1. Commercial SARS-CoV-2 targeted, protease inhibitor focused and protein–protein interaction inhibitor focused molecular libraries for virtual screening and drug designSebastjan Kralj, Marko Jukič, Urban Bren, 2022, review article Abstract: Since December 2019, the new SARS-CoV-2-related COVID-19 disease has caused a global
pandemic and shut down the public life worldwide. Several proteins have emerged as potential
therapeutic targets for drug development, and we sought out to review the commercially available
and marketed SARS-CoV-2-targeted libraries ready for high-throughput virtual screening (HTVS).
We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and protein–protein-interactioninhibitor-focused libraries to gain a better understanding of how these libraries were designed. The
most common were ligand- and structure-based approaches, along with various filtering steps, using
molecular descriptors. Often, these methods were combined to obtain the final library. We recognized
the abundance of targeted libraries offered and complimented by the inclusion of analytical data;
however, serious concerns had to be raised. Namely, vendors lack the information on the library
design and the references to the primary literature. Few references to active compounds were also
provided when using the ligand-based design and usually only protein classes or a general panel
of targets were listed, along with a general reference to the methods, such as molecular docking for
the structure-based design. No receptor data, docking protocols or even references to the applied
molecular docking software (or other HTVS software), and no pharmacophore or filter design
details were given. No detailed functional group or chemical space analyses were reported, and no
specific orientation of the libraries toward the design of covalent or noncovalent inhibitors could
be observed. All libraries contained pan-assay interference compounds (PAINS), rapid elimination
of swill compounds (REOS) and aggregators, as well as focused on the drug-like model, with the
majority of compounds possessing their molecular mass around 500 g/mol. These facts do not bode
well for the use of the reviewed libraries in drug design and lend themselves to commercial drug
companies to focus on and improve.
Keywords: targeted libraries, focused libraries, computer-aided drug design, virtual screening, in silico drug design, high-throughput virtual screening
Published in DKUM: 09.04.2025; Views: 0; Downloads: 1
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2. Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library ScreeningMarko 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: 353; Downloads: 88
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3. 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: 497; Downloads: 51
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