Author, as appears in the 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

Department: Bioquímica i Biotecnologia

URV's Author/s: 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

Keywords: 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

Abstract: 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.

Thematic Areas: 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

licence for use: https://creativecommons.org/licenses/by/3.0/es/

ISSN: 17568919

Author's mail: cristina.valls@urv.cat adrianjose.cereto@urv.cat raul.beltran@urv.cat gerard.pujadas@urv.cat santi.garcia-vallve@urv.cat montserrat.pinent@urv.cat miquel.mulero@urv.cat adrianjose.cereto@urv.cat

Author identifier: 0000-0001-5583-5695 0000-0001-9691-1906 0000-0003-2598-8089 0000-0002-0348-7497 0000-0003-3550-5378

Record's date: 2023-02-26

Journal volume: 11

Papper version: info:eu-repo/semantics/acceptedVersion

Link to the original source: https://www.future-science.com/doi/10.4155/fmc-2018-0597

Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/

Papper original source: Future Medicinal Chemistry. 11 (12): 1387-1401

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

Article's DOI: 10.4155/fmc-2018-0597

Entity: Universitat Rovira i Virgili

Journal publication year: 2019

Publication Type: Journal Publications