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With advances in computational biology and cheminformatics, the use of computer-assisted methods in target identification has become more widespread. Among them, ligand-based methods have become the de facto standard for target identification because they do not rely on protein structures, previous experimental data, or complex computational training. Chemical similarity search is one of the most commonly used among ligand-based target identification methods. This method has been widely used in the field of drug target identification and virtual screening due to its efficiency, lack of complex pre-conditions, and high accuracy. Through this method, researchers are able to rapidly screen potential drug targets, thus providing important support for subsequent biological tests and drug development.
Fig 1. 3D similarity analysis. (LO, Y-C.; et al, 2016)
To perform a similarity search, molecules are encoded into substructure fingerprints, which highlight specific chemical features. The similarity between compounds is quantified using the Tanimoto index, measuring shared bits between fingerprint representations.
Query ligands are compared against a bioactivity database to identify highly similar annotated ligands. Putative drug targets are inferred from these high-similarity ligands, allowing researchers to hypothesize potential targets for the compound of interest.
Encoding Molecules as Fingerprints
Each molecule (both query compounds and those in the database) is encoded as a substructure fingerprint. These fingerprints are essentially bit vectors that represent the presence or absence of certain molecular features or substructures.
Quantifying Similarity
The degree of similarity between the fingerprints of different compounds is quantified using metrics such as the Tanimoto index. The Tanimoto index measures the ratio of shared bits to the total number of bits set in either fingerprint, providing a score between 0 and 1.
Searching Bioactivity Databases
The encoded fingerprints of query ligands are compared against a bioactivity database containing annotated ligands and their known targets.
Inferring Drug Targets
Based on the similarity scores, putative drug targets are inferred. The assumption is that if a query ligand is highly similar to a ligand in the database, it is likely to interact with the same biological targets.
At CD ComputaBio, we leverage the latest advancements in computational tools and comprehensive bioactivity databases to provide high-accuracy target identification services. Our expert team ensures that each query ligand is meticulously processed and analyzed, delivering reliable and insightful results to support your research endeavors. Partnering with us enables you to harness the power of ligand-based similarity searches, accelerating your path to novel drug discoveries and therapeutic innovations.
Contact us today to learn more about our target identification services and start your research with precision and confidence.
Reference
CD ComputaBio offers computation-driven peptide design services to research institutions, pharmaceutical, and biotechnology companies.
