1,720,996 research outputs found

    Relationship between energy distribution and fold stability: Insights from molecular dynamics simulations of native and mutant proteins

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    Most proteins must fold to a well-defined structure with a minimal stability to perform their function. Here we use a simple, molecular dynamics-based, energy decomposition approach to map the principal energetic interactions in a set of proteins representative of different folds. This work involves the all-atom simulation and analysis of the native structures and mutants of five different proteins representative of an all-alpha (yACPB, Protein A), all-beta (SH3), and a mixed alpha/beta fold (Proteins G and L). Given a certain structure, a native sequence and a set Of mutants, we show that our model discriminates the ability of a mutation to yield a more or less stable protein, in agreement with experimental data, catching the principal energetic determinants of protein stabilization. Our approach identifies the interaction determinants responsible to define a fold and shows that mutations can either modulate the strength of pair-wise coupling between residues important for folding or modify the profile of the principal interactions. Furthermore, we address the question of how to evaluate the fitness of a sequence to a given structure by comparing the information contained in the energy map, which recapitulates the chemistry of the sequence, to that contained in the contact map, which recapitulates the fold topology. The results show that the better fit between the energetic properties of the sequence and the fold topology corresponds to a higher stabilization of the protein. We discuss the relevance of these observations to the analysis of protein designability and to the rational evolution of new sequences

    Selecting sequences that fold into a defined 3D structure: A new approach for protein design based on molecular dynamics and energetics

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    The problem of finding amino acid sequences able to fold into a defined three-dimensional (3D) structure is at the basis of successful protein design efforts. Herein, we present the results of the application of a novel, all-atom molecular dynamics based, energy decomposition approach to the selection of sequences able to fold into a given 3D conformation. First, the energy decomposition approach is applied to natural sequences associated to a well-defined structure to identify the principal energetic coupling interactions necessary to stabilize it, defining the specific energetic signature for the fold. Then, several different sequences are threaded on the defined 3D structure and only those sequences whose energetic signature (pattern) is close to that of the natural sequence, according to a similarity criterion, are selected as able to populate the specific fold. Furthermore, it is possible to evaluate the fitness of a certain sequence for a fold by combining the information provided by the energetic signature to that contained in the contact map. which recapitulates the fold topology. The results show that the better fit between the energetic properties of a sequence and the topology corresponds to a better stabilization of the protein fold by that sequence. We applied this approach to a library of natural and artificial WW domain sequences, previously developed by the Ranganathan group. containing sequences that are experimentally known to be able and unable to fold into native structures. The results show that our approach can correctly identify 70\% of the sequences known to populate the typical WW domain fold. (C) 2009 Elsevier B.V. All rights reserved

    Investigating the Mechanism of Peptide Aggregation: Insights from Mixed Monte Carlo-Molecular Dynamics Simulations

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    AbstractThe early stages of peptide aggregation are currently not accessible by experimental techniques at atomic resolution. In this article, we address this problem through the application of a mixed simulation scheme in which a preliminary coarse-grained Monte Carlo analysis of the free-energy landscape is used to identify representative conformations of the aggregates and subsequent all-atom molecular dynamics simulations are used to analyze in detail possible pathways for the stabilization of oligomers. This protocol was applied to systems consisting of multiple copies of the model peptide GNNQQNY, whose detailed structures in the aggregated state have been recently solved in another study. The analysis of the various trajectories provides dynamical and structural insight into the details of aggregation. In particular, the simulations suggest a hierarchical mechanism characterized by the initial formation of stable parallel β-sheet dimers and identify the formation of the polar zipper motif as a fundamental feature for the stabilization of initial oligomers. Simulation results are consistent with experimentally derived observations and provide an atomically detailed view of the putative initial stages of fibril formation

    Predicting Interaction Sites from the Energetics of Isolated Proteins: A New Approach to Epitope Mapping

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    AbstractAn increasing number of functional studies of proteins have shown that sequence and structural similarities alone may not be sufficient for reliable prediction of their interaction properties. This is particularly true for proteins recognizing specific antibodies, where the prediction of antibody-binding sites, called epitopes, has proven challenging. The antibody-binding properties of an antigen depend on its structure and related dynamics. Aiming to predict the antibody-binding regions of a protein, we investigate a new approach based on the integrated analysis of the dynamical and energetic properties of antigens, to identify nonoptimized, low-intensity energetic interaction networks in the protein structure isolated in solution. The method is based on the idea that recognition sites may correspond to localized regions with low-intensity energetic couplings with the rest of the protein, which allows them to undergo conformational changes, to be recognized by a binding partner, and to tolerate mutations with minimal energetic expense. Upon analyzing the results on isolated proteins and benchmarking against antibody complexes, it is found that the method successfully identifies binding sites located on the protein surface that are accessible to putative binding partners. The combination of dynamics and energetics can thus discriminate between epitopes and other substructures based only on physical properties. We discuss implications for vaccine design

    Surface energetics and protein-protein interactions: analysis and mechanistic implications

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    Understanding protein-protein interactions (PPI) at the molecular level is a fundamental task in the design of new drugs, the prediction of protein function and the clarification of the mechanisms of (dis)regulation of biochemical pathways. In this study, we use a novel computational approach to investigate the energetics of aminoacid networks located on the surface of proteins, isolated and in complex with their respective partners. Interestingly, the analysis of individual proteins identifies patches of surface residues that, when mapped on the structure of their respective complexes, reveal regions of residue-pair couplings that extend across the binding interfaces, forming continuous motifs. An enhanced effect is visible across the proteins of the dataset forming larger quaternary assemblies. The method indicates the presence of energetic signatures in the isolated proteins that are retained in the bound form, which we hypothesize to determine binding orientation upon complex formation. We propose our method, BLUEPRINT, as a complement to different approaches ranging from the ab-initio characterization of PPIs, to protein-protein docking algorithms, for the physico-chemical and functional investigation of protein-protein interactions

    Investigating Allostery in Molecular Recognition: Insights from a Computational Study of Multiple Antibody-Antigen Complexes

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    Antibody-antigen recognition plays a key role in the immune response against pathogens. Here, we have investigated various aspects of this problem by analyzing a large and diverse set of antibodies and their respective complexes with protein antigens through atomistic simulations. Common features of antibody response to the presence of antigens are elucidated by the analysis of the proteins' internal dynamics and coordination in different ligand states, combined with the analysis of the interaction networks implicated in the stabilization of functional structures. The use of a common structural reference reveals preferential changes in the dynamic coordination and intramolecular interaction networks induced by antigen binding and shared by all antibodies. Such changes propagate from the binding region through the whole immunoglobulin domains. Overall, complexed antibodies show more diffuse networks of nonbonded interactions and a general higher internal dynamic coordination, which preferentially involve the immunoglobulin (Ig) domains of the heavy chain. The combined results provide atomistic insights into the correlations between the modulation of conformational dynamics, structural stability, and allosteric signal transduction. In particular, the results suggest that specific networks of residues, shared among all the analyzed proteins, define the molecular pathways by which antibody structures respond to antigen binding. Our studies may have implications in practical use, such as the rational design of antibodies with specifically modulated antigen-binding affinities

    Molecular dynamics simulations of proteins and peptides: From folding to drug design

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    Computer simulations of proteins, lipids and nucleic acids at equilibrium have become essentially routine. However, the fact remains that complete sampling of conformational space continues to be a bottle-neck in the field. The challenge for the future is to overcome such problems and use computational approaches to understand recognition and spontaneous self-organization in biomolecular systems (folding, aggregation and assembly of complexes), processes that cannot be directly observed experimentally. In this review, examples illustrating the extent to which simulations can be used to understand these phenomena in biomolecular systems will be presented along with examples of methodological developments to increase our physical understanding of the processes. The study cases will cover the problems of peptide-receptor recognition and the use of the information obtained for the design of new non-peptidic ligands; the study of the folding mechanism of small proteins and finally the study of the initial stages of peptide self-aggregation

    Understanding ligand-based modulation of the Hsp90 molecular chaperone dynamics at atomic resolution

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    Molecular switching and ligand-based modulation of the 90-kDa heat-shock protein (Hsp90) chaperone activity may ultimately facilitate conformational coupling to the ATPase cycle along with activation and recruitment of the broad range of client proteins. We present an atomic resolution analysis of the Hsp90 N-terminal domain (NTD) binding energy landscape by simulating protein dynamics with a range of binding partners. We show that the activity of the molecular chaperone may be linked to (i) local folding-unfolding transitions and conformational switching of the ``active site lid'' upon binding and (it) differences in the underlying protein dynamics as a function of the binding partner. This study suggests that structural plasticity of the Hsp90 NTD can be exploited by the molecular chaperone machinery to modulate enhanced structural rigidity during ATP binding and increased protein flexibility as a consequence of the inhibitor binding. The present study agrees with the experimental structural data and provides a plausible molecular model for understanding mechanisms of modulation of molecular chaperone activities by binding partners

    An atomistic view of Hsp70 allosteric crosstalk: from the nucleotide to the substrate binding domain and back

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    The Hsp70 is an allosterically regulated family of molecular chaperones. They consist of two structural domains, NBD and SBD, connected by a flexible linker. ATP hydrolysis at the NBD modulates substrate recognition at the SBD, while peptide binding at the SBD enhances ATP hydrolysis. In this study we apply Molecular Dynamics (MD) to elucidate the molecular determinants underlying the allosteric communication from the NBD to the SBD and back. We observe that local structural and dynamical modulation can be coupled to large-scale rearrangements, and that different combinations of ligands at NBD and SBD differently affect the SBD domain mobility. Substituting ADP with ATP in the NBD induces specific structural changes involving the linker and the two NBD lobes. Also, a SBD-bound peptide drives the linker docking by increasing the local dynamical coordination of its C-terminal end: a partially docked DnaK structure is achieved by combining ATP in the NBD and peptide in the SBD. We propose that the MD-based analysis of the inter domain dynamics and structure modulation could be used as a tool to computationally predict the allosteric behaviour and functional response of Hsp70 upon introducing mutations or binding small molecules, with potential applications for drug discovery
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