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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

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Target essentiality and centrality characterize drug side effects.

Xiujuan Wang¹, Bram Thijssen, Haiyuan Yu

¹Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA.

Plos Computational Biology

|July 23, 2013

Summary

The number of essential protein targets, not total targets, dictates drug side effects. Drug target centrality and shared interaction interfaces also contribute to adverse effects, guiding rational drug design.

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Area of Science:

Pharmacology
Systems Biology
Computational Chemistry

Background:

Drug side effects pose a significant challenge in pharmaceutical development.
Understanding the molecular basis of drug side effects is crucial for improving drug safety and efficacy.

Purpose of the Study:

To systematically investigate the relationship between drug properties, human protein targets, and associated side effects.
To identify key factors determining the number and severity of drug-induced side effects.

Main Methods:

Systematic examination of 4,199 side effects across 996 drugs and their 647 human protein targets.
Analysis of drug-target interactions within a 3D network, considering target essentiality, centrality (degree and betweenness), and interface sharing.

Main Results:

The number of essential protein targets, rather than the total number of targets, is the primary determinant of drug side effects.
Drugs with more side effects target proteins with higher degree and betweenness centrality.
Highly shared interaction interfaces on drug targets correlate with increased drug side effects.

Conclusions:

Drug target essentiality and centrality are critical factors influencing drug side effects.
These findings provide valuable insights for rational drug design, aiming to minimize adverse effects.
Consideration of target network properties can lead to safer and more effective therapeutics.