Autor segons l'article: 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
Departament: Bioquímica i Biotecnologia
Autor/s 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
Paraules clau: 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
Resum: 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.
Àrees temàtiques: 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
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 17568919
Adreça de correu electrònic de l'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 de l'autor: 0000-0001-5583-5695 0000-0003-3550-5378 0000-0002-0348-7497 0000-0003-2598-8089 0000-0001-9691-1906
Data d'alta del registre: 2024-07-27
Volum de revista: 11
Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
Enllaç font original: https://www.future-science.com/doi/10.4155/fmc-2018-0597
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Future Medicinal Chemistry. 11 (12): 1387-1401
Referència 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 de l'article: 10.4155/fmc-2018-0597
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2019
Tipus de publicació: Journal Publications
Repositori URV