{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T07:12:14Z","timestamp":1758265934598},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"S14","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2011,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Prediction of protein-ligand binding sites is an important issue for protein function annotation and structure-based drug design. Nowadays, although many computational methods for ligand-binding prediction have been developed, there is still a demanding to improve the prediction accuracy and efficiency. In addition, most of these methods are purely geometry-based, if the prediction methods improvement could be succeeded by integrating physicochemical or sequence properties of protein-ligand binding, it may also be more helpful to address the biological question in such studies.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>In our study, in order to investigate the contribution of sequence conservation in binding sites prediction and to make up the insufficiencies in purely geometry based methods, a simple yet efficient protein-binding sites prediction algorithm is presented, based on the geometry-based cavity identification integrated with sequence conservation information. Our method was compared with the other three classical tools: PocketPicker, SURFNET, and PASS, and evaluated on an existing comprehensive dataset of 210 non-redundant protein-ligand complexes. The results demonstrate that our approach correctly predicted the binding sites in 59% and 75% of cases among the TOP1 candidates and TOP3 candidates in the ranking list, respectively, which performs better than those of SURFNET and PASS, and achieves generally a slight better performance with PocketPicker.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>Our work has successfully indicated the importance of the sequence conservation information in binding sites prediction as well as provided a more accurate way for binding sites identification.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-12-s14-s9","type":"journal-article","created":{"date-parts":[[2011,12,14]],"date-time":"2011-12-14T19:40:45Z","timestamp":1323891645000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A new protein-ligand binding sites prediction method based on the integration of protein sequence conservation information"],"prefix":"10.1186","volume":"12","author":[{"given":"Tianli","family":"Dai","sequence":"first","affiliation":[]},{"given":"Qi","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Jun","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Zhiwei","family":"Cao","sequence":"additional","affiliation":[]},{"given":"Ruixin","family":"Zhu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2011,12,14]]},"reference":[{"issue":"Suppl","key":"4968_CR1","doi-asserted-by":"publisher","first-page":"991","DOI":"10.1038\/80784","volume":"7","author":"JM Thornton","year":"2000","unstructured":"Thornton JM, Todd AE, Milburn D, Borkakoti N, Orengo CA: From structure to function: approaches and limitations. 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