Simulated-annealing-based genetic algorithm for modeling the optical constants of solids

We propose a simulated-annealing-based genetic algorithm for solving model parameter estimation problems. The algorithm incorporates advantages of both genetic algorithms and simulated annealing. Tests on computer-generated synthetic data that closely resemble optical constants of a metal were performed to compare the efficiency of plain genetic algorithms against the simulated-annealing-based genetic algorithms. These tests assess the ability of the algorithms to and the global minimum and the accuracy of values obtained for model parameters. Finally, the algorithm with the best performance is used to fit the model dielectric function to data for platinum and aluminum. (C) 1997 Optical Society of America.

Modeling the optical constants of solids using acceptance-probability-controlled simulated annealing with an adaptive move generation procedure

The acceptance-probability-controlled simulated annealing with an adaptive move generation procedure, an optimization technique derived from the simulated annealing algorithm, is presented. The adaptive move generation procedure was compared against the random move generation procedure on seven multiminima test functions, as well as on the synthetic data, resembling the optical constants of a metal. In all cases the algorithm proved to have faster convergence and superior escaping from local minima. This algorithm was then applied to fit the model dielectric function to data for platinum and aluminum.

A simulated annealing algorithm for finding consensus sequences

Motivation: A consensus sequence for a family of related sequences is, as the name suggests, a sequence that captures the features common to most members of the family. Consensus sequences are important in various DNA sequencing applications and are a convenient way to characterize a family of molecules. Results: This paper describes a new algorithm for finding a consensus sequence, using the popular optimization method known as simulated annealing. Unlike the conventional approach of finding a consensus sequence by first forming a multiple sequence alignment, this algorithm searches for a sequence that minimises the sum of pairwise distances to each of the input sequences. The resulting consensus sequence can then be used to induce a multiple sequence alignment. The time required by the algorithm scales linearly with the number of input sequences and quadratically with the length of the consensus sequence. We present results demonstrating the high quality of the consensus sequences and alignments produced by the new algorithm. For comparison, we also present similar results obtained using ClustalW. The new algorithm outperforms ClustalW in many cases.

Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.

Using siting algorithms in the design of marine reserve networks

Using benthic habitat data from the Florida Keys (USA), we demonstrate how siting algorithms can help identify potential networks of marine reserves that comprehensively represent target habitat types. We applied a flexible optimization tool-simulated annealing-to represent a fixed proportion of different marine habitat types within a geographic area. We investigated the relative influence of spatial information, planning-unit size, detail of habitat classification, and magnitude of the overall conservation goal on the resulting network scenarios. With this method, we were able to identify many adequate reserve systems that met the conservation goals, e.g., representing at least 20% of each conservation target (i.e., habitat type) while fulfilling the overall aim of minimizing the system area and perimeter. One of the most useful types of information provided by this siting algorithm comes from an irreplaceability analysis, which is a count of the number of, times unique planning units were included in reserve system scenarios. This analysis indicated that many different combinations of sites produced networks that met the conservation goals. While individual 1-km(2) areas were fairly interchangeable, the irreplaceability analysis highlighted larger areas within the planning region that were chosen consistently to meet the goals incorporated into the algorithm. Additionally, we found that reserve systems designed with a high degree of spatial clustering tended to have considerably less perimeter and larger overall areas in reserve-a configuration that may be preferable particularly for sociopolitical reasons. This exercise illustrates the value of using the simulated annealing algorithm to help site marine reserves: the approach makes efficient use of;available resources, can be used interactively by conservation decision makers, and offers biologically suitable alternative networks from which an effective system of marine reserves can be crafted.

Mathematical methods for spatially cohesive reserve design

The problem of designing spatially cohesive nature reserve systems that meet biodiversity objectives is formulated as a nonlinear integer programming problem. The multiobjective function minimises a combination of boundary length, area and failed representation of the biological attributes we are trying to conserve. The task is to reserve a subset of sites that best meet this objective. We use data on the distribution of habitats in the Northern Territory, Australia, to show how simulated annealing and a greedy heuristic algorithm can be used to generate good solutions to such large reserve design problems, and to compare the effectiveness of these methods.

A new method for conservation planning for the persistence of multiple species

Although the aim of conservation planning is the persistence of biodiversity, current methods trade-off ecological realism at a species level in favour of including multiple species and landscape features. For conservation planning to be relevant, the impact of landscape configuration on population processes and the viability of species needs to be considered. We present a novel method for selecting reserve systems that maximize persistence across multiple species, subject to a conservation budget. We use a spatially explicit metapopulation model to estimate extinction risk, a function of the ecology of the species and the amount, quality and configuration of habitat. We compare our new method with more traditional, area-based reserve selection methods, using a ten-species case study, and find that the expected loss of species is reduced 20-fold. Unlike previous methods, we avoid designating arbitrary weightings between reserve size and configuration; rather, our method is based on population processes and is grounded in ecological theory.

Sampling phylogenetic tree space with the generalized Gibbs sampler

The generalized Gibbs sampler (GGS) is a recently developed Markov chain Monte Carlo (MCMC) technique that enables Gibbs-like sampling of state spaces that lack a convenient representation in terms of a fixed coordinate system. This paper describes a new sampler, called the tree sampler, which uses the GGS to sample from a state space consisting of phylogenetic trees. The tree sampler is useful for a wide range of phylogenetic applications, including Bayesian, maximum likelihood, and maximum parsimony methods. A fast new algorithm to search for a maximum parsimony phylogeny is presented, using the tree sampler in the context of simulated annealing. The mathematics underlying the algorithm is explained and its time complexity is analyzed. The method is tested on two large data sets consisting of 123 sequences and 500 sequences, respectively. The new algorithm is shown to compare very favorably in terms of speed and accuracy to the program DNAPARS from the PHYLIP package.

Solution structure of methionine-oxidized amyloid beta-peptide (1-40). Does oxidation affect conformational switching?

The solution structure of A beta(1-40)Met(O), the methionine-oxidized form of amyloid beta-peptide A beta(1-40), has been investigated by CD and NMR spectroscopy. Oxidation of Met35 may have implications in the aetiology of Alzheimer's disease. Circular dichroism experiments showed that whereas A beta(1-40) and A beta(1-40)Met(O) both adopt essentially random coil structures in water (pH 4) at micromolar concentrations, the former aggregates within several days while the latter is stable for at least 7 days under these conditions. This remarkable difference led us to determine the solution structure of A beta(1-40)Met(O) using H-1 NMR spectroscopy. In a water-SDS micelle medium needed to solubilize both peptides at the millimolar concentrations required to measure NMR spectra, chemical shift and NOE data for A beta(1-40)Met(O) strongly suggest the presence of a helical region between residues 16 and 24. This is supported by slow H-D exchange of amide protons in this region and by structure calculations using simulated annealing with the program XPLOR. The remainder of the structure is relatively disordered. Our previously reported NMR data for A beta(1-40) in the same solvent shows that helices are present over residues 15-24 (helix 1) and 28-36 (helix 2), Oxidation of Met35 thus causes a local and selective disruption of helix 2. In addition to this helix-coil rearrangement in aqueous micelles, the CD data show that oxidation inhibits a coil-to-beta-sheet transition in water. These significant structural rearrangements in the C-terminal region of A beta may be important clues to the chemistry and biology of A beta(1-40) and A beta(1-42).

Three-dimensional solution structure of alpha-conotoxin MII by NMR spectroscopy: Effects of solution environment on helicity

alpha-Conotoxin MII, a 16-residue polypeptide from the venom of the piscivorous cone snail Conus magus, is a potent and highly specific blocker of mammalian neuronal nicotinic acetylcholine receptors composed of alpha 3 beta 2 subunits. The role of this receptor type in the modulation of neurotransmitter release and its relevance to the problems of addiction and psychosis emphasize the importance of a structural understanding of the mode of interaction of MII with the alpha 3 beta 2 interface. Here we describe the three-dimensional solution structure of MIT determined using 2D H-1 NMR spectroscopy. Structural restraints consisting of 376 interproton distances inferred from NOEs and 12 dihedral restraints derived from spin-spin coupling constants were used as input for simulated annealing calculations and energy minimization in the program X-PLOR. The final set of 20 structures is exceptionally well-defined with mean pairwise rms differences over the whole molecule of 0.07 Angstrom for the backbone atoms and 0.34 Angstrom for all heavy atoms. MII adopts a compact structure incorporating a central segment of alpha-helix and beta-turns at the N- and C-termini. The molecule is stabilized by two disulfide bonds, which provide cross-links between the N-terminus and both the middle and C-terminus of the structure. The susceptibility of the structure to conformational change was examined using several different solvent conditions. While the global fold of MII remains the same, the structure is stabilized in a more hydrophobic environment provided by the addition of acetonitrile or trifluoroethanol to the aqueous solution. The distribution of amino acid side chains in MII creates distinct hydrophobic and polar patches on its surface that may be important for the specific interaction with the alpha 3 beta 2 neuronal nAChR. A comparison of the structure of MII with other neuronal-specific alpha-conotoxins provides insights into their mode of interaction with these receptors.

Role of the 6-20 disulfide bridge in the structure and activity of epidermal growth factor

Two synthetic analogues of murine epidermal. growth factor, [Abu6, 20] mEGF4-48 (where Abu denotes amino-butyric acid) and [G1, M3, K21, H40] mEGF1-48, have been investigated by NMR spectroscopy. [Abu6, 20] mEGF4-48 was designed to determine the contribution of the 6-20 disulfide bridge to the structure and function of mEGF The overall structure of this analogue was similar to that of native mEGF, indicating that the loss of the 6-20 disulfide bridge did not affect the global fold of the molecule. Significant structural differences were observed near the N-terminus, however, with the direction of the polypeptide chain between residues four and nine being altered such that these residues were now located on the opposite face of the main beta-sheet from their position in native mEGF Thermal denaturation experiments also showed that the structure of [Abu6, 20] mEGF4-48 was less stable than that of mEGF. Removal of this disulfide bridge resulted in a significant loss of both mitogenic activity in Balb/c 3T3 cells and receptor binding on A431 cells compared with native mEGF and mEGF4-48, implying that the structural changes in [Abu6, 20] mEGF4-48, although limited to the N-terminus, were sufficient to interfere with receptor binding. The loss of binding affinity probably arose mainly from steric interactions of the dislocated N-terminal region with part of the receptor binding surface of EGF [G1, M3, K21, H40] mEGF1-48 was also synthesized in order to compare the synthetic polypeptide with the corresponding product of recombinant expression. Its mitogenic activity in Balb/c 3T3 cells was similar to that of native mEGF and analysis of its H-1 chemical shifts suggested that its structure was also very similar to native.

An "openable," high-strength gradient set for orthopedic MRI

A novel three-axis gradient set and RF resonator for orthopedic MRT has been designed and constructed. The set is openable and may be wrapped around injured joints. The design methodology used was the minimization of magnetic field spherical harmonics by simulated annealing. Splitting of the longitudinal coil presents the major design challenge to a fully openable gradient set and in order to efficiently design such coils, we have developed a new fast algorithm for determining the magnetic field spherical harmonics generated by an are of multiturn wire. The algorithm allows a realistic impression of the effect of split longitudinal designs. A prototype set was constructed based on the new designs and tested in a 2-T clinical research system. The set generated 12 mT/m/A with a linear region of 12 cm and a switching time of 100 mu s, conforming closely with theoretical predictions. Preliminary images from the set are presented. (C) 1999 Academic Press.

CXTANNEAL: an improved program for estimating solute transport parameters

CXTANNEAL is a program for analysing contaminant transport in soils. The code, written in Fortran 77, is a modified version of CXTFIT, a commonly used package for estimating solute transport parameters in soils. The improvement of the present code is that it includes simulated annealing as the optimization technique for curve fitting. Tests with hypothetical data show that CXTANNEAL performs better than the original code in searching for optimal parameter estimates. To reduce the computational time, a parallel version of CXTANNEAL (CXTANNEAL_P) was also developed. (C) 1999 Elsevier Science Ltd. All rights reserved.

MiAMP1, a novel protein from Macadamia integrifolia adopts a Greek key beta-barrel fold unique amongst plant antimicrobial proteins

MiAMP1 is a recently discovered 76 amino acid residue, highly basic protein from the nut kernel of:Macadamia integrifolia which possesses no sequence homology to any known protein and inhibits the growth of several microbial plant pathogens in vitro while having no effect on mammalian or plant cells. It is considered to be a potentially useful tool for the genetic engineering of disease resistance in transgenic crop plants and for the design of new fungicides. The three-dimensional structure of MiAMP1 was determined through homonuclear and heteronuclear (N-15) 2D NMR spectroscopy and subsequent simulated annealing calculations with the ultimate aim of understanding the structure-activity relationships of the protein. MiAMP1 is made up of eight beta-strands which are arranged in two Greek key motifs. These Greek key motifs associate to form a Greek key beta-barrel. This structure is unique amongst plant antimicrobial proteins and forms a new class which we term the beta-barrelins. Interestingly, the structure of MiAMP1 bears remarkable similarity to a yeast killer toxin from Williopsis mrakii. This toxin acts by inhibiting beta-glucan synthesis and thereby cell wall construction in sensitive strains of yeast. The structural similarity of MiAMP1 and WmKT, which originate from plant and fungal phyla respectively, may reflect a similar mode of action. (C) 1999 Academic Press.