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LARMD: integration of bioinformatic resources to profile ligand-driven protein dynamics with a case on the activation of estrogen receptor.

Publication ,  Journal Article
Yang, J-F; Wang, F; Chen, Y-Z; Hao, G-F; Yang, G-F
Published in: Brief Bioinform
December 1, 2020

Protein dynamics is central to all biological processes, including signal transduction, cellular regulation and biological catalysis. Among them, in-depth exploration of ligand-driven protein dynamics contributes to an optimal understanding of protein function, which is particularly relevant to drug discovery. Hence, a wide range of computational tools have been designed to investigate the important dynamic information in proteins. However, performing and analyzing protein dynamics is still challenging due to the complicated operation steps, giving rise to great difficulty, especially for nonexperts. Moreover, there is a lack of web protocol to provide online facility to investigate and visualize ligand-driven protein dynamics. To this end, in this study, we integrated several bioinformatic tools to develop a protocol, named Ligand and Receptor Molecular Dynamics (LARMD, http://chemyang.ccnu.edu.cn/ccb/server/LARMD/ and http://agroda.gzu.edu.cn:9999/ccb/server/LARMD/), for profiling ligand-driven protein dynamics. To be specific, estrogen receptor (ER) was used as a case to reveal ERβ-selective mechanism, which plays a vital role in the treatment of inflammatory diseases and many types of cancers in clinical practice. Two different residues (Ile373/Met421 and Met336/Leu384) in the pocket of ERβ/ERα were the significant determinants for selectivity, especially Met336 of ERβ. The helix H8, helix H11 and H7-H8 loop influenced the migration of selective agonist (WAY-244). These computational results were consistent with the experimental results. Therefore, LARMD provides a user-friendly online protocol to study the dynamic property of protein and to design new ligand or site-directed mutagenesis.

Duke Scholars

Published In

Brief Bioinform

DOI

EISSN

1477-4054

Publication Date

December 1, 2020

Volume

21

Issue

6

Start / End Page

2206 / 2218

Location

England

Related Subject Headings

  • Molecular Dynamics Simulation
  • Ligands
  • Estrogen Receptor beta
  • Estrogen Receptor alpha
  • Drug Discovery
  • Computational Biology
  • Bioinformatics
  • 3105 Genetics
  • 3102 Bioinformatics and computational biology
  • 3101 Biochemistry and cell biology
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Yang, J.-F., Wang, F., Chen, Y.-Z., Hao, G.-F., & Yang, G.-F. (2020). LARMD: integration of bioinformatic resources to profile ligand-driven protein dynamics with a case on the activation of estrogen receptor. Brief Bioinform, 21(6), 2206–2218. https://doi.org/10.1093/bib/bbz141
Yang, Jing-Fang, Fan Wang, Yu-Zong Chen, Ge-Fei Hao, and Guang-Fu Yang. “LARMD: integration of bioinformatic resources to profile ligand-driven protein dynamics with a case on the activation of estrogen receptor.Brief Bioinform 21, no. 6 (December 1, 2020): 2206–18. https://doi.org/10.1093/bib/bbz141.
Yang, Jing-Fang, et al. “LARMD: integration of bioinformatic resources to profile ligand-driven protein dynamics with a case on the activation of estrogen receptor.Brief Bioinform, vol. 21, no. 6, Dec. 2020, pp. 2206–18. Pubmed, doi:10.1093/bib/bbz141.
Yang J-F, Wang F, Chen Y-Z, Hao G-F, Yang G-F. LARMD: integration of bioinformatic resources to profile ligand-driven protein dynamics with a case on the activation of estrogen receptor. Brief Bioinform. 2020 Dec 1;21(6):2206–2218.
Journal cover image

Published In

Brief Bioinform

DOI

EISSN

1477-4054

Publication Date

December 1, 2020

Volume

21

Issue

6

Start / End Page

2206 / 2218

Location

England

Related Subject Headings

  • Molecular Dynamics Simulation
  • Ligands
  • Estrogen Receptor beta
  • Estrogen Receptor alpha
  • Drug Discovery
  • Computational Biology
  • Bioinformatics
  • 3105 Genetics
  • 3102 Bioinformatics and computational biology
  • 3101 Biochemistry and cell biology