摘要:

Due to the high rate of data production and the need of researchers to have rapid access to new data, public databases have become the major medium through which genome mapping and sequencing data as well as macromolecular structural data are published. There are now more than 250 databases of biomolecular, structural, genetic, or phenotypic data, many of which are doubling in size annually. These databases, many of which were created and are maintained by experimentalists for their own research use, provide valuable collections of organized, validated data. However, the very number and diversity of databases now make efficient data resource discovery as important as effective data resource use. Existing autonomous biological databases contain related data which are more valuable when interconnected than when isolated. Political and scientific realities dictate that these databases will be built by different teams, in different locations, for different purposes, and using different data models and supporting DBMSs. As a consequence, connecting the related data they contain is not straightforward. Experience with existing biological databases indicates that it is possible to form useful queries across these databases, but that doing so usually requires expertise in the semantic structure of each source database. Advancing to the next level of integration among biological information resources poses significant technical and sociological challenges.

ISSN:1062-936X    

DOI:10.1080/10629369808039138

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

Problems arising in the collection of data in olfaction studies are discussed in relation with the specific nature of perception and description of odors. Olfactory data depend strongly on individual physiological differences, on measurement methods and on psychological factors.

ISSN:1062-936X    

DOI:10.1080/10629369808039139

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

Large data sets are becoming much more prevalent in drug discovery as high throughput screening and combinatorial chemistry data sets become available. Conventional linear parametric methods, linear regression, PCR, PLS, etc., often fail in analyzing structurally heterogeneous data sets. This is because the underlying relationships may involve nonlinearities, thresholds and interactions, all of which considerably impede linear additive modeling approaches. Also the conventional assumption that all compounds in data set are acting by the same mechanism is not expected to hold. Recursive partitioning (RP) is able to accommodate all these difficulties; it is also computationally fast; RP can deal with very large data sets - 10 to 100k observations pose no particular problems. Therefore RP invites investigation as a general approach for study of structure activity relationships in large chemistry data sets. The purpose of this paper is to explicate a recursive partitioning procedure, FIRM, through the analysis of a large, structure-activity data set, 1650 compounds with 153 fragment descriptors and monoamine oxidase, MAO, activity. The methodology is successful in uncovering compounds acting through different mechanisms.

ISSN:1062-936X    

DOI:10.1080/10629369808039140

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

Four compounds within a set of ligands for the benzodiazepine receptors are characterized by their electron density maps at different resolution levels and reconstructed from calculated structure factors. The resulting complex three-dimensional density maps are first simplified into connected graphs using topological analysis. Then, an original genetic algorithm method, GAGS (Genetic Algorithm for Graph Similarity search), is developed and implemented in order to compare the connected graphs. Finally, the analysis of the best solutions of the algorithm are expressed in terms of functional group superimpositions. The GAGS analysis is applied to different resolution levels of the electron density maps and the resulting models are compared in order to assess the influence of the resolution on the resulting pharmacophore models.

ISSN:1062-936X    

DOI:10.1080/10629369808039141

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

The field of computer graphics has played an important role in the advancement of structural molecular biology and in the development of structure-based drug design. This article will provide a brief background on the development of this technology, and then focus on the current trends and future directions in molecular graphics and how they will impact the practice of molecular modeling and design. Specific areas that will be covered include: 1) the development of surface and volume based representations of molecular properties and interactions; 2) new approaches to modeling flexible and multi-component structures, and 3) the impact of object-oriented graphics-based programming and the rapidly growing use of network based computing.

ISSN:1062-936X    

DOI:10.1080/10629369808039142

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

Two applications of neural networks in molecular recognition, incorporating at different levels the structural information, are presented. Interatomic distances are the basis of the search for a given 3D substructure, with a Hopfield network using either a Boltzmann machine or a « mean field annealing » algorithm (according to a model we previously proposed by analogy with the « travelling salesman problem »). Besides atom spatial locations, the model can incorporate characteristic points featuring selected electronic or steric features, and add supplementary constraints on the nature of these points or some property value on them. For model compounds, this approach retrieves the correct (flipped) orientations in binding the adenosine A1 receptor. In QSAR field, we use a three layers feed forward neural network to predict the activity of polychlorinated dibenzofurans toward the AcH receptor. Due to the high homogeneity of the studied population input data only consist here of a topological descriptor, refined by a cross validation process. Results compete favorably with the previous approaches, with no need for complex field calculations.

ISSN:1062-936X    

DOI:10.1080/10629369808039143

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

This article will discuss the motivations, technologies, and future directions of computational automated docking in the context of the structure-based rational design of HIV-1 protease inhibitors. Docking simulations are widely used for screening of compound libraries to identify new drug leads, employing a simple model for rapid testing of thousands of compounds. Docking simulations are also useful for lead enhancement, using more detailed models to analyze the atomic interactions between inhibitors and target macromolecules. Major advances have been reported in the development of empirical force fields, which now allow assessment of relative binding strength and drug specificity, and extensions of automated docking techniques allowde novodrug design.

ISSN:1062-936X    

DOI:10.1080/10629369808039144

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor

摘要:

This is a scanned image of the original Editorial Board page(s) for this issue.

ISSN:1062-936X    

DOI:10.1080/10629369808039137

出版商:Taylor & Francis Group    

年代:1998

数据来源: Taylor