PubMed Health⌕ Search

PubMed · 16185153

Second-generation kinase inhibitors.

Abstract

An increasing number of kinase inhibitor candidates are entering clinical development, representing an important change in the pharmaceutical industry; notably, the development of small-molecule kinase inhibitors for signal transduction therapies. Today, kinase inhibitors garner substantial attention in cancer research. Over the last few years, three distinct small-molecule kinase inhibitors reached the market for treatment of chronic myeloid leukaemia, gastrointestinal stromal tumours, and non-small cell lung cancers. These three drugs, imatinib, gefitinib and erlotinib, act on a distinct subset of dysregulated, and often cancer-relevant kinases. Imatinib, gefitinib and erlotinib are considered the front-runners of targeted kinase inhibitor drugs. The entire research field gains tremendous insights through the ongoing research and clinical trials with these three drugs and with fast following first-generation kinase inhibitors, many of which are in different phases of clinical development. In addition, novel chemogenomic and chemoproteomic technologies are emanating from the current kinase research area, focussing efforts on the generation of spectrum-selective inhibitors for anticancer therapies as opposed to the monospecific inhibitors for the remaining therapeutic areas.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Bert M Klebl, Gerhard Müller. 2005. Second-generation kinase inhibitors.. https://doi.org/10.1517/14728222.9.5.975

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Strategies to design pyrazolyl urea derivatives for p38 kinase inhibition: a molecular modeling study.

The p38 protein kinase is a serine-threonine mitogen activated protein kinase, which plays an important role in inflammation and arthritis. A combined study of 3D-QSAR and molecular docking has been undertaken to explore the structural insights of pyrazolyl urea p38 kinase inhibitors. The 3D-QSAR studies involved comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA). The best CoMFA model was derived from the atom fit alignment with a cross-validated r (2 )(q (2)) value of 0.516 and conventional r (2) of 0.950, while the best CoMSIA model yielded a q (2) of 0.455 and r (2) of 0.979 (39 molecules in training set, 9 molecules in test set). The CoMFA and CoMSIA contour maps generated from these models provided inklings about the influence of interactive molecular fields in the space on the activity. GOLD, Sybyl (FlexX) and AutoDock docking protocols were exercised to explore the protein-inhibitor interactions. The integration of 3D-QSAR and molecular docking has proffered essential structural features of pyrazolyl urea inhibitors and also strategies to design new potent analogues with enhanced activity.

Drug Design↗