A genetic algorithm for the structural optimization of Morse clusters

This article describes the application of a genetic algorithm for the structural optimization of 19–50-atom clusters bound by medium-range and short-range Morse pair potentials. The GA is found to be efficient and reliable for finding the geometries corresponding to the previously published global minima [Doye JPK, Wales DJ (1997) J Chem Soc Faraday Trans 93: 4233]. Using the genetic algorithm, only a relatively small number of energy evaluations and minimizations are required to find the global minima. By contrast, a simple random search algorithm often cannot find the global minima of the larger clusters, even after many thousands of searches. Received: 27 October 1999 / Accepted: 7 December 1999 / Published online: 19 April 2000     

Variable selection for multivariate calibration using a genetic algorithm: prediction of additive concentrations in polymer films from Fourier transform-infrared spectral data

Variable selection using a genetic algorithm is combined with partial least squares (PLS) for the prediction of additive concentrations in polymer films using Fourier transform-infrared (FT-IR) spectral data. An approach using an iterative application of the genetic algorithm is proposed. This approach allows for all variables to be considered and at the same time minimizes the risk of overfitting. We demonstrate that the variables selected by the genetic algorithm are consistent with expert knowledge. This very exciting result is a convincing application that the algorithm can select correct variables in an automated fashion.     

Genetic differentiation and subspecies development of the giant panda as revealed by DNA fingerprinting

Over the last 100 years giant pandas (Ailuropoda melanoleuca) have been separated into six completely isolated mountain ranges. DNA fingerprinting revealed different differentiation patterns in giant pandas, including early-stage, late-stage, recent divergence and recent genetic depression. A separation around 10 000 years ago resulted in highly significant differences in DNA fingerprints and morphological characteristics between Qinling and Sichuan populations. Supported by morphological differences, the genetic data were used to classify the Qinling population as a new subspecies, A. m. qinlingensis, while the Sichuan populations were classified into the original subspecies, A. m. melanoleuca. Thus, the Qinling population deserves management as a separate unit. In the Sichuan populations, two management units were defined, including Qionglai-Minshan and Daxiangling-Xiaoxiangling-Liangshan. Our data suggest urgent measures are needed to establish green corridors between subpopulations in each mountain range to increase gene flow and genetic variation to ensure long-term survival.     

Induction of decision trees using genetic programming for modelling ecotoxicity data: adaptive discretization of real-valued endpoints

Recent literature has demonstrated the applicability of genetic programming to induction of decision trees for modelling toxicity endpoints. Compared with other decision tree induction techniques that are based upon recursive partitioning employing greedy searches to choose the best splitting attribute and value at each node that will necessarily miss regions of the search space, the genetic programming based approach can overcome the problem. However, the method still requires the discretization of the often continuous-valued toxicity endpoints prior to the tree induction. A novel extension of this method, YAdapt, is introduced in this work which models the original continuous endpoint by adaptively finding suitable ranges to describe the endpoints during the tree induction process, removing the need for discretization prior to tree induction and allowing the ordinal nature of the endpoint to be taken into account in the models built.     

More QACs,more questions: Recent advances in structure activity relationships and hurdles in understanding resistance mechanisms

Quaternary ammonium compounds (QACs) are a class of antimicrobials that have been around for over a century; nevertheless, they have found continued renewal in the structures to which they can be appended. Ranging from antimicrobial polymers to adding novel modes of action to existing antibiotics, QACs have found ongoing use due to their potent properties. However, resistance against QACs has begun to emerge, and the mechanism of resistance is still only partially understood. In this review, we aim to summarize the current state of the field and what is known about the mechanisms of resistance so that the QACs of the future can be designed to be evermore efficacious and utilized to unearth the remaining mysteries that surround bacteria’s resistance to them.     

Simultaneous microemulsion liquid chromatographic analysis of fat-soluble vitamins in pharmaceutical formulations: Optimization using genetic algorithm

An environmentally benign and simple method has been proposed for separation and determination of fat-soluble vitamins using isocratic microemulsion liquid chromatography. Optimization of parameters affecting the separation selectivity and efficiency including surfactant concentration, percent of cosurfactant (1-butanol), and percent of organic oily solvent (diethyl ether), temperature and pH were performed simultaneously using genetic algorithm method. A new software package, MLR-GA, was developed for this purpose. The results indicated that 73.6 mM sodium dodecyl sulfate, 13.64% (v/v) 1-butanol, 0.48% (v/v) diethyl ether, column temperature of 32.5 °C and 0.02 M phosphate buffer of pH 6.99 are the best conditions for separation of fat-soluble vitamins. At the optimized conditions, the calibration plots for the vitamins were obtained and detection limits (1.06–3.69 μg mL⁻¹), accuracy (recoveries > 94.3), precision (RSD < 3.96) and linearity (0.01–10 mg mL⁻¹) were estimated. Finally, the amount of vitamins in multivitamin syrup and a sample of fish oil capsule were determined. The results showed a good agreement with those reported by manufactures.     

Development and optimisation of a novel genetic algorithm for studying model protein folding

Determination of the native state of a protein from its amino acid sequence is the goal of protein folding simulations, with potential applications in gene therapy and drug design. Location of the global minimum structure for a given sequence, however, is a difficult optimisation problem. In this paper, we describe the development and application of a genetic algorithm (GA) to find the lowest-energy conformations for the 2D HP lattice bead protein model. Optimisation of the parameters of our standard GA program reveals that the GA is most successful (at finding the lowest-energy conformations) for high rates of mating and mutation and relatively high elitism. We have also introduced a number of new genetic operators: a duplicate predator—which maintains population diversity by eliminating duplicate structures; brood selection—where two parent structures undergo crossover and give rise to a brood of (not just two) offspring; and a Monte Carlo based local search algorithm—to explore the neighbourhood of all members of the population. It is shown that these operators lead to significant improvements in the success and efficiency of the GA, both compared with our standard GA and with previously published GA studies for benchmark HP sequences with up to 50 beads.     

Chemical composition and antioxidant activity of Borago officinalis L. leaf extract growing in Algeria

The aqueous and hydroalcoholic extracts of borage (Borago officinalis) leaves from Annaba region (Algeria) were preliminary analyzed for their phenolic profile (total phenolics, total flavonoids, total flavonols, total tannins and total anthocyanins). These extracts were evaluated for their antioxidant properties by different methods such as DPPH radical scavenging, test NBT and total antioxidant activity. The two extracts have exhibited a high antiradical capacity. Indeed, the ethanolic extract showed the lower IC50 values and the highest amount of phenolics (94.09 ± 1.72 mg gallic acid/g dry extract). Using LC-MS/MS analysis, it was possible to identify phenolic acids, flavonoids, sterol and for the first time oleuropein was identified in the aqueous extract of the plant. The obtained results have demonstrated that phenolic compounds are the major contributor to the antioxidant activity of plants.