26 research outputs found

    A comprehensive analysis of the computed tautomer fractions of the imidazole ring of histidines in Loligo vulgaris

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    A recently introduced electrostatic-based method to determine the pKa values of ionizable residues and fractions of ionized and tautomeric forms of histidine (His) and acid residues in proteins, at a given fixed pH, is applied here to the analysis of a His-rich protein, namely Loligo vulgaris (pdb id 1E1A), a 314-residue all-β protein. The average tautomeric fractions for the imidazole ring of each of the six histidines in the sequence were computed using an approach that includes, but is not limited to, molecular dynamic simulations coupled with calculations of the ionization states for all 94 ionizable residues of protein 1E1A in water at pH 6.5 and 300 K. The electrostatic-calculated tautomeric fractions of the imidazole ring of His were compared with predictions obtained from an existent NMR-based methodology. Our results indicate that: (i) the averaged electrostatic-based tautomeric predictions for the imidazole ring of all histidines of Loligo vulgaris are dominated by the Nε2-H rather than the Nδ1-H form, although such preferences from the NMR-based methodology are not so well defined; (ii) the computed average absolute difference between the electrostatic- and the NMR-based tautomeric predictions among all six histidines vary among 0% to 17%; (iii) for the His showing the largest fraction of the neutral form (81%), the absolute difference between the NMR- and electrostatic-based computed tautomeric predictions is only 3%; and (iv) the tautomeric predictions for the imidazole ring of His computed with the NMR-based methodology are stable within a certain, well-defined, range of variations of a tautomer-related parameter.Fil: Vorobjev, Yury N.. Institute of Chemical Biology and Fundamental Medicine of the Siberian Branch of the Russian Academy of Science; Rusia. Novosibirsk State University; Rusia. Cornell University; Estados UnidosFil: Scheraga, Harold A.. Cornell University; Estados UnidosFil: Vila, Jorge Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; Argentin

    FAMBE-pH: a fast and accurate method to compute the total solvation free energies of proteins

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    A fast and accurate method to compute the total solvation free energies of proteins as a function of pH is presented. The method makes use of a combination of approaches, some of which have already appeared in the literature; (i) the Poisson equation is solved with an optimized fast adaptive multigrid boundary element (FAMBE) method; (ii) the electrostatic free energies of the ionizable sites are calculated for their neutral and charged states by using a detailed model of atomic charges; (iii) a set of optimal atomic radii is used to define a precise dielectric surface interface; (iv) a multilevel adaptive tessellation of this dielectric surface interface is achieved by using multisized boundary elements; and (v) 1:1 salt effects are included. The equilibrium proton binding/release is calculated with the Tanford−Schellman integral if the proteins contain more than ∼20−25 ionizable groups; for a smaller number of ionizable groups, the ionization partition function is calculated directly. The FAMBE method is tested as a function of pH (FAMBE-pH) with three proteins, namely, bovine pancreatic trypsin inhibitor (BPTI), hen egg white lysozyme (HEWL), and bovine pancreatic ribonuclease A (RNaseA). The results are (a) the FAMBE-pH method reproduces the observed pKaʼs of the ionizable groups of these proteins within an average absolute value of 0.4 pK units and a maximum error of 1.2 pK units and (b) comparison of the calculated total pH-dependent solvation free energy for BPTI, between the exact calculation of the ionization partition function and the Tanford−Schellman integral method, shows agreement within 1.2 kcal/mol. These results indicate that calculation of total solvation free energies with the FAMBE-pH method can provide an accurate prediction of protein conformational stability at a given fixed pH and, if coupled with molecular mechanics or molecular dynamics methods, can also be used for more realistic studies of protein folding, unfolding, and dynamics, as a function of pH.Fil: Vorobjev, Yury N.. Institute of Chemical Biology and Fundamental Medicine of the Siberian Branch of the Russian Academy of Science; RusiaFil: Vila, Jorge Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; ArgentinaFil: Scheraga, Harold A.. Cornell University; Estados Unido

    Assessing the fractions of tautomeric forms of the imidazole ring of histidine in proteins as a function of pH

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    A method is proposed to determine the fraction of the tautomeric forms of the imidazole ring of histidine in proteins as a function of pH, provided that the observed and chemical shifts and the protein structure, or the fraction of H(+) form, are known. This method is based on the use of quantum chemical methods to compute the (13)C NMR shieldings of all the imidazole ring carbons ((13)C(γ), , and ) for each of the two tautomers, N(δ1)-H and N(ε2)-H, and the protonated form, H(+), of histidine. This methodology enabled us (i) to determine the fraction of all the tautomeric forms of histidine for eight proteins for which the and chemical shifts had been determined in solution in the pH range of 3.2 to 7.5 and (ii) to estimate the fraction of tautomeric forms of eight histidine-containing dipeptide crystals for which the chemical shifts had been determined by solid-state (13)C NMR. Our results for proteins indicate that the protonated form is the most populated one, whereas the distribution of the tautomeric forms for the imidazole ring varies significantly among different histidines in the same protein, reflecting the importance of the environment of the histidines in determining the tautomeric forms. In addition, for ∼70% of the neutral histidine-containing dipeptides, the method leads to fairly good agreement between the calculated and the experimental tautomeric form. Coexistence of different tautomeric forms in the same crystal structure may explain the remaining 30% of disagreement.Fil: Vila, Jorge Alberto. Cornell University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis ; ArgentinaFil: Arnautova, Yelena A.. Cornell University; Estados UnidosFil: Vorobjev, Yury. Russian Academy of Science; RusiaFil: Scheraga, Harold A.. Cornell University; Estados Unido

    Identifying native‐like protein structures with scoring functions based on all‐atom ECEPP force fields, implicit solvent models and structure relaxation

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    Availability of energy functions which can discriminate native-like from non-native protein conformations is crucial for theoretical protein structure prediction and refinement of low-resolution protein models. This article reports the results of benchmark tests for scoring functions based on two all-atom ECEPP force fields, that is, ECEPP/3 and ECEPP05, and two implicit solvent models for a large set of protein decoys. The following three scoring functions are considered: (i) ECEPP05 plus a solvent-accessible surface area model with the parameters optimized with a set of protein decoys (ECEPP05/SA); (ii) ECEPP/3 plus the solvent-accessible surface area model of Ooi et al. (Proc Natl Acad Sci USA 1987;84:3086–3090) (ECEPP3/OONS); and (iii) ECEPP05 plus an implicit solvent model based on a solution of the Poisson equation with an optimized Fast Adaptive Multigrid Boundary Element (FAMBEpH) method (ECEPP05/FAMBEpH). Short Monte Carlo-with-Minimization (MCM) simulations, following local energy minimization, are used as a scoring method with ECEPP05/SA and ECEPP3/OONS potentials, whereas energy calculation is used with ECEPP05/FAMBEpH. The performance of each scoring function is evaluated by examining its ability to distinguish between native-like and non-native protein structures. The results of the tests show that the new ECEPP05/SA scoring function represents a significant improvement over the earlier ECEPP3/OONS version of the force field. Thus, it is able to rank native-like structures with Cα root-mean-square-deviations below 3.5 Å as lowest-energy conformations for 76% and within the top 10 for 87% of the proteins tested, compared with 69 and 80%, respectively, for ECEPP3/OONS. The use of the FAMBEpH solvation model, which provides a more accurate description of the protein-solvent interactions, improves the discriminative ability of the scoring function to 89%. All failed tests in which the native-like structures cannot be discriminated as those with low energy, are due to omission of protein–protein interactions. The results of this study represent a benchmark in force-field development, and may be useful for evaluation of the performance of different force fields. Proteins 2009.Fil: Arnautova, Yelena A.. Cornell University; Estados UnidosFil: Vorobjev, Yury N.. Russian Academy of Science; RusiaFil: Vila, Jorge Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; ArgentinaFil: Scheraga, Haroldo A.. Cornell University; Estados Unido

    Coupling between conformation and proton binding in proteins

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    Interest centers here on whether the use of a fixed charge distribution of a protein solute, or a treatment that considers proton-binding equilibria by solving the Poisson equation, is a better approach to discriminate native from non-native conformations of proteins. In this analysis of the charge distribution of 7 proteins, we estimate the solvation free energy contribution to the total free energy by exploring the 2ζ possible ionization states of the whole molecule, with ζ being the number of ionizable groups in the amino acid sequence, for every conformation in the ensembles of 7 proteins. As an additional consideration of the role of electrostatic interactions in determining the charge distribution of native folds, we carried out a comparison of alternative charge assignment models for the ionizable residues in a set of 21 native-like proteins. The results of this work indicate that (1) for 6 out of 7 proteins, estimation of solvent polarization based on the Generalized Born model with a fixed charge distribution provides the optimal trade-off between accuracy, with respect to the Poisson equation, and speed when compared to the accessible surface area model; for the seventh protein, consideration of all possible ionization states of the whole molecule appears to be crucial to discriminate the native from non-native conformations; (2) significant differences in the degree of ionization and hence the charge distribution for native folds are found between the different charge models examined; (3) the stability of the native state is determined by a delicate balance of all the energy components, and (4) conformational entropy, and hence the dynamics of folding, may play a crucial role for a successful ab initio protein folding prediction.Fil: Vila, Jorge Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; Argentina. Cornell University; Estados UnidosFil: Ripoll, Daniel R.. Cornell University; Estados UnidosFil: Arnautova, Yelena A.. Cornell University; Estados UnidosFil: Vorobjev, Yury N.. Institute of Chemical Biology and Fundamental Medicine of Siberian Brunch of Russian Academy of Science; RusiaFil: Scheraga, Harold A.. Cornell University; Estados Unido

    Modeling of Electrostatic Effects in Macromolecules

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    Free energies of protein decoys provide insight into determinants of protein stability

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    We have calculated the stability of decoy structures of several proteins (from the CASP3 models and the Park and Levitt decoy set) relative to the native structures. The calculations were performed with the force field–consistent ES/IS method, in which an implicit solvent (IS) model is used to calculate the average solvation free energy for snapshots from explicit simulations (ESs). The conformational free energy is obtained by adding the internal energy of the solute from the ESs and an entropic term estimated from the covariance positional fluctuation matrix. The set of atomic Born radii and the cavity-surface free energy coefficient used in the implicit model has been optimized to be consistent with the all-atom force field used in the ESs (cedar/gromos with simple point charge (SPC) water model). The decoys are found to have a consistently higher free energy than that of the native structure; the gap between the native structure and the best decoy varies between 10 and 15 kcal/mole, on the order of the free energy difference that typically separates the native state of a protein from the unfolded state. The correlation between the free energy and the extent to which the decoy structures differ from the native (as root mean square deviation) is very weak; hence, the free energy is not an accurate measure for ranking the structurally most native-like structures from among a set of models. Analysis of the energy components shows that stability is attained as a result of three major driving forces: (1) minimum size of the protein-water surface interface; (2) minimum total electrostatic energy, which includes solvent polarization; and (3) minimum protein packing energy. The detailed fit required to optimize the last term may underlie difficulties encountered in recovering the native fold from an approximate decoy or model structure
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