Transition Paths of Met-Enkephalin from Markov State Modeling of a Molecular Dynamics Trajectory

Digital nets conformational sampling (DNCS) - an enhanced sampling technique to explore the conformational space of intrinsically disordered peptides

We propose digital nets conformational sampling (DNCS) - an enhanced sampling technique to explore the conformational ensembles of peptides, especially intrinsically disordered peptides (IDPs). The DNCS algorithm relies on generating history-dependent samples of dihedral variables using bitwise XOR operations and binary angle measurements (BAM). The algorithm was initially studied using met-enkephalin, a highly elusive neuropeptide. The DNCS method predicted near-native structures and the energy landscape of met-enkephalin was observed to be in direct correlation with earlier studies on the neuropeptide. Clustering analysis revealed that there are only 24 low-lying conformations of the molecule. The DNCS method has then been tested for predicting optimal conformations of 42 oligopeptides of length varying from 3 to 8 residues. The closest-to-native structures of 86% of cases are near-native and 24% of them have a root mean square deviation of less than 1.00 Å with respect to their crystal structures. The results obtained reveal that the DNCS method performs well, that too in less computational time.

Energy Landscapes of a Pair of Adsorbed Peptides

The wide relevance of peptide adsorption in natural and synthetic contexts means it has attracted much attention. Molecular dynamics (MD) simulation has been widely used in these endeavors. Much of this has focused on single peptides due to the computational effort required to capture the rare events that characterize their adsorption. This focus is, however, of limited practical relevance as in reality, most systems of interest operate in the nondilute regime where peptides will interact with other adsorbed peptides. As an alternative to MD simulation, we have used energy landscape mapping (ELM) to investigate two met-enkephalin molecules adsorbed at a gas/graphite interface. Major conformations of the adsorbed peptides and the connecting transition states are elucidated along with the associated energy barriers and rates of exchange. The last of these makes clear that MD simulations are currently of limited use in probing the co-adsorption of two peptides, let alone more. The constant volume heat capacity as a function of temperature is also presented. Overall, this study represents a significant step toward characterizing peptide adsorption beyond the dilute limit.

Efficient maximum likelihood parameterization of continuous-time Markov processes

Continuous-time Markov processes over finite state-spaces are widely used to model dynamical processes in many fields of natural and social science. Here, we introduce a maximum likelihood estimator for constructing such models from data observed at a finite time interval. This estimator is dramatically more efficient than prior approaches, enables the calculation of deterministic confidence intervals in all model parameters, and can easily enforce important physical constraints on the models such as detailed balance. We demonstrate and discuss the advantages of these models over existing discrete-time Markov models for the analysis of molecular dynamics simulations.

Mechanical unfolding of a simple model protein goes beyond the reach of one-dimensional descriptions

We study the mechanical unfolding of a simple model protein. The Langevin dynamics results are analyzed using Markov-model methods which allow to describe completely the configurational space of the system. Using transition-path theory we also provide a quantitative description of the unfolding pathways followed by the system. Our study shows a complex dynamical scenario. In particular, we see that the usual one-dimensional picture: free-energy vs end-to-end distance representation, gives a misleading description of the process. Unfolding can occur following different pathways and configurations which seem to play a central role in one-dimensional pictures are not the intermediate states of the unfolding dynamics.