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

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

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

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

The NMRPipe system is a UNIX software environment of processing, graphics, and analysis tools designed to meet current routine and research-oriented multidimensional processing requirements, and to anticipate and accommodate future demands and developments. The system is based on UNIX pipes, which allow programs running simultaneously to exchange streams of data under user control. In an NMRPipe processing scheme, a stream of spectral data flows through a pipeline of processing programs, each of which performs one component of the overall scheme, such as Fourier transformation or linear prediction. Complete multidimensional processing schemes are constructed as simple UNIX shell scripts. The processing modules themselves maintain and exploit accurate records of data sizes, detection modes, and calibration information in all dimensions, so that schemes can be constructed without the need to explicitly define or anticipate data sizes or storage details of real and imaginary channels during processing. The asynchronous pipeline scheme provides other substantial advantages, including high flexibility, favorable processing speeds, choice of both all-in-memory and disk-bound processing, easy adaptation to different data formats, simpler software development and maintenance, and the ability to distribute processing tasks on multi-CPU computers and computer networks.

NMRPipe: a multidimensional spectral processing system based on UNIX pipes

Energy parameters in polypeptides. VII. Geometric parameters, partial atomic charges, nonbonded interactions, hydrogen bond interactions, and intrinsic torsional potentials for the naturally occurring amino acids

A Monte Carlo-minimization method has been developed to overcome the multiple-minima problem. The Metropolis Monte Carlo sampling, assisted by energy minimization, surmounts intervening barriers in moving through successive discrete local minima in the multidimensional energy surface. The method has located the lowest-energy minimum thus far reported for the brain pentapeptide [Met5]enkephalin in the absence of water. Presumably it is the global minimum-energy structure. This supports the concept that protein folding may be a Markov process. In the presence of water, the molecules appear to exist as an ensemble of different conformations.

https://www.pnas.org/content/pnas/84/19/6611.full.pdf

Monte Carlo-minimization approach to the multiple-minima problem in protein folding.

The thermodynamic parameters of liquid water are derived by means of a statistical thermodynamic treatment, based on the ``flickering cluster'' model proposed by Frank and Wen. Various models proposed for the structure of liquid water are reviewed, and the advantages of the Frank—Wen model are pointed out. The hydrogen‐bonded ice‐like clusters of H2O molecules in equilibrium with non‐hydrogen‐bonded liquid are described quantitatively in terms of the molecular species participating in different numbers of hydrogen bonds in the clusters. Equations expressing the mole fractions of the various species in terms of the average cluster size are derived. The partition function derived for the description of liquid water is based on a distribution of the H2O molecules over five energy levels, corresponding to four, three, two, one, and no hydrogen bonds per molecule. The most probable values of the average cluster size, the mole fraction of non‐hydrogen‐bonded water, and the thermodynamic parameters are obtained ...

Structure of Water and Hydrophobic Bonding in Proteins. I. A Model for the Thermodynamic Properties of Liquid Water

Finding the optimal solution to a complex optimization problem is of great importance in many fields, ranging from protein structure prediction to the design of microprocessor circuitry. Some recent progress in finding the global minima of potential energy functions is described, focusing on applications of the simple "basin-hopping" approach to atomic and molecular clusters and more complicated hypersurface deformation techniques for crystals and biomolecules. These methods have produced promising results and should enable larger and more complex systems to be treated in the future.

/pdf/global-optimization-of-clusters-crystals-and-biomolecules-2ehy01ydei.pdf

Global optimization of clusters, crystals, and biomolecules

Publisher Summary In the proper environment, a polypeptide chain can fold spontaneously to the three-dimensional structure of a native protein, and despite the possible presence of barriers in conformational space, the chain can find its way around these barriers to reach the structure of lowest free energy. This chapter describes the spontaneous folding of proteins; in vitro complementation of protein fragments; flexibility of proteins in solution: effect of cross-links and ligands, synthetic analogs of proteins; experimental approaches to the study of conformation; and energetic factors determining protein folding. The interatomic interactions within the chain and between the chain and the solvent dictate the folding and the range of the forces involved, is such that near-neighbor interactions are dominant. Folding is envisaged as taking place by the formation of nucleation sites in various parts of the chain, in response to near-neighbor interactions; the various nucleation sites become stabilized, when they are brought into proximity, so that long-range interactions can become operative. However, the development of conformational energy calculation procedures will enable the three-dimensional structure of a native protein to be predicted from the knowledge of its amino acid sequence and its interactions with the solvent in which it is dissolved.

Harold A. Scheraga

Papers

Energy parameters in polypeptides. VII. Geometric parameters, partial atomic charges, nonbonded interactions, hydrogen bond interactions, and intrinsic torsional potentials for the naturally occurring amino acids

Monte Carlo-minimization approach to the multiple-minima problem in protein folding.

Structure of Water and Hydrophobic Bonding in Proteins. I. A Model for the Thermodynamic Properties of Liquid Water

Global optimization of clusters, crystals, and biomolecules

Experimental and theoretical aspects of protein folding.