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MolOptimizer: A Molecular Optimization Toolkit for Fragment-Based Drug Design.
Soffer, Adam; Viswas, Samuel Joshua; Alon, Shahar; Rozenberg, Nofar; Peled, Amit; Piro, Daniel; Vilenchik, Dan; Akabayov, Barak.
Afiliación
  • Soffer A; Department of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.
  • Viswas SJ; Data Science Research Centre, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.
  • Alon S; Department of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.
  • Rozenberg N; Data Science Research Centre, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.
  • Peled A; Department of Software Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.
  • Piro D; Department of Software Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.
  • Vilenchik D; Department of Software Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.
  • Akabayov B; Department of Software Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.
Molecules ; 29(1)2024 Jan 04.
Article en En | MEDLINE | ID: mdl-38202859
ABSTRACT
MolOptimizer is a user-friendly computational toolkit designed to streamline the hit-to-lead optimization process in drug discovery. MolOptimizer extracts features and trains machine learning models using a user-provided, labeled, and small-molecule dataset to accurately predict the binding values of new small molecules that share similar scaffolds with the target in focus. Hosted on the Azure web-based server, MolOptimizer emerges as a vital resource, accelerating the discovery and development of novel drug candidates with improved binding properties.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Diseño de Fármacos / Descubrimiento de Drogas Tipo de estudio: Prognostic_studies Idioma: En Revista: Molecules Asunto de la revista: BIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Israel Pais de publicación: Suiza
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Diseño de Fármacos / Descubrimiento de Drogas Tipo de estudio: Prognostic_studies Idioma: En Revista: Molecules Asunto de la revista: BIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Israel Pais de publicación: Suiza