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Molekula

SMILES

SMILES (Simplified Molecular Input Line Entry System) is a notation for describing the structure of chemical molecules using short ASCII strings. It enables efficient data exchange, storage, and retrieval in cheminformatics and drug discovery workflows.

What is SMILES?

SMILES is a line notation used to represent the structure of chemical compounds in a human-readable and machine-processable format. Developed in the 1980s, it encodes molecular topology, atom types, bond orders, and stereochemistry using a standardised set of characters and rules. For example, ethanol is represented as CCO, while benzene is c1ccccc1. SMILES strings are widely used in cheminformatics for database indexing, molecular similarity searches, and virtual screening in drug discovery.

How is SMILES used in chemical data management?

In B2B procurement, regulatory compliance, and laboratory workflows, SMILES enables consistent representation of chemical entities across platforms. It supports integration with databases such as PubChem, ChEMBL, and Reaxys, and is essential for cheminformatics tools that predict physicochemical properties, toxicity, and biological activity. SMILES strings are also used in machine learning models for molecular property prediction, where they serve as input features for deep learning algorithms.

What are the limitations of SMILES?

While SMILES is widely adopted, it has limitations: multiple valid SMILES strings can represent the same molecule (isomeric and canonical forms), and the notation may not fully capture complex stereochemistry or tautomeric forms without additional annotations. Canonical SMILES, generated using standard algorithms, ensures unique representation for a given molecule, which is critical for database consistency and regulatory submissions.

Related concepts

SMILES is often used alongside other chemical identifiers such as InChI, CAS numbers, and molecular formulas. It is supported by cheminformatics software like RDKit, Open Babel, and ChemDraw, and is integral to regulatory submissions under frameworks such as REACH and TSCA.

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