ProBiS-Dock: A Hybrid Multitemplate Homology Flexible Docking Algorithm Enabled by Protein Binding Site Comparison

Konc, Janez; Lešnik, Samo; Škrlj, Blaž; Sova, Matej; Proj, Matic; Knez, Damijan; Gobec, Stanislav; Janežič, Dušanka

doi:10.1021/acs.jcim.1c01176

Cited by 5 publications

(6 citation statements)

References 37 publications

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“…ProBiS-Dock ( http://insilab.org/probisdock ) is a hybrid multitemplate homology algorithm for flexible docking enabled by protein binding site comparison (Konc et al 2022 ). It is a small molecule docking (and inverse docking) approach based on predicted binding sites that enables flexible docking of small ligands to flexible protein binding sites.…”

Section: Probis Tools Developmentmentioning

confidence: 99%

Protein binding sites for drug design

Konc

Janežič

2022

Biophys Rev

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Drug development is a lengthy and challenging process that can be accelerated at early stages by new mathematical approaches and modern computers. To address this important issue, we are developing new mathematical solutions for the detection and characterization of protein binding sites that are important for new drug development. In this review, we present algorithms based on graph theory combined with molecular dynamics simulations that we have developed for studying biological target proteins to provide important data for optimizing the early stages of new drug development. A particular focus is the development of new protein binding site prediction algorithms (ProBiS) and new web tools for modeling pharmaceutically interesting molecules—ProBiS Tools (algorithm, database, web server), which have evolved into a full-fledged graphical tool for studying proteins in the proteome. ProBiS differs from other structural algorithms in that it can align proteins with different folds without prior knowledge of the binding sites. It allows detection of similar binding sites and can predict molecular ligands of various types of pharmaceutical interest that could be advanced to drugs to treat a disease, based on the entire Protein Data Bank (PDB) and AlphaFold database, including proteins not yet in the PDB. All ProBiS Tools are freely available to the academic community at http://insilab.org and https://probis.nih.gov .

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Section: Probis Tools Developmentmentioning

confidence: 99%

Protein binding sites for drug design

Konc

Janežič

2022

Biophys Rev

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“…Molecular docking with ProBiS-Dock algorithm (Konc et al, 2022) was performed with the prepared CCR7 receptor. Similar receptors with allosterically bound ligands that were known at the time of screening, i.e., CCR9 (PDB ID: 5LWE, ligand 79K [vercirnon]) (Oswald et al, 2016) and CCR2 (PDB ID: 5T1A, ligand VT5) (Zheng et al, 2016), were aligned to the prepared CCR7 receptor.…”

Section: Molecular Docking With Probis-dock Algorithmmentioning

confidence: 99%

“…A SBVS approach was also explored using the ProBiS-Dock algorithm (Konc et al, 2022). Allosteric binding sites of other chemokine receptor crystal structures available at the time of our study were aligned and compared.…”

Section: Virtual Screening Campaignmentioning

confidence: 99%

A Set of Experimentally Validated Decoys for the Human CC Chemokine Receptor 7 (CCR7) Obtained by Virtual Screening

et al. 2022

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We present a state-of-the-art virtual screening workflow aiming at the identification of novel CC chemokine receptor 7 (CCR7) antagonists. Although CCR7 is associated with a variety of human diseases, such as immunological disorders, inflammatory diseases, and cancer, this target is underexplored in drug discovery and there are no potent and selective CCR7 small molecule antagonists available today. Therefore, computer-aided ligand-based, structure-based, and joint virtual screening campaigns were performed. Hits from these virtual screenings were tested in a CCL19-induced calcium signaling assay. After careful evaluation, none of the in silico hits were confirmed to have an antagonistic effect on CCR7. Hence, we report here a valuable set of 287 inactive compounds that can be used as experimentally validated decoys.

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“…A recent analog to this work is the ProBis-Score scoring function’s identification of template ligands for binding pockets. ProBis-Dock – identifies template ligands using local surface similarities from other binding sites in PDB. Similarly, in this work, we gather PDB ligand IDs from structurally matched templates in PDB.…”

Section: Introductionmentioning

confidence: 99%

“…It appears that the vast majority of protein pocket featurization and clustering methods rely, as do these studies, on protein features based on pocket structure and/or physicochemical properties – to the exclusion of features based on known interacting ligands. A recent analog to this work is the ProBis-Score scoring function’s identification of template ligands for binding pockets. ProBis-Dock – identifies template ligands using local surface similarities from other binding sites in PDB.…”

Section: Introductionmentioning

confidence: 99%

Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method

Stevenson,

Kirshner,

Bennion

et al. 2023

J. Chem. Inf. Model.

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Protein−ligand interactions are essential to drug discovery and drug development efforts. Desirable on-target or multitarget interactions are the first step in finding an effective therapeutic, while undesirable off-target interactions are the first step in assessing safety. In this work, we introduce a novel ligand-based featurization and mapping of human protein pockets to identify closely related protein targets and to project novel drugs into a hybrid protein−ligand feature space to identify their likely protein interactions. Using structure-based template matches from PDB, protein pockets are featured by the ligands that bind to their best co-complex template matches. The simplicity and interpretability of this approach provide a granular characterization of the human proteome at the protein-pocket level instead of the traditional protein-level characterization by family, function, or pathway. We demonstrate the power of this featurization method by clustering a subset of the human proteome and evaluating the predicted cluster associations of over 7000 compounds.

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ProBiS-Dock: A Hybrid Multitemplate Homology Flexible Docking Algorithm Enabled by Protein Binding Site Comparison

Cited by 5 publications

References 37 publications

Protein binding sites for drug design

Protein binding sites for drug design

A Set of Experimentally Validated Decoys for the Human CC Chemokine Receptor 7 (CCR7) Obtained by Virtual Screening

Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method

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