thermodynamically relevant charge microstates. The results provide quantitative estimates of the probabilities and preferred conformations associated with every thermodynamically accessible charge microstate. We showcase the application of q-canonical sampling using two model systems. The results establish the soundness of the method and the importance of charge regulation in systems characterized by conformational heterogeneity.
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Affiliation(s)
- Martin J. Fossat
- Department of Biomedical Engineering and Center for Science & Engineering of Living Systems (CSELS), Washington University in St. Louis, One Brookings Drive, Campus Box 1097, St. Louis, MO 63130
| | - Rohit V. Pappu
- Department of Biomedical Engineering and Center for Science & Engineering of Living Systems (CSELS), Washington University in St. Louis, One Brookings Drive, Campus Box 1097, St. Louis, MO 63130
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2
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Barroso da Silva FL, Sterpone F, Derreumaux P. OPEP6: A New Constant-pH Molecular Dynamics Simulation Scheme with OPEP Coarse-Grained Force Field. J Chem Theory Comput 2019; 15:3875-3888. [DOI: 10.1021/acs.jctc.9b00202] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Fernando Luís Barroso da Silva
- Departamento de Física e Química, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Av. do café, s/no, Ribeirão Preto, São Paulo BR-14040-903, Brazil
- Laboratoire de Biochimie Theórique, UPR 9080 CNRS, Institut de Biologie Physico Chimique, Université Paris Diderot − Paris 7 et Université Sorbonne Paris Cité, 13 rue Pierre et Marie Curie, 75005 Paris, France
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27606, United States
| | - Fabio Sterpone
- Laboratoire de Biochimie Theórique, UPR 9080 CNRS, Institut de Biologie Physico Chimique, Université Paris Diderot − Paris 7 et Université Sorbonne Paris Cité, 13 rue Pierre et Marie Curie, 75005 Paris, France
| | - Philippe Derreumaux
- Laboratory of Theoretical Chemistry, Ton Duc Thang University, Ho Chi Minh City, Vietnam
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam
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3
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Liu J, Swails J, Zhang JZH, He X, Roitberg AE. A Coupled Ionization-Conformational Equilibrium Is Required To Understand the Properties of Ionizable Residues in the Hydrophobic Interior of Staphylococcal Nuclease. J Am Chem Soc 2018; 140:1639-1648. [PMID: 29308643 DOI: 10.1021/jacs.7b08569] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Ionizable residues in the interior of proteins play essential roles, especially in biological energy transduction, but are relatively rare and seem incompatible with the complex and polar environment. We perform a comprehensive study of the internal ionizable residues on 21 variants of staphylococcal nuclease with internal Lys, Glu, or Asp residues. Using pH replica exchange molecular dynamics simulations, we find that, in most cases, the pKa values of these internal ionizable residues are shifted significantly from their values in solution. Our calculated results are in excellent agreement with the experimental observations of the Garcia-Moreno group. We show that the interpretation of the experimental pKa values requires the study of not only protonation changes but also conformational changes. The coupling between the protonation and conformational equilibria suggests a mechanism for efficient pH-sensing and regulation in proteins. This study provides new physical insights into how internal ionizable residues behave in the hydrophobic interior of proteins.
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Affiliation(s)
- Jinfeng Liu
- School of Chemistry and Molecular Engineering, Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, East China Normal University , Shanghai, 200062, China.,Department of Chemistry, University of Florida , Gainesville, Florida 32611, United States.,Department of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University , Nanjing, 210009, China
| | - Jason Swails
- Department of Chemistry and Chemical Biology and BioMaPS Institute, Rutgers University , Piscataway, New Jersey 08854, United States
| | - John Z H Zhang
- School of Chemistry and Molecular Engineering, Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, East China Normal University , Shanghai, 200062, China.,NYU-ECNU Center for Computational Chemistry at NYU Shanghai , Shanghai, 200062, China
| | - Xiao He
- School of Chemistry and Molecular Engineering, Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, East China Normal University , Shanghai, 200062, China.,NYU-ECNU Center for Computational Chemistry at NYU Shanghai , Shanghai, 200062, China
| | - Adrian E Roitberg
- Department of Chemistry, University of Florida , Gainesville, Florida 32611, United States
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4
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Barroso daSilva FL, Dias LG. Development of constant-pH simulation methods in implicit solvent and applications in biomolecular systems. Biophys Rev 2017; 9:699-728. [PMID: 28921104 PMCID: PMC5662048 DOI: 10.1007/s12551-017-0311-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2017] [Accepted: 08/01/2017] [Indexed: 12/20/2022] Open
Abstract
pH is a critical parameter for biological and technological systems directly related with electrical charges. It can give rise to peculiar electrostatic phenomena, which also makes them more challenging. Due to the quantum nature of the process, involving the forming and breaking of chemical bonds, quantum methods should ideally by employed. Nevertheless, due to the very large number of ionizable sites, different macromolecular conformations, salt conditions, and all other charged species, the CPU time cost simply becomes prohibitive for computer simulations, making this a quite complex problem. Simplified methods based on Monte Carlo sampling have been devised and will be reviewed here, highlighting the updated state-of-the-art of this field, advantages, and limitations of different theoretical protocols for biomolecular systems (proteins and nucleic acids). Following a historical perspective, the discussion will be associated with the applications to protein interactions with other proteins, polyelectrolytes, and nanoparticles.
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Affiliation(s)
- Fernando Luís Barroso daSilva
- Departamento de Física e Química, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Av. do café, s/no. - Universidade de São Paulo, BR-14040-903, Ribeirão Preto, SP, Brazil.
- UCD School of Physics, UCD Institute for Discovery, University College Dublin, Belfield, Dublin 4, Ireland.
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, USA.
| | - Luis Gustavo Dias
- Departamento de Química, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Av. Bandeirantes, 3900 - Universidade de São Paulo, BR-14040-901, Ribeirão Preto, SP, Brazil
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5
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Barroso da Silva FL, Derreumaux P, Pasquali S. Fast coarse-grained model for RNA titration. J Chem Phys 2017; 146:035101. [PMID: 28109220 DOI: 10.1063/1.4972986] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
A new numerical scheme for RNA (ribonucleic acid) titration based on the Debye-Hückel framework for the salt description is proposed in an effort to reduce the computational costs for further applications to study protein-RNA systems. By means of different sets of Monte Carlo simulations, we demonstrated that this new scheme is able to correctly reproduce the experimental titration behavior and salt pKa shifts. In comparison with other theoretical approaches, similar or even better outcomes are achieved at much lower computational costs. The model was tested on the lead-dependent ribozyme, the branch-point helix, and the domain 5 from Azotobacter vinelandii Intron 5.
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Affiliation(s)
- Fernando Luís Barroso da Silva
- Departamento de Física e Química, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ave. do café, s/no, BR-14040-903 Ribeirão Preto, São Paulo, Brazil
| | - Philippe Derreumaux
- Laboratoire de Biochimie Theórique, UPR 9080 CNRS, Institut de Biologie Physico Chimique, Université Paris Diderot - Paris 7 et Université Sorbonne Paris Cité, 13 rue Pierre et Marie Curie, 75005 Paris, France
| | - Samuela Pasquali
- Laboratoire de Biochimie Theórique, UPR 9080 CNRS, Institut de Biologie Physico Chimique, Université Paris Diderot - Paris 7 et Université Sorbonne Paris Cité, 13 rue Pierre et Marie Curie, 75005 Paris, France
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6
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Barroso da Silva FL, MacKernan D. Benchmarking a Fast Proton Titration Scheme in Implicit Solvent for Biomolecular Simulations. J Chem Theory Comput 2017; 13:2915-2929. [DOI: 10.1021/acs.jctc.6b01114] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Fernando Luís Barroso da Silva
- Departamento
de Fı́sica e Quı́mica, Faculdade
de Ciências Farmacêuticas de Ribeirão Preto,
Av. do café, s/no. − Universidade de São Paulo, BR-14040-903 Ribeirão Preto, São Paulo, Brazil
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7
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Li L, Chakravorty A, Alexov E. DelPhiForce, a tool for electrostatic force calculations: Applications to macromolecular binding. J Comput Chem 2017; 38:584-593. [PMID: 28130775 PMCID: PMC5315605 DOI: 10.1002/jcc.24715] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 12/10/2016] [Indexed: 12/31/2022]
Abstract
Long-range electrostatic forces play an important role in molecular biology, particularly in macromolecular interactions. However, calculating the electrostatic forces for irregularly shaped molecules immersed in water is a difficult task. Here, we report a new tool, DelPhiForce, which is a tool in the DelPhi package that calculates and visualizes the electrostatic forces in biomolecular systems. In parallel, the DelPhi algorithm for modeling electrostatic potential at user-defined positions has been enhanced to include triquadratic and tricubic interpolation methods. The tricubic interpolation method has been tested against analytical solutions and it has been demonstrated that the corresponding errors are negligibly small at resolution 4 grids/Å. The DelPhiForce is further applied in the study of forces acting between partners of three protein-protein complexes. It has been demonstrated that electrostatic forces play a dual role by steering binding partners (so that the partners recognize their native interfaces) and exerting an electrostatic torque (if the mutual orientations of the partners are not native-like). The output of DelPhiForce is in a format that VMD can read and visualize, and provides additional options for analysis of protein-protein binding. DelPhiForce is available for download from the DelPhi webpage at http://compbio.clemson.edu/downloadDir/delphiforce.tar.gz © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Lin Li
- Department of Physics, Clemson University, Clemson, SC 29634, USA
| | | | - Emil Alexov
- Department of Physics, Clemson University, Clemson, SC 29634, USA
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8
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Wu X, Lee J, Brooks BR. Origin of pK a Shifts of Internal Lysine Residues in SNase Studied Via Equal-Molar VMMS Simulations in Explicit Water. J Phys Chem B 2016; 121:3318-3330. [PMID: 27700118 DOI: 10.1021/acs.jpcb.6b08249] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Protein internal ionizable groups can exhibit large shifts in pKa values. Although the environment and interaction changes have been extensively studied both experimentally and computationally, direct calculation of pKa values of these internal ionizable groups in explicit water is challenging due to energy barriers in solvent interaction and in conformational transition. The virtual mixture of multiple states (VMMS) method is a new approach designed to study chemical state equilibrium. This method constructs a virtual mixture of multiple chemical states in order to sample the conformational space of all states simultaneously and to avoid crossing energy barriers related to state transition. By applying VMMS to 25 variants of staphylococcal nuclease with lysine residues at internal positions, we obtained the pKa values of these lysine residues and investigated the physics underlining the pKa shifts. Our calculation results agree reasonably well with experimental measurements, validating the VMMS method for pKa calculation and providing molecular details of the protonation equilibrium for protein internal ionizable groups. Based on our analyses of protein conformation relaxation, lysine side chain flexibility, water penetration, and the microenvironment, we conclude that the hydrophobicity of the microenvironment around the lysine side chain (which affects water penetration differently for different protonation states) plays an important role in the pKa shifts.
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Affiliation(s)
- Xiongwu Wu
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH) , Bethesda, Maryland 20892, United States
| | - Juyong Lee
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH) , Bethesda, Maryland 20892, United States
| | - Bernard R Brooks
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH) , Bethesda, Maryland 20892, United States
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9
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Lee J, Miller BT, Damjanović A, Brooks BR. Enhancing constant-pH simulation in explicit solvent with a two-dimensional replica exchange method. J Chem Theory Comput 2015; 11:2560-74. [PMID: 26575555 DOI: 10.1021/ct501101f] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
We present a new method for enhanced sampling for constant-pH simulations in explicit water based on a two-dimensional (2D) replica exchange scheme. The new method is a significant extension of our previously developed constant-pH simulation method, which is based on enveloping distribution sampling (EDS) coupled with a one-dimensional (1D) Hamiltonian exchange method (HREM). EDS constructs a hybrid Hamiltonian from multiple discrete end state Hamiltonians that, in this case, represent different protonation states of the system. The ruggedness and heights of the hybrid Hamiltonian's energy barriers can be tuned by the smoothness parameter. Within the context of the 1D EDS-HREM method, exchanges are performed between replicas with different smoothness parameters, allowing frequent protonation-state transitions and sampling of conformations that are favored by the end-state Hamiltonians. In this work, the 1D method is extended to 2D with an additional dimension, external pH. Within the context of the 2D method (2D EDS-HREM), exchanges are performed on a lattice of Hamiltonians with different pH conditions and smoothness parameters. We demonstrate that both the 1D and 2D methods exactly reproduce the thermodynamic properties of the semigrand canonical (SGC) ensemble of a system at a given pH. We have tested our new 2D method on aspartic acid, glutamic acid, lysine, a four residue peptide (sequence KAAE), and snake cardiotoxin. In all cases, the 2D method converges faster and without loss of precision; the only limitation is a loss of flexibility in how CPU time is employed. The results for snake cardiotoxin demonstrate that the 2D method enhances protonation-state transitions, samples a wider conformational space with the same amount of computational resources, and converges significantly faster overall than the original 1D method.
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Affiliation(s)
- Juyong Lee
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health , Bethesda, Maryland 20892, United States
| | - Benjamin T Miller
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health , Bethesda, Maryland 20892, United States
| | - Ana Damjanović
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health , Bethesda, Maryland 20892, United States.,Department of Biophysics, Johns Hopkins University , Baltimore, Maryland 21218, United States
| | - Bernard R Brooks
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health , Bethesda, Maryland 20892, United States
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10
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Advances in Human Biology: Combining Genetics and Molecular Biophysics to Pave the Way for Personalized Diagnostics and Medicine. ACTA ACUST UNITED AC 2014. [DOI: 10.1155/2014/471836] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Advances in several biology-oriented initiatives such as genome sequencing and structural genomics, along with the progress made through traditional biological and biochemical research, have opened up a unique opportunity to better understand the molecular effects of human diseases. Human DNA can vary significantly from person to person and determines an individual’s physical characteristics and their susceptibility to diseases. Armed with an individual’s DNA sequence, researchers and physicians can check for defects known to be associated with certain diseases by utilizing various databases. However, for unclassified DNA mutations or in order to reveal molecular mechanism behind the effects, the mutations have to be mapped onto the corresponding networks and macromolecular structures and then analyzed to reveal their effect on the wild type properties of biological processes involved. Predicting the effect of DNA mutations on individual’s health is typically referred to as personalized or companion diagnostics. Furthermore, once the molecular mechanism of the mutations is revealed, the patient should be given drugs which are the most appropriate for the individual genome, referred to as pharmacogenomics. Altogether, the shift in focus in medicine towards more genomic-oriented practices is the foundation of personalized medicine. The progress made in these rapidly developing fields is outlined.
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11
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Kukic P, Farrell D, McIntosh LP, García-Moreno E B, Jensen KS, Toleikis Z, Teilum K, Nielsen JE. Protein dielectric constants determined from NMR chemical shift perturbations. J Am Chem Soc 2013; 135:16968-76. [PMID: 24124752 DOI: 10.1021/ja406995j] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Understanding the connection between protein structure and function requires a quantitative understanding of electrostatic effects. Structure-based electrostatic calculations are essential for this purpose, but their use has been limited by a long-standing discussion on which value to use for the dielectric constants (ε(eff) and ε(p)) required in Coulombic and Poisson-Boltzmann models. The currently used values for ε(eff) and ε(p) are essentially empirical parameters calibrated against thermodynamic properties that are indirect measurements of protein electric fields. We determine optimal values for ε(eff) and ε(p) by measuring protein electric fields in solution using direct detection of NMR chemical shift perturbations (CSPs). We measured CSPs in 14 proteins to get a broad and general characterization of electric fields. Coulomb's law reproduces the measured CSPs optimally with a protein dielectric constant (ε(eff)) from 3 to 13, with an optimal value across all proteins of 6.5. However, when the water-protein interface is treated with finite difference Poisson-Boltzmann calculations, the optimal protein dielectric constant (ε(p)) ranged from 2 to 5 with an optimum of 3. It is striking how similar this value is to the dielectric constant of 2-4 measured for protein powders and how different it is from the ε(p) of 6-20 used in models based on the Poisson-Boltzmann equation when calculating thermodynamic parameters. Because the value of ε(p) = 3 is obtained by analysis of NMR chemical shift perturbations instead of thermodynamic parameters such as pK(a) values, it is likely to describe only the electric field and thus represent a more general, intrinsic, and transferable ε(p) common to most folded proteins.
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Affiliation(s)
- Predrag Kukic
- School of Biomolecular and Biomedical Science, Centre for Synthesis and Chemical Biology, UCD Conway Institute, University College Dublin , Belfield, Dublin 4, Ireland
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12
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Gosink LJ, Hogan EA, Pulsipher TC, Baker NA. Bayesian model aggregation for ensemble-based estimates of protein pKa values. Proteins 2013; 82:354-63. [PMID: 23946048 DOI: 10.1002/prot.24390] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2013] [Revised: 07/10/2013] [Accepted: 07/26/2013] [Indexed: 12/14/2022]
Abstract
This article investigates an ensemble-based technique called Bayesian Model Averaging (BMA) to improve the performance of protein amino acid pKa predictions. Structure-based pKa calculations play an important role in the mechanistic interpretation of protein structure and are also used to determine a wide range of protein properties. A diverse set of methods currently exist for pKa prediction, ranging from empirical statistical models to ab initio quantum mechanical approaches. However, each of these methods are based on a set of conceptual assumptions that can effect a model's accuracy and generalizability for pKa prediction in complicated biomolecular systems. We use BMA to combine eleven diverse prediction methods that each estimate pKa values of amino acids in staphylococcal nuclease. These methods are based on work conducted for the pKa Cooperative and the pKa measurements are based on experimental work conducted by the García-Moreno lab. Our cross-validation study demonstrates that the aggregated estimate obtained from BMA outperforms all individual prediction methods with improvements ranging from 45 to 73% over other method classes. This study also compares BMA's predictive performance to other ensemble-based techniques and demonstrates that BMA can outperform these approaches with improvements ranging from 27 to 60%. This work illustrates a new possible mechanism for improving the accuracy of pKa prediction and lays the foundation for future work on aggregate models that balance computational cost with prediction accuracy.
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Affiliation(s)
- Luke J Gosink
- Pacific Northwest National Laboratory, Computational and Statistical Analytics Division, MSID K7-2, Richland, Washington, 99352
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13
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Kilambi KP, Gray JJ. Rapid calculation of protein pKa values using Rosetta. Biophys J 2013; 103:587-595. [PMID: 22947875 DOI: 10.1016/j.bpj.2012.06.044] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2012] [Revised: 06/08/2012] [Accepted: 06/11/2012] [Indexed: 12/21/2022] Open
Abstract
We developed a Rosetta-based Monte Carlo method to calculate the pK(a) values of protein residues that commonly exhibit variable protonation states (Asp, Glu, Lys, His, and Tyr). We tested the technique by calculating pK(a) values for 264 residues from 34 proteins. The standard Rosetta score function, which is independent of any environmental conditions, failed to capture pK(a) shifts. After incorporating a Coulomb electrostatic potential and optimizing the solvation reference energies for pK(a) calculations, we employed a method that allowed side-chain flexibility and achieved a root mean-square deviation (RMSD) of 0.83 from experimental values (0.68 after discounting 11 predictions with an error over 2 pH units). Additional degrees of side-chain conformational freedom for the proximal residues facilitated the capture of charge-charge interactions in a few cases, resulting in an overall RMSD of 0.85 pH units. The addition of backbone flexibility increased the overall RMSD to 0.93 pH units but improved relative pK(a) predictions for proximal catalytic residues. The method also captures large pK(a) shifts of lysine and some glutamate point mutations in staphylococcal nuclease. Thus, a simple and fast method based on the Rosetta score function and limited conformational sampling produces pK(a) values that will be useful when rapid estimation is essential, such as in docking, design, and folding.
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Affiliation(s)
- Krishna Praneeth Kilambi
- Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, Maryland
| | - Jeffrey J Gray
- Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, Maryland; Program in Molecular Biophysics, The Johns Hopkins University, Baltimore, Maryland.
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14
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Ren P, Chun J, Thomas DG, Schnieders MJ, Marucho M, Zhang J, Baker NA. Biomolecular electrostatics and solvation: a computational perspective. Q Rev Biophys 2012; 45:427-91. [PMID: 23217364 PMCID: PMC3533255 DOI: 10.1017/s003358351200011x] [Citation(s) in RCA: 135] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.
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Affiliation(s)
- Pengyu Ren
- Department of Biomedical Engineering, The University of Texas at Austin
| | | | | | | | - Marcelo Marucho
- Department of Physics and Astronomy, The University of Texas at San Antonio
| | - Jiajing Zhang
- Department of Biomedical Engineering, The University of Texas at Austin
| | - Nathan A. Baker
- To whom correspondence should be addressed. Pacific Northwest National Laboratory, PO Box 999, MSID K7-29, Richland, WA 99352. Phone: +1-509-375-3997,
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15
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Johnston MA, Farrell D, Nielsen JE. A collaborative environment for developing and validating predictive tools for protein biophysical characteristics. J Comput Aided Mol Des 2012; 26:387-96. [DOI: 10.1007/s10822-012-9564-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2011] [Accepted: 03/18/2012] [Indexed: 11/29/2022]
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16
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Nielsen JE, Gunner MR, Bertrand García-Moreno E. The pKa Cooperative: a collaborative effort to advance structure-based calculations of pKa values and electrostatic effects in proteins. Proteins 2011; 79:3249-59. [PMID: 22002877 PMCID: PMC3375608 DOI: 10.1002/prot.23194] [Citation(s) in RCA: 91] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2011] [Accepted: 09/13/2011] [Indexed: 12/13/2022]
Abstract
The pK(a) Cooperative (http://www.pkacoop.org) was organized to advance development of accurate and useful computational methods for structure-based calculation of pK(a) values and electrostatic energies in proteins. The Cooperative brings together laboratories with expertise and interest in theoretical, computational, and experimental studies of protein electrostatics. To improve structure-based energy calculations, it is necessary to better understand the physical character and molecular determinants of electrostatic effects. Thus, the Cooperative intends to foment experimental research into fundamental aspects of proteins that depend on electrostatic interactions. It will maintain a depository for experimental data useful for critical assessment of methods for structure-based electrostatics calculations. To help guide the development of computational methods, the Cooperative will organize blind prediction exercises. As a first step, computational laboratories were invited to reproduce an unpublished set of experimental pK(a) values of acidic and basic residues introduced in the interior of staphylococcal nuclease by site-directed mutagenesis. The pK(a) values of these groups are unique and challenging to simulate owing to the large magnitude of their shifts relative to normal pK(a) values in water. Many computational methods were tested in this first Blind Prediction Challenge and critical assessment exercise. A workshop was organized in the Telluride Science Research Center to objectively assess the performance of many computational methods tested on this one extensive data set. This volume of Proteins: Structure, Function, and Bioinformatics introduces the pK(a) Cooperative, presents reports submitted by participants in the Blind Prediction Challenge, and highlights some of the problems in structure-based calculations identified during this exercise.
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Affiliation(s)
- Jens E. Nielsen
- School of Biomolecular and Biomedical Science, Centre for Synthesis and Chemical Biology, UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland
| | - M. R. Gunner
- Department of Physics, City College of New York, New York, NY 10031
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