Journal Papers
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Intl J of Robot Res
2009, submitted.
Coming soon.Coming soon.Restriction vs. Guidance: Fragment Assembly and Associative Memory Hamiltonians for Protein Structure Prediction.
Proc. Nat. Acad. Sci. USA
2009, 106(36):15302-15307.
@article{HeglerWolynesPNAS09, author = {Hegler, J. A. AND Laetzer, J. AND Shehu, A. AND Clementi, C. AND Wolynes, P. G.}, journal = {Proc. Nat. Acad. Sci. USA}, title = {Restriction vs. Guidance: Fragment Assembly and Associative Memory Hamiltonians for Protein Structure Prediction}, number = {36}, pages = {15302-15307}, volume = {106}, year = 2009, }Conformational restriction by fragment assembly and guidance in molecular dynamics are alternate conformational search strategies in protein structure prediction. We examine both approaches using a version of the associative memory Hamiltonian that incorporates the influence of water-mediated interactions (AMW). For short proteins (<70 residues), fragment assembly, while searching a restricted space, compares well to molecular dynamics and is often sufficient to fold such proteins to near-native conformations (4Å) via simulated annealing. Longer proteins encounter kinetic sampling limitations in fragment assembly not seen in molecular dynamics which generally samples more native-like conformations. We also present a fragment enriched version of the standard AMW energy function, AMW-FME, which incorporates the local sequence alignment derived fragment libraries from fragment assembly directly into the energy function. This energy function, in which fragment information acts as a guide not a restriction, is found by molecular dynamics to improve on both previous approaches.Multiscale Characterization of Protein Conformational Ensembles.
Proteins: Structure, Function, and Bioinformatics,
2009,76(4):837-851.
@article{ShehuKavrakiClementiProteins09, author = {Shehu, A. AND Kavraki, L. E. AND Clementi, C.}, journal = {Proteins: Struct, Funct, and Bioinf}, title = {Multiscale Characterization of Protein Conformational Ensembles}, number = {4}, pages = {837-851}, volume = {76}, year = 2009, }We propose a multiscale exploration method to characterize the conformational space populated by a protein at equilibrium. The method efficiently obtains a large set of equilibrium conformations in two stages: first exploring the entire space at a coarse-grained level of detail, then narrowing a refined exploration to selected low-energy regions. The coarse-grained exploration periodically adds all-atom detail to selected conformations to ensure that the search leads to regions which maintain low energies in all-atom detail. The second stage reconstructs selected low-energy coarse-grained conformations in all-atom detail. A low-dimensional energy landscape associated with all-atom conformations allows focusing the exploration to energy minima and their conformational ensembles. The lowest energy ensembles are enriched with additional all-atom conformations through further multiscale exploration. The lowest energy ensembles obtained from the application of the method to three different proteins correctly capture the known functional states of the considered systems.Unfolding the Fold of Cyclic Cysteine-rich Peptides.
Protein Science,
2008, 17(3):482-493.
@article{ShehuKavrakiClementiProtSci08, author = {Shehu, A. AND Kavraki, L. E. AND Clementi, C.}, journal = {Protein Sci}, number = {3}, pages = {482-493}, title = {Unfolding the Fold of Cyclic Cysteine-rich Peptides}, volume = {17}, year = 2008 }We propose a method to extensively characterize the native state ensemble of cyclic cysteine-rich peptides. The method uses minimal information, namely, amino acid sequence and cyclization, as a topological feature that characterizes the native state. The method does not assume a specific disulfide bond pairing for cysteines and allows the possibility of unpaired cysteines. A detailed view of the conformational space relevant for the native state is obtained through a hierarchic multi-resolution exploration. A crucial feature of the exploration is a geometric approach that efficiently generates a large number of distinct cyclic conformations independently of one another. A spatial and energetic analysis of the generated conformations associates a free-energy landscape to the explored conformational space. Application to three long cyclic peptides of different folds shows that the conformational ensembles and cysteine arrangements associated with free energy minima are fully consistent with available experimental data. The results provide a detailed analysis of the native state features of cyclic peptides that can be further tested in experiment.Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins.
Algorithmica,
2007, 48(4):303-327.
@article{ShehuClementiKavrakiAlgo07, author = {Shehu, A. AND Clementi, C. AND Kavraki, L. E.}, journal = {Algorithmica}, number = {4}, pages = {303-327}, title = {Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins}, volume = {48}, year = 2007 }This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of consecutive overlapping fragments of the chain. Local fluctuations are computed by a probabilistic exploration that exploits analogies between proteins and robots. All generated conformations are subjected to energy minimization and then are weighted according to a Boltzmann distribution. Using the theory of statistical mechanics the Boltzmann-weighted fluctuations corresponding to each fragment are combined to obtain fluctuations for the entire protein. The agreement obtained between PEM-modeled fluctuations, wet-lab experiment and guided simulation measurements, indicates that PEM is able to reproduce with high accuracy protein equilibrium fluctuations that occur over a broad range of timescales.On the Characterization of Protein Native State Ensembles.
Biophysical Journal,
2007, 92(5):1503-1511.
@article{ShehuKavrakiClementiBiophysJ07, author = {Shehu, A. AND Kavraki, L. E. AND Clementi, C.}, journal = {BiophysJ}, number = {5}, pages = {1503-1511}, title = {On the Characterization of Protein Native State Ensembles}, volume = {92}, year = 2007 }Describing and understanding the biological function of a protein requires a detailed structural and thermodynamic description of the protein's native state ensemble. Obtaining such a description often involves characterizing equilibrium fluctuations that occur beyond the nanosecond timescale. Capturing such fluctuations remains nontrivial even for very long molecular dynamics and Monte Carlo simulations. We propose a novel multiscale computational method to exhaustively characterize, in atomistic detail, the protein conformations constituting the native state with no inherent timescale limitations. Applications of this method to proteins of various folds and sizes show that thermodynamic observables measured as averages over the native state ensembles obtained by the method agree remarkably well with nuclear magnetic resonance data that span multiple timescales. By characterizing equilibrium fluctuations at atomistic detail over a broad range of timescales, from picoseconds to milliseconds, our method offers to complement current simulation techniques and wet-lab experiments and can impact our understanding and description of the relationship between protein flexibility and function.Modeling Protein Conformational Ensembles: From Missing Loops to Equilibrium Fluctuations.
Proteins: Structure, Function, and Bioinformatics
2006, 65(1):164-179.
@article{ShehuClementiKavrakiProt06, author = {Shehu, A. AND Clementi, C. AND Kavraki, L. E.}, journal = {Proteins: Struct, Funct, and Bioinf}, number = {1}, pages = {164-179}, title = {Modeling Protein Conformational Ensembles: {F}rom Missing Loops to Equilibrium Fluctuations}, volume = {65}, year = 2006 }Characterizing protein flexibility is an important goal for understanding the physical-chemical principles governing biological function. This paper presents a Fragment Ensemble Method to capture the mobility of a protein fragment such as a missing loop and its extension into a Protein Ensemble Method to characterize the mobility of an entire protein at equilibrium. The underlying approach in both methods is to combine a geometric exploration of conformational space with a statistical mechanics formulation to generate an ensemble of physical conformations on which thermodynamic quantities can be measured as ensemble averages. The Fragment Ensemble Method is validated by applying it to characterize loop mobility in both instances of strongly stable and disordered loop fragments. In each instance, fluctuations measured over generated ensembles are consistent with data from experiment and simulation. The Protein Ensemble Method captures the mobility of an entire protein by generating and combining ensembles of conformations for consecutive overlapping fragments defined over the protein sequence. This method is validated by applying it to characterize flexibility in ubiquitin and protein G. Thermodynamic quantities measured over the ensembles generated for both proteins are fully consistent with available experimental data. On these proteins, the method recovers nontrivial data such as order parameters, residual dipolar couplings, and scalar couplings. Results presented in this work suggest that the proposed methods can provide insight into the interplay between protein flexibility and function.What's New
Geometry-based Computation of Symmetric Homo-oligomeric Protein Complexes
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