Adaptability in protein structures: structural dynamics and implications in ligand design

Abstract

The basic framework of understanding the mechanisms of protein functions is achieved from the knowledge of their structures which can model the molecular recognition. Recent advancement in the structural biology has revealed that in spite of the availability of the structural data, it is nontrivial to predict the mechanism of the molecular recognition which progresses via situation-dependent structural adaptation. The mutual selectivity of protein–protein and protein–ligand interactions often depends on the modulations of conformations empowered by their inherent flexibility, which in turn regulates the function. The mechanism of a protein’s function, which used to be explained by the ideas of ‘lock and key’ has evolved today as the concept of ‘induced fit’ as well as the ‘population shift’ models. It is felt that the ‘dynamics’ is an essential feature to take into account for understanding the mechanism of protein’s function. The design principles of therapeutic molecules suffer from the problems of plasticity of the receptors whose binding conformations are accurately not predictable from the prior knowledge of a template structure. On the other hand, flexibility of the receptors provides the opportunity to improve the binding affinity of a ligand by suitable substitution that will maximize the binding by modulating the receptors surface. In this paper, we discuss with example how the protein’s flexibility is correlated with its functions in various systems, revealing the importance of its understanding and for making applications. We also highlight the methodological challenges to investigate it computationally and to account for the flexible nature of the molecules in drug design.

Keywords:

• protein structure
• flexibility
• dynamics
• ligand design
• computer simulation

Acknowledgement

AM receives funding from CSIR (Government of India), SM is funded by CoE programme of DBT (Government of India) running at Bioinformatics Centre, Bose Institute. PP receives funding from UGC (Government of India). SS thanks Department of Biotechnology for Ramalingaswamy fellowship (BT/RLF/Re-entry/11/2011). The funding received by SGD from DBT (Government of India) vides the project no. BT/PR793/BID/7/370/2011 and has been supportive to this work.