Comparative study of global minimum energy conformations of hydrated peptides

A global optimization method is described for identifying the global minimum energy conformation, as well as lower and upper bounds on the global minimum conformer of solvated peptides. In considering the effects of hydration, two independent continuum‐based solvation models are employed. The first method is based on the calculation of solvent‐accessible surface areas, whereas the second method uses information on the solvent‐accessible volume of hydration shells. The hydration effects predicted by the area‐ and volume‐based models, using a variety of atomic solvation parameter (ASP) sets, are tested and compared by identifying global minimum energy structures of terminally blocked peptides and oligopeptides. Significant differences are observed, indicating that appropriate model selection is essential for accurately predicting hydrated peptide structures. Using this information, the applicability of these hydration models and ASP sets is discussed. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 636–654, 1999

[1]  Harold A. Scheraga,et al.  Free energies of hydration of solute molecules. IV: Revised treatment of the hydration shell model , 1988 .

[2]  H. Scheraga,et al.  Energy parameters in polypeptides. 10. Improved geometrical parameters and nonbonded interactions for use in the ECEPP/3 algorithm, with application to proline-containing peptides , 1994 .

[3]  H. Scheraga,et al.  Accessible surface areas as a measure of the thermodynamic parameters of hydration of peptides. , 1987, Proceedings of the National Academy of Sciences of the United States of America.

[4]  M. L. Connolly.  Analytical molecular surface calculation , 1983 .

[5]  C. Anfinsen,et al.  The kinetics of formation of native ribonuclease during oxidation of the reduced polypeptide chain. , 1961, Proceedings of the National Academy of Sciences of the United States of America.

[6]  M. Karplus,et al.  CHARMM: A program for macromolecular energy, minimization, and dynamics calculations , 1983 .

[7]  B Honig,et al.  Reconciling the magnitude of the microscopic and macroscopic hydrophobic effects. , 1991, Science.

[8]  D. Eisenberg,et al.  Atomic solvation parameters applied to molecular dynamics of proteins in solution , 1992, Protein science : a publication of the Protein Society.

[9]  Peter A. Kollman,et al.  FREE ENERGY CALCULATIONS : APPLICATIONS TO CHEMICAL AND BIOCHEMICAL PHENOMENA , 1993 .

[10]  M. Karplus,et al.  Analysis of Coupling Schemes in Free Energy Simulations: A Unified Description of Nonbonded Contributions to Solvation Free Energies , 1996 .

[11]  Harold A. Scheraga,et al.  Free energies of hydration of solute molecules. 1. Improvement of the hydration shell model by exact computations of overlapping volumes , 1987 .

[12]  C. Anfinsen.  Principles that govern the folding of protein chains. , 1973, Science.

[13]  C. Floudas,et al.  A global optimization approach for Lennard‐Jones microclusters , 1992 .

[14]  Harold A. Scheraga,et al.  Gradient discontinuities in calculations involving molecular surface area , 1994 .

[15]  Harold A. Scheraga,et al.  Structure and free energy of complex thermodynamic systems , 1988 .

[16]  N. Go,et al.  A Method of Rapid Calculation of a Second Derivative Matrix of Conformational Energy for Large Molecules , 1983 .

[17]  C. Adjiman,et al.  A global optimization method, αBB, for general twice-differentiable constrained NLPs—II. Implementation and computational results , 1998 .

[18]  Akbar Nayeem,et al.  MSEED: A program for the rapid analytical determination of accessible surface areas and their derivatives , 1992 .

[19]  Effects of solvent on the conformation and the collective motions of a protein. II: Structure of hydration in melittin , 1993 .

[20]  Christodoulos A. Floudas,et al.  αBB: A global optimization method for general constrained nonconvex problems , 1995, J. Glob. Optim..

[21]  K. Kopple,et al.  Solvent-dependent conformational distributions of some dipeptides , 1980 .

[22]  R. Doolittle,et al.  A simple method for displaying the hydropathic character of a protein. , 1982, Journal of molecular biology.

[23]  G A Petsko,et al.  Aromatic-aromatic interaction: a mechanism of protein structure stabilization. , 1985, Science.

[24]  Arnold Neumaier,et al.  Molecular Modeling of Proteins and Mathematical Prediction of Protein Structure , 1997, SIAM Rev..

[25]  H. Scheraga,et al.  Experimental and theoretical aspects of protein folding. , 1975, Advances in protein chemistry.

[26]  Christodoulos A. Floudas,et al.  A global optimization method, αBB, for process design , 1996 .

[27]  Harold A. Scheraga,et al.  Free energies of hydration of solute molecules. 3. Application of the hydration shell model to charged organic molecules , 1987 .

[28]  Christodoulos A. Floudas,et al.  Global optimization for molecular conformation problems , 1993, Ann. Oper. Res..

[29]  A. J. Hopfinger,et al.  Polymer-Solvent Interactions for Homopolypeptides in Aqueous Solution , 1971 .

[30]  H. Scheraga,et al.  Conformational Energy Calculations on Polypeptides and Proteins , 1994 .

[31]  Christodoulos A Floudas,et al.  Global minimum potential energy conformations of small molecules , 1994, J. Glob. Optim..

[32]  Christodoulos A. Floudas,et al.  Global optimization of MINLP problems in Process Synthesis and Design , 1997 .

[33]  Arieh Ben-Naim,et al.  Size dependence of the solvation free energies of large solutes , 1993 .

[34]  H A Scheraga,et al.  Empirical solvation models in the context of conformational energy searches: Application to bovine pancreatic trypsin inhibitor , 1992, Proteins.

[35]  A. Neumaier,et al.  A global optimization method, αBB, for general twice-differentiable constrained NLPs — I. Theoretical advances , 1998 .

[36]  Christodoulos A. Floudas,et al.  Rigorous convex underestimators for general twice-differentiable problems , 1996, J. Glob. Optim..

[37]  Christodoulos A. Floudas,et al.  Prediction of Oligopeptide Conformations via Deterministic Global Optimization , 1997, J. Glob. Optim..

[38]  P. Kollman,et al.  Protein structure prediction with a combined solvation free energy-molecular mechanics force field , 1993 .

[39]  Harold A. Scheraga,et al.  An efficient, differentiable hydration potential for peptides and proteins , 1996, J. Comput. Chem..

[40]  A. H. Juffer,et al.  Comparison of atomic solvation parametric sets: Applicability and limitations in protein folding and binding , 1995, Protein science : a publication of the Protein Society.

[41]  R. Hicks,et al.  Conformational analysis of met‐enkephalin in both aqueous solution and in the presence of sodium dodecyl sulfate micelles using multidimensional NMR and molecular modeling , 1992, Biopolymers.

[42]  P M Cullis,et al.  Affinities of amino acid side chains for solvent water. , 1981, Biochemistry.

[43]  Harold A. Scheraga,et al.  Predicting Three-Dimensional Structures of Oligopeptides , 1993 .

[44]  Frank Eisenhaber,et al.  Improved strategy in analytic surface calculation for molecular systems: Handling of singularities and computational efficiency , 1993, J. Comput. Chem..

[45]  K. Sharp,et al.  Macroscopic models of aqueous solutions : biological and chemical applications , 1993 .

[46]  Chris Sander,et al.  The double cubic lattice method: Efficient approaches to numerical integration of surface area and volume and to dot surface contouring of molecular assemblies , 1995, J. Comput. Chem..

[47]  Werner Braun,et al.  Minimization of empirical energy functions in proteins including hydrophobic surface area effects , 1993, J. Comput. Chem..

[48]  C. Floudas,et al.  A deterministic global optimization approach for molecular structure determination , 1994 .