Rapid discovery of drug target engagement by isothermal shift assay

2019 ◽  
Author(s):  
Kristofor J. Webb ◽  
Kerri A. Ball ◽  
Stephen J. Coleman ◽  
Jeremy Jacobsen ◽  
Michael H.B. Stowell ◽  
...  
Keyword(s):  
Drug Target ◽  
Drug Targets ◽  
Kinase Inhibitors ◽  
Rapid Identification ◽  
Living Cells ◽  
Experimental Designs ◽  
Living Systems ◽  
Target Engagement ◽  
Protein Targets ◽  
Drug Molecules

Identifying protein targets directly bound by drug molecules within living systems remains challenging. Here we present the isothermal shift assay, iTSA, for rapid identification of drug targets. Compared with thermal proteome profiling, a prevailing method for target engagement, iTSA offers a simplified workflow, 4-fold higher throughput, and multiplexed experimental designs with higher replication. We demonstrate application of iTSA to identify targets for several kinase inhibitors in lysates and living cells.

Monitoring Drug-Target Interactions through Target Engagement-Mediated Amplification on Arrays and in situ

2021 ◽  
Author(s):  
Rasel Al-Amin ◽  
Lars Johansson ◽  
Eldar Abdurakhmanov ◽  
Nils Landegren ◽  
Liza Löf ◽  
...  
Keyword(s):  
Drug Target ◽  
Kinase Inhibitors ◽  
Expression Profiles ◽  
Clinical Samples ◽  
Target Engagement ◽  
Rolling Circle Replication ◽  
Target Proteins ◽  
Dna Conjugates

Abstract Drugs are designed to bind their target proteins in physiologically relevant tissues and organs to modulate biological functions and elicit desirable clinical outcomes. Information about target engagement at cellular and subcellular resolution is therefore critical for guiding compound optimization in drug discovery, and for probing resistance mechanisms to targeted therapies in clinical samples. We describe a target engagement-mediated amplification (TEMA) technology, where oligonucleotide-conjugated drugs are used to visualize and measure target engagement in situ, amplified via rolling-circle replication of circularized oligonucleotide probes. We illustrate the TEMA technique using dasatinib and gefitinib, two kinase inhibitors with distinct selectivity profiles. In vitro binding by dasatinib probe to arrays of displayed proteins accurately reproduced known selectivity profiles, while their differential binding to a panel of fixed adherent cells agreed with expectations from expression profiles of the cells. These findings were corroborated by competition experiments using kinase inhibitors with overlapping and non-overlapping target specificities, and translated to pathology tissue sections. We also introduce a proximity ligation variant of TEMA in which these drug-DNA conjugates are combined with antibody-DNA conjugates to selectively investigate binding to specific target proteins of interest. This form of the assay serves to improve resolution of binding to on- and off-target proteins. In conclusion, TEMA has the potential to aid in drug development and clinical routine by conferring valuable insights in drug-target interactions at spatial resolution in protein arrays, cells and tissues.

scholarly journals Interpretable Drug Target Predictions using Self-Expressiveness

2021 ◽  
Author(s):  
Diego Galeano ◽  
Santiago Noto ◽  
Ruben Jimenez ◽  
Alberto Paccanaro
Keyword(s):  
Drug Target ◽  
Drug Targets ◽  
Prediction Models ◽  
Matrix Completion ◽  
Closed Form Solution ◽  
Target Prediction ◽  
Form Solution ◽  
Protein Targets ◽  
Drug Target Prediction ◽  
Similarity Matrices

AbstractThe identification of missing drug targets is critical for the development of treatments and for the molecular elucidation of drug side effects. Drug targets have been predicted by exploiting molecular, biological or pharmacological features of drugs and protein targets. Yet, developing integrative and interpretable machine learning models for predicting drug targets remains a challenging task. We present Inception, an integrative and interpretable matrix completion model for predicting drug targets. Inception is a self-expressive model that learns two similarity matrices: one for drugs and another for protein targets. These learned similarity matrices are key for our models’ interpretability: they can explain how a predicted drug-target interaction can be explain in terms of a linear combination of chemical, biological and pharmacological similarities. We develop a novel objective function with efficient closed-form solution. To demonstrate the ability of Inception at recovering missing drug-target interactions (DTIs), we perform cross-validation experiments with stringent controls of data imbalance, chemical similarities between drugs and sequence similarities between targets. We also assess the performance of our model using a simulated prospective approach. Having trained our model with DTIs from a snapshot 2011 of the DrugBank database, we test whether we could predict DTIs from a 2020 snapshot of DrugBank. Inception outperforms two state-of-the-art drug target prediction models in all the scenarios. This suggests that Inception could be useful for predicting missing drug target interactions while providing interpretable predictions.

scholarly journals Detecting Drug-Target Binding in Cells using Fluorescence Activated Cell Sorting Coupled with Mass Spectrometry Analysis

2017 ◽  
Author(s):  
Kris Wilson ◽  
Scott P Webster ◽  
John P Iredale ◽  
Xiaozhong Zheng ◽  
Natalie Z Homer ◽  
...  
Keyword(s):  
Drug Target ◽  
Drug Targets ◽  
Mass Spectrometry Analysis ◽  
Protein Targets ◽  
Target Proteins ◽  
Spectrometry Analysis ◽  
Cellular Permeability ◽  
Target Binding ◽  
Hit Validation

AbstractThe assessment of drug-target engagement for determining the efficacy of a compound inside cells remains challenging, particularly for difficult target proteins. Existing techniques are more suited to soluble protein targets. Difficult target proteins include those with challenging in vitro solubility, stability or purification properties that preclude target isolation. Here, we report a novel technique that measures intracellular compound-target complex formation, as well as cellular permeability, specificity and cytotoxicity - the Toxicity-Affinity-Permeability-Selectivity (TAPS) technique. The TAPS assay is exemplified here using human kynurenine 3-monooxygenase (KMO), a challenging intracellular membrane protein target of significant current interest. TAPS confirmed target binding of known KMO inhibitors inside cells. We conclude that the TAPS assay can be used to facilitate intracellular hit validation on most, if not all intracellular drug targets.

scholarly journals LiP-Quant, an automated chemoproteomic approach to identify drug targets in complex proteomes

2019 ◽  
Author(s):  
Ilaria Piazza ◽  
Nigel Beaton ◽  
Roland Bruderer ◽  
Thomas Knobloch ◽  
Crystel Barbisan ◽  
...  
Keyword(s):  
Small Molecule ◽  
Binding Sites ◽  
Drug Target ◽  
Drug Targets ◽  
Target Identification ◽  
Limited Proteolysis ◽  
Drug Binding ◽  
Homologous Proteins ◽  
Protein Targets ◽  
Drug Target Identification

Chemoproteomics is a key technology to characterize the mode of action of drugs, as it directly identifies the protein targets of bioactive compounds and aids in developing optimized small-molecule compounds. Current unbiased approaches cannot directly pinpoint the interaction surfaces between ligands and protein targets. To address his limitation we have developed a new drug target deconvolution approach based on limited proteolysis coupled with mass spectrometry that works across species including human cells (LiP-Quant). LiP-Quant features an automated data analysis pipeline and peptide-level resolution for the identification of any small-molecule binding sites, Here we demonstrate drug target identification by LiP-Quant across compound classes, including compounds targeting kinases and phosphatases. We demonstrate that LiP-Quant estimates the half maximal effective concentration (EC50) of compound binding sites in whole cell lysates. LiP-Quant identifies targets of both selective and promiscuous drugs and correctly discriminates drug binding to homologous proteins. We finally show that the LiP-Quant technology identifies targets of a novel research compound of biotechnological interest.

Tracking cancer drugs in living cells by thermal profiling of the proteome

Science ◽  
2014 ◽  
Vol 346 (6205) ◽  
pp. 1255784 ◽  
Author(s):  
Mikhail M. Savitski ◽  
Friedrich B. M. Reinhard ◽  
Holger Franken ◽  
Thilo Werner ◽  
Maria Fälth Savitski ◽  
...  
Keyword(s):  
Drug Target ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Drug Efficacy ◽  
Living Cells ◽  
Live Cells ◽  
Downstream Effectors ◽  
Small Molecule Ligands ◽  
Thermal Profiling ◽  
Thermal Stability Of

The thermal stability of proteins can be used to assess ligand binding in living cells. We have generalized this concept by determining the thermal profiles of more than 7000 proteins in human cells by means of mass spectrometry. Monitoring the effects of small-molecule ligands on the profiles delineated more than 50 targets for the kinase inhibitor staurosporine. We identified the heme biosynthesis enzyme ferrochelatase as a target of kinase inhibitors and suggest that its inhibition causes the phototoxicity observed with vemurafenib and alectinib. Thermal shifts were also observed for downstream effectors of drug treatment. In live cells, dasatinib induced shifts in BCR-ABL pathway proteins, including CRK/CRKL. Thermal proteome profiling provides an unbiased measure of drug-target engagement and facilitates identification of markers for drug efficacy and toxicity.

Understanding Membrane Protein Drug Targets in Computational Perspective

2019 ◽  
Vol 20 (5) ◽  
pp. 551-564 ◽  
Author(s):  
Jianting Gong ◽  
Yongbing Chen ◽  
Feng Pu ◽  
Pingping Sun ◽  
Fei He ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Membrane Protein ◽  
Drug Target ◽  
Drug Targets ◽  
Computational Models ◽  
Drug Repurposing ◽  
Protein Targets ◽  
Target Interaction ◽  
Alternative Understanding

Membrane proteins play crucial physiological roles in vivo and are the major category of drug targets for pharmaceuticals. The research on membrane protein is a significant part in the drug discovery. The biological process is a cycled network, and the membrane protein is a vital hub in the network since most drugs achieve the therapeutic effect via interacting with the membrane protein. In this review, typical membrane protein targets are described, including GPCRs, transporters and ion channels. Also, we conclude network servers and databases that are referring to the drug, drug-target information and their relevant data. Furthermore, we chiefly introduce the development and practice of modern medicines, particularly demonstrating a series of state-of-the-art computational models for the prediction of drug-target interaction containing network-based approach and machine-learningbased approach as well as showing current achievements. Finally, we discuss the prospective orientation of drug repurposing and drug discovery as well as propose some improved framework in bioactivity data, created or improved predicted approaches, alternative understanding approaches of drugs bioactivity and their biological processes.

scholarly journals Defining the Neural Kinome: Strategies and Opportunities for Small Molecule Drug Discovery to Target Neurodegenerative Diseases

2020 ◽  
Author(s):  
Andrea I. Krahn ◽  
Carrow Wells ◽  
David H. Drewry ◽  
Lenore K. Beitel ◽  
Thomas M. Durcan ◽  
...  
Keyword(s):  
Neurodegenerative Diseases ◽  
Small Molecule ◽  
Drug Targets ◽  
Kinase Inhibitors ◽  
National Institutes Of Health ◽  
Target Engagement ◽  
Narrow Spectrum ◽  
Track Record ◽  
Intrinsic Complexity

ABSTRACTKinases are highly tractable drug targets that have reached unparalleled success in fields such as cancer but whose potential has not yet been realized in neuroscience. There are currently 55 approved small molecule kinase-targeting drugs, 48 of which have an anti-cancer indication. The intrinsic complexity linked to central nervous system (CNS) drug development and a lack of validated targets has hindered progress in developing kinase inhibitors for CNS disorders when compared to other therapeutic areas such as oncology. Identification and/or characterization of new kinases as potential drug targets for neurodegenerative diseases will create opportunities for development of CNS drugs in the future. The track record of kinase inhibitors in other disease indications supports the idea that with the best targets identified small molecule kinase modulators will become impactful therapeutics for neurodegenerative diseases.KEY CONCEPTSChemical probe: a high-quality small molecule that is potent, selective, and cell-active that meets the following criteria: (1) in vitro biochemical IC50 < 50 nM, (2) ≥ 30-fold selectivity relative to other kinases in a large assay panel such as DiscoverX scanMAX, and (3) cellular activity or target engagement with an IC50 < 1 μMNarrow spectrum: a selectivity threshold that can be defined as potently inhibiting ∼10% or less of all kinases screenedKinome: all human kinasesKinase chemogenomic set (KCGS): publicly-available curated physical library of narrow spectrum and potent kinase inhibitors for which the SGC-UNC has received permission to share the compounds; subsequent releases will increase kinome-wide coverageIlluminating the Druggable Genome (IDG) program: several interconnected projects currently funded by the National Institutes of Health to provide information on historically understudied members within protein families that have provided drug targets; the three main focus areas are kinases, G-protein coupled receptors, and ion channelsIDG kinase: a kinase that was nominated as dark (understudied) by the National Institutes of Health IDG program (curated list found here: https://druggablegenome.net/IDGProteinList); IDG consortium members generate data and resources to aid in the illumination of the function of these kinasesDK tool: a narrow spectrum inhibitor that exhibits a defined selectivity score (S10(1 μM) < 0.05) and cellular target engagement with an IC50 < 1 μM; S10(1 μM) is a measure of selectivity equal to the percentage of screened kinases biochemically inhibited by >90% at 1 μM

Abstract C085: A new method to determine drug-target residence time of kinase inhibitors in living cells

2019 ◽  
Author(s):  
Takeomi Inoue ◽  
Aki Emi ◽  
James D Vasta ◽  
Matthew B Robers ◽  
Yusuke Kawase
Keyword(s):  
Residence Time ◽  
Drug Target ◽  
Kinase Inhibitors ◽  
Living Cells ◽  
New Method

Lysine-Targeted Inhibitors and Chemoproteomic Probes

2019 ◽  
Vol 88 (1) ◽  
pp. 365-381 ◽  
Author(s):  
Adolfo Cuesta ◽  
Jack Taunton
Keyword(s):  
Drug Target ◽  
Chemical Biology ◽  
Large Set ◽  
Target Engagement ◽  
Covalent Bonds ◽  
Protein Targets ◽  
Ligand Binding Sites ◽  
Covalent Inhibitors ◽  
Enzyme Cofactors ◽  
Reversible Covalent

Covalent inhibitors are widely used in drug discovery and chemical biology. Although covalent inhibitors are frequently designed to react with noncatalytic cysteines, many ligand binding sites lack an accessible cysteine. Here, we review recent advances in the chemical biology of lysine-targeted covalent inhibitors and chemoproteomic probes. By analyzing crystal structures of proteins bound to common metabolites and enzyme cofactors, we identify a large set of mostly unexplored lysines that are potentially targetable with covalent inhibitors. In addition, we describe mass spectrometry–based approaches for determining proteome-wide lysine ligandability and lysine-reactive chemoproteomic probes for assessing drug–target engagement. Finally, we discuss the design of amine-reactive inhibitors that form reversible covalent bonds with their protein targets.

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