Searching for allosteric effects via QSAR. Part II

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Pharmacology

Background:

• Traditional methods for characterizing allosteric interactions include X-ray crystallography and single-molecule studies.
• These methods can be resource-intensive and may not fully capture dynamic changes in molecular interactions.
• A need exists for alternative, predictive methods to understand complex allosteric modulation.

Purpose of the Study:

• To develop and validate a Quantitative Structure-Activity Relationship (QSAR) approach for identifying allosteric interaction mechanisms.
• To establish a method for detecting a critical 'inversion point' in molecular activity based on physicochemical properties.
• To demonstrate the broad applicability of this QSAR method across various receptor-ligand systems.

Main Methods:

• Utilized Quantitative Structure-Activity Relationship (QSAR) modeling.
• Introduced the concept of an 'inversion point' related to changes in molecular polarizability (measured by CMR).
• Analyzed a congeneric set of compounds interacting with diverse biological targets.

Main Results:

• Successfully established a method to identify changes in reaction mechanisms via an inversion point.
• Observed that increasing polarizability initially decreases activity, followed by an increase after the inversion point.
• 14 out of 23 examples demonstrated inversion points within a narrow range (10±1), indicating a consistent phenomenon.

Conclusions:

• The developed QSAR method provides a powerful tool for predicting and understanding allosteric interactions.
• The identification of an inversion point offers new insights into the mechanism of action for various ligands.
• This approach is effective across a wide spectrum of receptors, including thrombin, 5-HT, dopamine, and tyrosine kinase.