From machine learning to deep learning: Advances in scoring functions for protein–ligand docking-Reference-Cited by-同舟云学术

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From machine learning to deep learning: Advances in scoring functions for protein–ligand docking

Published:2019-06-27 Issue:1 Volume:10 Page:
ISSN:1759-0876
Container-title:WIREs Computational Molecular Science
language:en
Short-container-title:WIREs Comput Mol Sci

Author:

Shen Chao¹,Ding Junjie²,Wang Zhe¹,Cao Dongsheng³,Ding Xiaoqin²,Hou Tingjun¹^ORCID

Affiliation:

1. Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University Hangzhou P. R. China

2. Beijing Institute of Pharmaceutical Chemistry Beijing P. R. China

3. Xiangya School of Pharmaceutical Sciences, Central South University Changsha P. R. China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Materials Chemistry,Computational Mathematics,Physical and Theoretical Chemistry,Computer Science Applications,Biochemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/wcms.1429

Reference170 articles.

1. Principles of early drug discovery

2. Efficient Drug Lead Discovery and Optimization

3. What has virtual screening ever done for drug discovery?

4. Virtual screening: an endless staircase?

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3. Improving the artificial bee colony algorithm with a proprietary estimation of distribution mechanism for protein–ligand docking;Applied Soft Computing;2024-08

4. Combining the Fragment Molecular Orbital and GRID Approaches for the Prediction of Ligand–Metalloenzyme Binding Affinity: The Case Study of hCA II Inhibitors;Molecules;2024-07-30

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