Folate receptor α (FRα) is a cell surface, glycophosphatidylinositol (GPI)-anchored protein with a high affinity for its ligand partner, which is highly expressed in malignant cells and has been selected as a therapeutic target and marker for the diagnosis of cancer. No direct structural information is available from either X-ray diffraction or NMR on the post-translational structure of this disulfide-rich protein. Three-dimensional models of the FRα structure have been derived with the recent homology modeling packages, using the crystal structure of the riboflavin-binding protein (RfBP) as a template. Molecular dynamics trajectories have been exploited allowing successfully the formation of a full disulfide bridge network, which was expected based on the similarities between FRα and RfBP. After the selection of the best model, a folic acid molecule was docked “in silico” onto the putative binding site and its binding mode was compared with that of vintafolide, a much larger molecule designed as a chemotherapy agent targeting specifically FRα. In both cases, a 40 ns molecular dynamics trajectory was calculated, providing suggestions regarding the key structural determinants driving the affinity and specificity of FRα for folic acid with respect to other folate homologues. Moreover, some other crucial experimental results related to the structure of the receptor are discussed, such as the expected location/accessibility of known immune epitopes, the set of N-linked glycosylation sites and the effect of point mutations on the impairment of folate binding. Our results may provide useful insights for studies related to folate-targeted drug delivery or cancer therapies involving folate uptake.

Della Longa, S., Arcovito, A., Structural and functional insights on folate receptor α (FRα) by homology modeling, ligand docking and molecular dynamics, <<JOURNAL OF MOLECULAR GRAPHICS & MODELLING>>, 2013; 44 (N/A): 197-207. [doi:10.1016/j.jmgm.2013.05.012] [http://hdl.handle.net/10807/44909]

Structural and functional insights on folate receptor α (FRα) by homology modeling, ligand docking and molecular dynamics

Arcovito, Alessandro
2013

Abstract

Folate receptor α (FRα) is a cell surface, glycophosphatidylinositol (GPI)-anchored protein with a high affinity for its ligand partner, which is highly expressed in malignant cells and has been selected as a therapeutic target and marker for the diagnosis of cancer. No direct structural information is available from either X-ray diffraction or NMR on the post-translational structure of this disulfide-rich protein. Three-dimensional models of the FRα structure have been derived with the recent homology modeling packages, using the crystal structure of the riboflavin-binding protein (RfBP) as a template. Molecular dynamics trajectories have been exploited allowing successfully the formation of a full disulfide bridge network, which was expected based on the similarities between FRα and RfBP. After the selection of the best model, a folic acid molecule was docked “in silico” onto the putative binding site and its binding mode was compared with that of vintafolide, a much larger molecule designed as a chemotherapy agent targeting specifically FRα. In both cases, a 40 ns molecular dynamics trajectory was calculated, providing suggestions regarding the key structural determinants driving the affinity and specificity of FRα for folic acid with respect to other folate homologues. Moreover, some other crucial experimental results related to the structure of the receptor are discussed, such as the expected location/accessibility of known immune epitopes, the set of N-linked glycosylation sites and the effect of point mutations on the impairment of folate binding. Our results may provide useful insights for studies related to folate-targeted drug delivery or cancer therapies involving folate uptake.
2013
Inglese
Della Longa, S., Arcovito, A., Structural and functional insights on folate receptor α (FRα) by homology modeling, ligand docking and molecular dynamics, <<JOURNAL OF MOLECULAR GRAPHICS & MODELLING>>, 2013; 44 (N/A): 197-207. [doi:10.1016/j.jmgm.2013.05.012] [http://hdl.handle.net/10807/44909]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/44909
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