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Silencing the Spark: CRISPR/Cas9 Genome Editing in Weakly Electric Fish

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Tools for in silico target fishing.

Adrià Cereto-Massagué¹, María José Ojeda¹, Cristina Valls¹

¹Group of Cheminformatics & Nutrition, Biochemistry and Biotechnology Department, Universitat Rovira i Virgili (URV), Tarragona, Catalonia, Spain.

Methods (San Diego, Calif.)

|October 4, 2014

Summary

Computational target fishing predicts molecule targets, aiding drug discovery and functional food development. This review covers methods, databases, and tools for in silico target prediction.

Keywords:

Computational target fishing Drug repositioning Drug research Functional foods Polypharmacology Reverse screening

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Area of Science:

Computational chemistry
Pharmacology
Bioinformatics

Background:

Computational target fishing aims to identify molecular targets for query compounds.
This aids in predicting bioactivity, drug action, polypharmacology, repositioning, and adverse effects.
Abundant bioactivity data enables the development of these predictive methods.

Purpose of the Study:

To review computational target fishing methods.
To discuss commonly used bioactivity databases.
To present publicly available tools for non-specialists.

Main Methods:

Review of existing literature on in silico target fishing.
Analysis of similarity-based approaches (similar molecules bind to similar targets).
Identification of key bioactivity databases and software resources.

Main Results:

Numerous in silico target fishing methods have emerged, primarily based on molecular similarity.
Validation challenges complicate performance comparisons between methods.
A range of databases and user-friendly tools are available.

Conclusions:

Computational target prediction is a rapidly developing field with significant implications.
The methods discussed can accelerate drug development and innovation in the functional food sector.
Accessibility of tools empowers non-specialists in target prediction tasks.