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Understanding the antitumor activity of novel hydroxysemicarbazide derivatives as ribonucleotide reductase inhibitors using CoMFA and CoMSIA.
J Med Chem. 2003 Oct 09; 46(21):4419-27.JM

Abstract

Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on a series of Schiff bases of hydroxysemicarbazide analogues using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods with their antitumor activities against L1210 cells. The models were generated using 24 molecules, out of which one molecule was a commercially available ribonucleotide reductase (RR) inhibitor, hydroxyurea (HU), and the predictive ability of the resulting each model was evaluated against a test set of four molecules. Maximum common substructure (MCS)-based method was used for alignment and compared with the known alignment methods. The QSAR models from both methods exhibited considerable correlative and predictive properties. Inclusion of additional descriptor ClogP improved the statistics of CoMFA model significantly. Both methods strongly suggest the necessity of lipophilicity for antitumor activity. CoMFA and CoMSIA methods predicted HU optimally, indicating a similar mechanism of action for the molecules considered for generating the models and HU to inhibit the tumor cells. The analysis of CoMFA contour maps provided insight into the possible modification of the molecules for better activity.

Authors+Show Affiliations

Raichurkar AV
Pharmaceutical Division, Institute of Chemical Technology, University of Mumbai, Matunga, Mumbai-400019, India.
Kulkarni VM
No affiliation info available

MeSH

AlgorithmsAnimalsAntineoplastic AgentsEnzyme InhibitorsLeukemia L1210Models, MolecularRibonucleotide ReductasesSemicarbazidesStructure-Activity Relationship

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

14521406

Citation

Raichurkar, Anand V., and Vithal M. Kulkarni. "Understanding the Antitumor Activity of Novel Hydroxysemicarbazide Derivatives as Ribonucleotide Reductase Inhibitors Using CoMFA and CoMSIA." Journal of Medicinal Chemistry, vol. 46, no. 21, 2003, pp. 4419-27.
Raichurkar AV, Kulkarni VM. Understanding the antitumor activity of novel hydroxysemicarbazide derivatives as ribonucleotide reductase inhibitors using CoMFA and CoMSIA. J Med Chem. 2003;46(21):4419-27.
Raichurkar, A. V., & Kulkarni, V. M. (2003). Understanding the antitumor activity of novel hydroxysemicarbazide derivatives as ribonucleotide reductase inhibitors using CoMFA and CoMSIA. Journal of Medicinal Chemistry, 46(21), 4419-27.
Raichurkar AV, Kulkarni VM. Understanding the Antitumor Activity of Novel Hydroxysemicarbazide Derivatives as Ribonucleotide Reductase Inhibitors Using CoMFA and CoMSIA. J Med Chem. 2003 Oct 9;46(21):4419-27. PubMed PMID: 14521406.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Understanding the antitumor activity of novel hydroxysemicarbazide derivatives as ribonucleotide reductase inhibitors using CoMFA and CoMSIA. AU - Raichurkar,Anand V, AU - Kulkarni,Vithal M, PY - 2003/10/3/pubmed PY - 2003/11/13/medline PY - 2003/10/3/entrez SP - 4419 EP - 27 JF - Journal of medicinal chemistry JO - J Med Chem VL - 46 IS - 21 N2 - Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on a series of Schiff bases of hydroxysemicarbazide analogues using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods with their antitumor activities against L1210 cells. The models were generated using 24 molecules, out of which one molecule was a commercially available ribonucleotide reductase (RR) inhibitor, hydroxyurea (HU), and the predictive ability of the resulting each model was evaluated against a test set of four molecules. Maximum common substructure (MCS)-based method was used for alignment and compared with the known alignment methods. The QSAR models from both methods exhibited considerable correlative and predictive properties. Inclusion of additional descriptor ClogP improved the statistics of CoMFA model significantly. Both methods strongly suggest the necessity of lipophilicity for antitumor activity. CoMFA and CoMSIA methods predicted HU optimally, indicating a similar mechanism of action for the molecules considered for generating the models and HU to inhibit the tumor cells. The analysis of CoMFA contour maps provided insight into the possible modification of the molecules for better activity. SN - 0022-2623 UR - https://www.unboundmedicine.com/medline/citation/14521406/Understanding_the_antitumor_activity_of_novel_hydroxysemicarbazide_derivatives_as_ribonucleotide_reductase_inhibitors_using_CoMFA_and_CoMSIA_ DB - PRIME DP - Unbound Medicine ER -