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In silico ADME/T modelling for rational drug design
Yulan Wang1, Jing Xing1, Yuan Xu1
1Drug Discovery and Design Center, State Key Laboratory of Drug Research,Shanghai Institute of Materia Medica,Chinese Academy of Sciences,555 Zuchongzhi Road,Shanghai 201203,China.
Quarterly Reviews of Biophysics
|September 3, 2015
Summary
In silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) models aid rational drug design. While valuable for streamlining development, their predictive accuracy for complex mechanisms requires further enhancement.
Area of Science:
- Pharmacology and Cheminformatics
- Computational Drug Discovery
Background:
- In silico ADME/T models are crucial for rational drug design, offering high-throughput and cost-effective analysis.
- These models guide hit identification and structural optimization by assessing bioavailability and safety alongside activity.
Purpose of the Study:
- To review the development of in silico models for physicochemical parameters, ADME properties, and toxicity.
- To emphasize modeling approaches, applications in drug discovery, and model limitations.
- To discuss future directions in ADME/T modeling using big data and systems science.
Main Methods:
- Review of existing literature on in silico ADME/T modeling approaches.
- Analysis of model applications in various stages of drug discovery.
- Evaluation of model strengths, weaknesses, and future potential.
Main Results:
- In silico ADME/T models have advanced significantly, supporting early-stage drug development.
- Predictive capabilities vary, with limitations in complex mechanistic endpoints.
- Current models offer valuable insights but require further refinement for optimal candidate selection.
Conclusions:
- In silico ADME/T modeling is an indispensable tool in modern drug discovery.
- Continued development, particularly leveraging big data and systems science, is essential for improving predictive accuracy.
- Future models promise more robust support for drug development pipelines.
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