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The S100A1ct peptide, consisting of the C-terminal 20 residues of the S100A1 protein fused to an N-terminal 6-residue hydrophilic tag, has been found to exert a positive inotropic effect, resulting in improved contractile performance of failing cardiac and skeletal muscle without arrhythmic side-effects. The S100A1ct peptide thus has high potential for the treatment of acute heart failure. As a step toward understanding its molecular mechanism of action, and to provide a basis for peptidomimetic design to optimize its properties, we here describe de novo structure predictions and molecular dynamics simulations to characterize the conformational landscape of S100A1ct in aqueous environment. In S100A1, the C-terminal 20 residues form an α-helix, but de novo peptide structure predictions indicate that other conformations are also possible. Conventional molecular dynamics simulations in implicit and explicit solvent corroborated this finding. To ensure adequate sampling, we performed simulations of a tagged 10-residue segment of S100A1ct, and we carried out Gaussian accelerated molecular dynamics simulations of the peptides. These simulations showed that although the helical conformation of S100A1ct was the most energetically stable, the peptide can adopt a range of kinked conformations, suggesting that its activity may be related to its ability to act as a conformational switch.

Simulations of macromolecular diffusion and adsorption in confined environments can offer valuable mechanistic insights into numerous biophysical processes. In order to model solutes at atomic detail on relevant time scales, Brownian dynamics simulations can be carried out with the approximation of rigid body solutes moving through a continuum solvent. This allows the precomputation of interaction potential grids for the solutes, thereby allowing the computationally efficient calculation of forces. However, hydrodynamic and long-range electrostatic interactions cannot be fully treated with grid-based approaches alone. Here, we develop a treatment of both hydrodynamic and electrostatic interactions to include the presence of surfaces by modeling grid-based and long-range interactions. We describe its application to simulate the self-association and many-molecule adsorption of the well-characterized protein hen egg-white lysozyme to mica-like and silica-like surfaces. We find that the computational model can recover a number of experimental observables of the adsorption process and provide insights into their determinants. The computational model is implemented in the Simulation of Diffusional Association (SDA) software package.

Human cytochrome P450 (CYP) enzymes play an important role in the metabolism of drugs, steroids, fatty acids, and xenobiotics. Microsomal CYPs are anchored in the endoplasmic reticulum membrane by an N-terminal transmembrane (TM) helix that is connected to the globular catalytic domain by a flexible linker sequence. However, the structural and functional importance of the TM-helix is unclear because it has been shown that CYPs can still associate with the membrane and have enzymatic activity in reconstituted systems after truncation or modification of the N-terminal sequence. Here, we investigated the effect of mutations in the N-terminal TM-helix residues of two human steroidogenic enzymes, CYP 17A1 and CYP 19A1, that are major drug targets for cancer therapy. These mutations were originally introduced to increase the expression of the proteins in Escherichia coli. To investigate the effect of the mutations on protein-membrane interactions and function, we carried out coarse-grained and all-atom molecular dynamics simulations of the CYPs in a phospholipid bilayer. We confirmed the orientations of the globular domain in the membrane observed in the simulations by linear dichroism measurements in a Nanodisc. Whereas the behavior of CYP 19A1 was rather insensitive to truncation of the TM-helix, mutations in the TM-helix of CYP 17A1, especially W2A and E3L, led to a gradual drifting of the TM-helix out of the hydrophobic core of the membrane. This instability of the TM-helix could affect interactions with the allosteric redox partner, cytochrome b5, required for CYP 17A1's lyase activity. Furthermore, the simulations showed that the mutant TM-helix influenced the membrane interactions of the CYP 17A1 globular domain. In some simulations, the mutated TM-helix obstructed the substrate access tunnel from the membrane to the CYP active site, indicating a possible effect on enzyme function.

The recent and growing evidence that the efficacy of a drug can be correlated to target binding kinetics has seeded the development of a multitude of novel methods aimed at computing rate constants for receptor-ligand binding processes, as well as gaining an understanding of the binding and unbinding pathways and the determinants of structure-kinetic relationships. These new approaches include various types of enhanced sampling molecular dynamics simulations and the combination of energy-based models with chemometric analysis. We assess these approaches in the light of the varying levels of complexity of protein-ligand binding processes.

The human cytochrome P450 (CYP) 2C9 and 2C19 enzymes are two highly similar isoforms with key roles in drug metabolism. They are anchored to the endoplasmic reticulum membrane by their N-terminal transmembrane helix and interactions of their cytoplasmic globular domain with the membrane. However, their crystal structures were determined after N-terminal truncation and mutating residues in the globular domain that contact the membrane. Therefore, the CYP-membrane interactions are not structurally well-characterized and their dynamics and the influence of membrane interactions on CYP function are not well understood. We describe herein the modeling and simulation of CYP 2C9 and CYP 2C19 in a phospholipid bilayer. The simulations revealed that, despite high sequence conservation, the small sequence and structural differences between the two isoforms altered the interactions and orientations of the CYPs in the membrane bilayer. We identified residues (including K72, P73, and I99 in CYP 2C9 and E72, R73, and H99 in CYP 2C19) at the protein-membrane interface that contribute not only to the differing orientations adopted by the two isoforms in the membrane, but also to their differing substrate specificities by affecting the substrate access tunnels. Our findings provide a mechanistic interpretation of experimentally observed effects of mutagenesis on substrate selectivity.

ERRATUM Rudi Tong, Rebecca C. Wade, Neil J. Bruce "Comparative electrostatic analysis of adenylyl cyclase for isoform dependent regulation properties" Proteins: Structure, Function and Bioinformatics 2019 87(7), pp.619-620https://doi.org/10.1002/prot.25167 ORIGINAL PAPER: Rudi Tong, Rebecca C. Wade, Neil J. Bruce "Comparative electrostatic analysis of adenylyl cyclase for isoform dependent regulation properties" Proteins: Structure, Function and Bioinformatics 201684(12), pp.1844-1858https://doi.org/10.1002/prot.25167

Long-term potentiation and depression of synaptic activity in response to stimuli is a key factor in reinforcement learning. Strengthening of the corticostriatal synapses depends on the second messenger cAMP, whose synthesis is catalysed by the enzyme adenylyl cyclase 5 (AC5), which is itself regulated by the stimulatory G alpha(olf) and inhibitory G alpha(i) proteins. AC isoforms have been suggested to act as coincidence detectors, promoting cellular responses only when convergent regulatory signals occur close in time. However, the mechanism for this is currently unclear, and seems to lie in their diverse regulation patterns. Despite attempts to isolate the ternary complex, it is not known if G alpha(olf) and G alpha(i) can bind to AC5 simultaneously, nor what activity the complex would have. Using protein structure-based molecular dynamics simulations, we show that this complex is stable and inactive. These simulations, along with Brownian dynamics simulations to estimate protein association rates constants, constrain a kinetic model that shows that the presence of this ternary inactive complex is crucial for AC5's ability to detect coincident signals, producing a synergistic increase in cAMP. These results reveal some of the prerequisites for corticostriatal synaptic plasticity, and explain recent experimental data on cAMP concentrations following receptor activation. Moreover, they provide insights into the regulatory mechanisms that control signal processing by different AC isoforms., Author summary Adenylyl cyclases (ACs) are enzymes that can translate extracellular signals into the intracellular molecule cAMP, which is thus a 2nd messenger of extracellular events. The brain expresses nine membrane-bound AC variants, and AC5 is the dominant form in the striatum. The striatum is the input stage of the basal ganglia, a brain structure involved in reward learning, i.e. the learning of behaviors that lead to rewarding stimuli (such as food, water, sugar, etc). During reward learning, cAMP production is crucial for strengthening the synapses from cortical neurons onto the striatal principal neurons, and its formation is dependent on several neuromodulatory systems such as dopamine and acetylcholine. It is, however, not understood how AC5 is activated by transient (subsecond) changes in the neuromodulatory signals. Here we combine several computational tools, from molecular dynamics and Brownian dynamics simulations to bioinformatics approaches, to inform and constrain a kinetic model of the AC5-dependent signaling system. We use this model to show how the specific molecular properties of AC5 can detect particular combinations of co-occuring transient changes in the neuromodulatory signals which thus result in a supralinear/synergistic cAMP production. Our results also provide insights into the computational capabilities of the different AC isoforms.

The past few years have seen increasing recognition of the importance of understanding molecular binding kinetics. This has led to the development of myriad computational methods for studying the kinetics of binding processes and predicting their associated rate constants that show varying ranges of application, degrees of accuracy, and computational requirements. In order to help researchers decide which method might be suitable for their projects, we have developed KBbox, a web server that guides users in choosing the methods they should consider on the basis of the information they wish to obtain, the data they currently have available, and the computational resources to which they have access. KBbox provides information on the toolbox of available methods, their associated software tools, an expanding list of curated examples of published applications, and tutorials explaining how to apply some of the methods. It has been designed to allow the easy addition of new methods, tools, and examples as they are developed and published. KBbox is available at https://kbbox.h-its.org/ .

The simulation of diffusional association (SDA) Brownian dynamics software package has been widely used in the study of biomacromolecular association. Initially developed to calculate bimolecular protein–protein association rate constants, it has since been extended to study electron transfer rates, to predict the structures of biomacromolecular complexes, to investigate the adsorption of proteins to inorganic surfaces, and to simulate the dynamics of large systems containing many biomacromolecular solutes, allowing the study of concentration‐dependent effects. These extensions have led to a number of divergent versions of the software. In this article, we report the development of the latest version of the software (SDA 7). This release was developed to consolidate the existing codes into a single framework, while improving the parallelization of the code to better exploit modern multicore shared memory computer architectures. It is built using a modular object‐oriented programming scheme, to allow for easy maintenance and extension of the software, and includes new features, such as adding flexible solute representations. We discuss a number of application examples, which describe some of the methods available in the release, and provide benchmarking data to demonstrate the parallel performance. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein–protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. We are most grateful to the PDBe at the European Bioinformatics Institute in Hinxton, UK, for hosting the CAPRI website. Our deepest thanks go to all the structural biologists and to the following structural genomics initiatives: Northeast Structural Genomics Consortium, Joint Center for Structural Genomics, NatPro PSI:Biology, New York Structural Genomics Research Center, Midwest Center for Structural Genomics, Structural Genomics Consortium, for contributing the targets for this joint CASP-CAPRI experiment. MFL acknowledges support from the FRABio FR3688 Research Federation “Structural & Functional Biochemistry of Biomolecular Assemblies.”

The enzyme adenylyl cyclase (AC) plays a pivotal role in a variety of signal transduction pathways inside the cell, where it catalyzes the cyclization of adenosine triphosphate (ATP) into the second-messenger cyclic adenosine monophosphate (cAMP). Among other roles, AC regulates processes involved in neural plasticity, innervation of smooth muscles of the heart and the endocrine system of the pancreas. The functional diversity of AC is manifested in its different isoforms, each having a specific regulation pattern. There is an increasing amount of data available concerning the regulatory properties of AC isoforms, however little is known about the interactions on a structural level. Here, we conducted a comparative electrostatic analysis of the catalytic domains of all nine transmembrane AC isoforms with the aim of detecting, verifying and predicting the binding sites of molecular regulators on AC. The results provide support for the positioning of the binding site of the inhibitory protein G

Accumulation and aggregation of the 42-residue amyloid-β (Aβ) protein fragment, which originates from the cleavage of amyloid precursor protein by β and γ secretase, correlates with the pathology of Alzheimer's disease (AD). Possible therapies for AD include peptides based on the Aβ sequence, and recently identified small molecular weight compounds designed to mimic these, that interfere with the aggregation of Aβ and prevent its toxic effects on neuronal cells in culture. Here, we use molecular dynamics simulations to compare the mode of interaction of an active (LPFFD) and inactive (LHFFD) β-sheet breaker peptide with an Aβ fibril structure from solid-state NMR studies. We found that LHFFD had a weaker interaction with the fibril than the active peptide, LPFFD, from geometric and energetic considerations, as estimated by the MM/PBSA approach. Cluster analysis and computational alanine scanning identified important ligand-fibril contacts, including a possible difference in the effect of histidine on ligand-fibril π-stacking interactions, and the role of the proline residue in establishing contacts that compete with those essential for maintenance of the inter-monomer β-sheet structure of the fibril. Our results show that molecular dynamics simulations can be a useful way to classify the stability of docking sites. These mechanistic insights into the ability of LPFFD to reverse aggregation of toxic Aβ will guide the redesign of lead compounds, and aid in developing realistic therapies for AD and other diseases of protein aggregation.

The use of atomistic simulation techniques to directly resolve the protein tertiary structure from the primary amino acid sequence is hindered by the rough topology of the protein free energy surface and the resulting simulation time scales required. We explore here the use of a molecular dynamics technique based on swarm intelligence to identify the native states of two peptides and a Trp-cage miniprotein. In all cases, the presence of cooperative swarm interactions significantly enhanced the efficiency of molecular dynamics simulations in predicting the native conformation.

Free energy simulations are an established computational tool in modelling chemical change in the condensed phase. However, sampling of kinetically distinct substates remains a challenge to these approaches. As a route to addressing this, we link the methods of thermodynamic integration (TI) and swarm-enhanced sampling molecular dynamics (sesMD), where simulation replicas interact cooperatively to aid transitions over energy barriers. We illustrate the approach by using alchemical alkane transformations in solution, comparing them with the multiple independent trajectory TI (IT-TI) method. Free energy changes for transitions computed by using IT-TI grew increasingly inaccurate as the intramolecular barrier was heightened. By contrast, swarm-enhanced sampling TI (sesTI) calculations showed clear improvements in sampling efficiency, leading to more accurate computed free energy differences, even in the case of the highest barrier height. The sesTI approach, therefore, has potential in addressing chemical change in systems where conformations exist in slow exchange.

Macromolecular interactions play a crucial role in biological systems. Simulation of diffusional association (SDA) is a software for carrying out Brownian dynamics simulations that can be used to study the interactions between two or more biological macromolecules. webSDA allows users to run Brownian dynamics simulations with SDA to study bimolecular association and encounter complex formation, to compute association rate constants, and to investigate macromolecular crowding using atomically detailed macromolecular structures. webSDA facilitates and automates the use of the SDA software, and offers user-friendly visualization of results. webSDA currently has three modules: 'SDA docking' to generate structures of the diffusional encounter complexes of two macromolecules, 'SDA association' to calculate bimolecular diffusional association rate constants, and 'SDA multiple molecules' to simulate the diffusive motion of hundreds of macromolecules. webSDA is freely available to all users and there is no login requirement. webSDA is available at http://mcm.h-its.org/webSDA/.

Protein plasticity, while often linked to biological function, also provides opportunities for rational design of selective and potent inhibitors of their function. The application of computational methods to the prediction of concealed protein concavities is challenging, as the motions involved can be significant and occur over long time scales. Here we introduce the swarm-enhanced sampling molecular dynamics (sesMD) method as a tool to improve sampling of conformational landscapes. In this approach, a swarm of replica simulations interact cooperatively via a set of pairwise potentials incorporating attractive and repulsive components. We apply the sesMD approach to explore the conformations of the DFG motif in the protein p38α mitogen-activated protein kinase. In contrast to multiple MD simulations, sesMD trajectories sample a range of DFG conformations, some of which map onto existing crystal structures. Simulated structures intermediate between the DFG-in and DFG-out conformations are predicted to have druggable pockets of interest for structure-based ligand design.

The paper of Neil J. Bruce, Gaurav K. Ganotra, Stefan Richter, and Rebecca C. Wade "KBbox: A Toolbox of Computational Methods for Studying the Kinetics of Molecular Bindig", published in J. Chem. Inf. Model.20195993630-3634