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Waterdock 2.0: Water placement prediction for Holo-structures with a pymol plugin.
Sridhar, Akshay; Ross, Gregory A; Biggin, Philip C.
Afiliación
  • Sridhar A; Department of Biochemistry, University of Oxford, Oxford, United Kingdom.
  • Ross GA; Department of Biochemistry, University of Oxford, Oxford, United Kingdom.
  • Biggin PC; Department of Biochemistry, University of Oxford, Oxford, United Kingdom.
PLoS One ; 12(2): e0172743, 2017.
Article en En | MEDLINE | ID: mdl-28235019
Water is often found to mediate interactions between a ligand and a protein. It can play a significant role in orientating the ligand within a binding pocket and contribute to the free energy of binding. It would thus be extremely useful to be able to accurately predict the position and orientation of water molecules within a binding pocket. Recently, we developed the WaterDock protocol that was able to predict 97% of the water molecules in a test set. However, this approach generated false positives at a rate of over 20% in most cases and whilst this might be acceptable for some applications, in high throughput scenarios this is not desirable. Here we tackle this problem via the inclusion of knowledge regarding the solvation structure of ligand functional groups. We call this new protocol WaterDock2 and demonstrate that this protocol maintains a similar true positive rate to the original implementation but is capable of reducing the false-positive rate by over 50%. To improve the usability of the method, we have also developed a plugin for the popular graphics program PyMOL. The plugin also contains an implementation of the original WaterDock.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Unión Proteica / Programas Informáticos / Agua / Proteínas Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2017 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Unión Proteica / Programas Informáticos / Agua / Proteínas Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2017 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: Estados Unidos