Predicting drug-likeness: why and how?

Area of Science:

• Drug Discovery and Development
• Computational Chemistry
• Pharmacology

Background:

• High attrition rates plague clinical trials, despite advances in high-throughput screening and combinatorial chemistry.
• Past decade's drug development efforts have yielded limited success, prompting a re-evaluation of fundamental requirements for drug candidates.
• Significant experimental and computational resources are now focused on identifying essential molecular properties for clinical success.

Purpose of the Study:

• To review the physiological, structural, and other critical requirements for developing successful drug molecules.
• To analyze and comment on current computational strategies employed in drug discovery.
• To bridge the gap between traditional computational chemistry and physiologically based simulations.

Main Methods:

• Literature review of physiological and structural requirements for drug candidates.
• Analysis of computational chemistry approaches focusing on molecular structure.
• Examination of physiologically based simulation methods used in pharmaceutical science.

Main Results:

• Identification of key physiological and structural determinants for drug efficacy and safety.
• Evaluation of the strengths and limitations of various computational drug discovery methodologies.
• Discussion on the integration of structure-based and simulation-based computational techniques.

Conclusions:

• Understanding fundamental molecular requirements is crucial to reduce clinical trial attrition.
• A comprehensive approach integrating structural and physiological considerations, aided by advanced computational methods, is vital for efficient drug development.
• Future pharmaceutical endeavors may benefit from re-organized strategies incorporating these insights.