Integrated Molecular Modeling and Machine Learning for Drug Design-Reference-Cited by-同舟云学术

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Integrated Molecular Modeling and Machine Learning for Drug Design

Published:2023-10-26 Issue:21 Volume:19 Page:7478-7495
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Xia Song¹,Chen Eric¹,Zhang Yingkai¹²³^ORCID

Affiliation:

1. Department of Chemistry, New York University, New York, New York 10003, United States

2. Simons Center for Computational Physical Chemistry at New York University, New York, New York 10003, United States

3. NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China

Funder

National Institute of General Medical Sciences

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.3c00814

Reference277 articles.

1. A Decade of FDA-Approved Drugs (2010–2019): Trends and Future Directions

2. 2020 FDA drug approvals

3. Research and Development Costs of New Drugs—Reply

4. In silico methods and tools for drug discovery

5. Computational approaches in target identification and drug discovery

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3. In Silico Identification of Selective KRAS G12D Inhibitor via Machine Learning‐Based Molecular Docking Combined with Molecular Dynamics Simulation;Advanced Theory and Simulations;2024-07-25

4. A Robust Induced Fit Docking Approach with the Combination of the Hybrid All-Atom/United-Atom/Coarse-Grained Model and Simulated Annealing;Journal of Chemical Theory and Computation;2024-07-05

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