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

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Frog2: Efficient 3D conformation ensemble generator for small compounds.

Maria A Miteva¹, Frederic Guyon, Pierre Tufféry

¹MTi, INSERM UMR-S973, Université Paris Diderot-Paris 7, Bat. Lamarck case 7113, 35 rue H. Brion, F75205, Paris, France.

Nucleic Acids Research

|May 7, 2010

Summary

This summary is machine-generated.

Frog2 generates diverse 3D small molecule conformers from 1D, 2D, or 3D data. This enhanced web tool is up to 20x faster than Frog1, improving computational efficiency for drug discovery.

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Area of Science:

Computational chemistry
Cheminformatics
Drug discovery

Background:

Small molecule 3D structure generation is crucial for drug discovery.
Previous tools like Frog1 had limitations in speed and conformational diversity.
Efficient generation of diverse molecular conformations is computationally intensive.

Purpose of the Study:

To introduce Frog2, an improved web tool for generating small molecule 3D conformation ensembles.
To enhance the speed and quality of 3D conformer generation compared to its predecessor.
To enable the processing of larger compound libraries through optimized computational performance.

Main Methods:

Utilizes a two-stage Monte Carlo approach in dihedral space for conformer generation.
Accepts 1D (SMILES), 2D, or 3D (SDF, mol2) compound descriptions.
Incorporates novel energy minimization and ring generation functionalities.

Main Results:

Frog2 generates diverse ensembles of small molecule conformers.
Capable of handling ambiguous stereoisomerism and sampling different stereoisomers.
Achieves up to 20x speed improvement over Frog1 while maintaining structural quality.

Conclusions:

Frog2 offers a significant advancement in rapid and high-quality 3D small molecule conformer generation.
The enhanced speed and diversity make it suitable for large-scale compound library analysis.
The freely available web server facilitates its use in computational chemistry and drug discovery research.