Download or read book Computational Methods for Small Molecule Identification written by Kai Dührkop and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Identification of small molecules remains a central question in analytical chemistry, in particular for natural product research, metabolomics, environmental research, and biomarker discovery. Mass spectrometry is the predominant technique for high-throughput analysis of small molecules. But it reveals only information about the mass of molecules and, by using tandem mass spectrometry, about the mass of molecular fragments. Automated interpretation of mass spectra is often limited to searching in spectral libraries, such that we can only dereplicate molecules for which we have already recorded reference mass spectra. In this thesis we present methods for answering two central questions: What is the molecular formula of the measured ion and what is its molecular structure? SIRIUS is a combinatorial optimization method for annotating a spectrum and identifying the ion's molecular formula by computing hypothetical fragmentation trees. We present a new scoring for computing fragmentation trees, transforming the combinatorial optimization into a maximum a posteriori estimator. This allows us to learn parameters and hyperparameters of the scoring directly from data. We demonstrate that the statistical model, which was fitted on a small dataset, generalises well across many different datasets and mass spectrometry instruments. In addition to tandem mass spectra, isotope pattern can be used for identifying the molecular formula of the precursor ion. We present a novel scoring for comparing isotope patterns based on maximum likelihood. We describe how to integrate the isotope pattern analysis into the fragmentation tree optimisation problem to analyse data were fragment peaks and isotope peaks occur within the same spectrum. We demonstrate that the new scorings significantly improves on the task of molecular formula assignment. We evaluate SIRIUS on several datasets and show that it outperforms all other methods for molecular formula annotation by a large margin. We also present CSI:FingerID, a method for predicting a molecular fingerprint from a tandem mass spectrum using kernel support vector machines. The predicted fingerprint can be searched in a structure database to identify the molecular structure. CSI:FingerID is based on FingerID, that uses probability product kernels on mass spectra for this task. We describe several novel kernels for comparing fragmentation trees instead of spectra. These kernels are combined using multiple kernel learning. We present a new scoring based on posterior probabilities and extend the method to use additional molecular fingerprints. We demonstrate on several datasets that CSI:FingerID identifies more molecules than its predecessor FingerID and outperforms all other methods for this task. We analyse how each of the methodological improvements of CSI:FingerID contributes to its identification performance and make suggestions for future improvements of the method. Both methods, SIRIUS and CSI:FingerID, are available as commandline tool and as user interface. The molecular fingerprint prediction is implemented as web service and receives over one million requests per month.

Download or read book Bayesian Methods for Small Molecule Identification written by Marcus Ludwig and published by . This book was released on 2020* with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Confident identification of small molecules remains a major challenge in untargeted metabolomics, natural product research and related fields. Liquid chromatography-tandem mass spectrometry is a predominant technique for the high-throughput analysis of small molecules and can detect thousands of different compounds in a biological sample. The automated interpretation of the resulting tandem mass spectra is highly non-trivial and many studies are limited to re-discovering known compounds by searching mass spectra in spectral reference libraries. But these libraries are vastly incomplete and a large portion of measured compounds remains unidentified. This constitutes a major bottleneck in the comprehensive, high-throughput analysis of metabolomics data. In this thesis, we present two computational methods that address different steps in the identification process of small molecules from tandem mass spectra. ZODIAC is a novel method for de novo -- that is, database-independent -- molecular formula annotation in complete datasets. It exploits similarities of compounds co-occurring in a sample to find the most likely molecular formula for each individual compound. ZODIAC improves on the currently best-performing method SIRIUS; on one dataset by 16.5 fold. We show that de novo molecular formula annotation is not just a theoretical advantage: We discover multiple novel molecular formulas absent from PubChem, one of the biggest structure databases. Furthermore, we introduce a novel scoring for CSI:FingerID, a state-of-the-art method for searching tandem mass spectra in a structure database. This scoring models dependencies between different molecular properties in a predicted molecular fingerprint via Bayesian networks. This problem has the unusual property, that the marginal probabilities differ for each predicted query fingerprint. Thus, we need to apply Bayesian networks in a novel, non-standard fashion. Modeling dependencies improves on the currently best scoring.

Download or read book Mass Spectrometry written by Edmond de Hoffmann and published by Wiley. This book was released on 2001-10-10 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers a complete overview of the principles, theories and key applications of modern mass spectrometry in this introductory textbook. Following on from the highly successful first edition, this edition is extensively updated including new techniques and applications. All instrumental aspects of mass spectrometry are clearly and concisely described; sources, analysers and detectors. * Revised and updated * Numerous examples and illustrations are combined with a series of exercises to help encourage student understanding * Includes biological applications, which have been significantly expanded and updated * Also includes coverage of ESI and MALDI

Download or read book High Throughput Calculation of Small Molecule NMR Chemical Shifts and Molecular Fragments written by Yasemin Yesiltepe and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The majority of metabolites are not available as authentic reference material, making confident identification of molecules in complex samples unachievable. Despite recent technological advances, the comprehensive, confident and high-throughput identification of compounds detected in metabolomics studies through currently available experimental methods represents a major roadblock for both technical and economic reasons. In silico NMR libraries are an attractive alternative to the reliance on reference libraries constructed by analysis of authentic reference materials with limited commercial availability. In silico calculation of nuclear magnetic resonance (NMR) chemical shifts is a promising approach to expand available libraries and databases. Firstly, to address the limitations in metabolomics, a high-performance cheminformatics workflow, in silico Chemical Library Engine (ISiCLE), is introduced, designed to predict NMR chemical shifts of organic molecules by employing density functional theory (DFT). ISiCLE is evaluated on a set of molecules integrated with an error reduction approach (conformational sampling).Secondly, the accuracy required for the identification of metabolites is investigated using 11,716 molecules. Of these molecules, 90% can be successfully identified in a pure sample when errors of 1H and 13C chemical shifts reach at least 0.6 ppm and 7.1 ppm, respectively. However, at that same level of accuracy, in complex mixtures, the level of accuracy for identification increases significantly.Thirdly, an automated solvation module is designed to evaluate explicit and implicit solvation at varying levels of theory. It is applied to a set of carboxylic acids of which the chemical shifts are extremely sensitive to water-solvent effects and concluded 2.78 ppm and 0.47 ppm error for 13C and 1H chemical shifts, respectively.Furthermore, an automated and efficient tool, substructure processing, enumeration, and comparison tool resource (SPECTRe), is introduced to provide an entire set of substructures for a given molecular structure. SPECTRe is validated with a set of 10,375 molecules.This dissertation represents computational methods to address the limitations of small molecule identification and offers an alternative to generating NMR libraries experimentally by analyzing authentic reference materials. High-throughput and comprehensive metabolite identifications will revolutionize the understanding of the role of metabolites in environmental and biological samples.

Download or read book Fragment Based Drug Design written by Lawrence C. Kuo and published by Academic Press. This book was released on 2011-03-09 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are numerous excellent reviews on fragment-based drug discovery (FBDD), but there are to date no hand-holding guides or protocols with which one can embark on this orthogonal approach to complement traditional high throughput screening methodologies. This Methods in Enzymology volume offers the tools, practical approaches, and hit-to-lead examples on how to conduct FBDD screens. The chapters in this volume cover methods that have proven to be successful in generating leads from fragments, including chapters on how to apply computational techniques, nuclear magnetic resonance, surface plasma resonance, thermal shift and binding assays, protein crystallography, and medicinal chemistry in FBDD. Also elaborated by experienced researchers in FBDD are sample preparations of fragments, proteins, and GPCR as well as examples of how to generate leads from hits. Offers the tools, practical approaches, and hit-to-lead examples on how to conduct FBDD screens The chapters in this volume cover methods that have proven to be successful in generating leads from fragments, including chapters on how to apply computational techniques, nuclear magnetic resonance, surface plasma resonance, thermal shift and binding assays, protein crystallography, and medicinal chemistry in FBDD

Download or read book Small Molecule Medicinal Chemistry written by Werngard Czechtizky and published by John Wiley & Sons. This book was released on 2015-11-02 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stressing strategic and technological solutions to medicinal chemistry challenges, this book presents methods and practices for optimizing the chemical aspects of drug discovery. Chapters discuss benefits, challenges, case studies, and industry perspectives for improving drug discovery programs with respect to quality and costs. • Focuses on small molecules and their critical role in medicinal chemistry, reviewing chemical and economic advantages, challenges, and trends in the field from industry perspectives • Discusses novel approaches and key topics, like screening collection enhancement, risk sharing, HTS triage, new lead finding approaches, diversity-oriented synthesis, peptidomimetics, natural products, and high throughput medicinal chemistry approaches • Explains how to reduce design-make-test cycle times by integrating medicinal chemistry, physical chemistry, and ADME profiling techniques • Includes descriptive case studies, examples, and applications to illustrate new technologies and provide step-by-step explanations to enable them in a laboratory setting

Download or read book Beyond the Molecular Frontier written by National Research Council and published by National Academies Press. This book was released on 2003-03-19 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chemistry and chemical engineering have changed significantly in the last decade. They have broadened their scopeâ€"into biology, nanotechnology, materials science, computation, and advanced methods of process systems engineering and controlâ€"so much that the programs in most chemistry and chemical engineering departments now barely resemble the classical notion of chemistry. Beyond the Molecular Frontier brings together research, discovery, and invention across the entire spectrum of the chemical sciencesâ€"from fundamental, molecular-level chemistry to large-scale chemical processing technology. This reflects the way the field has evolved, the synergy at universities between research and education in chemistry and chemical engineering, and the way chemists and chemical engineers work together in industry. The astonishing developments in science and engineering during the 20th century have made it possible to dream of new goals that might previously have been considered unthinkable. This book identifies the key opportunities and challenges for the chemical sciences, from basic research to societal needs and from terrorism defense to environmental protection, and it looks at the ways in which chemists and chemical engineers can work together to contribute to an improved future.

Download or read book Structure Based Drug Discovery written by Leslie W. Tari and published by Humana Press. This book was released on 2012-01-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last decade has seen the confluence of several enabling technologies that have allowed protein crystallographic methods to live up to their true potential. Taken together, the numerous recent advances have made it possible to tackle difficult biological targets with a high probability of success: intact bacterial ribosomes have been structurally elucidated, as well as eukaryotic trans-membrane proteins like the potassium channel and GPCRs. It is now possible for medicinal chemists to have access to structural information on their latest small molecule candidates bound to the therapeutic target within days of compound synthesis, allowing structure guided ligand optimization to occur in "real time". Structure-Based Drug Discovery presents an array of methods used to generate crystal structures of biological macromolecules, how to leverage the structural information to design novel ligands anew, and how to iteratively optimize hits and convert them to leads. Written in the successful Methods in Molecular BiologyTM series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and easily accessible, Structure-Based Drug Discovery aims to provide scientists interested in adding SBDD to their arsenal of drug discovery methods with well-honed, up-to-date methodologies.

Download or read book Computational Methods to Improve and Validate Peptide Identifications in Proteomics written by Lei Wang (Computer scientist) and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid development of mass spectrometry technology in the past decade and the recent large-scale proteomics projects, massive and highly redundant tandem mass spectra (MS/MS) are being generated at an unprecedented speed. Hundreds of publications have been made for proteomics studies, yet computational methods which can efficiently identify and analyze the sheer amount of proteomic MS/MS data are still outstanding. The thesis aims to provide systematic approaches to studying MS/MS data from three aspects: spectral clustering, spectral library searching and validation of peptide-spectrum matchings (PSMs).I first introduce a rapid algorithm accelerated by Locality Sensitive Hashing (LSH) techniques to reduce the redundancy in proteomics datasets via clustering similar spectra. The proposed method demonstrates 7-11X performance improvement in running time while retaining superior sensitivity and accuracy when compared to the state of the art spectral clustering algorithms. In addition to the reduction of repetition of similar spectra, the time to search protein database, i.e. a commonly used technique for peptide identification, can be greatly shortened when using the consensus spectra that usually exhibit higher quality than the raw spectra. As a result, It can be demonstrated that more peptide identifications were obtained at the same low false discovery rate (FDR).The second chapter delves into spectral library searching, a complementary approach to database searching for peptide identifications on MS/MS spectra. LSH techniques ensure that similar spectra are placed into the same buckets, whereas spectra with low pairwise similarity are scattered into different buckets. Each input experimental spectrum can then be compared against a subset of highly similar spectra, thus diminishing the unnecessary spectral similarity computation between the input spectrum and all possible combinations of candidate peptides. The identified peptides overlap with those reported by other existing algorithms to a great extent. More importantly, the acceleration rate in the running time of proposed algorithm compared to existing ones increases with the growing size of spectral libraries.Redundancy in large scale proteomic datasets are exploited to further improve the searching results by eliminating the false PSMs examined through a post-processing step. Despite the success of data searching algorithms in proteomics, the peptide identification results usually contain a small fraction of incorrect peptide assignments. Target decoy approach was introduced in previous work to assess the quality of identifications, by searching spectrum against both target and decoy sequences. I formalize the method to improve peptide identifications by removing false PSMs in a probabilistic post-processing approach. As a result, as low as 0.8\\% FDR can be obtained on the remaining PSMs previously reported at 1\\% FDR level and up to 38\\% more unique peptides can be reported at the expected FDR level.I anticipate the computational methods developed in the dissertation can advance the proteomics research field by improving the protein identification through database searching, spectral library searching and validating the searching outputs in a subsequent step. Although the algorithms were evaluated for proteomics studies, they can be extended to small molecules such as natural products, lipids and glycoconjugates. These algorithms can also be generalized to the identification of experimental MS/MS spectra from a molecule of specific interest in massive omic datasets.

Download or read book Small Molecule Drug Discovery written by Andrea Trabocchi and published by Elsevier. This book was released on 2019-11-23 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Small Molecule Drug Discovery: Methods, Molecules and Applications presents the methods used to identify bioactive small molecules, synthetic strategies and techniques to produce novel chemical entities and small molecule libraries, chemoinformatics to characterize and enumerate chemical libraries, and screening methods, including biophysical techniques, virtual screening and phenotypic screening. The second part of the book gives an overview of privileged cyclic small molecules and major classes of natural product-derived small molecules, including carbohydrate-derived compounds, peptides and peptidomimetics, and alkaloid-inspired compounds. The last section comprises an exciting collection of selected case studies on drug discovery enabled by small molecules in the fields of cancer research, CNS diseases and infectious diseases. The discovery of novel molecular entities capable of specific interactions represents a significant challenge in early drug discovery. Small molecules are low molecular weight organic compounds that include natural products and metabolites, as well as drugs and other xenobiotics. When the biological target is well defined and understood, the rational design of small molecule ligands is possible. Alternatively, small molecule libraries are being used for unbiased assays for complex diseases where a target is unknown or multiple factors contribute to a disease pathology. Outlines modern concepts and synthetic strategies underlying the building of small molecules and their chemical libraries useful for drug discovery Provides modern biophysical methods to screening small molecule libraries, including high-throughput screening, small molecule microarrays, phenotypic screening and chemical genetics Presents the most advanced chemoinformatics tools to characterize the structural features of small molecule libraries in terms of chemical diversity and complexity, also including the application of virtual screening approaches Gives an overview of structural features and classification of natural product-derived small molecules, including carbohydrate derivatives, peptides and peptidomimetics, and alkaloid-inspired small molecules

Download or read book Computational Drug Design written by D. C. Young and published by John Wiley & Sons. This book was released on 2009-01-28 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Helps you choose the right computational tools and techniques to meet your drug design goals Computational Drug Design covers all of the major computational drug design techniques in use today, focusing on the process that pharmaceutical chemists employ to design a new drug molecule. The discussions of which computational tools to use and when and how to use them are all based on typical pharmaceutical industry drug design processes. Following an introduction, the book is divided into three parts: Part One, The Drug Design Process, sets forth a variety of design processes suitable for a number of different drug development scenarios and drug targets. The author demonstrates how computational techniques are typically used during the design process, helping readers choose the best computational tools to meet their goals. Part Two, Computational Tools and Techniques, offers a series of chapters, each one dedicated to a single computational technique. Readers discover the strengths and weaknesses of each technique. Moreover, the book tabulates comparative accuracy studies, giving readers an unbiased comparison of all the available techniques. Part Three, Related Topics, addresses new, emerging, and complementary technologies, including bioinformatics, simulations at the cellular and organ level, synthesis route prediction, proteomics, and prodrug approaches. The book's accompanying CD-ROM, a special feature, offers graphics of the molecular structures and dynamic reactions discussed in the book as well as demos from computational drug design software companies. Computational Drug Design is ideal for both students and professionals in drug design, helping them choose and take full advantage of the best computational tools available. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Download or read book Computational Methods for Small Molecules written by Markus Heinonen and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Competitive Fragmentation Modeling of Mass Spectra for Metabolite Identification written by Felicity R. Allen and published by . This book was released on 2016 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the key obstacles to the effective use of mass spectrometry (MS) in high throughput metabolomics is the difficulty in interpreting measured spectra to accurately and efficiently identify metabolites. Traditional methods for automated metabolite identification compare the target MS spectrum to spectra of known molecules in a reference database, ranking candidate molecules based on the closeness of the spectral match. However the limited coverage of available databases has led to interest in computational methods for generating accurate reference MS spectra from chemical structures. This is the target application for this work. My main research contribution is to propose a method for spectrum prediction, which we call Competitive Fragmentation Modeling (CFM). I demonstrate that this method works effectively for both electron ionization (EI)-MS and electrospray tandem MS (ESI-MS/MS). It uses a probabilistic generative model for the fragmentation processes occurring in a mass spectrometer, and a machine learning approach to learn parameters for this model from data. CFM has been used in both a spectrum prediction task (ie, predicting the mass spectrum from a chemical structure), and in a putative metabolite identification task (ranking possible structures for a target spectrum). In the spectrum prediction task, CFM showed improved performance when compared to a full enumeration of all peaks corresponding to all substructures of the molecule. In the metabolite identification task, CFM obtained substantially better rankings for the correct candidate than existing methods. As further validation, this method won the structure identification category of the international Critical Assessment of Small Molecule Identification (CASMI) 2014 competition. The method is also available for general use via a web interface.

Download or read book Predicting Structured Data written by Neural Information Processing Systems Foundation and published by MIT Press. This book was released on 2007 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

Download or read book Computational Immunology written by Shyamasree Ghosh and published by CRC Press. This book was released on 2020-01-31 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Immunology: Applications focuses on different mathematical models, statistical tools, techniques, and computational modelling that helps in understanding complex phenomena of the immune system and its biological functions. The book also focuses on the latest developments in computational biology in designing of drugs, targets, biomarkers for early detection and prognosis of a disease. It highlights the applications of computational methods in deciphering the complex processes of the immune system and its role in health and disease. This book discusses the most essential topics, including Next generation sequencing (NGS) and computational immunology Computational modelling and biology of diseases Drug designing Computation and identification of biomarkers Application in organ transplantation Application in disease detection and therapy Computational methods and applications in understanding of the invertebrate immune system S Ghosh is MSc, PhD, PGDHE, PGDBI, is PhD from IICB, CSIR, Kolkata, awarded the prestigious National Scholarship from the Government of India. She has worked and published extensively in glycobiology, sialic acids, immunology, stem cells and nanotechnology. She has authored several publications that include books and encyclopedia chapters in reputed journals and books.

Download or read book Computational Methods to Analyze RNA Data for Human Diseases written by Min Zeng and published by Frontiers Media SA. This book was released on 2023-09-25 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computer Aided Drug Design written by Dev Bukhsh Singh and published by Springer Nature. This book was released on 2020-10-09 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides up-to-date information on bioinformatics tools for the discovery and development of new drug molecules. It discusses a range of computational applications, including three-dimensional modeling of protein structures, protein-ligand docking, and molecular dynamics simulation of protein-ligand complexes for identifying desirable drug candidates. It also explores computational approaches for identifying potential drug targets and for pharmacophore modeling. Moreover, it presents structure- and ligand-based drug design tools to optimize known drugs and guide the design of new molecules. The book also describes methods for identifying small-molecule binding pockets in proteins, and summarizes the databases used to explore the essential properties of drugs, drug-like small molecules and their targets. In addition, the book highlights various tools to predict the absorption, distribution, metabolism, excretion (ADME) and toxicity (T) of potential drug candidates. Lastly, it reviews in silico tools that can facilitate vaccine design and discusses their limitations.