Affiliation:
1. Bioinformatics Division, ICMR-National Institute of Cancer Prevention and Research, I-7, Sector-39, Noida-201301, India
Abstract
Background:
EGFR is a clinically approved drug target in cancer. The first generation
tyrosine kinase inhibitors targeting L858R mutated EGFR are routinely used to treat non-small cell
lung cancer (NSCLC). However, the presence of a secondary mutation (T790M) tenders these inhibitors
ineffective and thus results in the relapse of the disease.
Objective:
New reversible inhibitors are required, which act against T790M/L858R (TMLR) double
mutants and overcome resistance.
Method:
In the present study, various Fragment based QSAR (G-QSAR) models along with
interaction terms have been studied for amino-pyrimidine derivatives having biological activity
against TMLR mutant enzyme.
Results:
The G-QSAR models developed using partial least squares regression via stepwise forward-
backward variable selection technique showed the best results. The model showed a high
correlation coefficient (r² = 0.86), cross-validation coefficient (q² = 0.81) and predicted correlation
(predicted r² = 0.62), which indicated that the model is robust and predictive. Based on the model,
it was revealed that at R1 position increasing saturated carbon (number of –CH atom connected
with 3 single bonds i.e. SsssCHcount) and retention index (chi3) is desired for the enhancement of
bioactivity. Additionally, at the R2 position, increasing lipophilic character (slogp) and at site R3,
the polarizability of compound need to be increased for better inhibitory activity. We further studied
the contribution of interactions among significant descriptors in enhancing the activity of the
compounds. It revealed that the presence of Sum((R1-SsssCHcount, R2-slogp) and Mult(R1-chi3,
R3-polarizabilityAHC) are the most significantly influencing descriptors. We further compared the
variation in the most and least active compounds which established that retention of the above
properties is essential for imparting significant inhibitory activity to these molecules.
Conclusion:
The study provides site specific information wherein chemical group variation
influences the inhibitory potency of TMLR amino-pyrimidine inhibitors, which can be used for
designing new molecules with the desired activity.
Funder
Department of Health Research, India
Publisher
Bentham Science Publishers Ltd.
Cited by
4 articles.
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