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Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

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Published on: May 16, 2021

Incorporating Virtual Reactions into a Logic-based Ligand-based Virtual Screening Method to Discover New Leads.

Christopher R Reynolds¹, Stephen H Muggleton², Michael J E Sternberg¹

¹Department of Bioinformatics, Imperial College London, South Kensington Campus London SW7 2AZ, UK.

Molecular Informatics

|November 20, 2015

Summary

This study introduces virtual reactions and a de novo design algorithm to explore vast chemical space for drug discovery. This method generates focused libraries of potential drug derivatives, significantly increasing the chances of finding molecules similar to known active compounds.

Keywords:

Ligand Machine learning Reactions Synthesis Virtual screening

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Area of Science:

Computational Chemistry
Drug Discovery
Medicinal Chemistry

Background:

Ligand-based virtual screening is crucial in drug development but limited by existing compound databases.
Exploring novel chemical space is essential for identifying new drug candidates.
Current methods struggle to represent the full potential of chemical diversity.

Purpose of the Study:

To develop a method for exploring synthetic chemical space beyond existing databases.
To generate focused libraries of predicted drug derivatives using virtual reactions.
To enhance the efficiency of drug discovery by identifying novel, potentially active molecules.

Main Methods:

Utilized the Investigational Novel Drug Discovery by Example (INDDEx) tool as a foundation for virtual reactions.
Developed and integrated the Partial Logical-Rule Reactant Selection (PLoRRS) de novo design algorithm.
Applied virtual reactions to promising compounds to generate focused libraries of derivatives.

Main Results:

Virtual reactions expand accessible chemical space to an estimated 1.21×10¹² potential molecules.
The PLoRRS method significantly increases the likelihood of retrieving molecules similar to known actives (p-value=0.016).
Case studies confirmed the generation of molecules highly similar to known active drugs.

Conclusions:

Virtual reactions combined with PLoRRS offer a powerful approach to explore and expand chemical space for drug discovery.
This methodology effectively generates focused libraries of novel compounds with high similarity to known drugs.
The system enhances the drug development pipeline by enabling the discovery of new potential therapeutics.