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Title | Membrane protein prediction methods. |
Publication Type | Journal Article |
Year of Publication | 2007 |
Authors | Punta, M, Forrest, LR, Bigelow, H, Kernytsky, A, Liu, J, Rost, B |
Journal | Methods |
Volume | 41 |
Issue | 4 |
Pagination | 460-74 |
Date Published | 2007 Apr |
ISSN | 1046-2023 |
Keywords | Biochemistry, Databases, Factual, Genomics, Membrane Proteins, Models, Chemical, Predictive Value of Tests, Protein Conformation, Structure-Activity Relationship |
Abstract | We survey computational approaches that tackle membrane protein structure and function prediction. While describing the main ideas that have led to the development of the most relevant and novel methods, we also discuss pitfalls, provide practical hints and highlight the challenges that remain. The methods covered include: sequence alignment, motif search, functional residue identification, transmembrane segment and protein topology predictions, homology and ab initio modeling. In general, predictions of functional and structural features of membrane proteins are improving, although progress is hampered by the limited amount of high-resolution experimental information available. While predictions of transmembrane segments and protein topology rank among the most accurate methods in computational biology, more attention and effort will be required in the future to ameliorate database search, homology and ab initio modeling. |
DOI | 10.1016/j.ymeth.2006.07.026 |
Alternate Journal | Methods |
PubMed ID | 17367718 |
PubMed Central ID | PMC1934899 |
Grant List | R01 LM007329-01A1 / LM / NLM NIH HHS / United States R01-GM64633-01 / GM / NIGMS NIH HHS / United States R01-LM07329-01 / LM / NLM NIH HHS / United States U54-GM75026-01 / GM / NIGMS NIH HHS / United States |