Persistent spectral–based machine learning (PerSpect ML) for protein-ligand binding affinity prediction-Reference-Cited by-同舟云学术

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Persistent spectral–based machine learning (PerSpect ML) for protein-ligand binding affinity prediction

Published:2021-05-07 Issue:19 Volume:7 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Meng Zhenyu¹^ORCID,Xia Kelin¹^ORCID

Affiliation:

1. Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore.

Abstract

PerSpect-based machine learning models can significantly improve prediction accuracy for protein-ligand binding affinity.

Funder

National Supercomputer Centre in Guangzhou

Ministry of Education - Singapore

Nanyang Technological University

Kementerian Pendidikan Malaysia

Nanyang Techno logical University Startup

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference40 articles.

1. Machine learning in chemoinformatics and drug discovery

2. Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data Sets

3. Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening

4. A review of mathematical representations of biomolecular data

5. T. Puzyn J. Leszczynski M. T. Cronin Recent Advances in QSAR Studies: Methods and Applications (Springer Science & Business Media 2010) vol. 8.

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