chemoinformatic

Chemoinformatics, also spelled cheminformatics or chemoinformatics, is an interdisciplinary field that applies informatics, computer science, mathematics, and statistics to chemical data and problems. It covers methods for storing, indexing, searching, and analyzing chemical information and aims to support chemical design, discovery, and understanding.

Key techniques include representations of molecular structures using SMILES and InChI, descriptors and fingerprints, database mining, quantitative structure–activity relationships (QSAR), quantitative structure–property relationships (QSPR), machine learning, virtual screening, molecular docking, and pharmacophore modeling. The field combines experimental data with computational models to predict properties such as activity, toxicity, solubility, and permeability, helping guide research decisions.

Common data resources include PubChem, ChEMBL, ChEBI, and ZINC, along with corporate repositories. Open-source tools such as RDKit, Open Babel, the CDK, and workflow platforms like KNIME enable tasks from fingerprinting to model building.

In industry, chemoinformatics supports drug discovery, materials science, agrochemicals, and environmental chemistry; in academia, it underpins chemical biology and systems chemistry.

Historically, the integration of chemistry with computation advanced in the late 20th century with QSAR methods and digital databases. Today chemoinformatics is a core component of computational chemistry and data-driven chemical research.