Literature DB >> 26616606

Improved Hydrogen Bonding at the NDDO-Type Semiempirical Quantum Mechanical/Molecular Mechanical Interface.

Qiantao Wang1, Richard A Bryce1.   

Abstract

A semiempirical quantum mechanical (QM)/molecular mechanical (MM) potential with reformulated QM core-MM charge interactions is introduced, specifically to more accurately model hydrogen bonding at the QM/MM interface. Application of this potential using the PM3 Hamiltonian shows improved prediction of geometry and interaction energy for hydrogen bonded small molecule complexes typical of biomolecular interactions, without significantly impacting the modeling of other interaction types. Using this potential, more quantitative prediction of interaction energies is also found at a protein-ligand interface.

Entities:  

Year:  2009        PMID: 26616606     DOI: 10.1021/ct9002674

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  5 in total

1.  Dielectric and conformal studies of 1-propanol and 1-butanol in methanol.

Authors:  Baliram Lone; Vinjanmpaty Madhurima
Journal:  J Mol Model       Date:  2010-06-09       Impact factor: 1.810

Review 2.  Enhanced semiempirical QM methods for biomolecular interactions.

Authors:  Nusret Duygu Yilmazer; Martin Korth
Journal:  Comput Struct Biotechnol J       Date:  2015-02-28       Impact factor: 7.271

3.  Using docking and alchemical free energy approach to determine the binding mechanism of eEF2K inhibitors and prioritizing the compound synthesis.

Authors:  Qiantao Wang; Ramakrishna Edupuganti; Clint D J Tavares; Kevin N Dalby; Pengyu Ren
Journal:  Front Mol Biosci       Date:  2015-03-19

4.  General Model for Treating Short-Range Electrostatic Penetration in a Molecular Mechanics Force Field.

Authors:  Qiantao Wang; Joshua A Rackers; Chenfeng He; Rui Qi; Christophe Narth; Louis Lagardere; Nohad Gresh; Jay W Ponder; Jean-Philip Piquemal; Pengyu Ren
Journal:  J Chem Theory Comput       Date:  2015-04-28       Impact factor: 6.006

5.  Personalized prediction of EGFR mutation-induced drug resistance in lung cancer.

Authors:  Debby D Wang; Weiqiang Zhou; Hong Yan; Maria Wong; Victor Lee
Journal:  Sci Rep       Date:  2013-10-04       Impact factor: 4.379

  5 in total

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