Estimation of protein function using template-based alignment of enzyme active sites.
Estimation of protein function using template-based alignment of enzyme active sites.
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DOI：
10.1186/1471-2105-15-87
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发表时间：
2014-03-27
影响因子：
3
通讯作者：
Craig PA
中科院分区：
文献类型：
--
作者：
Hanson B;Westin C;Rosa M;Grier A;Osipovitch M;MacDonald ML;Dodge G;Boli PM;Corwin CW;Kessler H;McKay T;Bernstein HJ;Craig PA
The accumulation of protein structural data occurs more rapidly than it can be characterized by traditional laboratory means. This has motivated widespread efforts to predict enzyme function computationally. The most useful/accurate strategies employed to date are based on the detection of motifs in novel structures that correspond to a specific function. Functional residues are critical components of predictively useful motifs. We have implemented a novel method, to complement current approaches, which detects motifs solely on the basis of distance restraints between catalytic residues. ProMOL is a plugin for the PyMOL molecular graphics environment that can be used to create active site motifs for enzymes. A library of 181 active site motifs has been created with ProMOL, based on definitions published in the Catalytic Site Atlas (CSA). Searches with ProMOL produce better than 50% useful Enzyme Commission (EC) class suggestions for level 1 searches in EC classes 1, 4 and 5, and produce some useful results for other classes. 261 additional motifs automatically translated from Jonathan Barker’s JESS motif set [Bioinformatics 19:1644–1649, 2003] and a set of NMR motifs is under development. Alignments are evaluated by visual superposition, Levenshtein distance and root-mean-square deviation (RMSD) and are reasonably consistent with related search methods. The ProMOL plugin for PyMOL provides ready access to template-based local alignments. Recent improvements to ProMOL, including the expanded motif library, RMSD calculations and output selection formatting, have greatly increased the program’s usability and speed, and have improved the way that the results are presented.
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影响因子：
14.9
作者：
Ivanisenko, VA;Pintus, SS;Kolchanov, NA
通讯作者：
Kolchanov, NA
影响因子：
14.9
作者：
Debret, Gaelle;Martel, Arnaud;Cuniasse, Philippe
通讯作者：
Cuniasse, Philippe
影响因子：
14.9
作者：
Zhang, Z;Schaffer, AA;Altschul, SF
通讯作者：
Altschul, SF
影响因子：
17.3
作者：
Skolnick, J;Fetrow, JS
通讯作者：
Fetrow, JS
DOI：
10.1016/s0097-8485(98)00017-5
发表时间：
1998-01-01
期刊：
COMPUTERS & CHEMISTRY
影响因子：
--
作者：
Petitjean, M
通讯作者：
Petitjean, M