Work

Molecule discovery and optimization via evolutionary swarm intelligence

Year: 2024

Type: article

Abstract: Since the advent of computational analysis and visualization of chemical compounds, Computer-Aided Drug Design has made significant contributions to drug discovery. Recently, de novo drug design and molecular optimization have garnered considerable attention. Traditional optimization methods often struggle with the discrete nature of molecular space, but evolutionary computations have demonstrated their versatility across various optimization problems, regardless of the nature of the objective functions. This paper introduces a novel evolutionary algorithm, the Swarm Intelligence-Based Method for Single-Objective Molecular Optimization. Several experiments were conducted to showcase the efficiency of the proposed method, which identifies near-optimal solutions in a remarkably short time. The results were then compared with those of other state-of-the-art methods in the field.

Source: Scientific Reports

DOI: 10.1038/s41598-024-75515-w

Authors: Hsin-Ping Liu, Frederick Kin Hing Phoa, Saykat Dutta

Institutions: National Taiwan University, Institute of Statistical Science, Academia Sinica, Academia Sinica

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,590

Funders: Academia Sinica, National Taiwan University, National Science and Technology Council