0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      pIChemiSt — Free Tool for the Calculation of Isoelectric Points of Modified Peptides

      research-article

      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The isoelectric point (pI) is a fundamental physicochemical property of peptides and proteins. It is widely used to steer design away from low solubility and aggregation and guide peptide separation and purification. Experimental measurements of pI can be replaced by calculations knowing the ionizable groups of peptides and their corresponding p K a values. Different p K a sets are published in the literature for natural amino acids, however, they are insufficient to describe synthetically modified peptides, complex peptides of natural origin, and peptides conjugated with structures of other modalities. Noncanonical modifications (nCAAs) are ignored in the conventional sequence-based pI calculations, therefore producing large errors in their pI predictions. In this work, we describe a pI calculation method that uses the chemical structure as an input, automatically identifies ionizable groups of nCAAs and other fragments, and performs p K a predictions for them. The method is validated on a curated set of experimental measures on 29 modified and 119093 natural peptides, providing an improvement of R 2 from 0.74 to 0.95 and 0.96 against the conventional sequence-based approach for modified peptides for the two studied p K a prediction tools, ACDlabs and pKaMatcher, correspondingly. The method is available in the form of an open source Python library at https://github.com/AstraZeneca/peptide-tools, which can be integrated into other proprietary and free software packages. We anticipate that the pI calculation tool may facilitate optimization and purification activities across various application domains of peptides, including the development of biopharmaceuticals.

          Related collections

          Most cited references67

          • Record: found
          • Abstract: not found
          • Article: not found

          Matplotlib: A 2D Graphics Environment

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Biopython: freely available Python tools for computational molecular biology and bioinformatics

            Summary: The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning. Availability: Biopython is freely available, with documentation and source code at www.biopython.org under the Biopython license. Contact: All queries should be directed to the Biopython mailing lists, see www.biopython.org/wiki/_Mailing_lists peter.cock@scri.ac.uk.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical pKa Predictions.

              In this study, we have revised the rules and parameters for one of the most commonly used empirical pKa predictors, PROPKA, based on better physical description of the desolvation and dielectric response for the protein. We have introduced a new and consistent approach to interpolate the description between the previously distinct classifications into internal and surface residues, which otherwise is found to give rise to an erratic and discontinuous behavior. Since the goal of this study is to lay out the framework and validate the concept, it focuses on Asp and Glu residues where the protein pKa values and structures are assumed to be more reliable. The new and improved implementation is evaluated and discussed; it is found to agree better with experiment than the previous implementation (in parentheses): rmsd = 0.79 (0.91) for Asp and Glu, 0.75 (0.97) for Tyr, 0.65 (0.72) for Lys, and 1.00 (1.37) for His residues. The most significant advance, however, is in reducing the number of outliers and removing unreasonable sensitivity to small structural changes that arise from classifying residues as either internal or surface.
                Bookmark

                Author and article information

                Journal
                J Chem Inf Model
                J Chem Inf Model
                ci
                jcisd8
                Journal of Chemical Information and Modeling
                American Chemical Society
                1549-9596
                1549-960X
                27 December 2022
                09 January 2023
                : 63
                : 1
                : 187-196
                Affiliations
                []Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca , Gothenburg, Sweden
                []Early Chemical Development, Pharmaceutical Sciences, BioPharmaceuticals R&D, AstraZeneca , Gothenburg, Sweden
                [§ ]Augmented DMTA Engineering, R&D IT, AstraZeneca , Cambridge, U.K.
                Author notes
                Author information
                https://orcid.org/0000-0001-9801-3253
                https://orcid.org/0000-0001-8886-170X
                https://orcid.org/0000-0003-3868-8253
                https://orcid.org/0000-0002-2592-2939
                Article
                10.1021/acs.jcim.2c01261
                9832473
                36573842
                b26e7514-0c58-40e9-8ce9-baba22e1fa27
                © 2022 The Authors. Published by American Chemical Society

                Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 10 October 2022
                Categories
                Article
                Custom metadata
                ci2c01261
                ci2c01261

                Computational chemistry & Modeling
                Computational chemistry & Modeling

                Comments

                Comment on this article