The Evaluation Of Molecular Similarity And Molecular Diversity Methods Using Biological Activity Data

This paper reviews the techniques available for quantifying the effectiveness of methods for molecule similarity and molecular diversity, focusing in particular on similarity searching and on compound selection procedures. The evaluation criteria considered are based on biological activity data, both qualitative and quantitative, with rather different criteria needing to be used depending on the type of data available

Identification of diverse database subsets using property-based and fragment-based molecular descriptions

This paper reports a comparison of calculated molecular properties and of 2D fragment bit-strings when used for the selection of structurally diverse subsets of a file of 44295 compounds. MaxMin dissimilarity-based selection and k-means cluster-based selection are used to select subsets containing between 1% and 20% of the file. Investigation of the numbers of bioactive molecules in the selected subsets suggest: that the MaxMin subsets are noticeably superior to the k-means subsets; that the property-based descriptors are marginally superior to the fragment-based descriptors; and that both approaches are noticeably superior to random selection

Visual and computational analysis of structure-activity relationships in high-throughput screening data

Novel analytic methods are required to assimilate the large volumes of structural and bioassay data generated by combinatorial chemistry and high-throughput screening programmes in the pharmaceutical and agrochemical industries. This paper reviews recent work in visualisation and data mining that can be used to develop structure-activity relationships from such chemical/biological datasets

A review of common parameters and descriptors used in studies of the impacts of heavy metal pollution on marine macroalgae: identification of knowledge gaps and future needs

This study presents a systematic review to assess the main similarities and gaps in efforts to evaluate the impacts of heavy metals on benthic marine seaweeds. A total of 91 studies were compiled, the main parameters (abiotic, biological, ecotoxicological, and heavy metals) and descriptors of which were evaluated by quantitative and qualitative analyses. Our results indicate the importance of diversifying searches by including different languages (i.e. English, Portuguese and Spanish). Most of the studies were field characterizations, with few abiotic parameters and/or seasonality evaluations being employed. In contrast, the assessment of ecotoxicological parameters was highly frequent, which seems incoherent considering the absence of data to support the use of these results in biomonitoring applications. The genera Sargassum, Ulva and Enteromorpha were widely studied worldwide, apart from a small fraction of studies assessing higher levels of biological organization. Moreover, the use of different parameters and descriptors by the evaluated studies precludes making conclusive or reliable comparisons. These findings highlight the importance of greater efforts to construct a concise baseline of knowledge using similar parameters so that global evaluations of the impacts of heavy metals on photosynthetic organisms can be undertaken.info:eu-repo/semantics/publishedVersio

Integration of molecular functions at the ecosystemic level: breakthroughs and future goals of environmental genomics and post-genomics

Environmental genomics and genome-wide expression approaches deal with large-scale sequence-based information obtained from environmental samples, at organismal, population or community levels. To date, environmental genomics, transcriptomics and proteomics are arguably the most powerful approaches to discover completely novel ecological functions and to link organismal capabilities, organism–environment interactions, functional diversity, ecosystem processes, evolution and Earth history. Thus, environmental genomics is not merely a toolbox of new technologies but also a source of novel ecological concepts and hypotheses. By removing previous dichotomies between ecophysiology, population ecology, community ecology and ecosystem functioning, environmental genomics enables the integration of sequence-based information into higher ecological and evolutionary levels. However, environmental genomics, along with transcriptomics and proteomics, must involve pluridisciplinary research, such as new developments in bioinformatics, in order to integrate high-throughput molecular biology techniques into ecology. In this review, the validity of environmental genomics and post-genomics for studying ecosystem functioning is discussed in terms of major advances and expectations, as well as in terms of potential hurdles and limitations. Novel avenues for improving the use of these approaches to test theory-driven ecological hypotheses are also explored

Functional Group and Substructure Searching as a Tool in Metabolomics

BACKGROUND: A direct link between the names and structures of compounds and the functional groups contained within them is important, not only because biochemists frequently rely on literature that uses a free-text format to describe functional groups, but also because metabolic models depend upon the connections between enzymes and substrates being known and appropriately stored in databases. METHODOLOGY: We have developed a database named "Biochemical Substructure Search Catalogue" (BiSSCat), which contains 489 functional groups, >200,000 compounds and >1,000,000 different computationally constructed substructures, to allow identification of chemical compounds of biological interest. CONCLUSIONS: This database and its associated web-based search program (http://bisscat.org/) can be used to find compounds containing selected combinations of substructures and functional groups. It can be used to determine possible additional substrates for known enzymes and for putative enzymes found in genome projects. Its applications to enzyme inhibitor design are also discussed

MALDI imaging mass spectrometry for direct tissue analysis: a new frontier for molecular histology

Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a powerful tool for investigating the distribution of proteins and small molecules within biological systems through the in situ analysis of tissue sections. MALDI-IMS can determine the distribution of hundreds of unknown compounds in a single measurement and enables the acquisition of cellular expression profiles while maintaining the cellular and molecular integrity. In recent years, a great many advances in the practice of imaging mass spectrometry have taken place, making the technique more sensitive, robust, and ultimately useful. In this review, we focus on the current state of the art of MALDI-IMS, describe basic technological developments for MALDI-IMS of animal and human tissues, and discuss some recent applications in basic research and in clinical settings