Flooding in GROMACS: accelerated barrier crossings in molecular dynamics

Molecular Dynamics Simulations in Protein-Protein Docking

Concerted interactions between all the cell components form the basis of biological processes. Protein-protein interactions (PPIs) constitute a tremendous part of this interaction network. Deeper insight into PPIs can help us better understand numerous diseases and lead to the development of new diagnostic and therapeutic strategies. PPI interfaces, until recently, were considered undruggable. However, it is now believed that the interfaces contain "hot spots," which could be targeted by small molecules. Such a strategy would require high-quality structural data of PPIs, which are difficult to obtain experimentally. Therefore, in silico modeling can complement or be an alternative to in vitro approaches. There are several computational methods for analyzing the structural data of the binding partners and modeling of the protein-protein dimer/oligomer structure. The major problem with in silico structure prediction of protein assemblies is obtaining sufficient sampling of protein dynamics. One of the methods that can take protein flexibility and the effects of the environment into account is Molecular Dynamics (MD). While sampling of the whole protein-protein association process with plain MD would be computationally expensive, there are several strategies to harness the method to PPI studies while maintaining reasonable use of resources. This chapter reviews known applications of MD in the PPI investigation workflows.

CHARMM-GUI Enhanced Sampler for various collective variables and enhanced sampling methods

Enhanced sampling methodologies modifying underlying Hamiltonians can be used for the systems with a rugged potential energy surface that makes it hard to observe convergence using conventional unbiased molecular dynamics (MD) simulations. We present CHARMM-GUI Enhanced Sampler, a web-based tool to prepare various enhanced sampling simulations inputs with user-selected collective variables (CVs). Enhanced Sampler provides inputs for the following nine methods: accelerated MD, Gaussian accelerated MD, conformational flooding, metadynamics, adaptive biasing force, steered MD, temperature replica exchange MD, replica exchange solute tempering 2, and replica exchange umbrella sampling for the method-implemented MD packages including AMBER, CHARMM, GENESIS, GROMACS, NAMD, and OpenMM. Users only need to select a group of atoms via intuitive web-implementation in order to define commonly used nine CVs of interest: center of mass based distance, angle, dihedral, root-mean-square-distance, radius of gyration, distance projected on axis, two types of angles projected on axis, and coordination numbers. The enhanced sampling methods are tested with several biological systems to illustrate their efficiency over conventional MD. Enhanced Sampler with carefully optimized system-dependent parameters will help users to get meaningful results from their enhanced sampling simulations.

A review on application of molecular simulation technology in food molecules interaction

Molecular simulation is a new technology to analyze the interaction between molecules. This review mainly summarizes the application of molecular simulation technology in the food industry. This technology has been employed to assess structural changes of biomolecules, the interaction between components, and the mechanism of physical and chemical property alterations. These conclusions provide a deeper understanding of the molecular interaction mechanism in foods, break through the limitations of scientific experiments and avoid blind and time-consuming scientific research. In this paper, the advantages and development trends of molecular simulation technology in the food research field are described. This methodology can be used to contribute to further studies of the mechanism of molecular interactions in food, confirm experimental results and provide new ideas for research in the field of food sciences.

Interactions of Co, Cu, and non-metal phthalocyanines with external structures of SARS-CoV-2 using docking and molecular dynamics

The new coronavirus, SARS-CoV-2, caused the COVID-19 pandemic, characterized by its high rate of contamination, propagation capacity, and lethality rate. In this work, we approach the use of phthalocyanines as an inhibitor of SARS-CoV-2, as they present several interactive properties of the phthalocyanines (Pc) of Cobalt (CoPc), Copper (CuPc) and without a metal group (NoPc) can interact with SARS-CoV-2, showing potential be used as filtering by adsorption on paints on walls, masks, clothes, and air conditioning filters. Molecular modeling techniques through Molecular Docking and Molecular Dynamics were used, where the target was the external structures of the virus, but specifically the envelope protein, main protease, and Spike glycoprotein proteases. Using the g_MM-GBSA module and with it, the molecular docking studies show that the ligands have interaction characteristics capable of adsorbing the structures. Molecular dynamics provided information on the root-mean-square deviation of the atomic positions provided values between 1 and 2.5. The generalized Born implicit solvation model, Gibbs free energy, and solvent accessible surface area approach were used. Among the results obtained through molecular dynamics, it was noticed that interactions occur since Pc could bind to residues of the active site of macromolecules, demonstrating good interactions; in particular with CoPc. Molecular couplings and free energy showed that S-gly active site residues interacted strongly with phthalocyanines with values ​​of - 182.443 kJ/mol (CoPc), 158.954 kJ/mol (CuPc), and - 129.963 kJ/mol (NoPc). The interactions of Pc's with SARS-CoV-2 may predict some promising candidates for antagonists to the virus, which if confirmed through experimental approaches, may contribute to resolving the global crisis of the COVID-19 pandemic.

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard "lock and key" paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.

An allosteric interaction controls the activation mechanism of SHP2 tyrosine phosphatase

SHP2 is a protein tyrosine phosphatase (PTP) involved in multiple signaling pathways. Mutations of SHP2 can result in Noonan syndrome or pediatric malignancies. Inhibition of wild-type SHP2 represents a novel strategy against several cancers. SHP2 is activated by binding of a phosphopeptide to the N-SH2 domain of SHP2, thereby favoring dissociation of the N-SH2 domain and exposing the active site on the PTP domain. The conformational transitions controlling ligand affinity and PTP dissociation remain poorly understood. Using molecular simulations, we revealed an allosteric interaction restraining the N-SH2 domain into a SHP2-activating and a stabilizing state. Only ligands selecting for the activating N-SH2 conformation, depending on ligand sequence and binding mode, are effective activators. We validate the model of SHP2 activation by rationalizing modified basal activity and responsiveness to ligand stimulation of several N-SH2 variants. This study provides mechanistic insight into SHP2 activation and may open routes for SHP2 regulation.

In silico assessment of the conduction mechanism of the Ryanodine Receptor 1 reveals previously unknown exit pathways

The ryanodine receptor 1 is a large calcium ion channel found in mammalian skeletal muscle. The ion channel gained a lot of attention recently, after multiple independent authors published near-atomic cryo electron microscopy data. Taking advantage of the unprecedented quality of structural data, we performed molecular dynamics simulations on the entire ion channel as well as on a reduced model. We calculated potentials of mean force for Ba2+, Ca2+, Mg2+, K+, Na+ and Cl- ions using umbrella sampling to identify the key residues involved in ion permeation. We found two main binding sites for the cations, whereas the channel is strongly repulsive for chloride ions. Furthermore, the data is consistent with the model that the receptor achieves its ion selectivity by over-affinity for divalent cations in a calcium-block-like fashion. We reproduced the experimental conductance for potassium ions in permeation simulations with applied voltage. The analysis of the permeation paths shows that ions exit the pore via multiple pathways, which we suggest to be related to the experimental observation of different subconducting states.

Microtubule assembly governed by tubulin allosteric gain in flexibility and lattice induced fit

Microtubules (MTs) are key components of the cytoskeleton and play a central role in cell division and development. MT assembly is known to be associated with a structural change in αβ-tubulin dimers from kinked to straight conformations. How GTP binding renders individual dimers polymerization-competent, however, is still unclear. Here, we have characterized the conformational dynamics and energetics of unassembled tubulin using atomistic molecular dynamics and free energy calculations. Contrary to existing allosteric and lattice models, we find that GTP-tubulin favors a broad range of almost isoenergetic curvatures, whereas GDP-tubulin has a much lower bending flexibility. Moreover, irrespective of the bound nucleotide and curvature, two conformational states exist differing in location of the anchor point connecting the monomers that affects tubulin bending, with one state being strongly favored in solution. Our findings suggest a new combined model in which MTs incorporate and stabilize flexible GTP-dimers with a specific anchor point state.

Computational membrane biophysics: From ion channel interactions with drugs to cellular function

The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

Revisiting Partition in Hydrated Bilayer Systems

We discuss potential-of-mean force convergence issues involving the methods for generating starting structures of umbrella sampling simulations for the study of the water-bilayer permeation of drug-like compounds. We provide a proof of concept of the benefits of potential-energy modification methods, in particular the flooding technique, to enhance the sampling and improve the convergence of the potential-of-mean force. In addition, we also discuss how these potential modifiers could introduce the necessary bias to induce the correct description of other relevant internal degrees of freedom for the compounds, thus providing a more accurate description of the permeation process. Effective methodological approximations are taken into consideration, more specifically the inclusion of atomic polarization, and experimental data are used in the validation of computed values whenever possible. The parametrization of the atomic point charges is always a relevant issue in biomolecular simulations. We discuss the influence of a molecule's conformation-dependent atomic point charges and their impact on the predicted potential-of-mean force.

Special Pairs Are Decisive in the Autoionization and Recombination of Water

Although water's chemical properties are no less important than its exceptional physical properties, its acid-base behavior is relatively poorly understood. In fact, the Grotthus trajectories for ion recombination predicted by density functional theory do not comport well with the almost 100-fold slower diffusive trajectories observed in time-resolved spectroscopy. And, in the reverse reaction, the barrier to autoionization is not well characterized. Here we develop a self-consistent picture of both processes based on the occurrence and role of ultrashort hydrogen bonds. The predicted populations of these special pairs in bulk water are consistent with the high frequency electrodynamics of water and its pressure dependence. The rate-limiting role of the special pairs manifests in autoionization as a two-stage barrier, first to form a contact ion pair and then to separate it by one water molecule. From this configuration, similar frequencies are observed for further separation vs recombination. The requirement of ultrashort hydrogen bonds for proton transfer in autoionization is consistent with the rise in K_w with increasing pressure and points to a role for density fluctuations in autoionization events. In neutralization, the manifestation of the role of special pairs is the prolonged diffusional process observed in time-resolved spectroscopy experiments. The requirement of special pairs as transition states for proton transfer is less obvious for neutralization in isolated water chains than in the bulk liquid only because an unbroken sequence of ultrashort H-bonds is more easily formed in a 1D H-bonded chain than in a 3D H-bonded network.

Finding Our Way in the Dark Proteome

The traditional structure-function paradigm has provided significant insights for well-folded proteins in which structures can be easily and rapidly revealed by X-ray crystallography beamlines. However, approximately one-third of the human proteome is comprised of intrinsically disordered proteins and regions (IDPs/IDRs) that do not adopt a dominant well-folded structure, and therefore remain "unseen" by traditional structural biology methods. This Perspective considers the challenges raised by the "Dark Proteome", in which determining the diverse conformational substates of IDPs in their free states, in encounter complexes of bound states, and in complexes retaining significant disorder requires an unprecedented level of integration of multiple and complementary solution-based experiments that are analyzed with state-of-the art molecular simulation, Bayesian probabilistic models, and high-throughput computation. We envision how these diverse experimental and computational tools can work together through formation of a "computational beamline" that will allow key functional features to be identified in IDP structural ensembles.

Advanced molecular dynamics simulation methods for kinase drug discovery

Interest in the application of molecular dynamics (MD) simulations has increased in the field of protein kinase (PK) drug discovery. PKs belong to an important drug target class because they are directly involved in a number of diseases, including cancer. MD methods simulate dynamic biological and chemical events at an atomic level. This information can be combined with other in silico and experimental methods to efficiently target selected receptors. In this review, we present common and advanced methods of MD simulations and we focus on the recent applications of MD-based methodologies that provided significant insights into the elucidation of biological mechanisms involving PKs and into the discovery of novel kinase inhibitors.

Experimental and computational study of membrane affinity for selected energetic compounds

The affinity of various energetic compounds for a biological membrane was investigated using experimental and computational techniques. We measured octanol-water (log(Kow)) and liposome-water (log(Klipw)) partition coefficients for the following chemicals: trinitrotoluene (TNT), 2,4-dinitrotoluene (2,4-DNT), 2,6-dinitrotoluene (2,6-DNT), 2,4-dinitroanisole (DNAN), 2methoxy-5-nitrophenol (2M5NP), 2,4,6-trinitrobenzene (TNB), and 2,4-dinitrophenol (2,4-DNP). In order to determine log(Klipw) experimentally, we used artificial solid supported lipid liposomes produced under trade mark TRANSIL. Log(Kow) value were predicted with several program packages including the COSMOthermX software. Log(Klipw) were estimated with COSMOmic as implemented in the COSMOthermX program package. In order to verify accuracy of our experimentally obtained results, we performed basic statistical analysis of data taken from the literature. We concluded that compounds considered in this study possess a moderate ability to penetrate into membranes. Comparison of both coefficients has shown that in general, the log(Kow) values are slightly smaller than log(Klipw).

Exploring biomolecular dynamics and interactions using advanced sampling methods

Molecular dynamics (MD) and Monte Carlo (MC) simulations have emerged as a valuable tool to investigate statistical mechanics and kinetics of biomolecules and synthetic soft matter materials. However, major limitations for routine applications are due to the accuracy of the molecular mechanics force field and due to the maximum simulation time that can be achieved in current simulations studies. For improving the sampling a number of advanced sampling approaches have been designed in recent years. In particular, variants of the parallel tempering replica-exchange methodology are widely used in many simulation studies. Recent methodological advancements and a discussion of specific aims and advantages are given. This includes improved free energy simulation approaches and conformational search applications.

Comparison of structure determination methods for intrinsically disordered amyloid-β peptides

Intrinsically disordered proteins (IDPs) represent a new frontier in structural biology since the primary characteristic of IDPs is that structures need to be characterized as diverse ensembles of conformational substates. We compare two general but very different ways of combining NMR spectroscopy with theoretical methods to derive structural ensembles for the disease IDPs amyloid-β 1-40 and amyloid-β 1-42, which are associated with Alzheimer's Disease. We analyze the performance of de novo molecular dynamics and knowledge-based approaches for generating structural ensembles by assessing their ability to reproduce a range of NMR experimental observables. In addition to the comparison of computational methods, we also evaluate the relative value of different types of NMR data for refining or validating the IDP structural ensembles for these important disease peptides.

Enhancing protein adsorption simulations by using accelerated molecular dynamics

The atomistic modeling of protein adsorption on surfaces is hampered by the different time scales of the simulation ([Formula: see text][Formula: see text]s) and experiment (up to hours), and the accordingly different 'final' adsorption conformations. We provide evidence that the method of accelerated molecular dynamics is an efficient tool to obtain equilibrated adsorption states. As a model system we study the adsorption of the protein BMP-2 on graphite in an explicit salt water environment. We demonstrate that due to the considerably improved sampling of conformational space, accelerated molecular dynamics allows to observe the complete unfolding and spreading of the protein on the hydrophobic graphite surface. This result is in agreement with the general finding of protein denaturation upon contact with hydrophobic surfaces.

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.

Routine Access to Millisecond Time Scale Events with Accelerated Molecular Dynamics

In this work, we critically assess the ability of the all-atom enhanced sampling method accelerated molecular dynamics (aMD) to investigate conformational changes in proteins that typically occur on the millisecond time scale. We combine aMD with the inherent power of graphics processor units (GPUs) and apply the implementation to the bovine pancreatic trypsin inhibitor (BPTI). A 500 ns aMD simulation is compared to a previous millisecond unbiased brute force MD simulation carried out on BPTI, showing that the same conformational space is sampled by both approaches. To our knowledge, this represents the first implementation of aMD on GPUs and also the longest aMD simulation of a biomolecule run to date. Our implementation is available to the community in the latest release of the Amber software suite (v12), providing routine access to millisecond events sampled from dynamics simulations using off the shelf hardware.

Mimicking the action of folding chaperones by Hamiltonian replica-exchange molecular dynamics simulations: application in the refinement of de novo models

The efficiency of using a variant of Hamiltonian replica-exchange molecular dynamics (Chaperone H-replica-exchange molecular dynamics [CH-REMD]) for the refinement of protein structural models generated de novo is investigated. In CH-REMD, the interaction between the protein and its environment, specifically, the electrostatic interaction between the protein and the solvating water, is varied leading to cycles of partial unfolding and refolding mimicking some aspects of folding chaperones. In 10 of the 15 cases examined, the CH-REMD approach sampled structures in which the root-mean-square deviation (RMSD) of secondary structure elements (SSE-RMSD) with respect to the experimental structure was more than 1.0 Å lower than the initial de novo model. In 14 of the 15 cases, the improvement was more than 0.5 Å. The ability of three different statistical potentials to identify near-native conformations was also examined. Little correlation between the SSE-RMSD of the sampled structures with respect to the experimental structure and any of the scoring functions tested was found. The most effective scoring function tested was the DFIRE potential. Using the DFIRE potential, the SSE-RMSD of the best scoring structures was on average 0.3 Å lower than the initial model. Overall the work demonstrates that targeted enhanced-sampling techniques such as CH-REMD can lead to the systematic refinement of protein structural models generated de novo but that improved potentials for the identification of near-native structures are still needed.

Dynamics, flexibility and ligand-induced conformational changes in biological macromolecules: a computational approach

Biomolecules possess important dynamical properties that enable them to adapt and alternate their conformation as a response to environmental stimuli. Recent advancements in computational resources and methodology allow a higher capability to mimic in vitro conditions and open up the possibility of studying large systems over longer timescales. Here, we describe commonly used computational approaches for studying the dynamic properties of proteins. We review a selected set of simulation studies on ligand-induced changes in the chaperonin GroEL-GroES, a molecular folding machine, maltose-binding protein, a prototypical member of the periplasmic binding proteins, and the bacterial ribosomal A-site, focusing on aminoglycoside antibiotic recognition. We also discuss a recent quantitative reconstruction of the binding process of benzamidine and trypsin. These studies contribute to the understanding and further development of the medicinal regulation of large biomolecular systems.

Understanding biomolecular motion, recognition, and allostery by use of conformational ensembles

We review the role conformational ensembles can play in the analysis of biomolecular dynamics, molecular recognition, and allostery. We introduce currently available methods for generating ensembles of biomolecules and illustrate their application with relevant examples from the literature. We show how, for binding, conformational ensembles provide a way of distinguishing the competing models of induced fit and conformational selection. For allostery we review the classic models and show how conformational ensembles can play a role in unravelling the intricate pathways of communication that enable allostery to occur. Finally, we discuss the limitations of conformational ensembles and highlight some potential applications for the future.

Improved Binding Free Energy Predictions from Single-Reference Thermodynamic Integration Augmented with Hamiltonian Replica Exchange

Reliable predictions of relative binding free energies are essential in drug discovery, where chemists modify promising compounds with the aim of increasing binding affinity. Conventional Thermodynamic Integration (TI) approaches can estimate corresponding changes in binding free energies, but suffer from inadequate sampling due to ruggedness of the molecular energy surfaces. Here, we present an improved TI strategy for computing relative binding free energies of congeneric ligands. This strategy employs a specific, unphysical single-reference (SR) state and Hamiltonian replica exchange (HREX) to locally enhance sampling. We then apply this strategy to compute relative binding free energies of twelve ligands in the L99A mutant of T4 Lysozyme. Besides the ligands, our approach enhances hindered rotations of the important V111, as well as V87 and L118 sidechains. Concurrently, we devise practical strategies to monitor and improve HREX-SRTI efficiency. Overall, the HREX-SRTI results agree well (R(2) = 0.76, RMSE = 0.3 kcal/mol) with available experimental data. When optimized for efficiency, the HREX-SRTI precision matches that of experimental measurements.

Implementation of Accelerated Molecular Dynamics in NAMD

Accelerated molecular dynamics (aMD) is an enhanced-sampling method that improves the conformational space sampling by reducing energy barriers separating different states of a system. Here we present the implementation of aMD in the parallel simulation program NAMD. We show that aMD simulations performed with NAMD have only a small overhead compared with classical MD simulations. Through example applications to the alanine dipeptide, we discuss the choice of acceleration parameters, the interpretation of aMD results, as well as the advantages and limitations of the aMD method.

In silico phosphorylation of the autoinhibited form of p47(phox): insights into the mechanism of activation

Activation of the multicomponent enzyme NADPH oxidase requires the interaction between the tandem SH3 domain of the cytosolic subunit p47(phox) and the cytoplasmic tail of membrane-bound p22(phox). In the resting state, p47(phox) exists in an autoinhibited conformation stabilized by intramolecular contacts between the SH3 domains and an adjacent polybasic region. Phosphorylation of three serine residues, Ser(303), Ser(304), and Ser(328) within this polybasic region has been shown to be sufficient for the disruption of the intramolecular interactions thereby inducing an active state of p47(phox). This active conformation is accessible to the cytoplasmic tail of p22(phox) and initiates the formation of the membrane-bound functional enzyme complex. Molecular dynamics simulations reveal insights in the mechanism of activation of the autoinhibited form of p47(phox) by in silico phosphorylation, of the three serine residues, Ser(303), Ser(304), and Ser(328). The simulations highlight the major collective coordinates generating the opening and the closing of the two SH3 domains and the residues that cause the unmasking of the p22(phox) binding site.

Computing Relative Free Energies of Solvation using Single Reference Thermodynamic Integration Augmented with Hamiltonian Replica Exchange

This paper introduces an efficient single-topology variant of Thermodynamic Integration (TI) for computing relative transformation free energies in a series of molecules with respect to a single reference state. The presented TI variant that we refer to as Single-Reference TI (SR-TI) combines well-established molecular simulation methodologies into a practical computational tool. Augmented with Hamiltonian Replica Exchange (HREX), the SR-TI variant can deliver enhanced sampling in select degrees of freedom. The utility of the SR-TI variant is demonstrated in calculations of relative solvation free energies for a series of benzene derivatives with increasing complexity. Noteworthy, the SR-TI variant with the HREX option provides converged results in a challenging case of an amide molecule with a high (13-15 kcal/mol) barrier for internal cis/trans interconversion using simulation times of only 1 to 4 ns.

Understanding the dynamics behind the photoisomerization of a light-driven fluorene molecular rotary motor

Light-driven molecular rotary motors derived from chiral overcrowded alkenes represent a broad class of compounds for which photochemical rearrangements lead to large scale motion of one part of the molecule with respect to another. It is this motion/change in molecular shape that is employed in many of their applications. A key group in this class are the molecular rotary motors that undergo unidirectional light-driven rotation about a double bond through a series of photochemical and thermal steps. In the present contribution we report a combined quantum chemical and molecular dynamics study of the mechanism of the rotational cycle of the fluorene-based molecular rotary motor 9-(2,4,7-trimethyl-2,3-dihydro-1H-inden-1-ylidene)-9H-fluorene (1). The potential energy surfaces of the ground and excited singlet states of 1 were calculated, and it was found that conical intersections play a central role in the mechanism of photo conversion between the stable conformer of 1 and its metastable conformer. Molecular dynamics simulations indicate that the average lifetime of the fluorene motor in the excited state is 1.40 +/- 0.10 ps when starting from the stable conformer, which increases to 1.77 +/- 0.13 ps for the reverse photoisomerization. These simulations indicate that the quantum yield of photoisomerization of the stable conformer is 0.92, whereas it is only 0.40 for the reverse photoisomerization. For the first time, a theoretical understanding of the experimentally observed photostationary state of 1 is reported that provides a detailed picture of the photoisomerization dynamics in overcrowded alkene-based molecular motor 1. The analysis of the electronic structure of the fluorene molecular motor holds considerable implications for the design of molecular motors. Importantly, the role of pyramidalization and conical intersections offer new insight into the factors that dominate the photostationary state achieved in these systems.

Domain motions of hyaluronan lyase underlying processive hyaluronan translocation

Hyaluronan lyase (Hyal) is a surface enzyme occurring in many bacterial organisms including members of Streptococcus species. Streptococcal Hyal primarily degrades hyaluronan-substrate (HA) of the extracellular matrix. This degradation appears to facilitate the spread of this bacterium throughout host tissues. Unlike purely endolytic degradation of its other substrates, unsulfated chondroitin or some chondroitin sulfates, the degradation of HA by Hyal proceeds by processive exolytic cleavage of one disaccharide at a time following an initial endolytic cut. Molecular dynamics (MD) studies of Hyal from Streptococcus pneumoniae are presented that address the enzyme's molecular mechanism of action and the role of domain motions for processive functionality. The analysis of extensive sub-microsecond MD simulations of this enzyme action on HA-substrates of different lengths and the connection between the domain dynamics of Hyal and the translocation of the HA-substrate reveals that opening/closing and twisting domain motions of the Hyal are intimately linked to processive HA degradation. Enforced simulations confirmed this finding as the domain motions in SpnHyal were found to be induced by enforced substrate translocation. These results establish the dynamic interplay between Hyal flexibility and substrate translocation and provide insight into the processive mechanism of Hyal.

Principles of flexible protein-protein docking

Treating flexibility in molecular docking is a major challenge in cell biology research. Here we describe the background and the principles of existing flexible protein-protein docking methods, focusing on the algorithms and their rational. We describe how protein flexibility is treated in different stages of the docking process: in the preprocessing stage, rigid and flexible parts are identified and their possible conformations are modeled. This preprocessing provides information for the subsequent docking and refinement stages. In the docking stage, an ensemble of pre-generated conformations or the identified rigid domains may be docked separately. In the refinement stage, small-scale movements of the backbone and side-chains are modeled and the binding orientation is improved by rigid-body adjustments. For clarity of presentation, we divide the different methods into categories. This should allow the reader to focus on the most suitable method for a particular docking problem.

Chromophore protonation state controls photoswitching of the fluoroprotein asFP595

Fluorescent proteins have been widely used as genetically encodable fusion tags for biological imaging. Recently, a new class of fluorescent proteins was discovered that can be reversibly light-switched between a fluorescent and a non-fluorescent state. Such proteins can not only provide nanoscale resolution in far-field fluorescence optical microscopy much below the diffraction limit, but also hold promise for other nanotechnological applications, such as optical data storage. To systematically exploit the potential of such photoswitchable proteins and to enable rational improvements to their properties requires a detailed understanding of the molecular switching mechanism, which is currently unknown. Here, we have studied the photoswitching mechanism of the reversibly switchable fluoroprotein asFP595 at the atomic level by multiconfigurational ab initio (CASSCF) calculations and QM/MM excited state molecular dynamics simulations with explicit surface hopping. Our simulations explain measured quantum yields and excited state lifetimes, and also predict the structures of the hitherto unknown intermediates and of the irreversibly fluorescent state. Further, we find that the proton distribution in the active site of the asFP595 controls the photochemical conversion pathways of the chromophore in the protein matrix. Accordingly, changes in the protonation state of the chromophore and some proximal amino acids lead to different photochemical states, which all turn out to be essential for the photoswitching mechanism. These photochemical states are (i) a neutral chromophore, which can trans-cis photoisomerize, (ii) an anionic chromophore, which rapidly undergoes radiationless decay after excitation, and (iii) a putative fluorescent zwitterionic chromophore. The overall stability of the different protonation states is controlled by the isomeric state of the chromophore. We finally propose that radiation-induced decarboxylation of the glutamic acid Glu215 blocks the proton transfer pathways that enable the deactivation of the zwitterionic chromophore and thus leads to irreversible fluorescence. We have identified the tight coupling of trans-cis isomerization and proton transfers in photoswitchable proteins to be essential for their function and propose a detailed underlying mechanism, which provides a comprehensive picture that explains the available experimental data. The structural similarity between asFP595 and other fluoroproteins of interest for imaging suggests that this coupling is a quite general mechanism for photoswitchable proteins. These insights can guide the rational design and optimization of photoswitchable proteins.

Proteins whose fluorescence can be reversibly switched on and off hold great promise for applications in high-resolution optical microscopy and nanotechnology. To systematically exploit the potential of such photoswitchable proteins and to enable rational improvements of their properties requires a detailed understanding of the molecular switching mechanism. Here, we have studied the photoswitching mechanism of the reversibly switchable fluoroprotein asFP595 by atomistic molecular dynamics simulations. Our simulations explain measured quantum yields and excited state lifetimes, and also predict the structures of the hitherto unknown intermediates and of the irreversibly fluorescent state. Further, we find that the proton distribution in the active site of the asFP595 controls the photochemical conversion pathways of the chromophore in the protein matrix. Our results show that a tight coupling between trans-cis isomerization of the chromophore and proton transfer is essential for the function of asFP595. The structural similarity between asFP595 and other fluoroproteins suggests that this coupling is a quite general mechanism for photoswitchable proteins. These insights can guide the rational design and optimization of photoswitchable proteins.

Geometry-based sampling of conformational transitions in proteins

The fast and accurate prediction of protein flexibility is one of the major challenges in protein science. Enzyme activity, signal transduction, and ligand binding are dynamic processes involving essential conformational changes ranging from small side chain fluctuations to reorientations of entire domains. In the present work, we describe a reimplementation of the CONCOORD approach, termed tCONCOORD, which allows a computationally efficient sampling of conformational transitions of a protein based on geometrical considerations. Moreover, it allows for the extraction of the essential degrees of freedom, which, in general, are the biologically relevant ones. The method rests on a reliable estimate of the stability of interactions observed in a starting structure, in particular those interactions that change during a conformational transition. Applications to adenylate kinase, calmodulin, aldose reductase, T4-lysozyme, staphylococcal nuclease, and ubiquitin show that experimentally known conformational transitions are faithfully predicted.

An exact formulation of hyperdynamics simulations

We introduce a new formula for the acceleration weight factor in the hyperdynamics simulation method, the use of which correctly provides an exact simulation of the true dynamics of a system. This new form of hyperdynamics is valid and applicable where the transition state theory (TST) is applicable and also where the TST is not applicable. To illustrate this new formulation, we perform hyperdynamics simulations for four systems ranging from one degree of freedom to 591 degrees of freedom: (1) We first analyze free diffusion having one degree of freedom. This system does not have a transition state. The TST and the original form of hyperdynamics are not applicable. Using the new form of hyperdynamics, we compute mean square displacement for a range of time. The results obtained agree perfectly with the analytical formula. (2) Then we examine the classical Kramers escape rate problem. The rate computed is in perfect agreement with the Kramers formula over a broad range of temperature. (3) We also study another classical problem: Computing the rate of effusion out of a cubic box through a tiny hole. This problem does not involve an energy barrier. Thus, the original form of hyperdynamics excludes the possibility of using a nonzero bias and is inappropriate. However, with the new weight factor formula, our new form of hyperdynamics can be easily implemented and it produces the exact results. (4) To illustrate applicability to systems of many degrees of freedom, we analyze diffusion of an atom adsorbed on the (001) surface of an fcc crystal. The system is modeled by an atom on top of a slab of six atomic layers. Each layer has 49 atoms. With the bottom two layers of atoms fixed, this system has 591 degrees of freedom. With very modest computing effort, we are able to characterize its diffusion pathways in the exchange-with-the-substrate and hop-over-the-bridge mechanisms.

Structure optimization and folding mechanisms of off-lattice protein models using statistical temperature molecular dynamics simulation: Statistical temperature annealing

The recently proposed statistical temperature molecular dynamics (STMD) algorithm [Kim, Phys. Rev. Lett. 97, 050601 (2006)] is used as the core of an optimization algorithm, statistical temperature annealing (STA), for finding low-lying energy minima of complex potential energy landscapes. Since STMD realizes a random walk in energy, the idea is simply to initiate repeated minimizations from configurations in the low-energy segments of STMD trajectories. STA is tested in structural optimization of various off-lattice AB and extended AB protein models in two and three dimensions with different chain lengths. New putative ground states were found for the two- and three-dimensional AB 55-mer, and for the three-dimensional extended AB 21-mer and 55-mer. The distinct folding features of the models are analyzed in terms of the statistical temperature and other representations of the structure of the potential energy landscape. It is shown that the characteristic behavior of the statistical temperature undergoes a qualitative change with the inclusion of a torsional potential in the extended AB model, as the more rigid backbone makes the potential energy landscape more funnel-like.

Metadynamics in Essential Coordinates: Free Energy Simulation of Conformational Changes

We propose an approach that combines an extraction of collective motions of a molecular system with a sampling of its free energy surface. A recently introduced method of metadynamics allows exploration of the free energy surface of a molecular system by means of coarse-grained dynamics with flooding of free energy minima. This free energy surface is defined as a function of a set of collective variables (e.g., interatomic distances, angles, torsions, and others). In this study, essential coordinates determined by essential dynamics (principle component analysis) were used as collective variables in metadynamics. First, dynamics of the model system (explicitly solvated alanine dipeptide, Ace-Ala-Nme) was simulated by a classical molecular dynamics simulation. The trajectory (1 ns) was then analyzed by essential dynamics to obtain essential coordinates. The free energy surface as a function of the first and second essential coordinates was then explored by metadynamics. The resulting free energy surface is in agreement with other studies of this system. We propose that a combination of these two methods (metadynamics and essential dynamics) has great potential in studies of conformational changes in peptides and proteins.

A highly strained nuclear conformation of the exportin Cse1p revealed by molecular dynamics simulations

To investigate the stability of the open nuclear state of the exportin Cse1p and its closing mechanism at the atomic level, we have performed multiple molecular dynamics simulations. The simulations revealed a strikingly fast transition of Cse1p from the open conformation to the closed cytoplasmic form, consistent with the proposal that Cse1p represents a "spring-loaded molecule." The structure of the ring-shaped state obtained in the simulations is remarkably close to the crystal structure of the cytoplasmic state, though the open nuclear structure was used as the only input. The conformational change is initially driven by release of strain due to RanGTP/importin-alpha binding. Subsequently, a stable closed state is formed, driven by attraction of electrostatically complementary interfaces. These results are consistent with and extend previous proposals. Reverse-charge and neutral mutants remained in an open state. The simulations predict a detailed reaction pathway and resolve the role of suggested hinge regions.