A computational method to simulate global conformational changes of proteins induced by cosolvent

Conformational Features and Hydration Dynamics of Proteins in Cosolvents: A Perspective from Computational Approaches

The importance of solvent in stabilizing protein structures has long been recognized. Water is the common solvent for proteins, and hydration is elemental in governing protein stability, flexibility, and function through various interactions. The addition of small organic molecules known as cosolvents may deploy stabilization (folding) or destabilization (unfolding) effects on native protein conformations. Despite exhaustive literature, the molecular mechanism by which cosolvents regulate protein conformations and dynamics is controversial. Specifically, the cosolvent behavior has been unpredictable with the nature and concentrations that lead to protein stabilizing/destabilizing effects as it changes in water content near the vicinity of proteins. With the massive development of computational resources, advancement of computational methods, and the availability of numerous experimental techniques, various theoretical and computational studies of proteins in a mixture of solvents have been instigated. The growing interest in such studies has been to unravel the underlying mechanism of protein folding and cosolvent/solvent-protein interactions that have significant implications in biomedical and biotechnological applications. In this mini-review, apart from the brief overview of important theories and force-field model-based cosolvent effects on proteins, we present the current state of knowledge and recent advances in the field to describe cosolvent-guided conformational features of proteins and hydration dynamics from computational approaches. The mini-review further explains the mechanistic details of protein stability in various popularly used cosolvents, including limitations of present studies and future outlooks. The counteracting effects of cosolvent on the proteins in the mixture of stabilizing and destabilizing cosolvents are also presented and discussed.

Computation of the Protein Conformational Transition Pathway on Ligand Binding by Linear Response-Driven Molecular Dynamics

While extremely important for relating the protein structure to its biological function, determination of the protein conformational transition pathway upon ligand binding is made difficult due to the transient nature of intermediates, a large and rugged conformational space, and coupling between protein dynamics and ligand-protein interactions. Existing methods that rely on prior knowledge of the bound (holo) state structure are restrictive. A second concern relates to the correspondence of intermediates obtained to the metastable states on the apo → holo transition pathway. Here, we have taken the protein apo structure and ligand-binding site as only inputs and combined an elastic network model (ENM) representation of the protein Hamiltonian with linear response theory (LRT) for protein-ligand interactions to identify the set of slow normal modes of protein vibrations that have a high overlap with the direction of the protein conformational change. The structural displacement along the chosen direction was performed using excited normal modes molecular dynamics (MDeNM) simulations rather than by the direct use of LRT. Herein, the MDeNM excitation velocity was optimized on-the-fly on the basis of its coupling to protein dynamics and ligand-protein interactions. Thus, a determined set of structures was validated against crystallographic and simulation data on four protein-ligand systems, namely, adenylate kinase-di(adenosine-5')pentaphosphate, ribose binding protein-β-d-ribopyranose, DNA β-glucosyltransferase-uridine-5'-diphosphate, and G-protein α subunit-guanosine-5'-triphosphate, which present important differences in protein conformational heterogeneity, ligand binding mechanism, viz. induced-fit or conformational selection, extent, and nonlinearity in protein conformational changes upon ligand binding, and presence of allosteric effects. The obtained set of intermediates was used as an input to path metadynamics simulations to obtain the free energy profile for the apo → holo transition.