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Drug Discovery: Overview

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...

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Updated: Sep 22, 2025

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

Creation of targeted compound libraries based on 3D shape recognition.

Andrii Kyrylchuk^1,2, Iryna Kravets^1,3, Anton Cherednichenko^1,3

¹Chemspace LLC, Kiev, Ukraine.

Molecular Diversity

|May 24, 2022

Summary

This study introduces a rapid, efficient workflow for virtual screening of large compound libraries in drug discovery. The method identifies novel drug candidates with desired properties and similar 3D shapes to reference molecules.

Keywords:

3D Shape recognition Computer-aided drug discovery Ligand-based drug discovery Novel chemotypes USRCAT

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Last Updated: Sep 22, 2025

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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

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Published on: June 20, 2025

Area of Science:

Computational Chemistry
Medicinal Chemistry
Drug Discovery

Background:

Ultra-large virtual chemical spaces require efficient screening methods for identifying bioactive molecules.
Existing virtual screening approaches may lack speed, computational efficiency, or the ability to expand chemical diversity.

Purpose of the Study:

To present a fast, resource-efficient, and simple workflow for screening targeted compound libraries from ultra-large virtual chemical spaces.
To identify compounds with similar 3D molecular shapes to reference compounds while expanding chemical diversity.
To enrich generated libraries with novel chemotypes and ensure desired physicochemical property distributions.

Main Methods:

Development of a computationally resource-efficient screening workflow.
Generation of targeted compound libraries from ultra-large virtual chemical space.
Tailoring of physicochemical parameters for search sets.
Visual inspection of identified structures for receptor binding similarity.

Main Results:

Successful creation of protein-targeted libraries: GPCRs Targeted Library (531K compounds) and Protein Kinases Targeted Library (113K compounds).
Demonstration of enrichment with novel chemotypes and desired property distributions.
Visual evidence of similar binding modes to reference compounds.

Conclusions:

The presented workflow is effective for rapid, efficient screening of large compound libraries in drug discovery.
The workflow facilitates the identification of novel, potentially active scaffolds with desired properties and binding characteristics.
The developed pipeline and scripts are publicly accessible, promoting further research and application.