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CIRCLE-Seq for Interrogation of Off-Target Gene Editing

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Published on: November 1, 2024

PatchSearch: A Fast Computational Method for Off-Target Detection.

Inès Rasolohery¹, Gautier Moroy¹, Frédéric Guyon¹

¹Molécules Thérapeutiques in Silico, UMRS 973, Université Paris Diderot, INSERM , F-75013 Paris, France.

Journal of Chemical Information and Modeling

|March 11, 2017

Summary

This summary is machine-generated.

Identifying unintended protein interactions, known as off-target binding, is crucial for drug safety. PatchSearch offers a novel computational method for early detection of potential off-targets, aiding in predicting and preventing adverse drug effects.

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Area of Science:

Computational chemistry
Drug discovery
Bioinformatics

Background:

Therapeutic molecules can interact with unintended proteins (off-targets), leading to adverse effects.
Early identification of off-targets is vital for drug safety and discovering new therapeutic applications.

Purpose of the Study:

To introduce PatchSearch, a novel computational program for identifying similar protein binding sites.
To enable early prediction of potential off-target interactions for therapeutic molecules.

Main Methods:

PatchSearch utilizes local nonsequential searching with controlled flexibility to compare protein surfaces.
The method is based on detecting quasi-cliques in product graphs representing structural matchings.
Benchmarked on diverse ligands and datasets ranging from 12 to over 7000 protein structures.

Main Results:

Demonstrated the utility of PatchSearch in identifying potential off-targets.
The method shows promise for early-stage drug development and safety assessment.
The PatchSearch program and benchmarks are available as an R package.

Conclusions:

PatchSearch provides a valuable tool for the early identification of off-target binding.
This computational approach can help mitigate adverse drug effects and optimize drug development.
The availability of the R package facilitates broader application and further research.