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      AdductHunter: identifying protein-metal complex adducts in mass spectra

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          Abstract

          Mass spectrometry (MS) is an analytical technique for molecule identification that can be used for investigating protein-metal complex interactions. Once the MS data is collected, the mass spectra are usually interpreted manually to identify the adducts formed as a result of the interactions between proteins and metal-based species. However, with increasing resolution, dataset size, and species complexity, the time required to identify adducts and the error-prone nature of manual assignment have become limiting factors in MS analysis. AdductHunter is a open-source web-based analysis tool that  automates the peak identification process using constraint integer optimization to find feasible combinations of protein and fragments, and dynamic time warping to calculate the dissimilarity between the theoretical isotope pattern of a species and its experimental isotope peak distribution. Empirical evaluation on a collection of 22 unique MS datasetsshows fast and accurate identification of protein-metal complex adducts in deconvoluted mass spectra.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13321-023-00797-7.

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          SciPy 1.0: fundamental algorithms for scientific computing in Python

          SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
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            MSFragger: ultrafast and comprehensive peptide identification in shotgun proteomics

            There is a need to better understand and handle the “dark matter” of proteomics – the vast diversity of post-translational and chemical modifications that are unaccounted in a typical analysis and thus remain unidentified. We present a novel fragment-ion indexing method, and its implementation in peptide identification tool MSFragger, that enables an over 100-fold improvement in speed over most existing tools. Using some of the largest proteomic datasets to date, we demonstrate how MSFragger empowers the open database search concept for comprehensive identification of peptides and all their modified forms, uncovering dramatic differences in the modification rates across experimental samples and conditions. We further illustrate its utility using protein-RNA crosslinked peptide data, and using affinity purification experiments where we observe on average a 300% increase in the number of identified spectra for enriched proteins. We also discuss the benefits of open searching for improved false discovery rate estimation in proteomics.
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              Philosopher: a versatile toolkit for shotgun proteomics data analysis

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                Author and article information

                Contributors
                j.wicker@auckland.ac.nz
                Journal
                J Cheminform
                J Cheminform
                Journal of Cheminformatics
                Springer International Publishing (Cham )
                1758-2946
                6 February 2024
                6 February 2024
                2024
                : 16
                : 15
                Affiliations
                [1 ]School of Computer Science, University of Auckland, ( https://ror.org/03b94tp07) 1010 Auckland, New Zealand
                [2 ]School of Chemical Sciences, University of Auckland, ( https://ror.org/03b94tp07) 1142 Auckland, New Zealand
                [3 ]School of Biological Sciences, University of Auckland, ( https://ror.org/03b94tp07) 1142 Auckland, New Zealand
                [4 ]Department of Engineering Science, University of Auckland, ( https://ror.org/03b94tp07) 1010 Auckland, New Zealand
                [5 ]Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, ( https://ror.org/03prydq77) 1090 Vienna, Austria
                Article
                797
                10.1186/s13321-023-00797-7
                10845562
                38321500
                e4cf6b77-0c6c-4870-a24d-e4eb2ed7d405
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 31 August 2023
                : 17 December 2023
                Categories
                Software
                Custom metadata
                © Springer Nature Switzerland AG 2024

                Chemoinformatics
                mass spectrometry,protein adducts,constraint integer optimization,dynamic time warping

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