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Jiankun Lyu¹, John J Irwin², Brian K Shoichet³

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Summary

Virtual libraries offer billions of molecules, but tangible libraries show decreased bio-like diversity. Larger libraries yield better fits but increase artifactual findings, requiring careful selection strategies.

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Area of Science:

Computational chemistry
Drug discovery
Bioinformatics

Background:

Virtual libraries provide vast molecular resources for drug discovery.
Prioritizing molecules for synthesis requires computational methods like molecular docking.
Library diversity and bio-likeness impact docking campaign success.

Purpose of the Study:

To compare the diversity and bio-likeness of 'in-stock' versus 'tangible' virtual libraries.
To analyze how receptor fit and artifacts change with increasing library size in docking.
To evaluate the impact of library size on identifying high-ranking and artifactual molecules.

Main Methods:

Comparative analysis of molecular libraries ('in-stock' vs. tangible).
Molecular docking simulations on ultra-large libraries.
Assessment of molecule similarity to bio-like compounds.
Evaluation of scoring functions and artifact identification across varying library sizes.

Main Results:

Tangible libraries exhibit a 19,000-fold decrease in bio-like molecule bias compared to 'in-stock' libraries.
Thousands of high-ranking molecules from ultra-large libraries are dissimilar to bio-like molecules.
Molecular docking scores improve log-linearly with library size, indicating better fits.
Rare molecules with artifactually high rankings increase with library size.

Conclusions:

Ultra-large virtual libraries, while offering more potential hits, contain significantly less bio-like diversity.
Increasing library size in docking improves hit quality but also amplifies artifactual results.
Simple strategies are necessary to mitigate the impact of artifacts in large-scale virtual screening.