Zeyed Abdulkarim’s scientific contributions

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Publications (1)


Figure 5. Validation of pIChemiSt on a set of modified peptides. (a) Predictions by the sequence-based model where all noncanonical amino acids and N-and C-termini modifications are ignored; (b) Predictions by pIChemiSt using pKaMatcher as a tool for calculating pK a of noncanonical amino acids; (c) Same as b but with ACDlabs for pK a calculations. The coefficient of determination and root-mean-squared deviation are denoted on the plots. Experimental data are from the following refs 72−76.
Figure 6. Validation of pIChemiSt on IPC2_peptide set of 119093 natural peptides. The coloring is proportional to the density of the points on the plot with lighter color representing denser regions.
pK a Sets Used in the Study
pIChemiSt ─ Free Tool for the Calculation of Isoelectric Points of Modified Peptides
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December 2022

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52 Reads

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15 Citations

Journal of Chemical Information and Modeling

Andrey I. Frolov

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Sunay V. Chankeshwara

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Zeyed Abdulkarim

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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 pKa values. Different pKa 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 pKa 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 R2 from 0.74 to 0.95 and 0.96 against the conventional sequence-based approach for modified peptides for the two studied pKa 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.

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Citations (1)


... For this, the tools implemented within the pIChemist package, developed by Frolov and collaborators, were employed. 46 The implementation of this tool to identify ionizable groups was added to our GitHub repository to ensure reproducibility (ionizable-group-counter.ipynb). As a result, 323 ionizable molecules were obtained. ...

Reference:

LiProS: FAIR simulation workflow to Predict Accurate Lipophilicity Profiles for Small Molecules
pIChemiSt ─ Free Tool for the Calculation of Isoelectric Points of Modified Peptides

Journal of Chemical Information and Modeling