Literature DB >> 27934233

Modeling Membrane Protein-Ligand Binding Interactions: The Human Purinergic Platelet Receptor.

D'Artagnan Greene1, Wesley M Botello-Smith1, Alec Follmer1, Li Xiao1, Eleftherios Lambros1, Ray Luo1.   

Abstract

Membrane proteins, due to their roles as cell receptors and signaling mediators, make prime candidates for drug targets. The computational analysis of protein-ligand binding affinities has been widely employed as a tool in rational drug design efforts. Although efficient implicit solvent-based methods for modeling globular protein-ligand binding have been around for many years, the extension of such methods to membrane protein-ligand binding is still in its infancy. In this study, we extended the widely used Amber/MMPBSA method to model membrane protein-ligand systems, and we used it to analyze protein-ligand binding for the human purinergic platelet receptor (P2Y12R), a prominent drug target in the inhibition of platelet aggregation for the prevention of myocardial infarction and stroke. The binding affinities, computed by the Amber/MMPBSA method using standard parameters, correlate well with experiment. A detailed investigation of these parameters was conducted to assess their impact on the accuracy of the method. These analyses show the importance of properly treating the nonpolar solvation interactions and the electrostatic polarization in the binding of nucleotide agonists and non-nucleotide antagonists to P2Y12R. On the basis of the crystal structures and the experimental conditions in the binding assay, we further hypothesized that the nucleotide agonists lose their bound magnesium ion upon binding to P2Y12R, and our computational study supports this hypothesis. Ultimately, this work illustrates the value of computational analysis in the interpretation of experimental binding reactions.

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Year:  2016        PMID: 27934233      PMCID: PMC5460638          DOI: 10.1021/acs.jpcb.6b09535

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  97 in total

1.  The conformational states of Mg.ATP in water.

Authors:  Jung-Chi Liao; Sean Sun; David Chandler; George Oster
Journal:  Eur Biophys J       Date:  2003-08-07       Impact factor: 1.733

2.  Physical scoring function based on AMBER force field and Poisson-Boltzmann implicit solvent for protein structure prediction.

Authors:  Meng-Juei Hsieh; Ray Luo
Journal:  Proteins       Date:  2004-08-15

3.  pKa's of ionizable groups in proteins: atomic detail from a continuum electrostatic model.

Authors:  D Bashford; M Karplus
Journal:  Biochemistry       Date:  1990-11-06       Impact factor: 3.162

4.  Computations of Absolute Solvation Free Energies of Small Molecules Using Explicit and Implicit Solvent Model.

Authors:  Devleena Shivakumar; Yuqing Deng; Benoît Roux
Journal:  J Chem Theory Comput       Date:  2009-03-24       Impact factor: 6.006

5.  Overcoming entropic barrier with coupled sampling at dual resolutions.

Authors:  Thur Zar Lwin; Ray Luo
Journal:  J Chem Phys       Date:  2005-11-15       Impact factor: 3.488

6.  Peptide and protein folding and conformational equilibria: theoretical treatment of electrostatics and hydrogen bonding with implicit solvent models.

Authors:  Wonpil Im; Jianhan Chen; Charles L Brooks
Journal:  Adv Protein Chem       Date:  2005

7.  Quantitative analysis of Poisson-Boltzmann implicit solvent in molecular dynamics.

Authors:  Jun Wang; Chunhu Tan; Emmanuel Chanco; Ray Luo
Journal:  Phys Chem Chem Phys       Date:  2009-12-23       Impact factor: 3.676

8.  Computation of molecular electrostatics with boundary element methods.

Authors:  J Liang; S Subramaniam
Journal:  Biophys J       Date:  1997-10       Impact factor: 4.033

9.  Structures of rhodopsin kinase in different ligand states reveal key elements involved in G protein-coupled receptor kinase activation.

Authors:  Puja Singh; Benlian Wang; Tadao Maeda; Krzysztof Palczewski; John J G Tesmer
Journal:  J Biol Chem       Date:  2008-03-13       Impact factor: 5.157

10.  Calculating protein-ligand binding affinities with MMPBSA: Method and error analysis.

Authors:  Changhao Wang; Peter H Nguyen; Kevin Pham; Danielle Huynh; Thanh-Binh Nancy Le; Hongli Wang; Pengyu Ren; Ray Luo
Journal:  J Comput Chem       Date:  2016-08-11       Impact factor: 3.376

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  7 in total

1.  Robustness and Efficiency of Poisson-Boltzmann Modeling on Graphics Processing Units.

Authors:  Ruxi Qi; Ray Luo
Journal:  J Chem Inf Model       Date:  2018-12-31       Impact factor: 4.956

2.  In Silico Screening of Novel TMPRSS2 Inhibitors for Treatment of COVID-19.

Authors:  Shuo Wang; Xuexun Fang; Ye Wang
Journal:  Molecules       Date:  2022-06-30       Impact factor: 4.927

3.  A Continuum Poisson-Boltzmann Model for Membrane Channel Proteins.

Authors:  Li Xiao; Jianxiong Diao; D'Artagnan Greene; Junmei Wang; Ray Luo
Journal:  J Chem Theory Comput       Date:  2017-06-14       Impact factor: 6.006

4.  Computational Analysis for the Rational Design of Anti-Amyloid Beta (Aβ) Antibodies.

Authors:  D'Artagnan Greene; Theodora Po; Jennifer Pan; Tanya Tabibian; Ray Luo
Journal:  J Phys Chem B       Date:  2018-04-16       Impact factor: 2.991

Review 5.  Recent Developments and Applications of the MMPBSA Method.

Authors:  Changhao Wang; D'Artagnan Greene; Li Xiao; Ruxi Qi; Ray Luo
Journal:  Front Mol Biosci       Date:  2018-01-10

6.  A Finite Element Solution of Lateral Periodic Poisson-Boltzmann Model for Membrane Channel Proteins.

Authors:  Nan Ji; Tiantian Liu; Jingjie Xu; Longzhu Q Shen; Benzhuo Lu
Journal:  Int J Mol Sci       Date:  2018-02-28       Impact factor: 5.923

7.  Understanding G Protein Selectivity of Muscarinic Acetylcholine Receptors Using Computational Methods.

Authors:  Luis Jaimes Santiago; Ravinder Abrol
Journal:  Int J Mol Sci       Date:  2019-10-24       Impact factor: 5.923

  7 in total

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