Discovering Highly Potent Molecules from an Initial Set of Inactives Using Iterative Screening-Reference-Cited by-同舟云学术

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Discovering Highly Potent Molecules from an Initial Set of Inactives Using Iterative Screening

Published:2018-08-21 Issue:9 Volume:58 Page:2000-2014
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Cortés-Ciriano Isidro¹^ORCID,Firth Nicholas C.²³,Bender Andreas¹^ORCID,Watson Oliver³

Affiliation:

1. Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom

2. Centre for Medical Image Computing, Department of Computer Science, UCL, London WC1E 6BT, United Kingdom

3. Evariste Technologies Ltd, Goring on Thames RG8 9AL, United Kingdom

Funder

Engineering and Physical Sciences Research Council

H2020 Marie Sklodowska-Curie Actions

FP7 Ideas: European Research Council

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.8b00376

Reference89 articles.

1. The rise of deep learning in drug discovery

2. Machine-learning approaches in drug discovery: methods and applications

3. Use of machine learning approaches for novel drug discovery

4. Machine learning in drug discovery and development

5. Large-scale prediction and testing of drug activity on side-effect targets

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1. MATEO: intermolecular α-amidoalkylation theoretical enantioselectivity optimization. Online tool for selection and design of chiral catalysts and products;Journal of Cheminformatics;2024-01-23

2. Iterative machine learning-based chemical similarity search to identify novel chemical inhibitors;Journal of Cheminformatics;2023-09-23

3. MATEO: InterMolecular α-Amidoalkylation Theoretical Enantioselectivity Optimization. Online Tool for Selection and Design of Chiral Catalysts and Products;2023-03-03

4. Machine Learning in Drug Design;The Handbook of Medicinal Chemistry;2023-02-03

5. Maximizing the integration of virtual and experimental screening in hit discovery;Expert Opinion on Drug Discovery;2022-06-03

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