Fragment databases from screened ligands for drug discovery (FDSL-DD)-Reference-Cited by-同舟云学术

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Fragment databases from screened ligands for drug discovery (FDSL-DD)

Published:2024-03 Issue: Volume:127 Page:108669
ISSN:1093-3263
Container-title:Journal of Molecular Graphics and Modelling
language:en
Short-container-title:Journal of Molecular Graphics and Modelling

Author:

Wilson Jerica,Sokhansanj Bahrad A.,Chong Wei Chuen,Chandraghatgi Rohan,Rosen Gail L.,Ji Hai-Feng

Funder

NSF

Publisher

Elsevier BV

Subject

Materials Chemistry,Computer Graphics and Computer-Aided Design,Physical and Theoretical Chemistry,Spectroscopy

Reference31 articles.

1. Why 90% of clinical drug development fails and how to improve it?;Sun;Acta Pharm. Sin. B,2022

2. Computational approaches streamlining drug discovery;Sadybekov;Nature,2023

3. A critical overview of computational approaches employed for COVID-19 drug discovery;Muratov;Chem. Soc. Rev.,2021

4. Artificial intelligence to deep learning: machine intelligence approach for drug discovery;Gupta;Mol. Divers.,2021

5. Big data and artificial intelligence modeling for drug discovery;Zhu;Annu. Rev. Pharmacol. Toxicol.,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Streamlining Computational Fragment-Based Drug Discovery through Evolutionary Optimization Informed by Ligand-Based Virtual Prescreening;2023-11-28

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