Literature DB >> 19627157

Quantitative prediction of fold resistance for inhibitors of EGFR.

Trent E Balius1, Robert C Rizzo.   

Abstract

Clinical use of ATP-competitive inhibitors of the epidermal growth factor receptor (EGFR) kinase domain can lead to an acquired drug resistant mutant L858R&T790M which dramatically reduces binding affinity relative to a prevalent cancer causing mutation L858R. In this study, we have used molecular dynamics (MD) computer simulations, free energy calculations (MM-GBSA method), and per-residue footprint analysis to characterize binding of three inhibitors (erlotinib, gefitinib, and AEE788) with wildtype EGFR and three mutants. The goal is to characterize how variation in structure and energy correlate with changes in experimental activities and to deduce origins of drug resistance. For seven fold resistance values, each computed from the difference of two independent computer simulations, excellent agreement was obtained with available experimental data (r2 = 0.84). Importantly, the results correctly predict that affinity will increase as a result of L858R and decrease due to L858R&T790M. Per-residue analysis shows an increase in favorable packing at the site of the methionine mutation reaffirming that a steric clash hypothesis is unlikely; however, large losses in van der Waals, Coulombic, and H-bond interactions strongly suggest that resistance is not due solely to changes in affinity for the native substrate ATP as recently proposed. Instead, the present results indicate that drug resistance more likely involves disruption of favorable interactions, including a water-mediated H-bond network between the ligands and residues T854, T790, and Q791, which could have important implication for guiding rational design of inhibitors with improved resistance profiles.

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Year:  2009        PMID: 19627157      PMCID: PMC2741091          DOI: 10.1021/bi900729a

Source DB:  PubMed          Journal:  Biochemistry        ISSN: 0006-2960            Impact factor:   3.162


  49 in total

1.  Development and testing of a general amber force field.

Authors:  Junmei Wang; Romain M Wolf; James W Caldwell; Peter A Kollman; David A Case
Journal:  J Comput Chem       Date:  2004-07-15       Impact factor: 3.376

2.  Comparison of multiple Amber force fields and development of improved protein backbone parameters.

Authors:  Viktor Hornak; Robert Abel; Asim Okur; Bentley Strockbine; Adrian Roitberg; Carlos Simmerling
Journal:  Proteins       Date:  2006-11-15

3.  Structures of lung cancer-derived EGFR mutants and inhibitor complexes: mechanism of activation and insights into differential inhibitor sensitivity.

Authors:  Cai-Hong Yun; Titus J Boggon; Yiqun Li; Michele S Woo; Heidi Greulich; Matthew Meyerson; Michael J Eck
Journal:  Cancer Cell       Date:  2007-03       Impact factor: 31.743

Review 4.  The epidermal growth factor receptor pathway: a model for targeted therapy.

Authors:  Maurizio Scaltriti; José Baselga
Journal:  Clin Cancer Res       Date:  2006-09-15       Impact factor: 12.531

Review 5.  Molecular predictors of response to epidermal growth factor receptor antagonists in non-small-cell lung cancer.

Authors:  Lecia V Sequist; Daphne W Bell; Thomas J Lynch; Daniel A Haber
Journal:  J Clin Oncol       Date:  2007-02-10       Impact factor: 44.544

Review 6.  EGFR targeting of solid tumors.

Authors:  Caio M Rocha-Lima; Heloisa P Soares; Luis E Raez; Rakesh Singal
Journal:  Cancer Control       Date:  2007-07       Impact factor: 3.302

7.  Clinical course of patients with non-small cell lung cancer and epidermal growth factor receptor exon 19 and exon 21 mutations treated with gefitinib or erlotinib.

Authors:  Gregory J Riely; William Pao; Duykhanh Pham; Allan R Li; Naiyer Rizvi; Ennapadam S Venkatraman; Maureen F Zakowski; Mark G Kris; Marc Ladanyi; Vincent A Miller
Journal:  Clin Cancer Res       Date:  2006-02-01       Impact factor: 12.531

8.  Acquired resistance to epidermal growth factor receptor kinase inhibitors associated with a novel T854A mutation in a patient with EGFR-mutant lung adenocarcinoma.

Authors:  James Bean; Gregory J Riely; Marissa Balak; Jenifer L Marks; Marc Ladanyi; Vincent A Miller; William Pao
Journal:  Clin Cancer Res       Date:  2008-11-15       Impact factor: 12.531

9.  Tyrosine kinase inhibitors. 5. Synthesis and structure-activity relationships for 4-[(phenylmethyl)amino]- and 4-(phenylamino)quinazolines as potent adenosine 5'-triphosphate binding site inhibitors of the tyrosine kinase domain of the epidermal growth factor receptor.

Authors:  G W Rewcastle; W A Denny; A J Bridges; H Zhou; D R Cody; A McMichael; D W Fry
Journal:  J Med Chem       Date:  1995-09-01       Impact factor: 7.446

10.  Lung cancer.

Authors:  W D Travis; L B Travis; S S Devesa
Journal:  Cancer       Date:  1995-01-01       Impact factor: 6.860

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  25 in total

1.  Fatty acid-binding proteins (FABPs) are intracellular carriers for Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD).

Authors:  Matthew W Elmes; Martin Kaczocha; William T Berger; KwanNok Leung; Brian P Ralph; Liqun Wang; Joseph M Sweeney; Jeremy T Miyauchi; Stella E Tsirka; Iwao Ojima; Dale G Deutsch
Journal:  J Biol Chem       Date:  2015-02-09       Impact factor: 5.157

2.  Dissecting the molecular recognition of dual lapatinib derivatives for EGFR/HER2.

Authors:  Martiniano Bello; Concepción Guadarrama-García; Rolando Alberto Rodriguez-Fonseca
Journal:  J Comput Aided Mol Des       Date:  2019-12-11       Impact factor: 3.686

3.  Origins of resistance to the HIVgp41 viral entry inhibitor T20.

Authors:  Brian E McGillick; Trent E Balius; Sudipto Mukherjee; Robert C Rizzo
Journal:  Biochemistry       Date:  2010-05-04       Impact factor: 3.162

4.  Rapid and accurate ranking of binding affinities of epidermal growth factor receptor sequences with selected lung cancer drugs.

Authors:  Shunzhou Wan; Peter V Coveney
Journal:  J R Soc Interface       Date:  2011-01-12       Impact factor: 4.118

5.  Strategies for lead discovery: application of footprint similarity targeting HIVgp41.

Authors:  Patrick M Holden; William J Allen; Miriam Gochin; Robert C Rizzo
Journal:  Bioorg Med Chem       Date:  2013-10-26       Impact factor: 3.641

Review 6.  Structure-based methods for predicting target mutation-induced drug resistance and rational drug design to overcome the problem.

Authors:  Ge-Fei Hao; Guang-Fu Yang; Chang-Guo Zhan
Journal:  Drug Discov Today       Date:  2012-07-10       Impact factor: 7.851

7.  Implementation and evaluation of a docking-rescoring method using molecular footprint comparisons.

Authors:  Trent E Balius; Sudipto Mukherjee; Robert C Rizzo
Journal:  J Comput Chem       Date:  2011-05-03       Impact factor: 3.376

8.  Accurate calculation of mutational effects on the thermodynamics of inhibitor binding to p38α MAP kinase: a combined computational and experimental study.

Authors:  Shun Zhu; Sue M Travis; Adrian H Elcock
Journal:  J Chem Theory Comput       Date:  2013-07-09       Impact factor: 6.006

9.  Luteolin is effective in the non-small cell lung cancer model with L858R/T790M EGF receptor mutation and erlotinib resistance.

Authors:  Zhuan Hong; Xiang Cao; Na Li; Yizhou Zhang; Lei Lan; Yi Zhou; Xiaolong Pan; Lei Shen; Zhimin Yin; Lan Luo
Journal:  Br J Pharmacol       Date:  2014-06       Impact factor: 8.739

10.  Computational study of EGFR inhibition: molecular dynamics studies on the active and inactive protein conformations.

Authors:  Napat Songtawee; M Paul Gleeson; Kiattawee Choowongkomon
Journal:  J Mol Model       Date:  2012-09-07       Impact factor: 1.810

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