Biomolecular simulation: a computational microscope for molecular biology

The Theory of Ultra-Coarse-Graining. 1. General Principles

Coarse-grained (CG) models provide a computationally efficient means to study biomolecular and other soft matter processes involving large numbers of atoms correlated over distance scales of many covalent bond lengths and long time scales. Variational methods based on information from simulations of finer-grained (e.g., all-atom) models, for example the multiscale coarse-graining (MS-CG) and relative entropy minimization methods, provide attractive tools for the systematic development of CG models. However, these methods have important drawbacks when used in the "ultra-coarse-grained" (UCG) regime, e.g., at a resolution level coarser or much coarser than one amino acid residue per effective CG particle in proteins. This is due to the possible existence of multiple metastable states "within" the CG sites for a given UCG model configuration. In this work, systematic variational UCG methods are presented that are specifically designed to CG entire protein domains and subdomains into single effective CG particles. This is accomplished by augmenting existing effective particle CG schemes to allow for discrete state transitions and configuration-dependent resolution. Additionally, certain conclusions of this work connect back to single-state force matching and open up new avenues for method development in that area. These results provide a formal statistical mechanical basis for UCG methods related to force matching and relative entropy CG methods and suggest practical algorithms for constructing optimal approximate UCG models from fine-grained simulation data.

Progress in developing Poisson-Boltzmann equation solvers

This review outlines the recent progress made in developing more accurate and efficient solutions to model electrostatics in systems comprised of bio-macromolecules and nano-objects, the last one referring to objects that do not have biological function themselves but nowadays are frequently used in biophysical and medical approaches in conjunction with bio-macromolecules. The problem of modeling macromolecular electrostatics is reviewed from two different angles: as a mathematical task provided the specific definition of the system to be modeled and as a physical problem aiming to better capture the phenomena occurring in the real experiments. In addition, specific attention is paid to methods to extend the capabilities of the existing solvers to model large systems toward applications of calculations of the electrostatic potential and energies in molecular motors, mitochondria complex, photosynthetic machinery and systems involving large nano-objects.

Microsecond folding experiments and simulations: a match is made

For the past two decades, protein folding experiments have been speeding up from the second or millisecond time scale to the microsecond time scale, and full-atom simulations have been extended from the nanosecond to the microsecond and even millisecond time scale. Where the two meet, it is now possible to compare results directly, allowing force fields to be validated and refined, and allowing experimental data to be interpreted in atomistic detail. In this perspective we compare recent experiments and simulations on the microsecond time scale, pointing out the progress that has been made in determining native structures from physics-based simulations, refining experiments and simulations to provide more quantitative underlying mechanisms, and tackling the problems of multiple reaction coordinates, downhill folding, and complex underlying structure of unfolded or misfolded states.

iBIOMES: managing and sharing biomolecular simulation data in a distributed environment

Biomolecular simulations, which were once batch queue or compute limited, have now become data analysis and management limited. In this paper we introduce a new management system for large biomolecular simulation and computational chemistry data sets. The system can be easily deployed on distributed servers to create a mini-grid at the researcher's site. The system not only offers a simple data deposition mechanism but also a way to register data into the system without moving the data from their original location. Any registered data set can be searched and downloaded using a set of defined metadata for molecular dynamics and quantum mechanics and visualized through a dynamic Web interface.

Molecular Dynamics Computer Simulations of Multidrug RND Efflux Pumps

Over-expression of multidrug efflux pumps of the Resistance Nodulation Division (RND) protein super family counts among the main causes for microbial resistance against pharmaceuticals. Understanding the molecular basis of this process is one of the major challenges of modern biomedical research, involving a broad range of experimental and computational techniques. Here we review the current state of RND transporter investigation employing molecular dynamics simulations providing conformational samples of transporter components to obtain insights into the functional mechanism underlying efflux pump-mediated antibiotics resistance in Escherichia coli and Pseudomonas aeruginosa.

The underappreciated role of allostery in the cellular network

Allosteric propagation results in communication between distinct sites in the protein structure; it also encodes specific effects on cellular pathways, and in this way it shapes cellular response. One example of long-range effects is binding of morphogens to cell surface receptors, which initiates a cascade of protein interactions that leads to genome activation and specific cellular action. Allosteric propagation results from combinations of multiple factors, takes place through dynamic shifts of conformational ensembles, and affects the equilibria of macromolecular interactions. Here, we (a) emphasize the well-known yet still underappreciated role of allostery in conveying explicit signals across large multimolecular assemblies and distances to specify cellular action; (b) stress the need for quantitation of the allosteric effects; and finally, (c) propose that each specific combination of allosteric effectors along the pathway spells a distinct function. The challenges are colossal; the inspiring reward will be predicting function, misfunction, and outcomes of drug regimes.

Molecular simulation studies of reversed-phase liquid chromatography

Over the past 20 years, molecular simulation methods have been applied to the modeling of reversed-phase liquid chromatography (RPLC). The purpose of these simulations was to provide a molecular-level understanding of: (i) the structure and dynamics of the bonded phase and its interface with the mobile phase, (ii) the interactions of analytes with the bonded phase, and (iii) the retention mechanism for different analytes. However, the investigation of chromatographic systems poses significant challenges for simulations with respect to the accuracy of the molecular mechanics force fields and the efficiency of the sampling algorithms. This review discusses a number of aspects concerning molecular simulation studies of RPLC systems including the historical development of the subject, the background needed to understand the two prevalent techniques, molecular dynamics (MD) and Monte Carlo (MC) methods, and the wealth of insight provided by these simulations. Examples from the literature employing MD approaches and from the authors' laboratory using MC methods are discussed. The former can provide information on chain dynamics and transport properties, whereas the latter techniques are uniquely suited for the investigation of phase and sorption equilibria that underly RPLC retention, and both can be used to elucidate the bonded-chain conformations and solvent distributions.

Intracellular gating in an inward-facing state of aspartate transporter Glt(Ph) is regulated by the movements of the helical hairpin HP2

Sodium-coupled neurotransmitter transporters play a key role in neuronal signaling by clearing excess transmitter from the synapse. Structural data on a trimeric archaeal aspartate transporter, Glt_Ph, have provided valuable insights into structural features of human excitatory amino acid transporters. However, the time-resolved mechanisms of substrate binding and release, as well as that of coupling to sodium co-transport, remain largely unknown for this important family. We present here the results of the most extensive simulations performed to date for Glt_Ph in both outward-facing and inward-facing states by taking advantage of significant advances made in recent years in molecular simulation technology. The generated multiple microsecond trajectories consistently show that the helical hairpin HP2, not HP1, serves as an intracellular gate (in addition to its extracellular gating role). In contrast to previous proposals, HP1 can neither initiate nor accommodate neurotransmitter release without prior opening of HP2 by at least 4.0 Å. Aspartate release invariably follows that of a sodium ion located near the HP2 gate entrance. Asp-394 on TM8 and Arg-276 on HP1 emerge as key residues that promote the reorientation and diffusion of substrate toward the cell interior. These findings underscore the significance of examining structural dynamics, as opposed to static structure(s), to make inferences on the mechanisms of transport and key interactions.

Advanced replica-exchange sampling to study the flexibility and plasticity of peptides and proteins

Molecular dynamics (MD) simulations are ideally suited to investigate protein and peptide plasticity and flexibility simultaneously at high spatial (atomic) and high time resolution. However, the applicability is still limited by the force field accuracy and by the maximum simulation time that can be routinely achieved in current MD simulations. In order to improve the sampling the replica-exchange (REMD) methodology has become popular and is now the most widely applied advanced sampling approach. Many variants of the REMD method have been designed to reduce the computational demand or to enhance sampling along specific sets of conformational variables. An overview on recent methodological advances and discussion of specific aims and advantages of the approaches will be given. Applications in the area of free energy simulations and advanced sampling of intrinsically disordered peptides and proteins will also be discussed. This article is part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly.

Conformational heterogeneity within the LID domain mediates substrate binding to Escherichia coli adenylate kinase: function follows fluctuations

Proteins exist as dynamic ensembles of molecules, implying that protein amino acid sequences evolved to code for both the ground state structure as well as the entire energy landscape of excited states. Accumulating theoretical and experimental evidence suggests that enzymes use such conformational fluctuations to facilitate allosteric processes important for substrate binding and possibly catalysis. This phenomenon can be clearly demonstrated in Escherichia coli adenylate kinase, where experimentally observed local unfolding of the LID subdomain, as opposed to a more commonly postulated rigid-body opening motion, is related to substrate binding. Because "entropy promoting" glycine mutations designed to increase specifically the local unfolding of the LID domain also affect substrate binding, changes in the excited energy landscape effectively tune the function of this enzyme without changing the ground state structure or the catalytic site. Thus, additional thermodynamic information, above and beyond the single folded structure of an enzyme-substrate complex, is likely required for a full and quantitative understanding of how enzymes work.

Folding and association of a homotetrameric protein complex in an all-atom Go model

The 84-residue homotetrameric BBAT1 is one of the smallest stable protein complexes and therefore is a good test system to study the self-assembly of multimeric proteins. We have researched for this protein the interplay between the folding of monomers and their assembly into tetramers. Replica exchange molecular dynamics simulations relying on a Go model are compared with earlier simulations that use the physics-based coarse-grained UNRES model.

To milliseconds and beyond: challenges in the simulation of protein folding

Quantitatively accurate all-atom molecular dynamics (MD) simulations of protein folding have long been considered a holy grail of computational biology. Due to the large system sizes and long timescales involved, such a pursuit was for many years computationally intractable. Further, sufficiently accurate forcefields needed to be developed in order to realistically model folding. This decade, however, saw the first reports of folding simulations describing kinetics on the order of milliseconds, placing many proteins firmly within reach of these methods. Progress in sampling and forcefield accuracy, however, presents a new challenge: how to turn huge MD datasets into scientific understanding. Here, we review recent progress in MD simulation techniques and show how the vast datasets generated by such techniques present new challenges for analysis. We critically discuss the state of the art, including reaction coordinate and Markov state model (MSM) methods, and provide a perspective for the future.

Computer-Aided Protein Directed Evolution: a Review of Web Servers, Databases and other Computational Tools for Protein Engineering

The combination of computational and directed evolution methods has proven a winning strategy for protein engineering. We refer to this approach as computer-aided protein directed evolution (CAPDE) and the review summarizes the recent developments in this rapidly growing field. We will restrict ourselves to overview the availability, usability and limitations of web servers, databases and other computational tools proposed in the last five years. The goal of this review is to provide concise information about currently available computational resources to assist the design of directed evolution based protein engineering experiment.

Molecular simulations of drug–receptor complexes in anticancer research

Molecular modeling and computer simulation techniques have matured significantly in recent years and proved their value in the study of drug–DNA, drug–DNA–protein, drug–protein and protein–protein interactions. Evolution in this area has gone hand-in-hand with an increased availability of structural data on biological macromolecules, major advances in molecular mechanics force fields and considerable improvements in computer technologies, most significantly processing speeds, multiprocessor programming and data-storage capacity. The information derived from molecular simulations of drug–receptor complexes can be used to extract structural and energetic information that is usually beyond current experimental possibilities, provide independent accounts of experimentally observed behavior, help in the interpretation of biochemical or pharmacological results, and open new avenues for research by posing novel relevant questions that can guide the design of new experiments. As drug-screening tools, ligand- and fragment-docking platforms stand out as powerful techniques that can provide candidate molecules for hit and lead development. This review provides an overall perspective of the main methods and focuses on some selected applications to both classical and novel anticancer targets.

Combining coarse-grained nonbonded and atomistic bonded interactions for protein modeling

A hybrid coarse-grained (CG) and atomistic (AT) model for protein simulations and rapid searching and refinement of peptide-protein complexes has been developed. In contrast to other hybrid models that typically represent spatially separate parts of a protein by either a CG or an AT force field model, the present approach simultaneously represents the protein by an AT (united atom) and a CG model. The interactions of the protein main chain are described based on the united atom force field allowing a realistic representation of protein secondary structures. In addition, the AT description of all other bonded interactions keeps the protein compatible with a realistic bonded geometry. Nonbonded interactions between side chains and side chains and main chain are calculated at the level of a CG model using a knowledge-based potential. Unrestrained molecular dynamics simulations on several test proteins resulted in trajectories in reasonable agreement with the corresponding experimental structures. Applications to the refinement of docked peptide-protein complexes resulted in improved complex structures. Application to the rapid refinement of docked protein-protein complex is also possible but requires further optimization of force field parameters.

Molecular dynamics simulations of membrane proteins

Membrane proteins control the traffic across cell membranes and thereby play an essential role in cell function from transport of various solutes to immune response via molecular recognition. Because it is very difficult to determine the structures of membrane proteins experimentally, computational methods have been increasingly used to study their structure and function. Here we focus on two classes of membrane proteins-ion channels and transporters-which are responsible for the generation of action potentials in nerves, muscles, and other excitable cells. We describe how computational methods have been used to construct models for these proteins and to study the transport mechanism. The main computational tool is the molecular dynamics (MD) simulation, which can be used for everything from refinement of protein structures to free energy calculations of transport processes. We illustrate with specific examples from gramicidin and potassium channels and aspartate transporters how the function of these membrane proteins can be investigated using MD simulations.

Stapled BH3 peptides against MCL-1: mechanism and design using atomistic simulations

Atomistic simulations of a set of stapled alpha helical peptides derived from the BH3 helix of MCL-1 (Stewart et al. (2010) Nat Chem Biol 6: 595–601) complexed to a fragment (residues 172–320) of MCL-1 revealed that the highest affinity is achieved when the staples engage the surface of MCL-1 as has also been demonstrated for p53-MDM2 (Joseph et al. (2010) Cell Cycle 9: 4560–4568; Baek et al. (2012) J Am Chem Soc 134: 103–106). Affinity is also modulated by the ability of the staples to pre-organize the peptides as helices. Molecular dynamics simulations of these stapled BH3 peptides were carried out followed by determination of the energies of interactions using MM/GBSA methods. These show that the location of the staple is a key determinant of a good binding stapled peptide from a bad binder. The good binder derives binding affinity from interactions between the hydrophobic staple and a hydrophobic patch on MCL-1. The position of the staple was varied, guiding the design of new stapled peptides with higher affinities.

SIMONA 1.0: an efficient and versatile framework for stochastic simulations of molecular and nanoscale systems

Molecular simulation methods have increasingly contributed to our understanding of molecular and nanoscale systems. However, the family of Monte Carlo techniques has taken a backseat to molecular dynamics based methods, which is also reflected in the number of available simulation packages. Here, we report the development of a generic, versatile simulation package for stochastic simulations and demonstrate its application to protein conformational change, protein-protein association, small-molecule protein docking, and simulation of the growth of nanoscale clusters of organic molecules. Simulation of molecular and nanoscale systems (SIMONA) is easy to use for standard simulations via a graphical user interface and highly parallel both via MPI and the use of graphical processors. It is also extendable to many additional simulations types. Being freely available to academic users, we hope it will enable a large community of researchers in the life- and materials-sciences to use and extend SIMONA in the future. SIMONA is available for download under http://int.kit.edu/nanosim/simona.