OFraMP: a fragment-based tool to facilitate the parametrization of large molecules.

An Online tool for Fragment-based Molecule Parametrization (OFraMP) is described. OFraMP is a web application for assigning atomic interaction parameters to large molecules by matching sub-fragments within the target molecule to equivalent sub-fragments within the Automated Topology Builder (ATB, atb.uq.edu.au) database. OFraMP identifies and compares alternative molecular fragments from the ATB database, which contains over 890,000 pre-parameterized molecules, using a novel hierarchical matching procedure. Atoms are considered within the context of an extended local environment (buffer region) with the degree of similarity between an atom in the target molecule and that in the proposed match controlled by varying the size of the buffer region. Adjacent matching atoms are combined into progressively larger matched sub-structures. The user then selects the most appropriate match. OFraMP also allows users to manually alter interaction parameters and automates the submission of missing substructures to the ATB in order to generate parameters for atoms in environments not represented in the existing database. The utility of OFraMP is illustrated using the anti-cancer agent paclitaxel and a dendrimer used in organic semiconductor devices. OFraMP applied to paclitaxel (ATB ID 35922).

Miniature microscopes for manipulating and recording in vivo brain activity.

Here we describe the development and application of miniature integrated microscopes (miniscopes) paired with microendoscopes that allow for the visualization and manipulation of neural circuits in superficial and subcortical brain regions in freely behaving animals. Over the past decade the miniscope platform has expanded to include simultaneous optogenetic capabilities, electrically-tunable lenses that enable multi-plane imaging, color-corrected optics, and an integrated data acquisition platform that streamlines multimodal experiments. Miniscopes have given researchers an unprecedented ability to monitor hundreds to thousands of genetically-defined neurons from weeks to months in both healthy and diseased animal brains. Sophisticated algorithms that take advantage of constrained matrix factorization allow for background estimation and reliable cell identification, greatly improving the reliability and scalability of source extraction for large imaging datasets. Data generated from miniscopes have empowered researchers to investigate the neural circuit underpinnings of a wide array of behaviors that cannot be studied under head-fixed conditions, such as sleep, reward seeking, learning and memory, social behaviors, and feeding. Importantly, the miniscope has broadened our understanding of how neural circuits can go awry in animal models of progressive neurological disorders, such as Parkinson's disease. Continued miniscope development, including the ability to record from multiple populations of cells simultaneously, along with continued multimodal integration of techniques such as electrophysiology, will allow for deeper understanding into the neural circuits that underlie complex and naturalistic behavior.

2.7 Å cryo-EM structure of vitrified M. musculus H-chain apoferritin from a compact 200 keV cryo-microscope.

Here we present the structure of mouse H-chain apoferritin at 2.7 Å (FSC = 0.143) solved by single particle cryogenic electron microscopy (cryo-EM) using a 200 kV device, the Thermo Fisher Glacios®. This is a compact, two-lens illumination system with a constant power objective lens, without any energy filters or aberration correctors, often thought of as a "screening cryo-microscope". Coulomb potential maps reveal clear densities for main chain carbonyl oxygens, residue side chains (including alternative conformations) and bound solvent molecules. We used a quasi-crystallographic reciprocal space approach to fit model coordinates to the experimental cryo-EM map. We argue that the advantages offered by (a) the high electronic and mechanical stability of the microscope, (b) the high emission stability and low beam energy spread of the high brightness Field Emission Gun (X-FEG), (c) direct electron detection technology and (d) particle-based Contrast Transfer Function (CTF) refinement have contributed to achieving high resolution. Overall, we show that basic electron optical settings for automated cryo-electron microscopy imaging can be used to determine structures approaching atomic resolution.

Deriving a Polarizable Force Field for Biomolecular Building Blocks with Minimal Empirical Calibration.

Force field parametrization involves a complex set of linked optimization problems, with the goal of describing complex molecular interactions by using simple classical potential-energy functions that model Coulomb interactions, dispersion, and exchange repulsion. These functions comprise a set of atomic (and molecular) parameters and together with the bonded terms they constitute the molecular mechanics force field. Traditionally, many of these parameters have been fitted in a calibration approach in which experimental measures for thermodynamic and other relevant properties of small-molecule compounds are used for fitting and validation. As these approaches are laborious and time-consuming and represent an underdetermined optimization problem, we study methods to fit and derive an increasing number of parameters directly from electronic structure calculations, in order to greatly reduce possible parameter space for the remaining free parameters. In the current work we investigate a polarizable model with a higher order dispersion term for use in biomolecular simulation. Results for 49 biochemically relevant molecules are presented including updated parameters for hydrocarbon side chains. We show that our recently presented set of QM/MM derived atomic polarizabilities can be used in direct conjunction with partial charges and a higher order dispersion model that are quantum-mechanically determined, to freeze nearly all (i.e., 132 out of 138) nonbonded parameters to their quantum determined values.

Deriving Force-Field Parameters from First Principles Using a Polarizable and Higher Order Dispersion Model.

In this work we propose a strategy based on quantum mechanical (QM) calculations to parametrize a polarizable force field for use in molecular dynamics (MD) simulations. We investigate the use of multiple atoms-in-molecules (AIM) strategies to partition QM determined molecular electron densities into atomic subregions. The partitioned atomic densities are subsequently used to compute atomic dispersion coefficients from effective exchange-hole-dipole moment (XDM) calculations. In order to derive values for the repulsive van der Waals parameters from first principles, we use a simple volume relation to scale effective atomic radii. Explicit inclusion of higher order dispersion coefficients was tested for a series of alkanes, and we show that combining C6 and C8 attractive terms together with a C11 repulsive potential yields satisfying models when used in combination with our van der Waals parameters and electrostatic and bonded parameters as directly obtained from quantum calculations as well. This result highlights that explicit inclusion of higher order dispersion terms could be viable in simulation, and it suggests that currently available QM analysis methods allow for first-principles parametrization of molecular mechanics models.

A QM/MM Derived Polarizable Water Model for Molecular Simulation.

In this work, we propose an improved QM/MM-based strategy to determine condensed-phase polarizabilities and we use this approach to optimize a new and simple polarizable four-site water model for classical molecular simulation. For the determination of the model value for the polarizability from QM/MM, we show that our proposed consensus-fitting strategy significantly reduces the uncertainty in calculated polarizabilities in cases where the size of the local external electric field is small. By fitting electrostatic, polarization and dispersion properties of our water model based on quantum and/or combined QM/MM calculations, only a single model parameter (describing exchange repulsion) is left for empirical calibration. The resulting model performs well in describing relevant pure-liquid thermodynamic and transport properties, which illustrates the merit of our approach to minimize the number of free variables in our model.

Automated Topology Builder Version 3.0: Prediction of Solvation Free Enthalpies in Water and Hexane.

The ability of atomic interaction parameters generated using the Automated Topology Builder and Repository version 3.0 (ATB3.0) to predict experimental hydration free enthalpies (Δ Gwater) and solvation free enthalpies in the apolar solvent hexane (Δ Ghexane) is presented. For a validation set of 685 molecules the average unsigned error (AUE) between Δ Gwater values calculated using the ATB3.0 and experiment is 3.8 kJ·mol-1. The slope of the line of best fit is 1.00, the intercept -1.0 kJ·mol-1, and the R2 0.90. For the more restricted set of 239 molecules used to validate OPLS3 ( J. Chem. Theory Comput. 2016 , 12 , 281 - 296 , DOI: 10.1021/acs.jctc.5b00864 ) the AUE using the ATB3.0 is just 2.7 kJ·mol-1 and the R2 0.93. A roadmap for further improvement of the ATB parameters is presented together with a discussion of the challenges of validating force fields against the available experimental data.

Predicting the Prevalence of Alternative Warfarin Tautomers in Solution.

Warfarin, a widely used oral anticoagulant, is prescribed as a racemic mixture. Each enantiomer of neutral Warfarin can exist in 20 possible tautomeric states leading to complex pharmacokinetics and uncertainty as to the relevant species under different conditions. Here, the ability of alternative computational approaches to predict the preferred tautomeric form(s) of neutral Warfarin in different solvents is examined. It is shown that varying the method used to estimate the heat of formation in vacuum (direct or via homodesmic reactions), whether entropic corrections were included, and the method used to estimate the free enthalpy of solvation (i.e., PCM, COSMO, or SMD implicit models or explicit solvent) lead to large differences in the predicted rank and relative populations of the tautomers. In this case, only a combination of the enthalpy of formation using homodesmic reactions and explicit solvent to estimate the free enthalpy of solvation yielded results compatible with the available experimental data. The work also suggests that a small but significant subset of the possible Warfarin tautomers are likely to be physiologically relevant.

Engineered factor Xa variants retain procoagulant activity independent of direct factor Xa inhibitors.

The absence of an adequate reversal strategy to prevent and stop potential life-threatening bleeding complications is a major drawback to the clinical use of the direct oral inhibitors of blood coagulation factor Xa. Here we show that specific modifications of the substrate-binding aromatic S4 subpocket within the factor Xa active site disrupt high-affinity engagement of the direct factor Xa inhibitors. These modifications either entail amino-acid substitution of S4 subsite residues Tyr99 and/or Phe174 (chymotrypsinogen numbering), or extension of the 99-loop that borders the S4 subsite. The latter modifications led to the engineering of a factor Xa variant that is able to support coagulation in human plasma spiked with (supra-)physiological concentrations of direct factor Xa inhibitors. As such, this factor Xa variant has the potential to be employed to bypass the direct factor Xa inhibitor-mediated anticoagulation in patients that require restoration of blood coagulation.A major drawback in the clinical use of the oral anticoagulants that directly inhibit factor Xa in order to prevent blood clot formation is the potential for life threatening bleeding events. Here the authors describe factor Xa variants that are refractory to inhibition by these anticoagulants and could serve as rescue agents in treated patients.

Supramolecular Organization and Functional Implications of K+ †Channel Clusters in Membranes.

The segregation of cellular surfaces in heterogeneous patches is considered to be a common motif in bacteria and eukaryotes that is underpinned by the observation of clustering and cooperative gating of signaling membrane proteins such as receptors or channels. Such processes could represent an important cellular strategy to shape signaling activity. Hence, structural knowledge of the arrangement of channels or receptors in supramolecular assemblies represents a crucial step towards a better understanding of signaling across membranes. We herein report on the supramolecular organization of clusters of the K+ channel KcsA in bacterial membranes, which was analyzed by a combination of DNP-enhanced solid-state NMR experiments and MD simulations. We used solid-state NMR spectroscopy to determine the channel-channel interface and to demonstrate the strong correlation between channel function and clustering, which suggests a yet unknown mechanism of communication between K+ channels.

A systematic approach to calibrate a transferable polarizable force field parameter set for primary alcohols.

In this work, parameters are optimized for a charge-on-spring based polarizable force field for linear alcohols. We show that parameter transferability can be obtained using a systematic approach in which the effects of parameter changes on physico-chemical properties calculated from simulation are predicted. Our previously described QM/MM calculations are used to attribute condensed-phase polarizabilities, and starting from the non-polarizable GROMOS 53A5/53A6 parameter set, van der Waals and Coulomb interaction parameters are optimized to reproduce pure-liquid (thermodynamic, dielectric, and transport) properties, as well as hydration free energies. For a large set of models, which were obtained by combining small perturbations of 10 distinct parameters, values for pure-liquid properties of the series methanol to butanol were close to experiment. From this large set of models, we selected 34 models without special repulsive van der Waals parameters to distinguish between hydrogen-bonding and non-hydrogen-bonding atom pairs, to make the force field simple and transparent. © 2017 Wiley Periodicals, Inc.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment.

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. Proteins 2016; 84(Suppl 1):323-348. © 2016 Wiley Periodicals, Inc.

-1 Programmed Ribosomal Frameshifting as a Force-Dependent Process.

-1 Programmed ribosomal frameshifting is a translational recoding event in which ribosomes slip backward along messenger RNA presumably due to increased tension disrupting the codon-anticodon interaction at the ribosome's coding site. Single-molecule physical methods and recent experiments characterizing the physical properties of mRNA's slippery sequence as well as the mechanical stability of downstream mRNA structure motifs that give rise to frameshifting are discussed. Progress in technology, experimental assays, and data analysis methods hold promise for accurate physical modeling and quantitative understanding of -1 programmed ribosomal frameshifting.

The Supramolecular Organization of a Peptide-Based Nanocarrier at High Molecular Detail.

Nanovesicles self-assembled from amphiphilic peptides are promising candidates for applications in drug delivery. However, complete high-resolution data on the local and supramolecular organization of such materials has been elusive thus far, which is a substantial obstacle to their rational design. In the absence of precise information, nanovesicles built of amphiphilic "lipid-like" peptides are generally assumed to resemble liposomes that are organized from bilayers of peptides with a tail-to-tail ordering. Using the nanocarrier formed by the amphiphilic self-assembling peptide 2 (SA2 peptide) as an example, we derive the local and global organization of a multimega-Dalton peptide-based nanocarrier at high molecular detail and at close-to physiological conditions. By integrating a multitude of experimental techniques (solid-state NMR, AFM, SLS, DLS, FT-IR, CD) with large- and multiscale MD simulations, we show that SA2 nanocarriers are built of interdigitated antiparallel ß-sheets, which bear little resemblance to phospholipid liposomes. Our atomic level study allows analyzing the vesicle surface structure and dynamics as well as the intermolecular forces between peptides, providing a number of potential leads to improve and tune the biophysical properties of the nanocarrier. The herein presented approach may be of general utility to investigate peptide-based nanomaterials at high-resolution and at physiological conditions.

Non-interacting surface solvation and dynamics in protein-protein interactions.

Protein-protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure-based drug design methods, as well as design of de novo binders with preferred interaction properties. At a structural and molecular level, interface and rim regions are not enough to fully account for the energetics of protein-protein binding, even for simple lock-and-key rigid binders. As we have recently shown, properties of the global surface might also play a role in protein-protein interactions. Here, we report on molecular dynamics simulations performed to understand solvent effects on protein-protein surfaces. We compare properties of the interface, rim, and non-interacting surface regions for five different complexes and their free components. Interface and rim residues become, as expected, less mobile upon complexation. However, non-interacting surface appears more flexible in the complex. Fluctuations of polar residues are always lower compared with charged ones, independent of the protein state. Further, stable water molecules are often observed around polar residues, in contrast to charged ones. Our analysis reveals that (a) upon complexation, the non-interacting surface can have a direct entropic compensation for the lower interface and rim entropy and (b) the mobility of the first hydration layer, which is linked to the stability of the protein-protein complex, is influenced by the local chemical properties of the surface. These findings corroborate previous hypotheses on the role of the hydration layer in shielding protein-protein complexes from unintended protein-protein interactions.

A stochastic model of translation with -1 programmed ribosomal frameshifting.

Many viruses produce multiple proteins from a single mRNA sequence by encoding overlapping genes. One mechanism to decode both genes, which reside in alternate reading frames, is -1 programmed ribosomal frameshifting. Although recognized for over 25 years, the molecular and physical mechanism of -1 frameshifting remains poorly understood. We have developed a mathematical model that treats mRNA translation and associated -1 frameshifting as a stochastic process in which the transition probabilities are based on the energetics of local molecular interactions. The model predicts both the location and efficiency of -1 frameshift events in HIV-1. Moreover, we compute -1 frameshift efficiencies upon mutations in the viral mRNA sequence and variations in relative tRNA abundances, predictions that are directly testable in experiment.

Solvated protein-DNA docking using HADDOCK.

Interfacial water molecules play an important role in many aspects of protein-DNA specificity and recognition. Yet they have been mostly neglected in the computational modeling of these complexes. We present here a solvated docking protocol that allows explicit inclusion of water molecules in the docking of protein-DNA complexes and demonstrate its feasibility on a benchmark of 30 high-resolution protein-DNA complexes containing crystallographically-determined water molecules at their interfaces. Our protocol is capable of reproducing the solvation pattern at the interface and recovers hydrogen-bonded water-mediated contacts in many of the benchmark cases. Solvated docking leads to an overall improvement in the quality of the generated protein-DNA models for cases with limited conformational change of the partners upon complex formation. The applicability of this approach is demonstrated on real cases by docking a representative set of 6 complexes using unbound protein coordinates, model-built DNA and knowledge-based restraints. As HADDOCK supports the inclusion of a variety of NMR restraints, solvated docking is also applicable for NMR-based structure calculations of protein-DNA complexes.

Solvated protein-protein docking using Kyte-Doolittle-based water preferences.

HADDOCK is one of the few docking programs that can explicitly account for water molecules in the docking process. Its solvated docking protocol starts from hydrated molecules and a fraction of the resulting interfacial waters is subsequently removed in a biased Monte Carlo procedure based on water-mediated contact probabilities. The latter were derived from an analysis of water contact frequencies from high-resolution crystal structures. Here, we introduce a simple water-mediated amino acid-amino acid contact probability scale derived from the Kyte-Doolittle hydrophobicity scale and assess its performance on the largest high-resolution dataset developed to date for solvated docking. Both scales yield high-quality docking results. The novel and simple hydrophobicity scale, which should reflect better the physicochemical principles underlying contact propensities, leads to a performance improvement of around 10% in ranking, cluster quality and water recovery at the interface compared with the statistics-based original solvated docking protocol.

Optical trapping and unfolding of RNA.

Optical tweezers have proven a useful tool for exploring the structure and function of individual molecules, such as proteins, DNA, and RNA. The ability to unfold and refold biological molecules has provided novel insights that complement and go beyond traditional biochemical and structural approaches. With sophisticated optical tweezers instrumentation coming to the market, single-molecule stretching studies now have become feasible and available to a wide range of users. Therefore, a step-by-step protocol for stretching individual biomolecules utilizing a simple experimental geometry is timely and presented here. While we have taken the unfolding of an RNA structure held between two RNA/DNA hybrid handles as an example, the technical protocol should be readily applicable to other biomolecules and may serve as a starting point for more sophisticated experiments.

Mechanical unfolding of the beet western yellow virus -1 frameshift signal.

Using mechanical unfolding by optical tweezers (OT) and steered molecular dynamics (SMD) simulations, we have demonstrated the critical role of Mg(2+) ions for the resistance of the Beet Western Yellow Virus (BWYV) pseudoknot (PK) to unfolding. The two techniques were found to be complementary, providing information at different levels of molecular scale. Findings from the OT experiments indicated a critical role of stem 1 for unfolding of the PK, which was confirmed in the SMD simulations. The unfolding pathways of wild type and mutant appeared to depend upon pH and nucleotide sequence. SMD simulations support the notion that the stability of stem 1 is critical for -1 frameshifting. The all-atom scale nature of the SMD enabled clarification of the precise role of two Mg(2+) ions, Mg45 and Mg52, as identified in the BWYV X-ray crystallography structure, in -1 frameshifting. On the basis of simulations with "partially" and "fully" hydrated Mg(2+) ions, two possible mechanisms of stabilizing stem 1 are proposed. In both these cases Mg(2+) ions play a critical role in stabilizing stem 1, either by directly forming a salt bridge between the strands of stem 1 or by stabilizing parallel orientation of the strands in stem 1, respectively. These findings explain the unexpected drop in frameshifting efficiency to null levels of the C8U mutant in a manner consistent with experimental observations.