Path-LZerD: Predicting Assembly Order of Multimeric Protein Complexes.

Assembly order Multimeric protein complex PPI PPI network Protein docking Protein structure modeling Protein–protein interaction Structure prediction

Journal

Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969

Informations de publication

Date de publication:
2020
Historique:
entrez: 5 10 2019
pubmed: 5 10 2019
medline: 12 1 2021
Statut: ppublish

Résumé

Many important functions in a cell are carried out by protein complexes with more than two subunits. Similar to the folding of a single protein, multimeric protein complexes in general follow an energetically favored assembly path. Knowing the assembly path not only provides critical information about the molecular mechanism of the assembly but also serves as a foundation for artificial design of protein complexes, as well as development of drugs that interfere with complex formation. There are experimental approaches for determining the assembly path of a complex; however, such methods are resource intensive. We have recently developed a computational method, Path-LZerD, which predicts the assembly path of a complex by simulating the docking process of the complex. Here, we explain how to use the Path-LZerD software with examples.

Identifiants

pubmed: 31583633
doi: 10.1007/978-1-4939-9873-9_8
doi:

Substances chimiques

Proteins 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

95-112

Subventions

Organisme : NIGMS NIH HHS
ID : R01 GM123055
Pays : United States

Auteurs

Genki Terashi (G)

Department of Biological Sciences, Purdue University, West Lafayette, IN, USA.

Charles Christoffer (C)

Department of Computer Science, Purdue University, West Lafayette, IN, USA.

Daisuke Kihara (D)

Department of Biological Sciences, Purdue University, West Lafayette, IN, USA. dkihara@purdue.edu.
Department of Computer Science, Purdue University, West Lafayette, IN, USA. dkihara@purdue.edu.

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Classifications MeSH