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

A series of successful decoupling experiments on CαH protons under the H2O peak in aqueous solutions of oligopeptides is described.

Decoupling proton magnetic resonance signals located under the H2O peak

Monte Carlo treatment of hydration of models for side chains of proteins

The interaction of inhibitors with the active site of arsanilazocarboxypeptidase A has been investigated by means of resonance Raman spectroscopy. The resonance Raman bands of the active-site azotyrosine-248 residue have been shown previously to be sensitive to its state of ionization and its interactions with nearby groups. In particular, the azophenol form of azotyrosine-248 can adopt two different coexisting conformations that differ with respect to the presence or absence of an intramolecular hydrogen bond between the phenolic proton and a nitrogen atom of the azo group. Each of these conformations exhibits characteristic vNN and v phi N azo stretching frequencies. The relative concentrations of these two forms, revealed by resonance Raman spectroscopy, are a sensitive probe of the hydrogen bond accepting ability of the local environment. The present study shows that the binding of L-benzylsuccinate, phenylacetate, L-phenyllactate, and beta-phenylpropionate markedly perturbs the distribution of the intra- and intermolecularly hydrogen-bonded forms of azotyrosine-248 in water. In contrast, glycyl-L-tyrosine and L-phenylalanine leave this distribution unperturbed. These results, taken jointly with other data on inhibitor binding, serve to identify common binding sites for groups of inhibitors and result in plausible suggestions concerning the interactions between azotyrosine-248 and these inhibitors that lead to binding.

Resonance Raman spectroscopy of arsanilazocarboxypeptidase A: mode of inhibitor binding and active-site topography.

Helix-coil transition in multicomponent random copolypeptides in water. 2. Application to random copolymers of (hydroxybutyl)-L-glutamine, L-phenylalanine, and L-lysine

Solution structure of murine epidermal growth factor determined by NMR spectroscopy and refined by energy minimization with restraints. [Erratum to document cited in CA116(5):34702j]

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