Classical Monte Carlo simulations have been carried out for liquid water in the NPT ensemble at 25 °C and 1 atm using six of the simpler intermolecular potential functions for the water dimer: Bernal–Fowler (BF), SPC, ST2, TIPS2, TIP3P, and TIP4P. Comparisons are made with experimental thermodynamic and structural data including the recent neutron diffraction results of Thiessen and Narten. The computed densities and potential energies are in reasonable accord with experiment except for the original BF model, which yields an 18% overestimate of the density and poor structural results. The TIPS2 and TIP4P potentials yield oxygen–oxygen partial structure functions in good agreement with the neutron diffraction results. The accord with the experimental OH and HH partial structure functions is poorer; however, the computed results for these functions are similar for all the potential functions. Consequently, the discrepancy may be due to the correction terms needed in processing the neutron data or to an effect uniformly neglected in the computations. Comparisons are also made for self‐diffusion coefficients obtained from molecular dynamics simulations. Overall, the SPC, ST2, TIPS2, and TIP4P models give reasonable structural and thermodynamic descriptions of liquid water and they should be useful in simulations of aqueous solutions. The simplicity of the SPC, TIPS2, and TIP4P functions is also attractive from a computational standpoint.

Comparison of simple potential functions for simulating liquid water

Introduction Statistical mechanics Molecular dynamics Monte Carlo methods Some tricks of the trade How to analyse the results Advanced simulation techniques Non-equilibrium molecular dynamics Brownian dynamics Quantum simulations Some applications Appendix A: Computers and computer simulation Appendix B: Reduced units Appendix C: Calculation of forces and torques Appendix D: Fourier transforms Appendix E: The gear predictor - corrector Appendix F: Programs on microfiche Appendix G: Random numbers References Index.

Computer Simulation of Liquids

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

For a successful analysis of the relation between amino acid sequence and protein structure, an unambiguous and physically meaningful definition of secondary structure is essential. We have developed a set of simple and physically motivated criteria for secondary structure, programmed as a pattern-recognition process of hydrogen-bonded and geometrical features extracted from x-ray coordinates. Cooperative secondary structure is recognized as repeats of the elementary hydrogen-bonding patterns “turn” and “bridge.” Repeating turns are “helices,” repeating bridges are “ladders,” connected ladders are “sheets.” Geometric structure is defined in terms of the concepts torsion and curvature of differential geometry. Local chain “chirality” is the torsional handedness of four consecutive Cα positions and is positive for right-handed helices and negative for ideal twisted β-sheets. Curved pieces are defined as “bends.” Solvent “exposure” is given as the number of water molecules in possible contact with a residue. The end result is a compilation of the primary structure, including SS bonds, secondary structure, and solvent exposure of 62 different globular proteins. The presentation is in linear form: strip graphs for an overall view and strip tables for the details of each of 10.925 residues. The dictionary is also available in computer-readable form for protein structure prediction work.

Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features

CHARMM (Chemistry at HARvard Macromolecular Mechanics) is a highly flexible computer program which uses empirical energy functions to model macromolecular systems. The program can read or model build structures, energy minimize them by first- or second-derivative techniques, perform a normal mode or molecular dynamics simulation, and analyze the structural, equilibrium, and dynamic properties determined in these calculations. The operations that CHARMM can perform are described, and some implementation details are given. A set of parameters for the empirical energy function and a sample run are included.

CHARMM: A program for macromolecular energy, minimization, and dynamics calculations

The development of three physics-based energy functions (force fields), designed to simulate the restricted free energy of proteins of the α, β, and α/β structural classes, is described. Each force field corresponds to a particular weighting of the united-residue (UNRES) interactions defined in earlier work.1-6 To find the optimal weights for the α, β, and α/β force fields, both the Z-score and energy gap of the native versus nonnative structures are minimized simultaneously for four benchmark proteins:  1pou (for the α force field), 1tpm (for the β force field), and 1bdd and betanova (for the α/β force field). The simultaneous minimization was carried out by using a novel Monte Carlo method, Vector Monte Carlo (VMC). For α-helical proteins, another weighting of the UNRES interactions (denoted as the α0 force field) was developed; this fourth force field is described in a companion publication (Lee, J. et al. J. Phys. Chem. B 2001, 105, 7291). The structural implications of the final weights of the four f...

Development of Physics-Based Energy Functions that Predict Medium-Resolution Structures for Proteins of the α, β, and α/β Structural Classes

Aharon Katzir-Katchalsky

The intrinsic component of the standard free energy change for the formation of a disulfide bond in a protein molecule is compared to that for an analogous chemical reaction. The former reaction, which represents theintramolecular formation of a disulfide bond in a protein molecule from a cysteine group containing a mixed disulfide bond with glutathione, and a free cysteine residue, is a unimolecular reaction. In contrast, its chemical analogue is a bimolecular reaction, and corresponds to theintermolecular disulfide interchange between a mixed disulfide-bonded compound between a cysteine residue and glutathione, and a free cysteine molecule. The difference in the intrinsic free energy of the above two reactions is estimated by two different approaches. First, a theoretical estimate of the magnitude of the difference in free energy of the two reactions (for a standard state of 1 M) is obtained using a gas-phase statistical thermodynamic approach, which indicates that the intramolecular reaction is energetically favored over its intermolecular counterpart by as much as 15.6 kcal/mole. For comparison, an experimentally derived value is also obtained, using experimental data from a study by Konishi et al. of the regeneration of the protein ribonuclease A (RNase A) from its reduced form by reduced and oxidized glutathiones. The intrinsic component of the free energy change of the intramolecular reaction, as it occurs in the protein molecule, is obtained from such experimental data by accounting explicitly for the free energy change (assumed to be solely an entropy change) pertaining to the conformational changes (ring closure) that the protein molecule undergoes in the course of the reaction. On the basis of the value derived from such an experimental approach, the intramolecular reaction is also energetically more favorable as compared to its intermolecular analogue, but only by a difference of 2.3 kcal/mole (for a standard state of 1 M). The large apparent discrepancy between the two values estimated from the theoretical and experimental approaches is rationalized by the postulation of several additional factors not inherent in the gas-phase theoretical estimate, such as dehydration and intramolecular hydrogen-bonding effects, which can largely compensate for the otherwise favorable energetics of the intramolecular reaction.

Comparison of intramolecular and intermolecular reactions in protein folding

This chapter presents the configurational studies of insulin, lysozyme, and ribonuclease. It discusses the way in which experiments carried out on native and denatured proteins and on derivatives prepared by chemical modification provide information about the secondary and tertiary structures of proteins of known sequence. Two methods for determining the enthalpy of ionization of the lysyl residue in insulin have been employed. First, the titration curve of the protein in the region of lysyl ionization has been determined at several temperatures. Second, the change in pH with temperature at a fixed degree of ionization x of the lysyl group has been measured directly. The enthalpy of ionization is obtained more directly by this second method, but the free energy of ionization cannot be calculated because the degree of ionization is not determined.

Configurational Studies of Insulin, Lysozyme, and Ribonuclease

Treatment of Hydration in Conformational Energy Calculation on Polypeptides and Proteins.

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