Literature DB >> 20309456

Computational enzymology.

Richard Lonsdale1, Kara E Ranaghan, Adrian J Mulholland.   

Abstract

Molecular simulations and modelling are changing the science of enzymology. Calculations can provide detailed, atomic-level insight into the fundamental mechanisms of biological catalysts. Computational enzymology is a rapidly developing area, and is testing theories of catalysis, challenging 'textbook' mechanisms, and identifying novel catalytic mechanisms. Increasingly, modelling is contributing directly to experimental studies of enzyme-catalysed reactions. Potential practical applications include interpretation of experimental data, catalyst design and drug development.

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Year:  2010        PMID: 20309456     DOI: 10.1039/b925647d

Source DB:  PubMed          Journal:  Chem Commun (Camb)        ISSN: 1359-7345            Impact factor:   6.222


  22 in total

1.  Uricases as therapeutic agents to treat refractory gout: Current states and future directions.

Authors:  Xiaolan Yang; Yonghua Yuan; Chang-Guo Zhan; Fei Liao
Journal:  Drug Dev Res       Date:  2011-12-29       Impact factor: 4.360

Review 2.  A practical guide to modelling enzyme-catalysed reactions.

Authors:  Richard Lonsdale; Jeremy N Harvey; Adrian J Mulholland
Journal:  Chem Soc Rev       Date:  2012-01-26       Impact factor: 54.564

3.  GTKDynamo: a PyMOL plug-in for QC/MM hybrid potential simulations.

Authors:  José Fernando R Bachega; Luís Fernando S M Timmers; Lucas Assirati; Leonardo R Bachega; Martin J Field; Troy Wymore
Journal:  J Comput Chem       Date:  2013-09-30       Impact factor: 3.376

4.  Combination of docking, molecular dynamics and quantum mechanical calculations for metabolism prediction of 3,4-methylenedioxybenzoyl-2-thienylhydrazone.

Authors:  Rodolpho C Braga; Vinícius M Alves; Carlos A M Fraga; Eliezer J Barreiro; Valéria de Oliveira; Carolina H Andrade
Journal:  J Mol Model       Date:  2011-09-08       Impact factor: 1.810

5.  Application of a SCC-DFTB QM/MM approach to the investigation of the catalytic mechanism of fatty acid amide hydrolase.

Authors:  Luigi Capoferri; Marco Mor; Jitnapa Sirirak; Ewa Chudyk; Adrian J Mulholland; Alessio Lodola
Journal:  J Mol Model       Date:  2011-03-02       Impact factor: 1.810

6.  Quantum mechanics/molecular mechanics modeling of fatty acid amide hydrolase reactivation distinguishes substrate from irreversible covalent inhibitors.

Authors:  Alessio Lodola; Luigi Capoferri; Silvia Rivara; Giorgio Tarzia; Daniele Piomelli; Adrian Mulholland; Marco Mor
Journal:  J Med Chem       Date:  2013-03-07       Impact factor: 7.446

Review 7.  Enzyme informatics.

Authors:  Rosanna G Alderson; Luna De Ferrari; Lazaros Mavridis; James L McDonagh; John B O Mitchell; Neetika Nath
Journal:  Curr Top Med Chem       Date:  2012       Impact factor: 3.295

8.  A catalytic mechanism for cysteine N-terminal nucleophile hydrolases, as revealed by free energy simulations.

Authors:  Alessio Lodola; Davide Branduardi; Marco De Vivo; Luigi Capoferri; Marco Mor; Daniele Piomelli; Andrea Cavalli
Journal:  PLoS One       Date:  2012-02-28       Impact factor: 3.240

9.  Determinants of reactivity and selectivity in soluble epoxide hydrolase from quantum mechanics/molecular mechanics modeling.

Authors:  Richard Lonsdale; Simon Hoyle; Daniel T Grey; Lars Ridder; Adrian J Mulholland
Journal:  Biochemistry       Date:  2012-02-10       Impact factor: 3.162

10.  Modeling catalytic promiscuity in the alkaline phosphatase superfamily.

Authors:  Fernanda Duarte; Beat Anton Amrein; Shina Caroline Lynn Kamerlin
Journal:  Phys Chem Chem Phys       Date:  2013-06-03       Impact factor: 3.676

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