scholarly journals Crowdsourced mapping of unexplored target space of kinase inhibitors

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Anna Cichońska ◽  
Balaguru Ravikumar ◽  
Robert J. Allaway ◽  
Fangping Wan ◽  
Sungjoon Park ◽  
...  

AbstractDespite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound–kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome.

Author(s):  
Anna Cichonska ◽  
Balaguru Ravikumar ◽  
Robert J Allaway ◽  
Sungjoon Park ◽  
Fangping Wan ◽  
...  

AbstractDespite decades of intensive search for compounds that modulate the activity of particular targets, there are currently small-molecules available only for a small proportion of the human proteome. Effective approaches are therefore required to map the massive space of unexplored compound-target interactions for novel and potent activities. Here, we carried out a crowdsourced benchmarking of predictive models for kinase inhibitor potencies across multiple kinase families using unpublished bioactivity data. The top-performing predictions were based on kernel learning, gradient boosting and deep learning, and their ensemble resulted in predictive accuracy exceeding that of kinase activity assays. We then made new experiments based on the model predictions, which further improved the accuracy of experimental mapping efforts and identified unexpected potencies even for under-studied kinases. The open-source algorithms together with the novel bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking new prediction algorithms and for extending the druggable kinome.


Marine Drugs ◽  
2019 ◽  
Vol 17 (2) ◽  
pp. 81 ◽  
Author(s):  
Fabien Plisson ◽  
Andrew Piggott

The recent success of small-molecule kinase inhibitors as anticancer drugs has generated significant interest in their application to other clinical areas, such as disorders of the central nervous system (CNS). However, most kinase inhibitor drug candidates investigated to date have been ineffective at treating CNS disorders, mainly due to poor blood–brain barrier (BBB) permeability. It is, therefore, imperative to evaluate new chemical entities for both kinase inhibition and BBB permeability. Over the last 35 years, marine biodiscovery has yielded 471 natural products reported as kinase inhibitors, yet very few have been evaluated for BBB permeability. In this study, we revisited these marine natural products and predicted their ability to cross the BBB by applying freely available open-source chemoinformatics and machine learning algorithms to a training set of 332 previously reported CNS-penetrant small molecules. We evaluated several regression and classification models, and found that our optimised classifiers (random forest, gradient boosting, and logistic regression) outperformed other models, with overall cross-validated model accuracies of 80%–82% and 78%–80% on external testing. All 3 binary classifiers predicted 13 marine-derived kinase inhibitors with appropriate physicochemical characteristics for BBB permeability.


2019 ◽  
Vol 4 (1-2) ◽  
pp. 41-45 ◽  
Author(s):  
Takeo Koshida ◽  
Sylvia Wu ◽  
Hitoshi Suzuki ◽  
Rimda Wanchoo ◽  
Vanesa Bijol ◽  
...  

Dasatinib is the second-generation tyrosine kinase inhibitor used in the treatment of chronic myeloid leukemia. Proteinuria has been reported with this agent. We describe two kidney biopsy–proven cases of dasatinib-induced thrombotic microangiopathy that responded to stoppage of dasatinib and using an alternate tyrosine kinase inhibitor. Certain specific tyrosine kinase inhibitors lead to endothelial injury and renal-limited thrombotic microangiopathy. Hematologists and nephrologists need to be familiar with this off-target effect of dasatinib.


2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Abdullahi Bello Umar ◽  
Adamu Uzairu ◽  
Gideon Adamu Shallangwa ◽  
Sani Uba

Abstract Background V600E-BRAF is a major protein target involved in various types of human cancers. However, the acquired resistance of the V600E-BRAF kinase to the vemurafenib and the side effects of other identified drugs initiate the search for efficient inhibitors. In the current paper, virtual docking screening combined with drug likeness and ADMET properties predictions were jointly applied to evaluate potent 2-(1H-imidazol-2-yl) pyridines as V600E-BRAF kinase inhibitors. Results Most of the studied compounds showed better docking scores and favorable interactions with theiV600E-BRAF target. Among the screened compounds, the two most potent (14 and 30) with good rerank scores (−124.079 and − 122.290) emerged as the most effective, and potent V600E-BRAF kinase inhibitors which performed better than vemurafenib (−116.174), an approved V600E-BRAF kinase inhibitor. Thus, the docking studies exhibited that these compounds have shown competing inhibition of V600E-BRAF kinase with vemurafenib at the active site and revealed better pharmacological properties based on Lipinski’s and Veber’s drug-likeness rules for oral bioavailability and ADMET properties. Conclusion The docking result, drug-likeness rules, and ADMET parameters identified compounds (14 and 30) as the best hits against V600E-BRAF kinase with better pharmacological properties. This suggests that these compounds may be developed as potent V600E-BRAF inhibitors.


2021 ◽  
Vol 10 (6) ◽  
pp. 234
Author(s):  
Ishmael Mugari ◽  
Emeka E. Obioha

There has been a significant focus on predictive policing systems, as law enforcement agents embrace modern technology to forecast criminal activity. Most developed nations have implemented predictive policing, albeit with mixed reactions over its effectiveness. Whilst at its inception, predictive policing involved simple heuristics and algorithms, it has increased in sophistication in the ever-changing technological environment. This paper, which is based on a literature survey, examines predictive policing over the last decade (2010 to 2020). The paper examines how various nations have implemented predictive policing and also documents the impediments to predictive policing. The paper reveals that despite the adoption of predictive software applications such as PredPol, Risk Terrain Modelling, HunchLab, PreMap, PRECOBS, Crime Anticipation System, and Azevea, there are several impediments that have militated against the effectiveness of predictive policing, and these include low predictive accuracy, limited scope of crimes that can be predicted, high cost of predictive policing software, flawed data input, and the biased nature of some predictive software applications. Despite these challenges, the paper reveals that there is consensus by the majority of the researchers on the importance of predictive algorithms on the policing landscape.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hu Lei ◽  
Han-Zhang Xu ◽  
Hui-Zhuang Shan ◽  
Meng Liu ◽  
Ying Lu ◽  
...  

AbstractIdentifying novel drug targets to overcome resistance to tyrosine kinase inhibitors (TKIs) and eradicating leukemia stem/progenitor cells are required for the treatment of chronic myelogenous leukemia (CML). Here, we show that ubiquitin-specific peptidase 47 (USP47) is a potential target to overcome TKI resistance. Functional analysis shows that USP47 knockdown represses proliferation of CML cells sensitive or resistant to imatinib in vitro and in vivo. The knockout of Usp47 significantly inhibits BCR-ABL and BCR-ABLT315I-induced CML in mice with the reduction of Lin−Sca1+c-Kit+ CML stem/progenitor cells. Mechanistic studies show that stabilizing Y-box binding protein 1 contributes to USP47-mediated DNA damage repair in CML cells. Inhibiting USP47 by P22077 exerts cytotoxicity to CML cells with or without TKI resistance in vitro and in vivo. Moreover, P22077 eliminates leukemia stem/progenitor cells in CML mice. Together, targeting USP47 is a promising strategy to overcome TKI resistance and eradicate leukemia stem/progenitor cells in CML.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 35-36
Author(s):  
Mario Tiribelli ◽  
Roberto Latagliata ◽  
Massimo Breccia ◽  
Isabella Capodanno ◽  
Maria Cristina Miggiano ◽  
...  

Introduction : therapy of chronic phase (CP) chronic myeloid leukemia (CML) is based on tyrosine kinase inhibitors (TKIs) in virtually all patients. Three TKIs are approved for first-line therapy in Italy: imatinib and two second-generation (2G) TKIs, dasatinib and nilotinib. Choice of the front-line TKI is based on a combined evaluation of patient's and disease characteristics, age, risk, comorbidities and concomitant medications. Treating physician's preference and, in some cases, economic considerations, particularly after the advent of generic imatinib, may play a role in TKI selection. However, to date, few data are available on TKI use in a whole nation and on the possible drivers of treatment choice. Aim of the present work was to analyse the use of front-line TKI therapy in a large, unselected cohort of Italian CP-CML patients, correlating patient's features to drug choice. Methods: in the framework of the national Campus CML program, we retrospectively evaluated 1422 patients with CP-CML diagnosed from 2012 and 2019 in 21 haematologic Centres, mostly in academic and/or tertiary hospitals, widespread through the entire Italian territory and treated frontline with imatinib, dasatinib or nilotinib. Results: median age at diagnosis was 59.9 years [interquartile range (IQR) 47.1 - 71.7], with 317 (22.3%) patients under 45 years, 552 (38.8%) between 45 and 65 years and 553 (38.9%) older than 65 years; 821 (57.7%) patients were males. Among 1364 evaluable patients, CML risk according to Sokal score was low in 540 (39.6%), intermediate in 610 (44.7%) and high in 214 (15.7%) patients respectively; the number at low, intermediate or high risk according to the novel ELTS score among 1325 evaluable patients was 759 (57.3%), 402 (30.3%) and 164 (12.4%) respectively. Considering comorbidities, 1003 (70.6%) patients had at least one active disease at the time of CML diagnosis, the most common being hypertension (n=547, 38.5%), previous neoplasms (n=185, 13.0%), diabetes (n=150, 10.6%), chronic bronchopulmonary diseases (n=114, 8.0%), acute myocardial infarction (n=95, 6.7%), previous stroke (n=36, 2.5%) and other vascular diseases (n=98, 6.9%). Among 1335 evaluable patients, 813 (60.9%) were taking at least one concomitant medication, with 280 (21.0%) taking 3-5 drugs and 140 (10.5%) taking 6+ drugs at time of TKI start. As to the frontline therapy, 794 (55.8%) received imatinib and 628 (44.2%) were treated with 2G-TKIs, (226 dasatinib and 402 nilotinib) respectively. According to age, 2G-TKIs were chosen for majority of patients aged <45 (69.1%) while imatinib was used in 76.9% of patients over 65 (p<0.001). There was a predominance of imatinib use across all Sokal (51.1% in low, 61.3% in intermediate and 51.4% in high) and ELTS (50.3% in low, 60.4% in intermediate and 66.5%) risk categories. We observed a prevalent use of 2G-TKIs in patients presenting with higher WBC counts (55.1% if WBC >100,000/mm3 vs 38.2% if WBC <100,000/mm3; p<0.001), lower Hb (53.8% if Hb <10 g/dl vs 41.9 if Hb >10 g/dl; p=0.001) and bigger spleen (65.1% if spleen >5 cm vs 44.8% if spleen 1-5 cm vs 37.3% if spleen not palpable; p<0.001). There was a decreasing use of 2G-TKIs with higher number of concomitant drugs: 64.4% for 0, 47.7% for 1-2, 27.0% for 3-5 and 13.6% for >5 drugs, respectively (p<0.001). Concordantly, there was a significant higher use of imatinib in patients with hypertension (69.8%), diabetes (70.0%), COPD (73.7%), previous neoplasms (73.0%), AMI (86.3%) or stroke (97.2%) history (p<0.001 for all conditions). Lastly, we observed a wider use of imatinib (61.1%) in patients diagnosed in years 2018-19, compared to those of the period 2012-17 (53.7%; p=0.01). In multivariable analysis, factors correlated with imatinib use were age > 45 years, intermediate or high Sokal risk, presence of some comorbidities (2nd neoplasia and stroke) and number of concomitant medications. Conclusions: preliminary results of this observational study on almost 1500 patients show that around 55% of newly diagnosed Italian CP-CML patients receive imatinib as front-line therapy, and that the use of 2G-TKI is prevalent in the younger patients and in those with no concomitant clinical conditions. The counterintuitive finding of imatinib prevalence as frontline treatment in high risk patients might be explained by the older age of these patients. Introduction of the generic formulation in 2018 seems to have fostered the use of imatinib. Figure Disclosures Breccia: Novartis: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Abbvie: Consultancy; Bristol-Myers Squibb/Celgene: Consultancy, Honoraria. Cavazzini:Pfize: Honoraria; Incyte: Honoraria; Novartis: Honoraria. Saglio:Bristol-Myers Squibb: Research Funding; Pfizer: Research Funding; Incyte: Research Funding; Novartis: Research Funding; Ariad: Research Funding; Roche: Research Funding.


2021 ◽  
Author(s):  
Alessandro Rizzo ◽  
Veronica Mollica ◽  
Matteo Santoni ◽  
Matteo Rosellini ◽  
Andrea Marchetti ◽  
...  

Aim: Few data are available regarding the safety profile of immunotherapy–tyrosine kinase inhibitor (IO-TKI) combinations in metastatic renal cell carcinoma. The authors investigated all-grade and grade 3–4 (G3–4) adverse events in trials comparing IO-TKI combinations with sunitinib monotherapy. Methods: The relative risks of several all-grade and G3–4 adverse events were analyzed. Results: Relative risks were similar between patients receiving IO-TKI combinations versus sunitinib monotherapy. However, the use of IO-TKI combinations was associated with a higher risk of all-grade and G3–4 diarrhea, all-grade hypothyroidism, G3–4 decreased appetite, all-grade and G3–4 aspartate transaminase increase and all-grade and G3–4 alanine transaminase increase. Conclusion: The results of the authors' meta-analysis suggest that risks of treatment-related adverse events should be carefully considered when choosing IO-TKI combinations in metastatic renal cell carcinoma patients.


Blood ◽  
2005 ◽  
Vol 106 (12) ◽  
pp. 3958-3961 ◽  
Author(s):  
Jörg Cammenga ◽  
Stefan Horn ◽  
Ulla Bergholz ◽  
Gunhild Sommer ◽  
Peter Besmer ◽  
...  

Multiple genetic alterations are required to induce acute myelogenous leukemia (AML). Mutations in the extracellular domain of the KIT receptor are almost exclusively found in patients with AML carrying translocations or inversions affecting members of the core binding factor (CBF) gene family and correlate with a high risk of relapse. We demonstrate that these complex insertion and deletion mutations lead to constitutive activation of the KIT receptor, which induces factor-independent growth of interleukin-3 (IL-3)–dependent cells. Mutation of the evolutionary conserved amino acid D419 within the extracellular domain was sufficient to constitutively activate the KIT receptor, although high expression levels were required. Dose-dependent growth inhibition and apoptosis were observed using either the protein tyrosine kinase inhibitor imatinib mesylate (STI571, Gleevec) or by blocking the phosphoinositide-3-kinase (PI3K)–AKT pathway. Our data show that the addition of kinase inhibitors to conventional chemotherapy might be a new therapeutic option for CBF-AML expressing mutant KIT.


2005 ◽  
Vol 13 (15) ◽  
pp. 4704-4712 ◽  
Author(s):  
Ram Thaimattam ◽  
Pankaj R. Daga ◽  
Rahul Banerjee ◽  
Javed Iqbal

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