日本プロテオーム学会大会要旨集
日本ヒトプロテオーム機構第6回大会
セッションID: ST-4
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Combining Computational and Experimental Approaches
*高本 圭司
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会議録・要旨集 フリー

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Our group has been developing an experimental technology called hydroxyl radical footprinting. This technology is an experimentally probe the solvent accessibility of protein surface by reaction with hydroxyl radical, which is highly reactive and almost same size as water molecule. The technology has been proved to be very successful for probing protein structure changes, protein/DNA binding and protein/protein interactions. These studies are only done with protein with solved structures since it is extremely difficult to interpret the data without knowing structures. The next logical step is to study on the proteins without solved structure. The computational modeling has been coming long way to achieve the place as regular structural biology tool. Ab initio or de novo prediction has achieved the level of accuracy that can be even used for molecular replacement for phasing in some cases. Rosetta is a powerful tool for de novo prediction, developed by Baker group. The critics for this approach are sometimes it predicts completely different fold, thus completely wrong structure. It is true for some cases for blind prediction such as CASP targets, as only criteria for structure selection are energy score and intuition if target sequence has no sequence identity high enough for comparative approach. The experimental data provide significant clues for such cases. The data have to be satisfied by predicted structure. Wrong fold usually has some inconsistency with experimental data. Baker group has been working on use of dipolar coupling data. Our group works with them for incorporating surface accessibility data into Rosetta protocols. For structure prediction, accessibility data indicate crucial information such as hydrophobic core residues. In the case of protein/protein interaction, accessibility data defines interaction interface directly. The study is still in early stage but we are having encouraging data. More detail and some real world work will be presented.

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