Tripeptide loop closure: A detailed study of reconstructions based on Ramachandran distributions.

Tripeptide loop closure (TLC) is a standard procedure to reconstruct protein backbone conformations, by solving a zero-dimensional polynomial system yielding up to 16 solutions. In this work, we first show that multiprecision is required in a TLC solver to guarantee the existence and the accuracy of solutions. We then compare solutions yielded by the TLC solver against tripeptides from the Protein Data Bank. We show that these solutions are geometrically diverse (up to 3Å Root mean square deviation with respect to the data) and sound in terms of potential energy. Finally, we compare Ramachandran distributions of data and reconstructions for the three amino acids. The distribution of reconstructions in the second angular space ϕ2ψ2 stands out, with a rather uniform distribution leaving a central void. We anticipate that these insights, coupled to our robust implementation in the Structural Bioinformatics Library ( https://sbl.inria.fr/doc/Tripeptide_loop_closure-user-manual.html), will help understanding the properties of TLC reconstructions, with potential applications to the generation of conformations of flexible loops in particular.

Mobility and Core-Protein Binding Patterns of Disordered C-Terminal Tails in ß-Tubulin Isotypes.

Although they play a significant part in the regulation of microtubule structure, dynamics, and function, the disordered C-terminal tails of tubulin remain invisible to experimental structural methods and do not appear in the crystallographic structures that are currently available in the Protein Data Bank. Interestingly, these tails concentrate most of the sequence variability between tubulin isotypes and are the sites of the principal post-translational modifications undergone by this protein. Using homology modeling, we developed two complete models for the human αI/ßI- and αI/ßIII-tubulin isotypes that include their C-terminal tails. We then investigated the conformational variability of the two ß-tails using long time-scale classical molecular dynamics simulations that revealed similar features, notably the unexpected presence of common anchoring regions on the surface of the tuulin dimer, but also distinctive mobility or interaction patterns, some of which could be related to the tail lengths and charge distributions. We also observed in our simulations that the C-terminal tail from the ßI isotype, but not the ßIII isotype, formed contacts in the putative binding site of a recently discovered peptide that disrupts microtubule formation in glioma cells. Hindering the binding site in the ßI isotype would be consistent with this peptide's preferential disruption of microtubule formation in glioma, whose cells overexpress ßIII, compared to normal glial cells. While these observations need to be confirmed with more intensive sampling, our study opens new perspectives for the development of isotype-specific chemotherapy drugs.

Hybridizing rapidly exploring random trees and basin hopping yields an improved exploration of energy landscapes.

The number of local minima of the potential energy landscape (PEL) of molecular systems generally grows exponentially with the number of degrees of freedom, so that a crucial property of PEL exploration algorithms is their ability to identify local minima, which are low lying and diverse. In this work, we present a new exploration algorithm, retaining the ability of basin hopping (BH) to identify local minima, and that of transition based rapidly exploring random trees (T-RRT) to foster the exploration of yet unexplored regions. This ability is obtained by interleaving calls to the extension procedures of BH and T-RRT, and we show tuning the balance between these two types of calls allows the algorithm to focus on low lying regions. Computational efficiency is obtained using state-of-the art data structures, in particular for searching approximate nearest neighbors in metric spaces. We present results for the BLN69, a protein model whose conformational space has dimension 207 and whose PEL has been studied exhaustively. On this system, we show that the propensity of our algorithm to explore low lying regions of the landscape significantly outperforms those of BH and T-RRT.

Investigating the Structural Variability and Binding Modes of the Glioma Targeting NFL-TBS.40-63 Peptide on Tubulin.

NFL-TBS.40-63 is a 24 amino acid peptide corresponding to the tubulin-binding site located on the light neurofilament subunit, which selectively enters glioblastoma cells, where it disrupts their microtubule network and inhibits their proliferation. We investigated its structural variability and binding modes on a tubulin heterodimer using a combination of NMR experiments, docking, and molecular dynamics (MD) simulations. Our results show that, while lacking a stable structure, the peptide preferentially binds on a specific single site located near the ß-tubulin C-terminal end, thus giving us precious hints regarding the mechanism of action of the NFL-TBS.40-63 peptide's antimitotic activity at the molecular level.

Conformational ensembles and sampled energy landscapes: Analysis and comparison.

We present novel algorithms and software addressing four core problems in computational structural biology, namely analyzing a conformational ensemble, comparing two conformational ensembles, analyzing a sampled energy landscape, and comparing two sampled energy landscapes. Using recent developments in computational topology, graph theory, and combinatorial optimization, we make two notable contributions. First, we present a generic algorithm analyzing height fields. We then use this algorithm to perform density-based clustering of conformations, and to analyze a sampled energy landscape in terms of basins and transitions between them. In both cases, topological persistence is used to manage (geometric) frustration. Second, we introduce two algorithms to compare transition graphs. The first is the classical earth mover distance metric which depends only on local minimum energy configurations along with their statistical weights, while the second incorporates topological constraints inherent to conformational transitions. Illustrations are provided on a simplified protein model (BLN69), whose frustrated potential energy landscape has been thoroughly studied. The software implementing our tools is also made available, and should prove valuable wherever conformational ensembles and energy landscapes are used.

Building Biological Relevance Into Integrative Modelling of Macromolecular Assemblies.

Recent advances in structural biophysics and integrative modelling methods now allow us to decipher the structures of large macromolecular assemblies. Understanding the dynamics and mechanisms involved in their biological function requires rigorous integration of all available data. We have developed a complete modelling pipeline that includes analyses to extract biologically significant information by consistently combining automated and interactive human-guided steps. We illustrate this idea with two examples. First, we describe the ryanodine receptor, an ion channel that controls ion flux across the cell membrane through transitions between open and closed states. The conformational changes associated with the transitions are small compared to the considerable system size of the receptor; it is challenging to consistently track these states with the available cryo-EM structures. The second example involves homologous recombination, in which long filaments of a recombinase protein and DNA catalyse the exchange of homologous DNA strands to reliably repair DNA double-strand breaks. The nucleoprotein filament reaction intermediates in this process are short-lived and heterogeneous, making their structures particularly elusive. The pipeline we describe, which incorporates experimental and theoretical knowledge combined with state-of-the-art interactive and immersive modelling tools, can help overcome these challenges. In both examples, we point to new insights into biological processes that arise from such interdisciplinary approaches.

Modeling Perturbations in Protein Filaments at the Micro and Meso Scale Using NAMD and PTools/Heligeom.

Protein filaments are dynamic entities that respond to external stimuli by slightly or substantially modifying the internal binding geometries between successive protomers. This results in overall changes in the filament architecture, which are difficult to model due to the helical character of the system. Here, we describe how distortions in RecA nucleofilaments and their consequences on the filament-DNA and bound DNA-DNA interactions at different stages of the homologous recombination process can be modeled using the PTools/Heligeom software and subsequent molecular dynamics simulation with NAMD. Modeling methods dealing with helical macromolecular objects typically rely on symmetric assemblies and take advantage of known symmetry descriptors. Other methods dealing with single objects, such as MMTK or VMD, do not integrate the specificities of regular assemblies. By basing the model building on binding geometries at the protomer-protomer level, PTools/Heligeom frees the building process from a priori knowledge of the system topology and enables irregular architectures and symmetry disruption to be accounted for. Graphical abstract: Model of ATP hydrolysis-induced distortions in the recombinant nucleoprotein, obtained by combining RecA-DNA and two RecA-RecA binding geometries.

Side-chain rotamer transitions at protein-protein interfaces.

We compare the changes in side chain conformations that accompany the formation of protein-protein complexes, in residues forming either the interface or the remainder of the solvent-accessible surface of the proteins in the Docking Benchmark 3.0. We find that the interface residues undergo significantly more changes than other surface residues, and these changes are more likely to convert them from a high-energy torsion angle state to a lower-energy one than the reverse. Moreover, in both the unbound proteins and the complexes, the interface residues are more frequently found to be in a high-energy torsion angle state than the noninterface residues. As these differences exist before the binding step, they may be relevant to specificity and help in identifying binding sites for docking predictions.

How does heparin prevent the pH inactivation of cathepsin B? Allosteric mechanism elucidated by docking and molecular dynamics.

BACKGROUND: Cathepsin B (catB) is a promising target for anti-cancer drug design due to its implication in several steps of tumorigenesis. catB activity and inhibition are pH-dependent, making it difficult to identify efficient inhibitor candidates for clinical trials. In addition it is known that heparin binding stabilizes the enzyme in alkaline conditions. However, the molecular mechanism of stabilization is not well understood, indicating the need for more detailed structural and dynamic studies in order to clarify the influence of pH and heparin binding on catB stability. RESULTS: Our pKa calculations of catB titratable residues revealed distinct protonation states under different pH conditions for six key residues, of which four lie in the crucial interdomain interface. This implies changes in the overall charge distribution at the catB surface, as revealed by calculation of the electrostatic potential. We identified two basic surface regions as possible heparin binding sites, which were confirmed by docking calculations. Molecular dynamics (MD) of both apo catB and catB-heparin complexes were performed using protonation states for catB residues corresponding to the relevant acidic or alkaline conditions. The MD of apo catB at pH 5.5 was very stable, and presented the highest number and occupancy of hydrogen bonds within the inter-domain interface. In contrast, under alkaline conditions the enzyme's overall flexibility was increased: interactions between active site residues were lost, helical content decreased, and domain separation was observed as well as high-amplitude motions of the occluding loop - a main target of drug design studies. Essential dynamics analysis revealed that heparin binding modulates large amplitude motions promoting rearrangement of contacts between catB domains, thus favoring the maintenance of helical content as well as active site stability. CONCLUSIONS: The results of our study contribute to unraveling the molecular events involved in catB inactivation in alkaline pH, highlighting the fact that protonation changes of few residues can alter the overall dynamics of an enzyme. Moreover, we propose an allosteric role for heparin in the regulation of catB stability in such a manner that the restriction of enzyme flexibility would allow the establishment of stronger contacts and thus the maintenance of overall structure.

Role of nucleic acid binding in Sir3p-dependent interactions with chromatin fibers.

Recent studies of the mechanisms involved in the regulation of gene expression in eukaryotic organisms depict a highly complex process requiring a coordinated rearrangement of numerous molecules to mediate DNA accessibility. Silencing in Saccharomyces cerevisiae involves the Sir family of proteins. Sir3p, originally described as repressing key areas of the yeast genome through interactions with the tails of histones H3 and H4, appears to have additional roles in that process, including involvement with a DNA binding component. Our in vitro studies focused on the characterization of Sir3p-nucleic acid interactions and their biological functions in Sir3p-mediated silencing using binding assays, EM imaging, and theoretical modeling. Our results suggest that the initial Sir3p recruitment is partially DNA-driven, highly cooperative, and dependent on nucleosomal features other than histone tails. The initial step appears to be rapidly followed by the spreading of silencing using linker DNA as a track.

Disulfide bond substitution by directed evolution in an engineered binding protein.

Breaking ties: The antitumour protein, neocarzinostatin (NCS), is one of the few drug-carrying proteins used in human therapeutics. However, the presence of disulfide bonds limits this protein's potential development for many applications. This study describes a generic directed-evolution approach starting from NCS-3.24 (shown in the figure complexed with two testosterone molecules) to engineer stable disulfide-free NCS variants suitable for a variety of purposes, including intracellular applications.The chromoprotein neocarzinostatin (NCS) has been intensively studied for its antitumour properties. It has recently been redesigned as a potential drug-carrying scaffold. A potential limit of this protein scaffold, especially for intracellular applications, is the presence of disulfide bonds. The objective of this work was to create a disulfide-free NCS-derived scaffold. A generic targeted approach was developed by using directed evolution methods. As a starting point we used a previously engineered NCS variant in which a hapten binding site had been created. A library was then generated in which cysteine Cys88 and Cys93 and neighbouring residues were randomly substituted. Variants that preserved the hapten binding function were selected by phage display and further screened by colony filtration methods. Several sequences with common features emerged from this process. The corresponding proteins were expressed, purified and their biophysical properties characterised. How these selected sequences rescued folding ability and stability of the disulfide-free protein was carefully examined by using calorimetry and the results were interpreted with molecular simulation techniques.

Normal mode analysis as a prerequisite for drug design: application to matrix metalloproteinases inhibitors.

We demonstrate the utility of normal mode analysis in correctly predicting the binding modes of inhibitors in the active sites of matrix metalloproteinases (MMPs). We show the accuracy in predicting the positions of MMP-3 inhibitors is strongly dependent on which structure is used as the target, especially when it has been energy minimized. This dependency can be overcome by using intermediate structures generated along one of the normal modes previously calculated for a given target. These results may be of prime importance for further in silico drug discovery.

Integrating three views of Arf1 activation dynamics.

The proteins Arno and Gea2 of the Sec7 family can promote GDP-GTP exchange on Arf1, a small GTP-binding protein, which coordinates coated vesicle formation for protein transport within the cell. Crystal structures of the essential Sec7 domain (Sec7d) of Gea2 in the free and Arf1-bound forms suggest that conformational dynamics of the Sec7d as well as those of the G-protein play a role in nucleotide exchange. Starting from a set of complementary crystal structures, we compared the collective movements of unbound Gea2 and Arno Sec7 domains, Arf1-GDP, and the Arf1-Gea2(Sec7d) nucleotide-free complex using normal modes analyses. In all unbound Sec7d analyses, significant low-energy movements were found to lead to closure of the hydrophobic groove towards the form seen in the Arf1-Gea2(Sec7d) complex, suggesting that groove closure is a general feature of the Sec7 family. Low-energy movements in Arf1-GDP implicate critical switch 1 and 2 residues which are coupled to modifications in the myristoylated N-terminal-helix binding site at the other end of the "interswitch" beta hairpin. It is suggested that Sec7d groove closure upon docking of the two molecules may permit extraction of switch 1 from Arf1-GDP and prepare the complex for movement of the interswitch, which is central to the membrane-linked exchange activity. Large-scale collective movements in the Arf1-Sec7d complex appear to participate in the insertion of the Sec7d Glu finger into the GDP binding site to promote actual nucleotide release.

Changes in protein structure at the interface accompanying complex formation.

Protein interactions are essential in all biological processes. The changes brought about in the structure when a free component forms a complex with another molecule need to be characterized for a proper understanding of molecular recognition as well as for the successful implementation of docking algorithms. Here, unbound (U) and bound (B) forms of protein structures from the Protein-Protein Interaction Affinity Database are compared in order to enumerate the changes that occur at the interface atoms/residues in terms of the solvent-accessible surface area (ASA), secondary structure, temperature factors (B factors) and disorder-to-order transitions. It is found that the interface atoms optimize contacts with the atoms in the partner protein, which leads to an increase in their ASA in the bound interface in the majority (69%) of the proteins when compared with the unbound interface, and this is independent of the root-mean-square deviation between the U and B forms. Changes in secondary structure during the transition indicate a likely extension of helices and strands at the expense of turns and coils. A reduction in flexibility during complex formation is reflected in the decrease in B factors of the interface residues on going from the U form to the B form. There is, however, no distinction in flexibility between the interface and the surface in the monomeric structure, thereby highlighting the potential problem of using B factors for the prediction of binding sites in the unbound form for docking another protein. 16% of the proteins have missing (disordered) residues in the U form which are observed (ordered) in the B form, mostly with an irregular conformation; the data set also shows differences in the composition of interface and non-interface residues in the disordered polypeptide segments as well as differences in their surface burial.

An integrative approach to the study of filamentous oligomeric assemblies, with application to RecA.

Oligomeric macromolecules in the cell self-organize into a wide variety of geometrical motifs such as helices, rings or linear filaments. The recombinase proteins involved in homologous recombination present many such assembly motifs. Here, we examine in particular the polymorphic characteristics of RecA, the most studied member of the recombinase family, using an integrative approach that relates local modes of monomer/monomer association to the global architecture of their screw-type organization. In our approach, local modes of association are sampled via docking or Monte Carlo simulations. This enables shedding new light on fiber morphologies that may be adopted by the RecA protein. Two distinct RecA helical morphologies, the so-called "extended" and "compressed" forms, are known to play a role in homologous recombination. We investigate the variability within each form in terms of helical parameters and steric accessibility. We also address possible helical discontinuities in RecA filaments due to multiple monomer-monomer association modes. By relating local interface organization to global filament morphology, the strategies developed here to study RecA self-assembly are particularly well suited to other DNA-binding proteins and to filamentous protein assemblies in general.

Differential core histone binding behavior: RNA polymerase I promoter region vs 5S rDNA positioning DNA sequences.

In order to further characterize the previously observed disruptive effect of the RNA polymerase I promoter sequence (Pol I) from Acanthamoeba castellanii on tandemly repeated 5S rDNA positioning sequences from sea urchin (Lytechinus variegatus), we compared the histone-binding ability of the isolated 199-bp Pol I promoter region to that of the 208-bp 5S rDNA and that of nucleosome core particle sequences isolated from chicken erythocytes. We found the 5S rDNA positioning sequence to be more efficient at forming nucleosomes than the RNA polymerase I promoter sequence. Nevertheless, examination of the free-DNA half-depletion points during the titrations suggested that twice as much histone had bound to the RNA polymerase I promoter sequence as to the 5S nucleosome-positioning or core particle sequences. DNA bending analysis suggested two potential DNA bending loci in the RNA polymerase I promoter, whereas only one such locus was predicted for the 5S positioning sequence. Such mixed bending signals on the RNA polymerase I promoter could favor non-nucleosomal deposition of histones on these sequences.

Reassessing buried surface areas in protein-protein complexes.

The buried surface area (BSA), which measures the size of the interface in a protein-protein complex may differ from the accessible surface area (ASA) lost upon association (which we call DSA), if conformation changes take place. To evaluate the DSA, we measure the ASA of the interface atoms in the bound and unbound states of the components of 144 protein-protein complexes taken from the Protein-Protein Interaction Affinity Database of Kastritis et al. (2011). We observe differences exceeding 20%, and a systematic bias in the distribution. On average, the ASA calculated in the bound state of the components is 3.3% greater than in their unbound state, and the BSA, 7% greater than the DSA. The bias is observed even in complexes where the conformation changes are small. An examination of the bound and unbound structures points to a possible origin: local movements optimize contacts with the other component at the cost of internal contacts, and presumably also the binding free energy.

Free Energy Profiles along Consensus Normal Modes Provide Insight into HIV-1 Protease Flap Opening.

Describing biological macromolecular energetics from computer simulations can pose major challenges, and often necessitates enhanced conformational sampling. We describe the calculation of conformational free-energy profiles along carefully chosen collective coordinates: "consensus" normal modes, developed recently as robust alternatives to conventional normal modes. In an application to the HIV-1 protease, we obtain efficient sampling of significant flap opening movements governing inhibitor binding from relatively short simulations, in close correspondence with experimental results.

Community-wide assessment of protein-interface modeling suggests improvements to design methodology.

The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder.

A computational study of a recreated G protein-GEF reaction intermediate competent for nucleotide exchange: fate of the Mg ion.

Small G-proteins of the superfamily Ras function as molecular switches, interacting with different cellular partners according to their activation state. G-protein activation involves the dissociation of bound GDP and its replacement by GTP, in an exchange reaction that is accelerated and regulated in the cell by guanine-nucleotide exchange factors (GEFs). Large conformational changes accompany the exchange reaction, and our understanding of the mechanism is correspondingly incomplete. However, much knowledge has been derived from structural studies of blocked or inactive mutant GEFs, which presumably closely represent intermediates in the exchange reaction and yet which are by design incompetent for carrying out the nucleotide exchange reaction. In this study we have used comparative modelling to recreate an exchange-competent form of a late, pre-GDP-ejection intermediate species in Arf1, a well-characterized small G-protein. We extensively characterized three distinct models of this intermediate using molecular dynamics simulations, allowing us to address ambiguities related to the mutant structural studies. We observed in particular the unfavorable nature of Mg2+ associated forms of the complex and the establishment of closer Arf1-GEF contacts in its absence. The results of this study shed light on GEF-mediated activation of this small G protein and on predicting the fate of the Mg ion at a critical point in the exchange reaction. The structural models themselves furnish additional targets for interfacial inhibitor design, a promising direction for exploring potentially druggable targets with high biological specificity.