کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6451301 1416279 2017 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Research ArticleA new search subspace to compensate failure of cavity-based localization of ligand-binding sites
ترجمه فارسی عنوان
مقاله پژوهشی: زیرمجموعه جستجو جدید برای جبران شکست محلول مبتنی بر حفره در سایت های اتصال لیگاند
کلمات کلیدی
سایت سازی مرتبط با لیگند، جستجوی زیرمجموعه، زبری خوشه اتمی پروتئین،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی بیو مهندسی (مهندسی زیستی)
چکیده انگلیسی


- A new R-subspace alternative to protein-cavity is proposed to localize binding sites.
- R-subspace is found to be better to localize ligand-binding site (LBS).
- Proteins for which cavity-subspace fails to localize LBS can be predicted.
- R-subspace compensates most of the cavity-failure cases.
- R-subspace and cavity-subspace complementarily enhance success rate to localize LBS.

The common exercise adopted in almost all the ligand-binding sites (LBS) predictive methods is to considerably reduce the search space up to a meager fraction of the whole protein. In this exercise it is assumed that the LBS are mostly localized within a search subspace, cavities, which topologically appear to be valleys within a protein surface. Therefore, extraction of cavities is considered as a most important preprocessing step for finally predicting LBS. However, prediction of LBS based on cavity search subspace is found to fail for some proteins. To solve this problem a new search subspace was introduced which was found successful to localize LBS in most of the proteins used in this work for which cavity-based method MetaPocket 2.0 failed. Therefore this work appeared to augment well the existing binding site predictive methods through its applicability for complementary set of proteins for which cavity-based methods might fail. Also, to decide on the proteins for which instead of cavity-subspace the new subspace should be explored, a decision framework based on simple heuristic is made which uses geometric parameters of cavities extracted through MetaPocket 2.0. It is found that option for selecting the new or cavity-search subspace can be predicted correctly for nearly 87.5% of test proteins.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Biology and Chemistry - Volume 68, June 2017, Pages 6-11
نویسندگان
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