{"title":"Intensity-fading MALDI-TOF-MS: novel screening for ligand binding and drug discovery","authors":"Óscar Yanes , Josep Villanueva , Enrique Querol , Francesc X. Aviles","doi":"10.1016/S1741-8372(04)02417-X","DOIUrl":"10.1016/S1741-8372(04)02417-X","url":null,"abstract":"<div><p>Ligand discovery technologies largely rely on a primary screening for molecules showing affinity to a target, coupled with an approach to identify these molecules. Matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) is attracting increasing attention as a suitable analytical technique for ligand identification owing to its high sensitivity and capacity for discrimination, its fast analysis and its ease of automation. There is now a range of related strategies for drug discovery, including a novel MS-based methodology to screen noncovalent interactions between macromolecular targets (proteases) and peptide or organic ligands (protease inhibitors) called intensity-fading (IF) MALDI-TOF-MS.</p></div>","PeriodicalId":100382,"journal":{"name":"Drug Discovery Today: TARGETS","volume":"3 2","pages":"Pages 23-30"},"PeriodicalIF":0.0,"publicationDate":"2004-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1741-8372(04)02417-X","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78144828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unraveling the human interactome: lessons from the yeast","authors":"J. Daniel Navarro , Akhilesh Pandey","doi":"10.1016/S1741-8372(04)02413-2","DOIUrl":"10.1016/S1741-8372(04)02413-2","url":null,"abstract":"<div><p><span>One of greatest promises of the post-genomic era is the use of genomic and proteomic information to discover how a cell works as a complex molecular machine. Mere cataloging of genes is insufficient for this purpose because the cellular architecture and functionality is largely decided by proteins and </span>protein complexes. Elucidation of protein–protein interactions and networks is a challenging task that will require an integrated approach that combines different types of experiments in addition to bioinformatics analyses.</p></div>","PeriodicalId":100382,"journal":{"name":"Drug Discovery Today: TARGETS","volume":"3 2","pages":"Pages 79-84"},"PeriodicalIF":0.0,"publicationDate":"2004-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1741-8372(04)02413-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78341407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Keiryn L. Bennett, Jan C. Brønd, Dan B. Kristensen, Alexandre V. Podtelejnikov, Jacek R. Wisniewski
{"title":"Analysis of large-scale MS data sets: the dramas and the delights","authors":"Keiryn L. Bennett, Jan C. Brønd, Dan B. Kristensen, Alexandre V. Podtelejnikov, Jacek R. Wisniewski","doi":"10.1016/S1741-8372(04)02412-0","DOIUrl":"10.1016/S1741-8372(04)02412-0","url":null,"abstract":"<div><p><span>The biotechnology and pharmaceutical industries are faced with the serious challenge of consolidating the enormous quantities of data that have been generated from high-throughput proteomic applications. The bottleneck of data validation and placement of the information obtained into sound biological context urgently needs to be addressed. Here, we review the issues that arise when analysing large quantities of data generated by </span>liquid chromatography mass spectrometry, offer potential solutions for data management and predict the future direction of large-scale data analysis by mass spectrometry.</p></div>","PeriodicalId":100382,"journal":{"name":"Drug Discovery Today: TARGETS","volume":"3 2","pages":"Pages 43-49"},"PeriodicalIF":0.0,"publicationDate":"2004-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1741-8372(04)02412-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85824183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Quantitative proteomics by metabolic labeling with stable isotopes","authors":"Jeroen Krijgsveld, Albert J.R. Heck","doi":"10.1016/S1741-8372(04)02420-X","DOIUrl":"10.1016/S1741-8372(04)02420-X","url":null,"abstract":"<div><p><span>Protein quantification based on mass spectrometry (MS) is an emerging application in the field of proteomics<span>. This approach involves not only the identification of proteins on a global scale, but also the accurate quantification of their expression levels. Over the past few years several techniques have been developed to achieve this aim, most of which incorporate the labeling of proteins with stable isotopes, including chemical (</span></span><em>in vitro</em><span>) derivatization techniques such as isotope-coded affinity tags (ICATs). Recently, however, there has been an increase in the development of methods for the metabolic (</span><em>in vivo</em>) labeling of organisms ranging from bacteria to fruitflies. These methods have numerous potential applications in biomedical research.</p></div>","PeriodicalId":100382,"journal":{"name":"Drug Discovery Today: TARGETS","volume":"3 2","pages":"Pages 11-15"},"PeriodicalIF":0.0,"publicationDate":"2004-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1741-8372(04)02420-X","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77671343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Genome fingerprint scanning for protein identification and gene finding","authors":"Michael C. Giddings","doi":"10.1016/S1741-8372(04)02411-9","DOIUrl":"10.1016/S1741-8372(04)02411-9","url":null,"abstract":"<div><p>The genome fingerprint scanning (GFS) system was developed to link proteomic<span> data, consisting of peptide mass fingerprints and tandem mass spectrometry<span> (MS/MS) data, to the genome sequence of an organism. It maps MS data directly to the genomic locus responsible for expression of a protein, without relying on prior genome annotation. The GFS approach provides the intriguing possibility of identifying novel genes straight from protein data, thereby potentially enhancing ongoing efforts to annotate the genomes.</span></span></p></div>","PeriodicalId":100382,"journal":{"name":"Drug Discovery Today: TARGETS","volume":"3 2","pages":"Pages 56-62"},"PeriodicalIF":0.0,"publicationDate":"2004-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1741-8372(04)02411-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84294190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proteogest: a tool for facilitating proteomics using mass spectrometry","authors":"Gerard Cagney , Andrew Emili","doi":"10.1016/S1741-8372(04)02419-3","DOIUrl":"10.1016/S1741-8372(04)02419-3","url":null,"abstract":"<div><p><span><span>In a typical proteomic<span> experiment, mass spectrometry (MS) is coupled to protein or peptide separation steps for the identification of many hundreds to thousands of peptides. With the continuing advances in instrumentation and data generation, effective software is needed to link the different stages of proteomic analysis. Proteogest has been developed to carry out descriptive and statistical analyses of the biophysical properties of thousands of </span></span>protein sequences and to perform </span><em>in silico</em><span> proteolytic digestions of proteomes coupled to subsequent sequence analysis.</span></p></div>","PeriodicalId":100382,"journal":{"name":"Drug Discovery Today: TARGETS","volume":"3 2","pages":"Pages 63-65"},"PeriodicalIF":0.0,"publicationDate":"2004-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1741-8372(04)02419-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86356123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mass spectrometry has married statistics: uncle is functionality, children are selectivity and sensitivity","authors":"Jacques Colinge, Alexandre Masselot","doi":"10.1016/S1741-8372(04)02418-1","DOIUrl":"10.1016/S1741-8372(04)02418-1","url":null,"abstract":"<div><p>Techniques for analyzing tandem mass spectrometry (MS/MS) data are moving from empirically determined heuristics to standard statistical methods. OLAV, an advanced database search engine, applies statistical models to capture essential structural properties of correct peptide identifications. Moreover, as exemplified by OLAV, it is important to have extended functionalities in MS/MS search engines both to exploit database annotations and to carry out advanced search strategies.</p></div>","PeriodicalId":100382,"journal":{"name":"Drug Discovery Today: TARGETS","volume":"3 2","pages":"Pages 50-55"},"PeriodicalIF":0.0,"publicationDate":"2004-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1741-8372(04)02418-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79417575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"PRISM: a new strategy to analyze the mammalian proteome","authors":"Thomas Kislinger , Brian Cox , Andrew Emili","doi":"10.1016/S1741-8372(04)02422-3","DOIUrl":"10.1016/S1741-8372(04)02422-3","url":null,"abstract":"<div><p><span>Advances in microcapillary </span>liquid chromatography tandem mass spectrometry<span> (LC–MS/MS), in combination with the completion of genome sequencing projects, have opened the door to systematic large-scale mammalian protein expression<span> profiling. The aim of this emerging field is to gain insight into the systems biology of complex multicellular organisms. A recently developed multistep analytical strategy, called PRISM (proteome investigation strategy for mammals), is a promising technology platform for investigating the complex proteome of mammalian tissues.</span></span></p></div>","PeriodicalId":100382,"journal":{"name":"Drug Discovery Today: TARGETS","volume":"3 2","pages":"Pages 37-42"},"PeriodicalIF":0.0,"publicationDate":"2004-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1741-8372(04)02422-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75072395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}