Current Physical Chemistry - Volume 2, Issue 4, 2012

Advances in theoretical methods, coupled with ever increasing computing power, mean that the techniques of quantum chemistry can now be routinely applied to biological molecules. This review will describe the current state of such calculations, ranging from high accuracy benchmark studies on model systems to efficient but more approximate description of entire macromolecules. Particular focus will be placed on recent developments in local correlation approaches, density functional theory (DFT), and semi-empirical methods, whose favorable scaling with system size bring realistic calculations within reach.

Computational tools have been used extensively to examine protein-protein and protein-ligand interactions. Continuum electrostatics calculations and molecular dynamics simulations can provide insight into the structural stability, binding, and function of proteins, and in turn can serve as predictive tools for guiding the design of experiments to probe specific molecular phenomena. In this review, we describe methods and tools used to understand protein interactions, and discuss steps taken toward improvement and optimization of these methods. We also describe a number of applications of in silico modeling tools to protein interactions with implications in pathogenic infections and autoimmune disorders.

Post-translational phosphorylation is a ubiquitous mechanism for cellular regulation, playing a crucial role in a diverse array of processes. At the molecular level, the phosphorylation seems to cause electrostatic perturbations which modulate the energy landscape governing protein folding, activity, protein-protein interactions and, conformational dynamics. However, details on structural effects induced by phosphorylation of proteins are still poorly understood. In this context, computational simulations recently provided a valuable alternative in the elucidation of principles and mechanisms of protein phosphorylation. In the present contribution, we review several recent studies devoted to molecular dynamics simulations of phospho-proteins with particular attention to proteins involved in the p53 pathway, ubiquitin pathway, protein kinases and intrinsically disordered proteins. Since application of biomolecular simulations to the investigation of mechanisms related to protein phospho-regulation is a newborn field for computational biology, our contribution could provide a suitable framework to plan future researches and to rationalize the available data in the field.

Located at the interface between the cell and organelle interior and exterior, membrane proteins are key players in a number of fundamental biological processes. In recent years, molecular dynamics simulations have become an increasingly important tool in the study of membrane proteins. Increases in computer power and the ongoing development in atomistic and coarse-grained MD techniques now permit simulations of membrane protein systems on a size and time scale that would have been impossible only a few years ago. At the beginning of each membrane protein simulation stands the generation of a suitable starting structure which can be done by either constructing the bilayer around the protein or by inserting the protein into a pre-equilibrated membrane patch. Here we review the current state of the art of the available techniques and carry out application benchmarks using five example membrane proteins of different size and transmembrane structure. We conclude this paper reviewing recent examples of molecular dynamics studies representing three major classes of membrane proteins: G protein-coupled receptors, channels and transporters.

Traditionally it has been assumed that drugs interact with membranes via specific binding with membrane proteins. This view has recently been questioned as more and more data support the perspective that membrane-mediated drug-protein interactions are also important, and some drugs interact directly with lipids too. Meanwhile unraveling the mechanisms of drug-induced effects on membranes is exceptionally difficult since the related phenomena take place over molecular scales in nanoseconds. In this review, we discuss how molecular simulations can be exploited to provide insight into these issues. In particular we discuss recent breakthroughs in this field and show the added value given by simulations in studies of drug-membrane interactions.

Replica-exchange molecular dynamics (REMD) method is one of the enhanced conformational sampling techniques in MD simulations of proteins or other systems with rugged-energy landscapes. In REMD method, copies of original simulation system at different temperatures are simulated separately and simultaneously. Every few steps, temperatures between neighboring replicas are exchanged if the Metropolis criteria for their instantaneous potential energies are satisfied. Due to its simplicity and high efficiency in parallel computers, the method has been applied to many biological problems including protein folding, aggregation, receptor-ligand binding, and so on. In the last ten years, continuous effort to improve sampling efficiency of REMD simulations for larger biological systems has been carried out by us and other theoretical scientists. In this review article, we introduce two different approaches in REMD simulations to reduce the computational cost. One is the multicanonical replica-exchange method (MUCAREM) for reducing the number of replicas. In this method, each replica has a different multicanonical weight factor and takes a flat energy distribution to cover a wider potential energy space. Another approach is to employ implicit solvent/membrane models for representing surrounding environments of target proteins in REMD simulations. We show two applications of proteinfolding simulations in explicit solvent using the former approach and a structural prediction of a transmembrane protein dimer using the latter. Finally, we discuss possibilities of REMD method to simulate a large-scale conformational change of protein systems using massively parallel supercomputers.

A new class of compounds, the large-ring cyclodextrins (LR-CDs), attracted attention in recent years, and advances were marked in the study of their physicochemical properties in spite of existing difficulties in their synthesis, isolation and purification. Practical applications were also reported of this new class of compounds. Understanding the mechanism of their action requires knowledge of the macroring conformational dynamics. In view of the difficulties with the experimental examination of the conformations of LR-CDs, computational modeling and simulation methods provide useful tool to gain information about their conformational dynamics, the energetics, and the complex-forming ability. This review summarizes our computational results on the conformations of large-ring cyclodextrins. There are ample evidences to attempt classification (according to their preferred conformation) of the LR-CDs in the range for DP from 10 to 30. Open bend boat-like macrorings are the representative conformations of CD10 to CD13. Two loops situated in mutually perpendicular planes (shaped as number eight) were clearly seen in the average structure of CD14. CD13 and CD14 mark the borderline between lower and higher flexibilities of the CDs macrorings. Two winded single helical strands, apposing each other at different directions, dominate in the structures of the next three LR-CDs (CD15 to CD17), although the CD14-like conformation was also monitored for some of them (CD15, CD17). Two pseudo-cavities with the sizes of α- CD and β-CD were displayed by the average conformations of CD15. These are favorable circumstances for CD14 and CD15 to display better inclusion properties in comparison to the neighbor LR-CDs of higher DP. An expected resemblance with circularized three-turn single helical structure was confirmed for CD21. The CDs from CD22 to CD25 may assume also CD21- and CD26-like conformations during some simulation intervals. Two representative conformations of CD26 (and the CDs in the close vicinity of CD26) are characterized by the presence of two elongated loops with one or two helical turns. A conformation of CD27 resembles the CD21-like circularized three-turn single helical structure. Thus, it is reasonable to assume the possibility for a gradual transition from the CD26 conformations down to the three-turn single helical structure for CD21. The macrorings larger that CD28 most probably can acquire arbitrary shapes with multiple small cavities. All results from our studies are in a support for the domination of representative preferred conformations with a specific shape of the smaller-size LR-CDs (CDn, n=10 to 30) for different ranges of the number of residues.

Conformational dynamics and flexibility form the link between protein structure and function. Molecular dynamics (MD) simulations have been valuable for our understanding of conformational energy landscape and protein dynamics at the atomic scale, which is difficult to probe experimentally. In this respect, the essential dynamics of proteins revealed by principal component analysis of MD simulation data provide information on functional motions that generally bear a collective nature. In this review, we summarize literature on statistical analysis of MD data with an emphasis on recent promising methods that can be applied to study the effect of ligand binding.