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Journal ArticleDOI

IC50-to-Ki: a web-based tool for converting IC50 to Ki values for inhibitors of enzyme activity and ligand binding

TL;DR: A new web-server tool estimates Ki values from experimentally determined IC50 values for inhibitors of enzymes and of binding reactions between macromolecules and ligands to enable end users to help gauge the quality of the underlying assumptions used in these calculations.
Abstract: A new web-server tool estimates Ki values from experimentally determined IC50 values for inhibitors of enzymes and of binding reactions between macromolecules (e.g. proteins, polynucleic acids) and ligands. This converter was developed to enable end users to help gauge the quality of the underlying assumptions used in these calculations which depend on the type of mechanism of inhibitor action and the concentrations of the interacting molecular species. Additional calculations are performed for nonclassical, tightly bound inhibitors of enzyme-substrate or of macromolecule-ligand systems in which free, rather than total concentrations of the reacting species are required. Required userdefined input values include the total enzyme (or another target molecule) and substrate (or ligand) concentrations, the Km of the enzyme-substrate (or the Kd of the target-ligand) reaction, and the IC50 value. Assumptions and caveats for these calculations are discussed along with examples taken from the literature. The host database for this converter contains kinetic constants and other data for inhibitors of the proteolytic clostridial neurotoxins (http:// botdb.abcc.ncifcrf.gov/toxin/kiConverter.jsp).

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Citations
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Journal ArticleDOI
TL;DR: A deep learning based model that uses only sequence information of both targets and drugs to predict DT interaction binding affinities is proposed, outperforming the KronRLS algorithm and SimBoost, a state‐of‐the‐art method for DT binding affinity prediction.
Abstract: Motivation The identification of novel drug-target (DT) interactions is a substantial part of the drug discovery process. Most of the computational methods that have been proposed to predict DT interactions have focused on binary classification, where the goal is to determine whether a DT pair interacts or not. However, protein-ligand interactions assume a continuum of binding strength values, also called binding affinity and predicting this value still remains a challenge. The increase in the affinity data available in DT knowledge-bases allows the use of advanced learning techniques such as deep learning architectures in the prediction of binding affinities. In this study, we propose a deep-learning based model that uses only sequence information of both targets and drugs to predict DT interaction binding affinities. The few studies that focus on DT binding affinity prediction use either 3D structures of protein-ligand complexes or 2D features of compounds. One novel approach used in this work is the modeling of protein sequences and compound 1D representations with convolutional neural networks (CNNs). Results The results show that the proposed deep learning based model that uses the 1D representations of targets and drugs is an effective approach for drug target binding affinity prediction. The model in which high-level representations of a drug and a target are constructed via CNNs achieved the best Concordance Index (CI) performance in one of our larger benchmark datasets, outperforming the KronRLS algorithm and SimBoost, a state-of-the-art method for DT binding affinity prediction. Availability and implementation https://github.com/hkmztrk/DeepDTA. Supplementary information Supplementary data are available at Bioinformatics online.

634 citations


Cites background or methods from "IC50-to-Ki: a web-based tool for co..."

  • ...IC50 depends on the concentration of the target and ligand (Cer et al., 2009) and low IC50 values signal strong binding....

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  • ...lly expressed in measures such as dissociation constant (Kd), inhibition constant (Ki), or the half maximal inhibitory concentration (IC50). IC50 depends on the concentration of the target and ligand [8] and low IC50 values signal strong binding. Similarly, low Ki values indicate high binding affinity. Kd and Ki values are usually represented in terms of pKd or pKi, the negative logarithm of the diss...

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  • ...s we performed a search over [16, 32, 64, 128, 512]. We then narrowed the search range around the best performing parameter (e.g. if 16 was chosen as the best parameter, then our range was updated as [4, 8, 16, 20] etc.). As explained in the Proposed Model subsection, the second convolution layer was set to contain twice the number of filters of the first layer, and the third one was set to contain three times ...

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  • ... that were used for the compound CNN-block and protein CNN-block. Table 2. Parameter settings for CNN based DeepDTA model Parameters Range Number of filters 32*1; 32*2; 32*3 Filter length (compounds) [4,6,8] Filter length (proteins) [4,8,12] epoch 100 hidden neurons 1024; 1024; 512 batch size 256 dropout 0.1 optimizer Adam learning rate (lr) 0.001 In order to provide a more robust performance measure, we...

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Journal ArticleDOI
07 Apr 2016-Nature
TL;DR: This study provides a mechanistic explanation for the selective efficacy of lenalidomide in del(5q) MDS therapy and predicts that high-affinity protein–protein interactions induced by small molecules will provide opportunities for drug development, particularly for targeted protein degradation.
Abstract: Thalidomide and its derivatives, lenalidomide and pomalidomide, are immune modulatory drugs (IMiDs) used in the treatment of haematologic malignancies. IMiDs bind CRBN, the substrate receptor of the CUL4-RBX1-DDB1-CRBN (also known as CRL4(CRBN)) E3 ubiquitin ligase, and inhibit ubiquitination of endogenous CRL4(CRBN) substrates. Unexpectedly, IMiDs also repurpose the ligase to target new proteins for degradation. Lenalidomide induces degradation of the lymphoid transcription factors Ikaros and Aiolos (also known as IKZF1 and IKZF3), and casein kinase 1α (CK1α), which contributes to its clinical efficacy in the treatment of multiple myeloma and 5q-deletion associated myelodysplastic syndrome (del(5q) MDS), respectively. How lenalidomide alters the specificity of the ligase to degrade these proteins remains elusive. Here we present the 2.45 A crystal structure of DDB1-CRBN bound to lenalidomide and CK1α. CRBN and lenalidomide jointly provide the binding interface for a CK1α β-hairpin-loop located in the kinase N-lobe. We show that CK1α binding to CRL4(CRBN) is strictly dependent on the presence of an IMiD. Binding of IKZF1 to CRBN similarly requires the compound and both, IKZF1 and CK1α, use a related binding mode. Our study provides a mechanistic explanation for the selective efficacy of lenalidomide in del(5q) MDS therapy. We anticipate that high-affinity protein-protein interactions induced by small molecules will provide opportunities for drug development, particularly for targeted protein degradation.

359 citations

Journal ArticleDOI
TL;DR: SD-36 achieves complete and long-lasting tumor regression in multiple xenograft mouse models at well-tolerated dose schedules and is a promising cancer therapeutic strategy.

311 citations

Journal ArticleDOI
TL;DR: In addition to its continued utilization in high-throughput screening, FP has expanded into new disease and target areas and has been marked by increased use of labeled small molecule ligands for receptor-binding studies.
Abstract: Importance of the field: Fluorescence polarization (FP) is a homogeneous method that allows rapid and quantitative analysis of diverse molecular interactions and enzyme activities. This technique has been widely utilized in clinical and biomedical settings, including the diagnosis of certain diseases and monitoring therapeutic drug levels in body fluids. Recent developments in the field have been symbolized by the facile adoption of FP in high-throughput screening and small molecule drug discovery of an increasing range of target classes. Areas covered in this review: The article provides a brief overview of the theoretical foundation of FP, followed by updates on recent advancements in its application for various drug target classes, including GPCRs, enzymes and protein–protein interactions. The strengths and weaknesses of this method, practical considerations in assay design, novel applications and future directions are also discussed. What the reader will gain: The reader is informed of the most recent...

301 citations


Cites methods from "IC50-to-Ki: a web-based tool for co..."

  • ...Recently, two groups have incorporated derivations of Ki/Kd from IC50 data, including FP results, into web-based algorithm tools [16-19]....

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Journal ArticleDOI
02 Nov 2018-Science
TL;DR: The human ZF “degrome” is defined in the context of thalidomide, lenalidomid, and pomalidomides to characterize the ZF-drug-CRBN interaction structurally and functionally and determine whether different thalidmide analogs degrade distinct ZFs.
Abstract: The small molecules thalidomide, lenalidomide, and pomalidomide induce the ubiquitination and proteasomal degradation of the transcription factors Ikaros (IKZF1) and Aiolos (IKZF3) by recruiting a Cys2-His2 (C2H2) zinc finger domain to Cereblon (CRBN), the substrate receptor of the CRL4CRBN E3 ubiquitin ligase. We screened the human C2H2 zinc finger proteome for degradation in the presence of thalidomide analogs, identifying 11 zinc finger degrons. Structural and functional characterization of the C2H2 zinc finger degrons demonstrates how diverse zinc finger domains bind the permissive drug-CRBN interface. Computational zinc finger docking and biochemical analysis predict that more than 150 zinc fingers bind the drug-CRBN complex in vitro, and we show that selective zinc finger degradation can be achieved through compound modifications. Our results provide a rationale for therapeutically targeting transcription factors that were previously considered undruggable.

278 citations

References
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Journal ArticleDOI
TL;DR: The analysis described shows K I does not equal I 50 when competitive inhibition kinetics apply; however, K I is equal to I 50 under conditions of either noncompetitive or uncompetitive kinetics.

12,583 citations


"IC50-to-Ki: a web-based tool for co..." refers background in this paper

  • ...protein)-binding studies, the free concentrations also become sufficiently important to require modifications of these equations (1, 2), and (9)....

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Journal ArticleDOI
TL;DR: The development of a homogeneous high-throughput assay based on fluorescence polarization for measuring the binding affinities of small-molecule inhibitors to the BIR3 domain of XIAP and results obtained indicated that the FP-based competitive binding assay performs correctly as designed.

507 citations


"IC50-to-Ki: a web-based tool for co..." refers background or methods in this paper

  • ...protein)-binding studies, the free concentrations also become sufficiently important to require modifications of these equations (1, 2), and (9)....

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  • ...The website cited in (9) served as an initial design template for our IC50-to-Ki converter....

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  • ...(3), (6) and (9) whereas we derived Equation (5) for this study....

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Journal ArticleDOI
TL;DR: D dose-response measurements generate a linear plot of inhibitor concentration divided by degree of inhibition against velocity without inhibitor divided by velocity with inhibitor, which indicates that the inhibitors of oxidative phosphorylation, rutamycin and bongkrekic acid, are tightly bound to rat liver mitochondria.
Abstract: When an enzyme exhibits a high affinity for an inhibitor, the steady-state analysis of the mechanism is complicated by the non-linearity of normal dose–response plots or of reciprocal replots. It is shown here that dose–response measurements generate a linear plot of inhibitor concentration divided by degree of inhibition against velocity without inhibitor divided by velocity with inhibitor; the concentration of enzyme may be derived from the extrapolated intercept of such plots, and the mechanism of inhibition from replots of the variation of the slope with substrate concentration. The limiting cases where virtually all inhibitor molecules are bound or virtually all are free are described, together with the situation when a significant proportion of the substrate becomes bound. This type of analysis indicates that the inhibitors of oxidative phosphorylation, rutamycin and bongkrekic acid, are tightly bound to rat liver mitochondria.

486 citations

Journal ArticleDOI
TL;DR: The web service via a SOAP (Simple Object Access Protocol) interface for access to the BRENDA data has been further enhanced and a new search option provides the access to protein-specific data.
Abstract: The BRENDA (BRaunschweig ENzyme DAtabase) (http://www.brenda-enzymes.org) represents the largest freely available information system containing a huge amount of biochemical and molecular information on all classified enzymes as well as software tools for querying the database and calculating molecular properties. The database covers information on classification and nomenclature, reaction and specificity, functional parameters, occurrence, enzyme structure and stability, mutants and enzyme engineering, preparation and isolation, the application of enzymes, and ligand-related data. The data in BRENDA are manually curated from more than 79 000 primary literature references. Each entry is clearly linked to a literature reference, the origin organism and, where available, to the protein sequence of the enzyme protein. A new search option provides the access to protein-specific data. FRENDA (Full Reference ENzyme DAta) and AMENDA (Automatic Mining of ENzyme DAta) are additional databases created by continuously improved text-mining procedures. These databases ought to provide a complete survey on enzyme data of the literature collection of PubMed. The web service via a SOAP (Simple Object Access Protocol) interface for access to the BRENDA data has been further enhanced.

455 citations


"IC50-to-Ki: a web-based tool for co..." refers methods in this paper

  • ...Experimental data (IC50 values) and accompanying assay information were manually extracted from primary literature results and other relevant databases: JCVIPathema-Clostridium (13), Brenda (14) and Protein Data Bank (15)....

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Journal ArticleDOI
TL;DR: The higher the affinity of the fluorescent ligand, the wider the range of inhibitor potency that can be resolved, and an approximate estimate for the low end of inhibitor K(i) values thatCan be resolved is the K(d) value of theorescent ligand.
Abstract: For the development of fluorescence polarization (FP) competition assays, there is a widespread belief that tight-binding fluorescent ligands should be avoided to identify inhibitors of low or intermediate potency in the screening of small-molecule compound libraries. It is demonstrated herein that this statement is a misconception; in fact, the higher the affinity of the fluorescent ligand, the wider the range of inhibitor potency that can be resolved. An approximate estimate for the low end of inhibitor Ki values that can be resolved is the Kd value of the fluorescent ligand. Because FP competition assays are typically conducted under nonstoichiometric titration conditions, it is suggested that a fluorescent ligand of highest affinity that also has an adequate quantum yield to satisfy such conditions be selected. (Journal of Biomolecular Screening 2003:34-38)

177 citations