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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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FastTargetPred: a program enabling the fast prediction of putative protein targets for input chemical databases
Ludovic Chaput1, Valentin Guillaume1, Natesh Singh1
1Univ. Lille, Inserm, Institut Pasteur de Lille, U1177-Drugs and Molecules for Living Systems, Lille F-59000, France.
Bioinformatics (Oxford, England)
|May 14, 2020
Summary
FastTargetPred is a new program for predicting protein targets of small molecules locally. It uses structural similarity to known bioactivities, enabling rapid annotation of large chemical libraries on personal computers.
Area of Science:
- Computational chemistry
- Drug discovery
- Bioinformatics
Background:
- Web-based tools predict small molecule targets using molecular fingerprints.
- Local computation of target predictions is often desirable.
Purpose of the Study:
- Introduce FastTargetPred, a novel program for local prediction of protein targets for small molecule queries.
- Enable efficient target prediction on personal computers.
Main Methods:
- Utilizes structural similarity computations based on protein-ligand activities from ChEMBL 25.
- Employs molecular fingerprints for similarity assessments.
- Written in Python 3 and C for cross-platform compatibility.
Main Results:
- FastTargetPred can annotate a chemical library of approximately 100,000 compounds within hours on a standard personal computer.
- Provides a local alternative to web-based prediction tools.
Conclusions:
- FastTargetPred offers a valuable solution for researchers needing to perform local small molecule target predictions.
- Facilitates efficient analysis of chemical libraries on accessible hardware.
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