Transformer-Based Generative Model Accelerating the Development of Novel BRAF Inhibitors-Reference-Cited by-同舟云学术

Transformer-Based Generative Model Accelerating the Development of Novel BRAF Inhibitors

Published:2021-12-01 Issue:49 Volume:6 Page:33864-33873
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Yang Lijuan¹²³⁴,Yang Guanghui¹⁴,Bing Zhitong¹⁴,Tian Yuan¹⁵,Niu Yuzhen⁶,Huang Liang²^ORCID,Yang Lei¹⁴^ORCID

Affiliation:

1. Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000, China

2. School of Physics and Technology, Lanzhou University, Lanzhou 730000, China

3. School of Physics, University of Chinese Academy of Sciences, Beijing 100049, China

4. Advanced Energy Science and Technology, Guangdong Laboratory, Huizhou 516000, China

5. School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China

6. Shandong Provincial Research Center for Bioinformatic Engineering and Technique, School of Life Sciences, Shandong University of Technology, Zibo 255000, China

Funder

Chinese Academy of Sciences

Guangdong Laboratory of Advanced Energy Science and Technology

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.1c05145

Reference35 articles.

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2. Deep Scoring Neural Network Replacing the Scoring Function Components to Improve the Performance of Structure-Based Molecular Docking

3. MONN: A Multi-objective Neural Network for Predicting Compound-Protein Interactions and Affinities

4. A Recent Appraisal of Artificial Intelligence and In Silico ADMET Prediction in the Early Stages of Drug Discovery

5. RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions

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