Gufeng Yu, Kaiwen Yu, Xi Wang, Chenxi Zhang, Yicong Luo, Xiaohong Huo, Yang Yang
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引用次数: 0
Abstract
The design and optimization of chiral ligands and catalysts are fundamental to advancing asymmetric catalysis, a critical area in organic chemistry with wide-ranging impacts across scientific disciplines. Traditional experimental approaches, while essential, are often hindered by their slow pace and complexity. Recent advancements have demonstrated that computational methods, particularly machine learning, offer transformative potential by significantly accelerating these processes through enhanced prediction and modeling capabilities. However, limitations such as data scarcity and model inaccuracies continue to challenge their broader application. To address these issues, we present the Chiral Ligand and Catalyst Database (CLC-DB), the first open-source, comprehensive database specifically designed for chiral ligands and catalysts. CLC-DB contains 1,861 molecules spanning 32 distinctive chiral ligand and catalyst categories, with each entry annotated with 34 types of curated information, validated by chemical experts and linked to authoritative chemical databases. The database features a user-friendly interface that supports efficient single and batch searches, as well as an integrated, high-performance online molecular clustering tool to facilitate computational analyses. CLC-DB is freely accessible at https://compbio.sjtu.edu.cn/services/clc-db, where all data are available for download.
期刊介绍:
Journal of Cheminformatics is an open access journal publishing original peer-reviewed research in all aspects of cheminformatics and molecular modelling.
Coverage includes, but is not limited to:
chemical information systems, software and databases, and molecular modelling,
chemical structure representations and their use in structure, substructure, and similarity searching of chemical substance and chemical reaction databases,
computer and molecular graphics, computer-aided molecular design, expert systems, QSAR, and data mining techniques.