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Chemical Fingerprints

Definition
Definition
Definition

Chemical fingerprints are compact, computer-readable representations of molecular structures, typically encoded as binary strings or bit vectors. Each bit in a fingerprint corresponds to the presence or absence of specific substructures, patterns, or molecular features, enabling rapid comparison, searching, and clustering of large chemical libraries. Fingerprints are compared through similarity coefficients like the Tanimoto coefficient that calculates the ratio of the number of shared features to the total number of unique features. Examples of fingerprints are MACCS keys where a bit corresponds to a specific substructure, and ECFP4 that encodes atomic environments up to a given radius.

Importance in Computational Drug Discovery:

  • Enables efficient similarity searching and clustering of vast compound libraries for hit identification and lead optimization.
  • Facilitates virtual screening by allowing rapid comparison of candidate molecules to known actives or reference structures.
  • Supports diversity analysis and compound selection for screening campaigns.
  • Underpins machine learning and cheminformatics workflows by providing standardized molecular descriptors.
  • Assists in scaffold hopping, analog searching, and structure–activity relationship (SAR) analysis.

Key Tools

  • RDKit: Open-source toolkit for generating and comparing chemical fingerprints (e.g., Morgan/ECFP, MACCS).
  • Open Babel: Converts molecular formats and computes various types of fingerprints.
  • ChemAxon JChem: Provides advanced fingerprinting and similarity search capabilities.
  • DataWarrior: Visualizes and analyzes chemical fingerprints for library design and SAR.
  • DeepOrigin (Balto): supports molecular similarity calculations (e.g. Tanimoto similarity) between molecules, which are typically based on underlying chemical fingerprints.

Literature

"Concepts and applications of chemical fingerprint for hit and lead discovery"

  • Publication Date: 2022
  • DOI: 10.1016/j.drudis.2022.103049
  • Summary: This comprehensive review provides guidance on selecting appropriate chemical fingerprints for various stages of drug research and development. It discusses the principles behind different fingerprint types and their applications in hit identification and lead optimization.

"Effectiveness of molecular fingerprints for exploring the chemical space and predicting bioactivity"

  • Publication Date: 2024
  • DOI: 10.1186/s13321-024-00830-3
  • Summary: This study evaluates the performance of various molecular fingerprints in capturing chemical diversity and predicting bioactivity. It emphasizes the importance of choosing the right fingerprint for specific tasks in virtual screening and drug discovery.

"One molecular fingerprint to rule them all: drugs, biomolecules, and the metabolome"

  • Publication Date: 2020
  • DOI: 10.1186/s13321-020-00445-4
  • Summary: This paper introduces the MAP4 fingerprint, designed to effectively represent both small molecules and larger biomolecules. The study demonstrates MAP4's utility in mapping chemical space and its potential as a universal fingerprint in drug discovery.

"An overview of molecular fingerprint similarity search in virtual screening"

  • Publication Date: 2016
  • DOI: 10.1517/17460441.2016.1117070
  • Summary: This article discusses the use of molecular fingerprints in similarity-based virtual screening. It covers the principles of fingerprint-based similarity searches and their role in identifying potential drug candidates.(jcheminf.biomedcentral.com)

"Are 2D fingerprints still valuable for drug discovery?"

  • Publication Date: 2020
  • DOI: 10.1039/D0CP00305K
  • Summary: This study evaluates the relevance of traditional 2D molecular fingerprints in the era of advanced 3D modeling and machine learning. It concludes that 2D fingerprints remain valuable tools in various drug discovery applications.(pubs.rsc.org)