Evaluation of machine-learning methods for ligand-based virtual screening

Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it is little different in screening performance from a previously described kernel that had been developed specifically for the analysis of binary fingerprint representations of molecular structure. We then evaluate the performance of an NBC when the training-set contains only a very few active molecules. In such cases, a simpler approach based on group fusion would appear to provide superior screening performance, especially when structurally heterogeneous datasets are to be processed

Adaptations for nocturnal vision in insect apposition eyes

Due to our own preference for bright light, we tend to forget that many insects are active in very dim light. The reasons for nocturnal activity are most easily seen in tropical areas of the world, where animals face severe competition for food and nocturnal insects are able to forage in a climate of reduced competition and predation. Generally nocturnal insects possess superposition compound eyes. This eye design is truly optimized for dim light as photons can be gathered through large apertures comprised of hundreds of lenses. In apposition eyes, on the other hand, the aperture consists of a single lens resulting in a poor photon catch and unreliable vision in dim light. Apposition eyes are therefore typically found in day-active insects and according to theoretical calculations should render bees blind by mid dusk. Nevertheless, the tropical bee Megalopta genalis and the wasp Apoica pallens have managed the transition to a nocturnal lifestyle while retaining their highly unsuitable apposition eye design. Far from being blind, these bees and wasps forage at extremely low light intensities. Moreover, M. genalis is the first insect shown to use landmark navigation at light intensities less than starlight. How do their apposition eyes permit such complex visual behaviour in so little light? Optical adaptations can significantly enhance sensitivity in apposition eyes. In bees and wasps, the major effect comes from their extremely wide photoreceptors, which are able to trap light reaching the eye from a large visual angle. These optical adaptations lead to a 30-fold increase in sensitivity compared to diurnal bees and wasps. This however is not sufficient for the 8 log units difference in light intensity between day and night. Our hypothesis is that neural adaptations in the form of spatial and temporal summation must be involved. By means of spatial summation the eyes could sum signals from large groups of visual units (ommatidia), in order to improve sensitivity at the cost of coarser spatial resolution. In nocturnal bees, spatial summation could be mediated via their wide laterally-spreading first-order interneurons (L-fibres) present in the first optic ganglion (lamina). These L-fibres have significantly larger dendritic fields than equivalent neurons in diurnal bees and the potential to sum photons from up to 18 visual units. Theoretical modelling further supports this hypothesis, as the optimal dendritic field size predicted by the model agrees well with the anatomical data

C. PRESL) at the transcriptional level.

This paper investigates differences in gene expression among the two Thlaspi caerulescens ecotypes La Calamine (LC) and Lellingen (LE) that have been shown to differ in metal tolerance and metal uptake. LC originates from a metalliferous soil and tolerates higher metal concentrations than LE which originates from a non-metalliferous soil. The two ecotypes were treated with different levels of zinc in solution culture, and differences in gene expression were assessed through application of a cDNA microarray consisting of 1,700 root and 2,700 shoot cDNAs. Hybridisation of root and shoot cDNA from the two ecotypes revealed a total of 257 differentially expressed genes. The regulation of selected genes was verified by quantitative reverse transcriptase polymerase chain reaction. Comparison of the expression profiles of the two ecotypes suggests that LC has a higher capacity to cope with reactive oxygen species and to avoid the formation of peroxynitrite. Furthermore, increased transcripts for the genes encoding for water channel proteins could explain the higher Zn tolerance of LC compared to LE. The higher Zn tolerance of LC was reflected by a lower expression of the genes involved in disease and defence mechanisms. The results of this study provide a valuable set of data that may help to improve our understanding of the mechanisms employed by plants to tolerate toxic concentrations of metal in the soil