Article: P56lck kinase inhibitor studies: a 3D QSAR approach towards designing new drugs from flavonoid derivatives Journal: International Journal of Computational Biology and Drug Design (IJCBDD) 2014 Vol.7 No.2/3 pp.278 - 294 Abstract: Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on 3D-QSAR (3D-quantitative structure activity relationship) studies were carried out on 97 flavonoid derivatives as potent P56lck protein tyrosine kinase inhibitors. The best prediction was obtained with CoMFA standard model (q² = 0.838, r² = 0.948) using steric, electrostatic along with CoMSIA standard model (q² = 0.714, r² = 0.921) using steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields. Of the 97 molecules a training set of 76 compounds and the predictive ability of the QSAR model were assessed employing a test set of 21 compounds. The resulting CoMFA and CoMSIA contour maps were used to identify the structural features relevant to the biological activity in this series of flavonoid derivatives, based upon which we identified and designed 10 novel molecules that showed superior inhibitory activity against P56lck protein which shed new light on effective therapeutic agents against these classes of enzymes. Inderscience Publishers - linking academia, business and industry through research

Title: P56^lck kinase inhibitor studies: a 3D QSAR approach towards designing new drugs from flavonoid derivatives

Authors: Shravan Kumar Gunda; Sandeep Kumar Mulukala Narasimha; Mahmood Shaik

Addresses: Bioinformatics Division, Osmania University, Hyderabad 500007, Andhra Pradesh, India ' Bioinformatics Division, Osmania University, Hyderabad 500007, Andhra Pradesh, India ' Bioinformatics Division, Osmania University, Hyderabad 500007, Andhra Pradesh, India

Abstract: Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on 3D-QSAR (3D-quantitative structure activity relationship) studies were carried out on 97 flavonoid derivatives as potent P56^lck protein tyrosine kinase inhibitors. The best prediction was obtained with CoMFA standard model (q² = 0.838, r² = 0.948) using steric, electrostatic along with CoMSIA standard model (q² = 0.714, r² = 0.921) using steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields. Of the 97 molecules a training set of 76 compounds and the predictive ability of the QSAR model were assessed employing a test set of 21 compounds. The resulting CoMFA and CoMSIA contour maps were used to identify the structural features relevant to the biological activity in this series of flavonoid derivatives, based upon which we identified and designed 10 novel molecules that showed superior inhibitory activity against P56^lck protein which shed new light on effective therapeutic agents against these classes of enzymes.

Keywords: P56^lck; protein tyrosine kinase; PTK inhibitors; comparative molecular field analysis; CoMFA; comparative molecular similarity indices analysis; CoMSIA; molecular docking; drug design; 3D-QSAR; contour maps; partial least squares; PLS; novel drugs; kinase inhibitors; flavonoid derivatives.

DOI: 10.1504/IJCBDD.2014.061648

International Journal of Computational Biology and Drug Design, 2014 Vol.7 No.2/3, pp.278 - 294

Received: 23 Jul 2013
Accepted: 26 Oct 2013
Published online: 21 Oct 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article

Title: P56lck kinase inhibitor studies: a 3D QSAR approach towards designing new drugs from flavonoid derivatives

Keep up-to-date

Title: P56^lck kinase inhibitor studies: a 3D QSAR approach towards designing new drugs from flavonoid derivatives