What is it about?
This paper proposes a machine learning framework for drug molecular generation, based on SMILES representations and deep reinforcement learning algorithm. This method demonstrates its effectiveness in designing small molecule inhibitors that bind well with SARS-CoV-2 targets, which has great significance on global human health.
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Why is it important?
The SARS-CoV-2 virus has posed a severe crisis to humanity over the past few years, challenging the traditional drug development process which typically takes billions of dollars and several decades. Artificial intelligence has become a promising approach to enhance the efficiency of drug discovery, and this paper gives an automatic solution for drug molecular design for SARS-CoV-2 targets.
Perspectives
With the rapid development of AI in recent years, we believe it will change the world and benefit human lives in various fields. Many machine learning techniques have been introduced to AI for drug discovery, and our paper is one of them which will potentially change the paradigm of pharmacological research and promote human health in the future.
Liang Zhao
Kyoto University
Read the Original
This page is a summary of: De novo Drug Design against SARS-CoV-2 Protein Targets using SMILES-based Deep Reinforcement Learning, December 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3638985.3639012.
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