Expanding the conformational selection paradigm in protein-ligand docking

Area of Science:

• Biochemistry
• Structural Biology
• Drug Discovery

Background:

• Conformational selection is a prevalent mechanism in various macromolecular interactions, including protein-protein, protein-DNA, protein-RNA, and drug recognition.
• This mechanism involves a heterogeneous ensemble of protein conformations, where a ligand can bind to a specific, low-population state, inducing a population shift.

Purpose of the Study:

• To explore the application of conformational selection in improving drug docking and discovery.
• To propose an expanded strategy for modeling protein interactions and ensemble generation for drug discovery.

Main Methods:

• Utilizing an ensemble-based approach rather than single protein conformers.
• Modeling protein interactions using Prism, an efficient motif-based protein-protein interaction modeling strategy.
• Generating protein ensembles following interaction modeling.

Main Results:

• The study validates conformational selection as a fundamental mechanism in biomolecular recognition.
• The proposed strategy of modeling interactions followed by ensemble generation is suggested for practical application.

Conclusions:

• Expanding the conformational selection paradigm by integrating interaction modeling and ensemble generation can enhance drug discovery.
• This strategy is particularly relevant for signaling proteins, which are crucial drug targets and exhibit conformational changes upon binding multiple partners.