| Title: | Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library Screening |
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| Authors: | ID Jukič, Marko (Author)
ID Kralj, Sebastjan (Author)
ID Kolarič, Anja (Author)
ID Bren, Urban (Author) |
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| Files: |  pharmaceuticals-16-01170-v2.pdf (8,11 MB)
MD5: F51D48DFFD3197B28111512BB201604F
 https://www.mdpi.com/1424-8247/16/8/1170
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FKKT - Faculty of Chemistry and Chemical Engineering
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| Abstract: | Abstract
Peptides, or short chains of amino-acid residues, are becoming increasingly important as active ingredients of drugs and as crucial probes and/or tools in medical, biotechnological, and pharmaceutical research. Situated at the interface between small molecules and larger macromolecular systems, they pose a difficult challenge for computational methods. We report an in silico peptide library generation and prioritization workflow using CmDock for identifying tetrapeptide ligands that bind to Fc regions of antibodies that is analogous to known in vitro recombinant peptide libraries’ display and expression systems. The results of our in silico study are in accordance with existing scientific literature on in vitro peptides that bind to antibody Fc regions. In addition, we postulate an evolving in silico library design workflow that will help circumvent the combinatorial problem of in vitro comprehensive peptide libraries by focusing on peptide subunits that exhibit favorable interaction profiles in initial in silico peptide generation and testing. |
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| Keywords: | peptide design, in silico combinatorial library, peptide combinatorial library, peptide library design, high-throughput virtual screening, peptide molecular docking, antibody purification, peptide drug design, recombinant peptide libraries |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 26.07.2023 |
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| Article acceptance date: | 10.08.2023 |
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| Publication date: | 17.08.2023 |
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| Publisher: | MDPI |
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| Year of publishing: | 2023 |
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| Number of pages: | 22 str. |
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| Numbering: | Vol. 16, no. 8, [Article no.] 1170 |
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| PID: | 20.500.12556/DKUM-86440  |
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| UDC: | 577 |
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| ISSN on article: | 1424-8247 |
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| COBISS.SI-ID: | 161574147 |
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| DOI: | 10.3390/ph16081170 |
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| Publication date in DKUM: | 01.12.2023 |
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| Views: | 353 |
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| Downloads: | 88 |
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| Metadata: |    |
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| Categories: | Misc.
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