Brief. Bioinformatics - A practical guide for the computational selection of residues to be experimentally characterized in protein families.

Tópicos

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{ analysi(2126) use(1163) compon(1037) }
{ research(1085) discuss(1038) issu(1018) }
{ process(1125) use(805) approach(778) }
{ data(1714) softwar(1251) tool(1186) }
{ use(976) code(926) identifi(902) }
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{ model(3480) simul(1196) paramet(876) }
{ age(1611) year(1155) adult(843) }
{ group(2977) signific(1463) compar(1072) }
{ data(3008) multipl(1320) sourc(1022) }
{ activ(1452) weight(1219) physic(1104) }
{ detect(2391) sensit(1101) algorithm(908) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
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{ method(984) reconstruct(947) comput(926) }
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Resumo

In recent years, numerous biocomputational tools have been designed to extract functional and evolutionary information from multiple sequence alignments (MSAs) of proteins and genes. Most biologists working actively on the characterization of proteins from a single or family perspective use the MSA analysis to retrieve valuable information about amino acid conservation and the functional role of residues in query protein(s). In MSAs, adjustment of alignment parameters is a key point to improve the quality of MSA output. However, this issue is frequently underestimated and/or misunderstood by scientists and there is no in-depth knowledge available in this field. This brief review focuses on biocomputational approaches complementary to MSA to help distinguish functional residues in protein families. These additional analyses involve issues ranging from phylogenetic to statistical, which address the detection of amino acids pivotal for protein function at any level. In recent years, a large number of tools has been designed for this very purpose. Using some of these relevant, useful tools, we have designed a practical pipeline to perform in silico studies with a view to improving the characterization of family proteins and their functional residues. This review-guide aims to present biologists a set of specially designed tools to study proteins. These tools are user-friendly as they use web servers or easy-to-handle applications. Such criteria are essential for this review as most of the biologists (experimentalists) working in this field are unfamiliar with these biocomputational analysis approaches.

Resumo Limpo

recent year numer biocomput tool design extract function evolutionari inform multipl sequenc align msas protein gene biologist work activ character protein singl famili perspect use msa analysi retriev valuabl inform amino acid conserv function role residu queri protein msas adjust align paramet key point improv qualiti msa output howev issu frequent underestim andor misunderstood scientist indepth knowledg avail field brief review focus biocomput approach complementari msa help distinguish function residu protein famili addit analys involv issu rang phylogenet statist address detect amino acid pivot protein function level recent year larg number tool design purpos use relev use tool design practic pipelin perform silico studi view improv character famili protein function residu reviewguid aim present biologist set special design tool studi protein tool userfriend use web server easytohandl applic criteria essenti review biologist experimentalist work field unfamiliar biocomput analysi approach

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