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Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library Screening
Marko Jukič, Sebastjan Kralj, Anja Kolarič, Urban Bren, 2023, original scientific article

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.
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
Published in DKUM: 01.12.2023; Views: 278; Downloads: 74
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Comparative Analyses of Medicinal Chemistry and Cheminformatics Filters with Accessible Implementation in Konstanz Information Miner (KNIME)
Sebastjan Kralj, Marko Jukič, Urban Bren, 2022, original scientific article

Abstract: High-throughput virtual screening (HTVS) is, in conjunction with rapid advances in computer hardware, becoming a staple in drug design research campaigns and cheminformatics. In this context, virtual compound library design becomes crucial as it generally constitutes the first step where quality filtered databases are essential for the efficient downstream research. Therefore, multiple filters for compound library design were devised and reported in the scientific literature. We collected the most common filters in medicinal chemistry (PAINS, REOS, Aggregators, van de Waterbeemd, Oprea, Fichert, Ghose, Mozzicconacci, Muegge, Egan, Murcko, Veber, Ro3, Ro4, and Ro5) to facilitate their open access use and compared them. Then, we implemented these filters in the open platform Konstanz Information Miner (KNIME) as a freely accessible and simple workflow compatible with small or large compound databases for the benefit of the readers and for the help in the early drug design steps.
Keywords: high-throughput virtual screening, virtual screening, compound libraries, library design, compound filtering
Published in DKUM: 25.07.2023; Views: 394; Downloads: 29
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