Autor según el artículo: Ojeda-Montes M, Casanova-Martí À, Gimeno A, Tomás-Hernández S, Cereto-Massagué A, Wolber G, Beltrán-Debón R, Valls C, Mulero M, Pinent M, Pujadas G, Garcia-Vallvé S
Departamento: Bioquímica i Biotecnologia
Autor/es de la URV: Beltrán Debón, Raúl Alejandro / CASANOVA MARTÍ, ANGELA / Cereto Massagué, Adrián José / Garcia Vallve, Santiago / Mulero Abellán, Miguel / OJEDA MONTES, Mª JOSÉ / Pinent Armengol, Montserrat / Pujadas Anguiano, Gerard / TOMAS HERNÁNDEZ, SARA / Valls Bautista, Cristina
Palabras clave: Virtual screening Virtual molecular libraries Molecular fingerprints Expanding chemical space Diversifying molecular scaffolds Dipeptidyl peptidase 4 Cd26 virtual molecular libraries molecular fingerprints expanding chemical space diversifying molecular scaffolds dipeptidyl peptidase 4 cd26
Resumen: Aim: Fragment-based drug design or bioisosteric replacement is used to find new actives with low (or no) similarity to existing ones but requires the synthesis of nonexisting compounds to prove their predicted bioactivity. Protein-ligand docking or pharmacophore screening are alternatives but they can become computationally expensive when applied to very large databases such as ZINC. Therefore, fast strategies are necessary to find new leads in such databases. Materials & methods: We designed a computational strategy to find lead molecules with very low (or no) similarity to existing actives and applied it to DPP-IV. Results: The bioactivity assays confirm that this strategy finds new leads for DPP-IV inhibitors. Conclusion: This computational strategy reduces the time of finding new lead molecules.
Áreas temáticas: Saúde coletiva Química Pharmacology Odontología Molecular medicine Medicina ii General medicine Farmacia Engenharias iv Enfermagem Drug discovery Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciência da computação Chemistry, medicinal Biotecnología Astronomia / física
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 17568919
Direcció de correo del autor: adrianjose.cereto@urv.cat cristina.valls@urv.cat miquel.mulero@urv.cat montserrat.pinent@urv.cat santi.garcia-vallve@urv.cat gerard.pujadas@urv.cat raul.beltran@urv.cat
Identificador del autor: 0000-0001-5583-5695 0000-0003-3550-5378 0000-0002-0348-7497 0000-0003-2598-8089 0000-0001-9691-1906
Fecha de alta del registro: 2024-07-27
Volumen de revista: 11
Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
Enlace a la fuente original: https://www.future-science.com/doi/10.4155/fmc-2018-0597
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
Referencia al articulo segun fuente origial: Future Medicinal Chemistry. 11 (12): 1387-1401
Referencia de l'ítem segons les normes APA: Ojeda-Montes M, Casanova-Martí À, Gimeno A, Tomás-Hernández S, Cereto-Massagué A, Wolber G, Beltrán-Debón R, Valls C, Mulero M, Pinent M, Pujadas G, G (2019). Mining large databases to find new leads with low similarity to known actives: application to find new DPP-IV inhibitors. Future Medicinal Chemistry, 11(12), 1387-1401. DOI: 10.4155/fmc-2018-0597
DOI del artículo: 10.4155/fmc-2018-0597
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2019
Tipo de publicación: Journal Publications
Repositori URV