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Recognizing pitfalls in virtual screening: a critical review.

Thomas Scior¹, Andreas Bender, Gary Tresadern

¹Pharmacy Department, Facultad de Ciencias Químicas, Universidad Autónoma de Puebla, Puebla, Pue, México. tscior@gmail.com

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|March 23, 2012

Summary

This summary is machine-generated.

Virtual screening (VS) computationally identifies bioactive compounds. This review details common pitfalls in VS methods to improve the accuracy and efficiency of drug discovery.

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Area of Science:

Computational chemistry
Cheminformatics
Drug discovery

Background:

Virtual screening (VS) computationally identifies bioactive compounds using protein targets or known ligands.
VS ranks molecules by bioactivity likelihood, aiming to enrich top-ranked compounds for bioassays.
Maximizing the true positive rate is core to VS, prioritizing active molecules.

Purpose of the Study:

To catalogue known and unknown problems, failures, and technical traps in virtual screening methods.
To provide awareness of potential pitfalls to enhance the efficiency and utility of VS.
To guide researchers in choosing optimal VS approaches and parameters.

Main Methods:

Review of published and unpublished virtual screening (VS) literature.
Cataloguing of common issues, shortcomings, and failures associated with VS techniques.
Analysis of factors influencing the balance between efficiency and accuracy in VS algorithms.

Main Results:

Identification of numerous pitfalls that can reduce VS efficiency or render it ineffective.
Understanding of how different VS methods perform in specific situations.
Insights into the prospective utility of VS methods based on retrospective results.

Conclusions:

Awareness of VS pitfalls is crucial for successful computational drug discovery.
Careful consideration of algorithms, parameters, and datasets is necessary to avoid common traps.
This review serves as a guide to navigate the complexities of virtual screening for improved outcomes.