Literature DB >> 26476847

Statistical analysis of EGFR structures' performance in virtual screening.

Yan Li1, Xiang Li2, Zigang Dong3.   

Abstract

In this work the ability of EGFR structures to distinguish true inhibitors from decoys in docking and MM-PBSA is assessed by statistical procedures. The docking performance depends critically on the receptor conformation and bound state. The enrichment of known inhibitors is well correlated with the difference between EGFR structures rather than the bound-ligand property. The optimal structures for virtual screening can be selected based purely on the complex information. And the mixed combination of distinct EGFR conformations is recommended for ensemble docking. In MM-PBSA, a variety of EGFR structures have identically good performance in the scoring and ranking of known inhibitors, indicating that the choice of the receptor structure has little effect on the screening.

Entities:  

Keywords:  EGFR conformation; Enrichment; MM-PBSA; Molecular docking; Receptor flexibility

Mesh:

Substances:

Year:  2015        PMID: 26476847      PMCID: PMC4749411          DOI: 10.1007/s10822-015-9877-9

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  37 in total

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3.  The Amber biomolecular simulation programs.

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Journal:  J Comput Chem       Date:  2005-12       Impact factor: 3.376

4.  Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking.

Authors:  Sheng-You Huang; Xiaoqin Zou
Journal:  Proteins       Date:  2007-02-01

5.  Exploring experimental sources of multiple protein conformations in structure-based drug design.

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Journal:  J Am Chem Soc       Date:  2007-06-08       Impact factor: 15.419

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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

7.  An allosteric mechanism for activation of the kinase domain of epidermal growth factor receptor.

Authors:  Xuewu Zhang; Jodi Gureasko; Kui Shen; Philip A Cole; John Kuriyan
Journal:  Cell       Date:  2006-06-16       Impact factor: 41.582

8.  Use of MM-PBSA in reproducing the binding free energies to HIV-1 RT of TIBO derivatives and predicting the binding mode to HIV-1 RT of efavirenz by docking and MM-PBSA.

Authors:  J Wang; P Morin; W Wang; P A Kollman
Journal:  J Am Chem Soc       Date:  2001-06-06       Impact factor: 15.419

9.  A unique structure for epidermal growth factor receptor bound to GW572016 (Lapatinib): relationships among protein conformation, inhibitor off-rate, and receptor activity in tumor cells.

Authors:  Edgar R Wood; Anne T Truesdale; Octerloney B McDonald; Derek Yuan; Anne Hassell; Scott H Dickerson; Byron Ellis; Christopher Pennisi; Earnest Horne; Karen Lackey; Krystal J Alligood; David W Rusnak; Tona M Gilmer; Lisa Shewchuk
Journal:  Cancer Res       Date:  2004-09-15       Impact factor: 12.701

10.  Structure of the epidermal growth factor receptor kinase domain alone and in complex with a 4-anilinoquinazoline inhibitor.

Authors:  Jennifer Stamos; Mark X Sliwkowski; Charles Eigenbrot
Journal:  J Biol Chem       Date:  2002-08-23       Impact factor: 5.157

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  4 in total

1.  In silico studies of interactions of peptide-conjugated cholesterol metabolites and betulinic acid with EGFR, LDR, and N-terminal fragment of CCKA receptors.

Authors:  Madeline M Bashant; Saige M Mitchell; Lucy R Hart; Charlotta G Lebedenko; Ipsita A Banerjee
Journal:  J Mol Model       Date:  2021-12-28       Impact factor: 1.810

Review 2.  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

3.  In silico identification of genetic mutations conferring resistance to acetohydroxyacid synthase inhibitors: A case study of Kochia scoparia.

Authors:  Yan Li; Michael D Netherland; Chaoyang Zhang; Huixiao Hong; Ping Gong
Journal:  PLoS One       Date:  2019-05-07       Impact factor: 3.240

Review 4.  Application of MM-PBSA Methods in Virtual Screening.

Authors:  Giulio Poli; Carlotta Granchi; Flavio Rizzolio; Tiziano Tuccinardi
Journal:  Molecules       Date:  2020-04-23       Impact factor: 4.411

  4 in total

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