Literature DB >> 10611647

Towards understanding the mechanisms of molecular recognition by computer simulations of ligand-protein interactions.

G M Verkhivker1, P A Rejto, D Bouzida, S Arthurs, A B Colson, S T Freer, D K Gehlhaar, V Larson, B A Luty, T Marrone, P W Rose.   

Abstract

The thermodynamic and kinetic aspects of molecular recognition for the methotrexate (MTX)-dihydrofolate reductase (DHFR) ligand-protein system are investigated by the binding energy landscape approach. The impact of 'hot' and 'cold' errors in ligand mutations on the thermodynamic stability of the native MTX-DHFR complex is analyzed, and relationships between the molecular recognition mechanism and the degree of ligand optimization are discussed. The nature and relative stability of intermediates and thermodynamic phases on the ligand-protein association pathway are studied, providing new insights into connections between protein folding and molecular recognition mechanisms, and cooperativity of ligand-protein binding. The results of kinetic docking simulations are rationalized based on the thermodynamic properties determined from equilibrium simulations and the shape of the underlying binding energy landscape. We show how evolutionary ligand selection for a receptor active site can produce well-optimized ligand-protein systems such as MTX-DHFR complex with the thermodynamically stable native structure and a direct transition mechanism of binding from unbound conformations to the unique native structure. Copyright 1999 John Wiley & Sons, Ltd.

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Year:  1999        PMID: 10611647     DOI: 10.1002/(SICI)1099-1352(199911/12)12:6<371::AID-JMR479>3.0.CO;2-O

Source DB:  PubMed          Journal:  J Mol Recognit        ISSN: 0952-3499            Impact factor:   2.137


  6 in total

1.  Deciphering common failures in molecular docking of ligand-protein complexes.

Authors:  G M Verkhivker; D Bouzida; D K Gehlhaar; P A Rejto; S Arthurs; A B Colson; S T Freer; V Larson; B A Luty; T Marrone; P W Rose
Journal:  J Comput Aided Mol Des       Date:  2000-11       Impact factor: 3.686

2.  Femtosecond studies of protein-ligand hydrophobic binding and dynamics: human serum albumin.

Authors:  D Zhong; A Douhal; A H Zewail
Journal:  Proc Natl Acad Sci U S A       Date:  2000-12-19       Impact factor: 11.205

3.  A genetic algorithm for structure-based de novo design.

Authors:  S C Pegg; J J Haresco; I D Kuntz
Journal:  J Comput Aided Mol Des       Date:  2001-10       Impact factor: 3.686

4.  Towards a critical evaluation of an empirical and volume-based solvation function for ligand docking.

Authors:  Heloisa S Muniz; Alessandro S Nascimento
Journal:  PLoS One       Date:  2017-03-21       Impact factor: 3.240

5.  Can the energy gap in the protein-ligand binding energy landscape be used as a descriptor in virtual ligand screening?

Authors:  Arsen V Grigoryan; Hong Wang; Timothy J Cardozo
Journal:  PLoS One       Date:  2012-10-10       Impact factor: 3.240

6.  Molecular Dynamics Assisted Mechanistic Study of Isoniazid-Resistance against Mycobacterium tuberculosis InhA.

Authors:  Vivek Kumar; M Elizabeth Sobhia
Journal:  PLoS One       Date:  2015-12-14       Impact factor: 3.240

  6 in total

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