Elucidation of the ligand/protein binding interaction is of paramount relevance in pharmacology to increase the success rate of drug design. To this end a number of computational methods have been proposed, however all of them suffer from limitations since the ligand binding/unbinding transitions to the molecular target involve many slow degrees of freedom that hamper a full characterization of the binding process.

Many processes of scientific importance are characterized by time scales that extend far beyond the reach of standard simulation techniques. To circumvent this impediment a plethora of enhanced sampling methods has been developed. One important class of such methods relies on the application of a bias that is function of a set of collective variables specially designed for the problem under consideration. The design of good collective variables can be challenging and thereby constitutes the main bottle neck in the application of these methods. To address this problem, recently we have introduced Harmonic Linear Discriminant Analysis, a method to systematically construct collective variables. The method uses as input information on the metastable states visited during the process that is being considered, information that can be gathered in short unbiased MD simulations, to construct the collective variables as linear combinations of a set of descriptors.Here, to scale up our examination of the method's efficiency, we applied it to the folding of Chignolin in water. Interestingly, already before any biased simulations were run, the constructed one dimensional collective variable revealed much of the physics that underlies the folding process. In addition, using it in Metadynamics we were able to run simulations in which the system goes from the folded state to the unfolded one and back, where to get fully converged results we combined Metadynamics with Parallel Tempering. Finally, we examined how the collective variable performs when different sets of descriptors are used in its construction.

We present a novel transition path sampling shooting algorithm for the efficient sampling of complex (biomolecular) activated processes with asymmetric free energy barriers. The method employs a fictitious potential that biases the shooting point toward the transition state. The method is similar in spirit to the aimless shooting technique by Peters and Trout [J. Chem. Phys. 125, 054108 (2006)], but is targeted for use with the one-way shooting approach, which has been shown to be more effective than two-way shooting algorithms in systems dominated by diffusive dynamics. We illustrate the method on a 2D Langevin toy model, the association of two peptides and the initial step in dissociation of a β-lactoglobulin dimer. In all cases we show a significant increase in efficiency.

As water is an essential ingredient in protein structure, dynamics, and functioning, knowledge of its behavior near proteins is crucial. We investigate water dynamics around bovine α-lactalbumin by combining molecular dynamics simulations with polarization-resolved femtosecond infrared (fs-IR) spectroscopy. We identify slowly reorienting surface waters and establish their hydrogen-bond lifetime and reorientation dynamics, which we compare to the experimentally measured anisotropy decay. The calculated number of slow surface waters is in reasonable agreement with the results of fs-IR experiments. While surface waters form fewer hydrogen bonds than the bulk, within the hydration layer water is slower when donating more hydrogen bonds. At concave sites the protein-water hydrogen bonds break preferably via translational diffusion rather than via a hydrogen-bond jump mechanism. Water molecules reorient slower near these sites than at convex water-exposed sites. Protein misfolding leads to an increased exposure of hydrophobic groups, inducing relatively faster surface water dynamics. Nevertheless, the larger exposed surface slows down a larger amount of water. While for native proteins hydrating water is slower near hydrophobic than near hydrophilic residues, mainly due to stronger confinement, misfolding causes hydrophobic water to reorient relatively faster because exposure of hydrophobic groups destroys concave protein cavities with a large excluded volume.