Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 377

The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.

Kinase Drug Discovery – What’s Next in the Field?

Open access
Cohen, Philip, Alessi, Dario R.·2013·ACS Chemical Biology

Abstract

Over the past 15 years protein kinases have become the pharmaceutical industry's most important class of drug target in the field of cancer. Some 20 drugs that target kinases have been approved for clinical use over the past decade, and hundreds more are undergoing clinical trials. However, the recent approval of the first protein kinase inhibitors for the treatment of inflammatory diseases, coupled with an enhanced understanding of the signaling networks that control the immune system, suggests that there will be a surge of interest in this area over the next 10 years. In this connection, we discuss opportunities for targeting protein kinases in the MyD88 signaling network for the development of drugs to treat chronic inflammatory and autoimmune diseases. Activating mutations in protein kinases underlie many other diseases and conditions, and we also discuss why the protein kinases SPAK/OSR1 and LRRK2 have recently become interesting targets for the treatment of hypertension and Parkinson's disease, respectively, and the progress that has been made in developing LRRK2 inhibitors. Finally we suggest that more focus on the identification of inhibitors of kinase activation, rather than kinase activity, may pay dividends in identifying exquisitely specific inhibitors of signal transduction cascades, and we also highlight "pseudo-kinases" as an attractive and unexplored area for drug development that merits much more attention in the years to come.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/cb300610s

Cites

53 of 53 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 377

Metadata

Authors
Cohen, P., & Alessi, D. R.
Venue
ACS Chemical Biology
Published
2012-12-31
Volume
8
Issue
1
Pages
96-104
ISSN
  • 1554-8929 (ISSN-L)
  • 1554-8937
OpenAlex
W1966285532
Cited by
377
References
53
FWCI
14.29
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.