Multiscale Simulations of Biological Membranes : The Challenge To Understand Biological Phenomena in a Living Substance

Biological membranes are tricky to investigate. They are complex in terms of molecular composition and structure, functional over a wide range of time scales, and characterized by nonequilibrium conditions. Because of all of these features, simulations are a great technique to study biomembrane behavior. A significant part of the functional processes in biological membranes takes place at the molecular level; thus computer simulations are the method of choice to explore how their properties emerge from specific molecular features and how the interplay among the numerous molecules gives rise to function over spatial and time scales larger than the molecular ones. In this review, we focus on this broad theme. We discuss the current state-of-the-art of biomembrane simulations that, until now, have largely focused on a rather narrow picture of the complexity of the membranes. Given this, we also discuss the challenges that we should unravel in the foreseeable future. Numerous features such as the actin-cytoskeleton network, the glycocalyx network, and nonequilibrium transport under ATP-driven conditions have so far received very little attention; however, the potential of simulations to solve them would be exceptionally high. A major milestone for this research would be that one day we could say that computer simulations genuinely research biological membranes, not just lipid bilayers.Peer reviewe

Methods used to study the oligomeric structure of G protein-coupled receptors

G-protein coupled receptors (GPCRs), which constitute the largest family of cell surface receptors, were originally thought to function as monomers, but are now recognized as being able to act in a wide range of oligomeric states and indeed, it is known that the oligomerization state of a GPCR can modulate its pharmacology and function. A number of experimental techniques have been devised to study GPCR oligomerization including those based upon traditional biochemistry such as blue-native polyacrylamide gel-electrophoresis (BN-PAGE), co-immunoprecipitation and protein-fragment complementation assays, those based upon resonance energy transfer, fluorescence resonance energy transfer (FRET), time-resolved FRET, FRET spectrometry and bioluminescence resonance energy transfer (BRET). Those based upon microscopy such as fluorescence recovery after photo-bleaching (FRAP), total internal reflection fluorescence microscopy (TIRF), spatial intensity distribution analysis (SpIDA) and various single molecule imaging techniques. Finally with the solution of a growing number of crystal structures, X-ray crystallography must be acknowledged as an important source of discovery in this field. A different, but in many ways complementary approach to the use of more traditional experimental techniques, are those involving computational methods which possess obvious merit in the study of the dynamics of oligomer formation and function. Here we summarize the latest developments which have been made in the methods used to study GPCR oligomerization and give an overview of their application

Biomolecular simulations: From dynamics and mechanisms to computational assays of biological activity

Biomolecular simulation is increasingly central to understanding and designing biological molecules and their interactions. Detailed, physics‐based simulation methods are demonstrating rapidly growing impact in areas as diverse as biocatalysis, drug delivery, biomaterials, biotechnology, and drug design. Simulations offer the potential of uniquely detailed, atomic‐level insight into mechanisms, dynamics, and processes, as well as increasingly accurate predictions of molecular properties. Simulations can now be used as computational assays of biological activity, for example, in predictions of drug resistance. Methodological and algorithmic developments, combined with advances in computational hardware, are transforming the scope and range of calculations. Different types of methods are required for different types of problem. Accurate methods and extensive simulations promise quantitative comparison with experiments across biochemistry. Atomistic simulations can now access experimentally relevant timescales for large systems, leading to a fertile interplay of experiment and theory and offering unprecedented opportunities for validating and developing models. Coarse‐grained methods allow studies on larger length‐ and timescales, and theoretical developments are bringing electronic structure calculations into new regimes. Multiscale methods are another key focus for development, combining different levels of theory to increase accuracy, aiming to connect chemical and molecular changes to macroscopic observables. In this review, we outline biomolecular simulation methods and highlight examples of its application to investigate questions in biology. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Free Energy Method

Computational Modeling of Realistic Cell Membranes

Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead

Exploring the boundaries of molecular modeling : a study of nanochannels and transmembrane proteins

Many interesting physical and biological phenomena can be investigated using molecular modeling techniques, either theoretically or by using computer simulation methods, such as molecular dynamics and Monte Carlo simulations. Due to the increasing power of computer processing units, these simulation methods allowed over the last decades for the dramatic increase in knowledge of the behavior of systems at the molecular level. In the first part of this thesis the foundations of molecular modeling techniques are revisited. Empirical force fields and the physical background between thermodynamics and individual particles are discussed. The applicability of molecular modeling techniques is shown by two representative cases. First, the molecular dynamics simulation method is used to understand the dynamics of specific proteins at the molecular level. This is important, because drug design efforts are increasingly laborious, especially with the paucity of available structural information. Therefore, computational methods are helpful in predicting the structure of proteins, and, more importantly, to predict conformational dynamics leading to protein activation. To that end a specific asthma-related protein, the beta2-adrenergic receptor, is investigated in atomistic detail together with the molecules that can bind to the protein to cause activation or inhibition. Clearly, molecular dynamics simulations are an important tool to provide further knowledge on the activation pathway of this protein. Although these all-atom simulations give some insight on the dynamics, the computational demand does not allow for systems much larger than several nanometers or time scales exceeding several nanoseconds. An attempt to overcome these problems is presented by the development of a coarse grained description of the transmembrane proteins. Because coarse graining reduces the number of degrees of freedom, the computational demands decrease, and larger systems can be investigated. However, to maintain the specific characteristics of transmembrane proteins, the general force field used in molecular modeling techniques needs to be extended with hydrogen bonding capabilities and helical backbone stabilization. This new coarse grained model is applicable to transmembrane proteins, and is used to investigate two independent cases: WALP-peptides and antimicrobial peptides. The first serve as a model system for both experiments and theory to investigate the interaction between transmembrane peptides and lipid membranes, whereas the latter are antibiotics whose pore-forming capacities are of great interest to act as target-specific drug candidates. From the molecular dynamics simulations of the WALP-peptides it is shown that the apparent hydrophobic mismatch between peptide and membrane can be resolved by two mechanisms (membrane thickness adaptation and peptide tilting) and that these two mechanisms occur sequential and not in parallel. In the case of the antimicrobial peptides it is shown that many of the orientations found with the molecular simulation techniques are in agreement with experimental observations. The second case to show the applicability of the molecular modeling techniques is that of the heat transfer characteristics of gas flows in nanochannels. Understanding these characteristics is important, because these very small channels are considered to be promising devices to locally cool systems (such as computer processing units) or to be used in lab-on-chip devices for at home medical diagnostics. Thus, understanding the interactions between the channel walls and the gas flow is of great importance. Unfortunately, the computational cost involved in simulating the solid wall, currently restrains the size of the systems that can be investigated using molecular dynamics simulations. Therefore, instead of the explicit modeling of the solid wall, appropriate boundary conditions are used, such as wall potentials or stochastic models. Both of these boundary conditions are examined in great detail and a new wall potential is presented. Also the investigations of a specific case of a channel with platinum walls with a noble gas (argon or xenon) in between allows to introduce a new method to compute an important heat transfer determining parameter. Furthermore, it is shown that both boundary conditions have their benefits and drawbacks, and that the use of either one depends heavily on the application under consideration. Both cases used to show the applicability of molecular modeling techniques, although very different from each other, indicate the importance of particle simulation methods. Investigating the interactions at the molecular level, and the development of new models allows for an even better understanding of underlying molecular processes

Computational Approaches for the Characterization of the Structure and Dynamics of G Protein-Coupled Receptors: Applications to Drug Design

G Protein-Coupled Receptors (GPCRs) constitute the most pharmacologically relevant superfamily of proteins. In this thesis, a computational pipeline for modelling the structure and dynamics of GPCRs is presented, properly combined with experimental collaborations for GPCR drug design. These include the discovery of novel scaffolds as potential antipsychotics, and the design of a new series of A3 adenosine receptor antagonists, employing successful combinations of structure- and ligand-based approaches. Additionally, the structure of Adenosine Receptors (ARs) was computationally assessed, with implications in ligand affinity and selectivity. The employed protocol for Molecular Dynamics simulations has allowed the characterization of structural determinants of the activation of ARs, and the evaluation of the stability of GPCR dimers of CXCR4 receptor. Finally, the computational pipeline here developed has been integrated into the web server GPCR-ModSim (http://gpcr.usc.es), contributing to its application in biochemical and pharmacological studies on GPCRs

Mechanistic Understanding From Molecular Dynamics Simulation in Pharmaceutical Research 1 : Drug Delivery

In this review, we outline the growing role that molecular dynamics simulation is able to play as a design tool in drug delivery. We cover both the pharmaceutical and computational backgrounds, in a pedagogical fashion, as this review is designed to be equally accessible to pharmaceutical researchers interested in what this new computational tool is capable of and experts in molecular modeling who wish to pursue pharmaceutical applications as a context for their research. The field has become too broad for us to concisely describe all work that has been carried out; many comprehensive reviews on subtopics of this area are cited. We discuss the insight molecular dynamics modeling has provided in dissolution and solubility, however, the majority of the discussion is focused on nanomedicine: the development of nanoscale drug delivery vehicles. Here we focus on three areas where molecular dynamics modeling has had a particularly strong impact: (1) behavior in the bloodstream and protective polymer corona, (2) Drug loading and controlled release, and (3) Nanoparticle interaction with both model and biological membranes. We conclude with some thoughts on the role that molecular dynamics simulation can grow to play in the development of new drug delivery systems.Peer reviewe

Emerging Diversity in Lipid-Protein Interactions

Membrane lipids interact with proteins in a variety of ways, ranging from providing a stable membrane environment for proteins to being embedded in to detailed roles in complicated and well-regulated protein functions. Experimental and computational advances are converging in a rapidly expanding research area of lipid-protein interactions. Experimentally, the database of high-resolution membrane protein structures is growing, as are capabilities to identify the complex lipid composition of different membranes, to probe the challenging time and length scales of lipid-protein interactions, and to link lipid-protein interactions to protein function in a variety of proteins. Computationally, more accurate membrane models and more powerful computers now enable a detailed look at lipid-protein interactions and increasing overlap with experimental observations for validation and joint interpretation of simulation and experiment. Here we review papers that use computational approaches to study detailed lipid-protein interactions, together with brief experimental and physiological contexts, aiming at comprehensive coverage of simulation papers in the last five years. Overall, a complex picture of lipid-protein interactions emerges, through a range of mechanisms including modulation of the physical properties of the lipid environment, detailed chemical interactions between lipids and proteins, and key functional roles of very specific lipids binding to well-defined binding sites on proteins. Computationally, despite important limitations, molecular dynamics simulations with current computer power and theoretical models are now in an excellent position to answer detailed questions about lipid-protein interactions