1. Cheminformatic analysis of protein surfaces provides binding site insights andinforms identification strategiesAndrej Milisavljević, Jure Pražnikar, Urban Bren, Marko Jukič, 2025, original scientific article Abstract: Aims: Understanding protein–ligand binding site behavior is central to structure-based drug design. Weanalyzed amino acid composition and interactions in protein–ligand small-molecule binding sites anddeveloped a novel method for binding site prediction.Materials and methods: We analyzed the PDBBind+ database, which contains the largest protein–ligand binding site dataset known to us, using existing cheminformatics packages and in-house code.We used the resulting data to train a binding site prediction model.Results: Within solvent-accessible binding regions, tryptophan, phenylalanine, tyrosine, methionine,and glycine, were enriched. Interaction analysis revealed hydrophobic contacts as the most frequent,followed by hydrogen bonds, water-bridged hydrogen bonds, salt bridges, π–π, π–cation, and occa-sional halogen interactions. We introduced the amino acid binding site enrichment index (ABSE), tosupport small-molecule binding site detection, and developed a model that discriminates binding sitesequences from protein surface patches with 0.91 accuracy.Conclusions: This work offers interpretable composition–interaction relationships and practical tool forbinding site characterization. To facilitate application, we provide a free, open-source, fast, bindingsiteidentification tool (AABS), available at https://gitlab.com/Jukic/aabs. We anticipate that these findingsand tool will advance binding site prediction and accelerate computationally intensive drug discoverywithin medicinal chemistry.
Keywords: protein surface analysis, small-molecule binding site detection, machine learning, cheminformatics, amino acidindex, binding site, mall-molecule–protein interactions, in-silico drug design
Published in DKUM: 08.12.2025; Views: 0; Downloads: 1
 Full text (7,50 MB) |
2. 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: 7
Full text (6,53 MB)
This document has many files! More... |
3. Identification of furin protease small-molecule inhibitor with a 1,3-thiazol-2-ylaminosulfonyl scaffoldAnja Kolarič, Vid Ravnik, Sara Štumpf Horvat, Marko Jukič, Urban Bren, 2025, original scientific article Keywords: computer-assisted drug design, CADD, computer-assisted drug design, furin inhibitors, protease inhibitors, antivirals, protease inhibitors, furin assay, antiviral drug design
Published in DKUM: 20.03.2025; Views: 0; Downloads: 3
Full text (6,26 MB) |
4. Molecular Filters in Medicinal ChemistrySebastjan Kralj, Marko Jukič, Urban Bren, 2023, review article Keywords: medicinal chemistry, filtering chemical libraries, chemical space, HTVS, virtual screening, computer aided drug-design, in silico drug design, bioinformatics, chemoinformatic, compound library
Published in DKUM: 20.05.2024; Views: 168; Downloads: 26
Full text (1,66 MB)
This document has many files! More... |
5. Identification of triazolopyrimidinyl scaffold SARS-CoV-2 papain-like protease (PLpro) inhibitorSebastjan Kralj, Marko Jukič, Miha Bahun, Luka Krajnc, Anja Kolarič, Milan Hodošček, Nataša Poklar Ulrih, Urban Bren, 2024, original scientific article Abstract: The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
and its companion disease, COVID-19, has reminded us of the importance of basic coronaviral
research. In this study, a comprehensive approach using molecular docking, in vitro assays, and
molecular dynamics simulations was applied to identify potential inhibitors for SARS-CoV-2 papainlike protease (PLpro), a key and underexplored viral enzyme target. A focused protease inhibitor
library was initially created and molecular docking was performed using CmDock software (v0.2.0),
resulting in the selection of hit compounds for in vitro testing on the isolated enzyme. Among
them, compound 372 exhibited promising inhibitory properties against PLpro, with an IC50 value of
82 ± 34 µM. The compound also displayed a new triazolopyrimidinyl scaffold not yet represented
within protease inhibitors. Molecular dynamics simulations demonstrated the favorable binding
properties of compound 372. Structural analysis highlighted its key interactions with PLpro, and
we stress its potential for further optimization. Moreover, besides compound 372 as a candidate for
PLpro inhibitor development, this study elaborates on the PLpro binding site dynamics and provides
a valuable contribution for further efforts in pan-coronaviral PLpro inhibitor development.
Keywords: drug design, protease inhibitor, SARS-CoV-2, papain-like protease, PLpro, antiviral design, in silico drug design, CADD, virtual screening, HTVS, structure-based design
Published in DKUM: 26.01.2024; Views: 358; Downloads: 34
Full text (6,86 MB)
This document has many files! More... |
6. 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: 89
Full text (8,11 MB)
This document has many files! More... |
7. Neuropilin (NRPs) related pathological conditions and their modulatorsMatic Broz, Anja Kolarič, Marko Jukič, Urban Bren, 2022, review article Abstract: Neuropilin 1 (NRP1) represents one of the two homologous neuropilins (NRP, splice variants of neuropilin 2 are the other) found in all vertebrates. It forms a transmembrane glycoprotein distributed in many human body tissues as a (co)receptor for a variety of different ligands. In addition to its physiological role, it is also associated with various pathological conditions. Recently, NRP1 has been discovered as a coreceptor for the SARS-CoV-2 viral entry, along with ACE2, and has thus become one of the COVID-19 research foci. However, in addition to COVID-19, the current review also summarises its other pathological roles and its involvement in clinical diseases like cancer and neuropathic pain. We also discuss the diversity of native NRP ligands and perform a joint analysis. Last but not least, we review the therapeutic roles of NRP1 and introduce a series of NRP1 modulators, which are typical peptidomimetics or other small molecule antagonists, to provide the medicinal chemistry community with a state-of-the-art overview of neuropilin modulator design and NRP1 druggability assessment.
Keywords: neuropilins, computer-aided drug design, in silico drug design, receptor modulator design, peptidomimetics, small-molecule antagonists, cancer, COVID-19, neuropathic pain
Published in DKUM: 22.08.2023; Views: 379; Downloads: 375
Full text (11,93 MB)
This document has many files! More... |
8. Ensemble Docking Coupled to Linear Interaction Energy Calculations for Identification of Coronavirus Main Protease (3CLpro) Non-Covalent Small-Molecule InhibitorsMarko Jukič, Dušanka Janežič, Urban Bren, 2020, original scientific article Abstract: SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new strain of Coronaviridae. In the closing 2019 to early 2020 months, the virus caused a global pandemic of COVID-19 disease. We performed a virtual screening study in order to identify potential inhibitors of the SARS-CoV-2 main viral protease (3CLpro or Mpro). For this purpose, we developed a novel approach using ensemble docking high-throughput virtual screening directly coupled with subsequent Linear Interaction Energy (LIE) calculations to maximize the conformational space sampling and to assess the binding affinity of identified inhibitors. A large database of small commercial compounds was prepared, and top-scoring hits were identified with two compounds singled out, namely 1-[(R)-2-(1,3-benzimidazol-2-yl)-1-pyrrolidinyl]-2-(4-methyl-1,4-diazepan-1-yl)-1-ethanone and [({(S)-1-[(1H-indol-2-yl)methyl]-3-pyrrolidinyl}methyl)amino](5-methyl-2H-pyrazol-3-yl)formaldehyde. Moreover, we obtained a favorable binding free energy of the identified compounds, and using contact analysis we confirmed their stable binding modes in the 3CLpro active site. These compounds will facilitate further 3CLpro inhibitor design.
Keywords: COVID-19, SARS-CoV-2, Mpro, 3CLpro, 3C-like protease, virtual screening, inhibitors, in silico drug design, free-energy calculations
Published in DKUM: 10.12.2020; Views: 1252; Downloads: 193
Full text (3,08 MB)
This document has many files! More... |
9. Scaffold hopping and bioisosteric replacements based on binding site alignmentsSamo Lešnik, Janez Konc, Dušanka Janežič, 2016, original scientific article Abstract: Bioisosteric replacements and scaffold hopping play an important role in modern drug discovery and design, as they enable the change of either a core scaffold or substitutes in a drug structure, thereby facilitating optimization of pharmacokinetic properties and patenting, while the drug retains its activity. A new knowledge-based method was developed to obtain bioisosteric or scaffold replacements based on the extensive data existing in the Protein Data Bank. The method uses all-against-all ProBiS-based protein superimposition to identify ligand fragments that overlap in similar binding sites and could therefore be considered as bioisosteric replacements. The method was demonstrated on a specific example of drug candidate – a nanomolar butyrylcholinesterase inhibitor, on which bioisosteric replacements of the three ring fragments were performed. The new molecule containing bioisosteric replacements was evaluated virtually using AutoDock Vina; a similar score for the original and the compound with replacements was obtained, suggesting that the newly designed bioisostere compound might retain the potency of the original inhibitor.
Keywords: bioisosteres, scaffold hopping, protein alignment, ProBiS, drug design, analysis methods, matter structure, modelling
Published in DKUM: 05.07.2017; Views: 1237; Downloads: 444
Full text (2,30 MB)
This document has many files! More... |
