Validated ligand binding sites in CCK receptors. Next step: Computer aided design of novel CCK ligands

Computer-aided drug design becomes an important part of G-protein coupled receptors (GPCR) drug discovery process that is applied for improving the efficiency of derivation and optimization of novel ligands. It represents the combination of methods that-use-structural information of a receptor binding site of known ligands to design new ligands. In this report, we give a brief description of ligand binding sites in cholecystokinin and gastrin receptors (CK1R and CCK2R) which were delineated using experimental and computational methods, and then, we show how the validated ligand binding sites can be used to design and improve novel ligands. The translation of the knowledge of ligand-binding sites of different GPCRs to computer-aided design of novel ligands is summarized.

Distal dendrites of frog motor neurons: a computer-aided electron microscopic study of cobalt-filled cells.

With the aid of the cobalt labelling technique, frog spinal cord motor neuron dendrites of the subpial dendritic plexus have been identified in serial electron micrographs. Computer reconstructions of various lengths (2.5-9.8 micron) of dendritic segments showed the contours of these dendrites to be highly irregular, and to present many thorn-like projections 0.4-1.8 micron long. Number, size and distribution of synaptic contacts were also determined. Almost half of the synapses occurred at the origins of the thorns and these synapses had the largest contact areas. Only 8 out of 54 synapses analysed were found on thorns and these were the smallest. For the total length of reconstructed dendrites there was, on average, one synapse per 1.2 micron, while 4.4% of the total dendritic surface was covered with synaptic contacts. The functional significance of these distal dendrites and their capacity to influence the soma membrane potential is discussed.

Molecular quantum similarity in QSAR: applications in computer-aided molecular design

La present tesi està centrada en l'ús de la Teoria de Semblança Quàntica per a calcular descriptors moleculars. Aquests descriptors s'utilitzen com a paràmetres estructurals per a derivar correlacions entre l'estructura i la funció o activitat experimental per a un conjunt de compostos. Els estudis de Relacions Quantitatives Estructura-Activitat són d'especial interès per al disseny racional de molècules assistit per ordinador i, en particular, per al disseny de fàrmacs. Aquesta memòria consta de quatre parts diferenciades. En els dos primers blocs es revisen els fonaments de la teoria de semblança quàntica, així com l'aproximació topològica basada en la teoria de grafs. Ambdues teories es fan servir per a calcular els descriptors moleculars. En el segon bloc, s'ha de remarcar la programació i implementació de programari per a calcular els anomenats índexs topològics de semblança quàntica. La tercera secció detalla les bases de les Relacions Quantitatives Estructura-Activitat i, finalment, el darrer apartat recull els resultats d'aplicació obtinguts per a diferents sistemes biològics.

Application of computer-aided facilities management (CAFM) for intelligent buildings operation

Purpose – The purpose of this paper is to investigate the concepts of intelligent buildings (IBs), and the opportunities offered by the application of computer-aided facilities management (CAFM) systems. Design/methodology/approach – In this paper definitions of IBs are investigated, particularly definitions that are embracing open standards for effective operational change, using a questionnaire survey. The survey further investigated the extension of CAFM to IBs concepts and the opportunities that such integrated systems will provide to facilities management (FM) professionals. Findings – The results showed variation in the understanding of the concept of IBs and the application of CAFM. The survey showed that 46 per cent of respondents use a CAFM system with a majority agreeing on the potential of CAFM in delivery of effective facilities. Research limitations/implications – The questionnaire survey results are limited to the views of the respondents within the context of FM in the UK. Practical implications – Following on the many definitions of an IB does not necessarily lead to technologies of equipment that conform to an open standard. This open standard and documentation of systems produced by vendors is the key to integrating CAFM with other building management systems (BMS) and further harnessing the application of CAFM for IBs. Originality/value – The paper gives experience-based suggestions for both demand and supply sides of the service procurement to gain the feasible benefits and avoid the currently hindering obstacles, as the paper provides insight to the current and future tools for the mobile aspects of FM. The findings are relevant for service providers and operators as well.

Towards the computer-aided diagnosis of dementia based on the geometric and network connectivity of structural MRI data

We present an intuitive geometric approach for analysing the structure and fragility of T1-weighted structural MRI scans of human brains. Apart from computing characteristics like the surface area and volume of regions of the brain that consist of highly active voxels, we also employ Network Theory in order to test how close these regions are to breaking apart. This analysis is used in an attempt to automatically classify subjects into three categories: Alzheimer’s disease, mild cognitive impairment and healthy controls, for the CADDementia Challenge.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Computer-aided Structure Elucidation of Neolignans

This paper describes a new module of the expert system SISTEMAT used for the prediction of the skeletons of neolignans by (13)C NMR, (1)H NMR and botanical data obtained from the literature. SISTEMAT is composed of MACRONO, SISCONST, C13MACH, H1MACH and SISOCBOT programs, each analyzing data of the neolignan in question to predict the carbon skeleton of the compound. From these results, the global probability is computed and the most probable skeleton predicted. SISTEMAT predicted the skeletons of 75% of the 20 neolignans tested, in a rapid and simple procedure demonstrating its advantage for the structural elucidation of new compounds.