期刊
BIOCHIMICA ET BIOPHYSICA ACTA-BIOMEMBRANES
卷 1859, 期 10, 页码 2021-2039出版社
ELSEVIER
DOI: 10.1016/j.bbamem.2017.07.008
关键词
Membrane proteins; Computational modeling; Machine-learning; Transporters; GPCRs
资金
- Fundacao para a Ciencia e a Tecnologia (FCT) Investigator programme [IF/00578/2014]
- European Social Fund
- Programa Operacional Potencial Humano
- Marie Sklodowska-Curie Individual Fellowship [MSCA-IF-2015 [MEMBRANEPROT 659826]]
- European Regional Development Fund (ERDF) through the Centro 2020 Regional Operational Programme [CENTRO-01-0145-FEDER-000008: BrainHealth 2020]
- European Regional Development Fund (ERDF) through COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation
- Portuguese national funds via FCT [POCI-01-0145-FEDER-007440]
- Dutch Foundation for Scientific Research (NWO) (TOP-PUNT) [BC.000664.1]
Background: Membrane proteins (MPs) play diverse and important functions in living organisms. They constitute 20% to 30% of the known bacterial, archaean and eukaryotic organisms' genomes. In humans, their importance is emphasized as they represent 50% of all known drug targets. Nevertheless, experimental determination of their three-dimensional (3D) structure has proven to be both time consuming and rather expensive, which has led to the development of computational algorithms to complement the available experimental methods and provide valuable insights. Scope of review: This review highlights the importance of membrane proteins and how computational methods are capable of overcoming challenges associated with their experimental characterization. It covers various MP structural aspects, such as lipid interactions, allostery, and structure prediction, based on methods such as Molecular Dynamics (MD) and Machine-Learning (ML). Major conclusions: Recent developments in algorithms, tools and hybrid approaches, together with the increase in both computational resources and the amount of available data have resulted in increasingly powerful and trustworthy approaches to model MPs. General significance: Even though MPs are elementary and important in nature, the determination of their 3D structure has proven to be a challenging endeavor. Computational methods provide a reliable alternative to experimental methods. In this review, we focus on computational techniques to determine the 3D structure of MP and characterize their binding interfaces. We also summarize the most relevant databases and software programs available for the study of MPs. (C) 2017 Elsevier B.V. All rights reserved.
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