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Dissecting the molecular recognition of dual lapatinib derivatives for EGFR/HER2

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Abstract

Abnormalities in the expression levels of EGFR/HER2 are found in many different types of human cancer; therefore, the design of dual inhibitors of EGFR/HER2 is a recognized anti-cancer strategy. Some lapatinib derivatives have been previously synthesized by modification at the methylsulfonylethylaminomethylfuryl group and biologically evaluated, demonstrating that the 2i compound shows potent inhibitory activity against EGFR/HER2-overexpressing cancer cells. In the present study, we explored the structural and energetic features that guide the molecular recognition of 2i using various EGFR/HER2 states. Molecular dynamics (MD) simulation with an MMPB(GB)SA approach was used to generate the inactive EGFR/HER2–ligand complexes. Our results corroborate that slight modification of lapatinib contributes to an increase in the affinity of the 2i compound for inactive EGFR/HER2 as compared with lapatinib compound, which is in accordance with experimental results. Comparison with previous results reveals that lapatinib and its derivative bind more strongly to the inactive than the intermediate active-inactive HER2 state. Principal component analysis allowed the observation that coupling of 2i to EGFR/HER2 is linked to a reduction in the conformational mobility, which may also contribute to the improvement in affinity observed for this compound as compared with lapatinib.

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Acknowledgements

The work was supported by grants from CONACYT (CB-A1-S-21278) and SIP/IPN (20190133).

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  1. Laboratorio de Modelado Molecular, Bioinformática y Diseño de Fármacos de la Escuela Superior de Medicina, Instituto Politécnico Nacional, Mexico, Plan de San Luis Y Diaz Mirón S/N, Col. Casco de Santo Tomas, CP: 11340, Mexico City, Mexico

    Martiniano Bello, Concepción Guadarrama-García & Rolando Alberto Rodriguez-Fonseca

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  1. Martiniano Bello
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Bello, M., Guadarrama-García, C. & Rodriguez-Fonseca, R.A. Dissecting the molecular recognition of dual lapatinib derivatives for EGFR/HER2. J Comput Aided Mol Des 34, 293–303 (2020). https://doi.org/10.1007/s10822-019-00270-4

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