J Chem Inf Model - Improved helix and kink characterization in membrane proteins allows evaluation of kink sequence predictors.

Tópicos

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Resumo

Although the a-helical secondary structure of proteins is well-defined, the exact causes and structures of helical kinks are not. This is especially important for transmembrane (TM) helices of integral membrane proteins, many of which contain kinks providing functional diversity despite predominantly helical structure. We have developed a Monte Carlo method based algorithm, MC-HELAN, to determine helical axes alongside positions and angles of helical kinks. Analysis of all nonredundant high-resolution a-helical membrane protein structures (842 TM helices from 205 polypeptide chains) revealed kinks in 64% of TM helices, demonstrating that a significantly greater proportion of TM helices are kinked than those indicated by previous analyses. The residue proline is over-represented by a factor >5 if it is two or three residues C-terminal to a bend. Prolines also cause kinks with larger kink angles than other residues. However, only 33% of TM kinks are in proximity to a proline. Machine learning techniques were used to test for sequence-based predictors of kinks. Although kinks are somewhat predicted by sequence, kink formation appears to be driven predominantly by other factors. This study provides an improved view of the prevalence and architecture of kinks in helical membrane proteins and highlights the fundamental inaccuracy of the typical topological depiction of helical membrane proteins as series of ideal helices.

Resumo Limpo

although ahel secondari structur protein welldefin exact caus structur helic kink especi import transmembran tm helic integr membran protein mani contain kink provid function divers despit predomin helic structur develop mont carlo method base algorithm mchelan determin helic axe alongsid posit angl helic kink analysi nonredund highresolut ahel membran protein structur tm helic polypeptid chain reveal kink tm helic demonstr signific greater proport tm helic kink indic previous analys residu prolin overrepres factor two three residu ctermin bend prolin also caus kink larger kink angl residu howev tm kink proxim prolin machin learn techniqu use test sequencebas predictor kink although kink somewhat predict sequenc kink format appear driven predomin factor studi provid improv view preval architectur kink helic membran protein highlight fundament inaccuraci typic topolog depict helic membran protein seri ideal helic

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