Conformational Space of the Translocation Domain of Botulinum Toxin: Atomistic Modeling and Mesoscopic Description of the Coiled-Coil Helix Bundle.

The toxicity of botulinum multi-domain neurotoxins (BoNTs) arises from a sequence of molecular events, in which the translocation of the catalytic domain through the membrane of a neurotransmitter vesicle plays a key role. A recent structural study of the translocation domain of BoNTs suggests that the interaction with the membrane is driven by the transition of an α helical switch towards a ß hairpin. Atomistic simulations in conjunction with the mesoscopic Twister model are used to investigate the consequences of this proposition for the toxin-membrane interaction. The conformational mobilities of the domain, as well as the effect of the membrane, implicitly examined by comparing water and water-ethanol solvents, lead to the conclusion that the transition of the switch modifies the internal dynamics and the effect of membrane hydrophobicity on the whole protein. The central two α helices, helix 1 and helix 2, forming two coiled-coil motifs, are analyzed using the Twister model, in which the initial deformation of the membrane by the protein is caused by the presence of local torques arising from asymmetric positions of hydrophobic residues. Different torque distributions are observed depending on the switch conformations and permit an origin for the mechanism opening the membrane to be proposed.

New Crystal Form of Human Neuropilin-1 b1 Fragment with Six Electrostatic Mutations Complexed with KDKPPR Peptide Ligand.

Neuropilin 1 (NRP1), a cell-surface co-receptor of a number of growth factors and other signaling molecules, has long been the focus of attention due to its association with the development and the progression of several types of cancer. For example, the KDKPPR peptide has recently been combined with a photosensitizer and a contrast agent to bind NRP1 for the detection and treatment by photodynamic therapy of glioblastoma, an aggressive brain cancer. The main therapeutic target is a pocket of the fragment b1 of NRP1 (NRP1-b1), in which vascular endothelial growth factors (VEGFs) bind. In the crystal packing of native human NRP1-b1, the VEGF-binding site is obstructed by a crystallographic symmetry neighbor protein, which prevents the binding of ligands. Six charged amino acids located at the protein surface were mutated to allow the protein to form a new crystal packing. The structure of the mutated fragment b1 complexed with the KDKPPR peptide was determined by X-ray crystallography. The variant crystallized in a new crystal form with the VEGF-binding cleft exposed to the solvent and, as expected, filled by the C-terminal moiety of the peptide. The atomic interactions were analyzed using new approaches based on a multipolar electron density model. Among other things, these methods indicated the role played by Asp320 and Glu348 in the electrostatic steering of the ligand in its binding site. Molecular dynamics simulations were carried out to further analyze the peptide binding and motion of the wild-type and mutant proteins. The simulations revealed that specific loops interacting with the peptide exhibited mobility in both the unbound and bound forms.

Low-resolution description of the conformational space for intrinsically disordered proteins.

Intrinsically disordered proteins (IDP) are at the center of numerous biological processes, and attract consequently extreme interest in structural biology. Numerous approaches have been developed for generating sets of IDP conformations verifying a given set of experimental measurements. We propose here to perform a systematic enumeration of protein conformations, carried out using the TAiBP approach based on distance geometry. This enumeration was performed on two proteins, Sic1 and pSic1, corresponding to unphosphorylated and phosphorylated states of an IDP. The relative populations of the obtained conformations were then obtained by fitting SAXS curves as well as Ramachandran probability maps, the original finite mixture approach RamaMix being developed for this second task. The similarity between profiles of local gyration radii provides to a certain extent a converged view of the Sic1 and pSic1 conformational space. Profiles and populations are thus proposed for describing IDP conformations. Different variations of the resulting gyration radius between phosphorylated and unphosphorylated states are observed, depending on the set of enumerated conformations as well as on the methods used for obtaining the populations.

In Silico Conformational Features of Botulinum Toxins A1 and E1 According to Intraluminal Acidification.

Although botulinum neurotoxins (BoNTs) are among the most toxic compounds found in nature, their molecular mechanism of action is far from being elucidated. A key event is the conformational transition due to acidification of the interior of synaptic vesicles, leading to translocation of the BoNT catalytic domain into the neuronal cytosol. To investigate these conformational variations, homology modeling and atomistic simulations are combined to explore the internal dynamics of the sub-types BoNT/A1 (the most-used sub-type in medical applications) and BoNT/E1 (the most kinetically efficient sub-type). This first simulation study of di-chain BoNTs in closed and open states considers the effects of both neutral and acidic pH. The conformational mobility is driven by domain displacements of the ganglioside-binding site in the receptor binding domain, the translocation domain (HCNT) switch, and the belt α-helix, which present multiple conformations, depending on the primary sequence and the pH. Fluctuations of the belt α-helix are observed for closed conformations of the toxins and at acidic pH, while patches of more solvent-accessible residues appear under the same conditions in the core translocation domain HCNT. These findings suggest that, during translocation, the higher mobility of the belt could be transmitted to HCNT, leading to the favorable interaction of HCNT residues with the non-polar membrane environment.

Conformational Insights into the Control of CNF1 Toxin Activity by Peptidyl-Prolyl Isomerization: A Molecular Dynamics Perspective.

The cytotoxic necrotizing factor 1 (CNF1) toxin from uropathogenic Escherichia coli constitutively activates Rho GTPases by catalyzing the deamidation of a critical glutamine residue located in the switch II (SWII). In crystallographic structures of the CNF1 catalytic domain (CNF1CD), surface-exposed P768 and P968 peptidyl-prolyl imide bonds (X-Pro) adopt an unusual cis conformation. Here, we show that mutation of each proline residue into glycine abrogates CNF1CD in vitro deamidase activity, while mutant forms of CNF1 remain functional on RhoA in cells. Using molecular dynamics simulations coupled to protein-peptide docking, we highlight the long-distance impact of peptidyl-prolyl cis-trans isomerization on the network of interactions between the loops bordering the entrance of the catalytic cleft. The energetically favorable isomerization of P768 compared with P968, induces an enlargement of loop L1 that fosters the invasion of CNF1CD catalytic cleft by a peptide encompassing SWII of RhoA. The connection of the P968 cis isomer to the catalytic cysteine C866 via a ladder of stacking interactions is alleviated along the cis-trans isomerization. Finally, the cis-trans conversion of P768 favors a switch of the thiol side chain of C866 from a resting to an active orientation. The long-distance impact of peptidyl-prolyl cis-trans isomerizations is expected to have implications for target modification.

Tandem domain structure determination based on a systematic enumeration of conformations.

Protein structure determination is undergoing a change of perspective due to the larger importance taken in biology by the disordered regions of biomolecules. In such cases, the convergence criterion is more difficult to set up and the size of the conformational space is a obstacle to exhaustive exploration. A pipeline is proposed here to exhaustively sample protein conformations using backbone angle limits obtained by nuclear magnetic resonance (NMR), and then to determine the populations of conformations. The pipeline is applied to a tandem domain of the protein whirlin. An original approach, derived from a reformulation of the Distance Geometry Problem is used to enumerate the conformations of the linker connecting the two domains. Specifically designed procedure then permit to assemble the domains to the linker conformations and to optimize the tandem domain conformations with respect to two sets of NMR measurements: residual dipolar couplings and paramagnetic resonance enhancements. The relative populations of optimized conformations are finally determined by fitting small angle X-ray scattering (SAXS) data. The most populated conformation of the tandem domain is a semi-closed one, fully closed and more extended conformations being in minority, in agreement with previous observations. The SAXS and NMR data show different influences on the determination of populations.

Analyzing In Silico the Relationship Between the Activation of the Edema Factor and Its Interaction With Calmodulin.

Molecular dynamics (MD) simulations have been recorded on the complex between the edema factor (EF) of Bacilllus anthracis and calmodulin (CaM), starting from a structure with the orthosteric inhibitor adefovir bound in the EF catalytic site. The starting structure has been destabilized by alternately suppressing different co-factors, such as adefovir ligand or ions, revealing several long-distance correlations between the conformation of CaM, the geometry of the CaM/EF interface, the enzymatic site and the overall organization of the complex. An allosteric communication between CaM/EF interface and the EF catalytic site, highlighted by these correlations, was confirmed by several bioinformatics approaches from the literature. A network of hydrogen bonds and stacking interactions extending from the helix V of of CaM, and the residues of the switches A, B and C, and connecting to catalytic site residues, is a plausible candidate for the mediation of allosteric communication. The greatest variability in volume between the different MD conditions was also found for cavities present at the EF/CaM interface and in the EF catalytic site. The similarity between the predictions from literature and the volume variability might introduce the volume variability as new descriptor of allostery.

Systematic Exploration of Protein Conformational Space Using a Distance Geometry Approach.

The optimization approaches classically used during the determination of protein structure encounter various difficulties, especially when the size of the conformational space is large. Indeed, in such a case, algorithmic convergence criteria are more difficult to set up. Moreover, the size of the search space makes it difficult to achieve a complete exploration. The interval branch-and-prune (iBP) approach, based on the reformulation of the distance geometry problem (DGP) provides a theoretical frame for the generation of protein conformations, by systematically sampling the conformational space. When an appropriate subset of interatomic distances is known exactly, this worst-case exponential-time algorithm is provably complete and fixed-parameter tractable. These guarantees, however, immediately disappear as distance measurement errors are introduced. Here we propose an improvement of this approach: threading-augmented interval branch-and-prune (TAiBP), where the combinatorial explosion of the original iBP approach arising from its exponential complexity is alleviated by partitioning the input instances into consecutive peptide fragments and by using self-organizing maps (SOMs) to obtain clusters of similar solutions. A validation of the TAiBP approach is presented here on a set of proteins of various sizes and structures. The calculation inputs are a uniform covalent geometry extracted from force field covalent terms, the backbone dihedral angles with error intervals, and a few long-range distances. For most of the proteins smaller than 50 residues and interval widths of 20°, the TAiBP approach yielded solutions with RMSD values smaller than 3 Å with respect to the initial protein conformation. The efficiency of the TAiBP approach for proteins larger than 50 residues will require the use of nonuniform covalent geometry and may have benefits from the recent development of residue-specific force-fields.

Structural Biology and Molecular Modeling to Analyze the Entry of Bacterial Toxins and Virulence Factors into Host Cells.

Understanding the functions and mechanisms of biological systems is an outstanding challenge. One way to overcome it is to combine together several approaches such as molecular modeling and experimental structural biology techniques. Indeed, the interplay between structural and dynamical properties of the system is crucial to unravel the function of molecular machinery's. In this review, we focus on how molecular simulations along with structural information can aid in interpreting biological data. Here, we examine two different cases: (i) the endosomal translocation toxins (diphtheria, tetanus, botulinum toxins) and (ii) the activation of adenylyl cyclase inside the cytoplasm (edema factor, CyA, ExoY).

Minimal NMR distance information for rigidity of protein graphs.

Nuclear Magnetic Resonance (NMR) experiments provide distances between nearby atoms of a protein molecule. The corresponding structure determination problem is to determine the 3D protein structure by exploiting such distances. We present a new order on the atoms of the protein, based on information from the chemistry of proteins and NMR experiments, which allows us to formulate the problem as a combinatorial search. Additionally, this order tells us what kind of NMR distance information is crucial to understand the cardinality of the solution set of the problem and its computational complexity.

Conformational sampling of CpxA: Connecting HAMP motions to the histidine kinase function.

In the histidine kinase family, the HAMP and DHp domains are considered to play an important role into the transmission of signal arising from environmental conditions to the auto-phosphorylation site and to the binding site of response regulator. Several conformational motions inside HAMP have been proposed to transmit this signal: (i) the gearbox model, (ii) α helices rotations, pistons and scissoring, (iii) transition between ordered and disordered states. In the present work, we explore by temperature-accelerated molecular dynamics (TAMD), an enhanced sampling technique, the conformational space of the cytoplasmic region of histidine kinase CpxA. Several HAMP motions, corresponding to α helices rotations, pistoning and scissoring have been detected and correlated to the segmental motions of HAMP and DHp domains of CpxA.

Closed-Locked and Apo-Resting State Structures of the Human α7 Nicotinic Receptor: A Computational Study.

Nicotinic acetylcholine receptors, belonging to the Cys-loop superfamily of ligand-gated ion channels (LGICs), are membrane proteins present in neurons and at neuromuscular junctions. They are responsible for signal transmission, and their function is regulated by neurotransmitters, agonists, and antagonists drugs. A detailed knowledge of their conformational transition in response to ligand binding is critical to understanding the basis of ligand-receptor interaction, in view of new pharmacological approaches to control receptor activity. However, the scarcity of experimentally derived structures of human channels makes this perspective extremely challenging. To contribute overcoming this issue, we have recently reported structural models for the open and the desensitized states of the human α7 nicotinic receptor. Here, we provide all-atom structural models of the same receptor in two different nonconductive states. The first structure, built via homology modeling and relaxed with extensive Molecular Dynamics simulations, represents the receptor bound to the natural antagonist α-conotoxin ImI. After comparison with available experimental data and computational models of other eukaryotic LGICs, we deem it consistent with the "closed-locked" state. The second model, obtained with simulations from the spontaneous relaxation of the open, agonist-bound α7 structure after ligand removal, recapitulates the characteristics of the apo-resting state of the receptor. These results add to our previous work on the active and desensitized state conformations, contributing to the structural characterization of the conformational landscape of the human α7 receptor and suggesting benchmarks to discriminate among conformations found in experiments or in simulations of LGICs. In particular key interactions at the interface between the extracellular domain and the transmembrane domain are identified, that could be critical to the α7 receptor function.

re-TAMD: exploring interactions between H3 peptide and YEATS domain using enhanced sampling.

BACKGROUND: Analysis of preferred binding regions of a ligand on a protein is important for detecting cryptic binding pockets and improving the ligand selectivity. RESULT: The enhanced sampling approach TAMD has been adapted to allow a ligand to unbind from its native binding site and explore the protein surface. This so-called re-TAMD procedure was then used to explore the interaction between the N terminal peptide of histone H3 and the YEATS domain. Depending on the length of the peptide, several regions of the protein surface were explored. The peptide conformations sampled during the re-TAMD correspond to peptide free diffusion around the protein surface. CONCLUSIONS: The re-TAMD approach permitted to get information on the relative influence of different regions of the N terminal peptide of H3 on the interaction between H3 and YEATS.

Molecular Modeling of the Catalytic Domain of CyaA Deepened the Knowledge of Its Functional Dynamics.

Although CyaA has been studied for over three decades and revealed itself to be a very good prototype for developing various biotechnological applications, only a little is known about its functional dynamics and about the conformational landscape of this protein. Molecular dynamics simulations helped to clarify the view on these points in the following way. First, the model of interaction between AC and calmodulin (CaM) has evolved from an interaction centered on the surface between C-CaM hydrophobic patch and the α helix H of AC, to a more balanced view, in which the C-terminal tail of AC along with the C-CaM Calcium loops play an important role. This role has been confirmed by the reduction of the affinity of AC for calmodulin in the presence of R338, D360 and N347 mutations. In addition, enhanced sampling studies have permitted to propose a representation of the conformational space for the isolated AC. It remains to refine this representation using structural low resolution information measured on the inactive state of AC. Finally, due to a virtual screening study on another adenyl cyclase from Bacillus anthracis, weak inhibitors of AC have been discovered.

Building Graphs To Describe Dynamics, Kinetics, and Energetics in the d-ALa:d-Lac Ligase VanA.

The d-Ala:d-Lac ligase, VanA, plays a critical role in the resistance of vancomycin. Indeed, it is involved in the synthesis of a peptidoglycan precursor, to which vancomycin cannot bind. The reaction catalyzed by VanA requires the opening of the so-called "ω-loop", so that the substrates can enter the active site. Here, the conformational landscape of VanA is explored by an enhanced sampling approach: the temperature-accelerated molecular dynamics (TAMD). Analysis of the molecular dynamics (MD) and TAMD trajectories recorded on VanA permits a graphical description of the structural and kinetics aspects of the conformational space of VanA, where the internal mobility and various opening modes of the ω-loop play a major role. The other important feature is the correlation of the ω-loop motion with the movements of the opposite domain, defined as containing the residues A149-Q208. Conformational and kinetic clusters have been determined and a path describing the ω-loop opening was extracted from these clusters. The determination of this opening path, as well as the relative importance of hydrogen bonds along the path, permit one to propose some key residue interactions for the kinetics of the ω-loop opening.

Modification in hydrophobic packing of HAMP domain induces a destabilization of the auto-phosphorylation site in the histidine kinase CpxA.

The histidine kinases belong to the family of two-component systems, which serves in bacteria to couple environmental stimuli to adaptive responses. Most of the histidine kinases are homodimers, in which the HAMP and DHp domains assemble into an elongated helical region flanked by two CA domains. Recently, X-ray crystallographic structures of the cytoplasmic region of the Escherichia coli histidine kinase CpxA were determined and a phosphotransferase-defective mutant, M228V, located in HAMP, was identified. In the present study, we recorded 1 µs molecular dynamics trajectories to compare the behavior of the WT and M228V protein dimers. The M228V modification locally induces the appearance of larger voids within HAMP as well as a perturbation of the number of voids within DHp, thus destabilizing the HAMP and DHp hydrophobic packing. In addition, a disruption of the stacking interaction between F403 located in the lid of the CA domain involved in the auto-phosphorylation and R296 located in the interacting DHp region, is more often observed in the presence of the M228V modification. Experimental modifications R296A and R296D of CpxA have been observed to reduce also the CpxA activity. These observations agree with the destabilization of the R296/F403 stacking, and could be the sign of the transmission of a conformational event taking place in HAMP to the auto-phosphorylation site of histidine kinase. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 670-682, 2016.

Improving the prediction of organism-level toxicity through integration of chemical, protein target and cytotoxicity qHTS data.

Prediction of compound toxicity is essential because covering the vast chemical space requiring safety assessment using traditional experimentally-based, resource-intensive techniques is impossible. However, such prediction is nontrivial due to the complex causal relationship between compound structure and in vivo harm. Protein target annotations and in vitro experimental outcomes encode relevant bioactivity information complementary to chemicals' structures. This work tests the hypothesis that utilizing three complementary types of data will afford predictive models that outperform traditional models built using fewer data types. A tripartite, heterogeneous descriptor set for 367 compounds was comprised of (a) chemical descriptors, (b) protein target descriptors generated using an algorithm trained on 190 000 ligand-protein interactions from ChEMBL, and (c) descriptors derived from in vitro cell cytotoxicity dose-response data from a panel of human cell lines. 100 random forests classification models for predicting rat LD50 were built using every combination of descriptors. Successive integration of data types improved predictive performance; models built using the full dataset had an average external correct classification rate of 0.82, compared to 0.73-0.80 for models built using two data types and 0.67-0.78 for models built using one. Pairwise comparisons of models trained on the same data showed that including a third data domain on top of chemistry improved average correct classification rate by 1.4-2.4 points, with p-values <0.01. Additionally, the approach enhanced the models' applicability domains and proved useful for generating novel mechanism hypotheses. The use of tripartite heterogeneous bioactivity datasets is a useful technique for improving toxicity prediction. Both protein target descriptors - which have the practical value of being derived in silico - and cytotoxicity descriptors derived from experiment are suitable contributors to such datasets.

Improved large-scale prediction of growth inhibition patterns using the NCI60 cancer cell line panel.

MOTIVATION: Recent large-scale omics initiatives have catalogued the somatic alterations of cancer cell line panels along with their pharmacological response to hundreds of compounds. In this study, we have explored these data to advance computational approaches that enable more effective and targeted use of current and future anticancer therapeutics. RESULTS: We modelled the 50% growth inhibition bioassay end-point (GI50) of 17,142 compounds screened against 59 cancer cell lines from the NCI60 panel (941,831 data-points, matrix 93.08% complete) by integrating the chemical and biological (cell line) information. We determine that the protein, gene transcript and miRNA abundance provide the highest predictive signal when modelling the GI50 endpoint, which significantly outperformed the DNA copy-number variation or exome sequencing data (Tukey's Honestly Significant Difference, P <0.05). We demonstrate that, within the limits of the data, our approach exhibits the ability to both interpolate and extrapolate compound bioactivities to new cell lines and tissues and, although to a lesser extent, to dissimilar compounds. Moreover, our approach outperforms previous models generated on the GDSC dataset. Finally, we determine that in the cases investigated in more detail, the predicted drug-pathway associations and growth inhibition patterns are mostly consistent with the experimental data, which also suggests the possibility of identifying genomic markers of drug sensitivity for novel compounds on novel cell lines. CONTACT: terez@pasteur.fr; ab454@ac.cam.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Temperature Accelerated Molecular Dynamics with Soft-Ratcheting Criterion Orients Enhanced Sampling by Low-Resolution Information.

Many proteins exhibit an equilibrium between multiple conformations, some of them being characterized only by low-resolution information. Visiting all conformations is a demanding task for computational techniques performing enhanced but unfocused exploration of collective variable (CV) space. Otherwise, pulling a structure toward a target condition biases the exploration in a way difficult to assess. To address this problem, we introduce here the soft-ratcheting temperature-accelerated molecular dynamics (sr-TAMD), where the exploration of CV space by TAMD is coupled to a soft-ratcheting algorithm that filters the evolving CV values according to a predefined criterion. Any low resolution or even qualitative information can be used to orient the exploration. We validate this technique by exploring the conformational space of the inactive state of the catalytic domain of the adenyl cyclase AC from Bordetella pertussis. The domain AC gets activated by association with calmodulin (CaM), and the available crystal structure shows that in the complex the protein has an elongated shape. High-resolution data are not available for the inactive, CaM-free protein state, but hydrodynamic measurements have shown that the inactive AC displays a more globular conformation. Here, using as CVs several geometric centers, we use sr-TAMD to enhance CV space sampling while filtering for CV values that correspond to centers moving close to each other, and we thus rapidly visit regions of conformational space that correspond to globular structures. The set of conformations sampled using sr-TAMD provides the most extensive description of the inactive state of AC up to now, consistent with available experimental information.

Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules.

BACKGROUND: In silico predictive models have proved to be valuable for the optimisation of compound potency, selectivity and safety profiles in the drug discovery process. RESULTS: camb is an R package that provides an environment for the rapid generation of quantitative Structure-Property and Structure-Activity models for small molecules (including QSAR, QSPR, QSAM, PCM) and is aimed at both advanced and beginner R users. camb's capabilities include the standardisation of chemical structure representation, computation of 905 one-dimensional and 14 fingerprint type descriptors for small molecules, 8 types of amino acid descriptors, 13 whole protein sequence descriptors, filtering methods for feature selection, generation of predictive models (using an interface to the R package caret), as well as techniques to create model ensembles using techniques from the R package caretEnsemble). Results can be visualised through high-quality, customisable plots (R package ggplot2). CONCLUSIONS: Overall, camb constitutes an open-source framework to perform the following steps: (1) compound standardisation, (2) molecular and protein descriptor calculation, (3) descriptor pre-processing and model training, visualisation and validation, and (4) bioactivity/property prediction for new molecules. camb aims to speed model generation, in order to provide reproducibility and tests of robustness. QSPR and proteochemometric case studies are included which demonstrate camb's application.Graphical abstractFrom compounds and data to models: a complete model building workflow in one package.