All-Atom Structural Models for Complexes of Insulin-Like Growth Factors IGF1 and IGF2 with Their Cognate Receptor
Department of Chemical and Biological Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA. Journal of Molecular Biology
(Impact Factor: 4.33).
07/2010; 400(3):645-58. DOI: 10.1016/j.jmb.2010.05.025
Type 1 insulin-like growth factor receptor (IGF1R) is a membrane-spanning glycoprotein of the insulin receptor family that has been implicated in a variety of cancers. The key questions related to molecular mechanisms governing ligand recognition by IGF1R remain unanswered, partly due to the lack of testable structural models of apo or ligand-bound receptor complexes. Using a homology model of the IGF1R ectodomain IGF1RDeltabeta, we present the first experimentally consistent all-atom structural models of IGF1/IGF1RDeltabeta and IGF2/IGF1RDeltabeta complexes. Our explicit-solvent molecular dynamics (MD) simulation of apo-IGF1RDeltabeta shows that it displays asymmetric flexibility mechanisms that result in one of two binding pockets accessible to growth factors IGF1 and IGF2, as demonstrated via an MD-assisted Monte Carlo docking procedure. Our MD-generated ensemble of structures of apo and IGF1-bound IGF1RDeltabeta agrees reasonably well with published small-angle X-ray scattering data. We observe simultaneous contacts of each growth factor with sites 1 and 2 of IGF1R, suggesting cross-linking of receptor subunits. Our models provide direct evidence in favor of suggested electrostatic complementarity between the C-domain (IGF1) and the cysteine-rich domain (IGF1R). Our IGF1/IGF1RDeltabeta model provides structural bases for the observation that a single IGF1 molecule binds to IGF1RDeltabeta at low concentrations in small-angle X-ray scattering studies. We also suggest new possible structural bases for differences in the affinities of insulin, IGF1, and IGF2 for their noncognate receptors.
Available from: PubMed Central
- "Although IGF1 and IGF2 share similarity in structure to insulin (Rinderknecht and Humbel 1976), they bind distinct receptors. Insulin, IGF1 and IGF2 bind the insulin receptor, IGF1 receptor (IGF1R) and IGF2 receptor (IGF2R), respectively (Vashisth and Abrams 2010; Hawkes and Kar 2004). "
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ABSTRACT: Insulin signaling plays a critical role in coupling external changes to animal physiology and behavior. Despite remarkable conservation in the insulin signaling pathway components across species, divergence in the mechanism and function of the signal is evident. Focusing on recent findings from C. elegans, D. melanogaster and mammals, we discuss the role of insulin signaling in regulating adult neuronal function and behavior. In particular, we describe the transcription-dependent and transcription-independent aspects of insulin signaling across these three species. Interestingly, we find evidence of diverse mechanisms underlying complex networks of peptide action in modulating nervous system function.
Invertebrate Neuroscience 01/2014; 14(2). DOI:10.1007/s10158-013-0166-9 · 0.90 Impact Factor
Available from: Mari Gabrielsen
- "The homology modeling approach is a valuable tool for investigating protein structures when experimental structures are lacking. Homology models are useful for predicting ligand potency and specificity through the use of different docking approaches, and high-quality homology models have also been used in the study of conformational changes using MD simulations . In the present study, 5-HT and ten other tryptamine derivatives (SERT substrates) and the SSRI (S)-citalopram were docked into the putative substrate binding site of a SERT homology model, and possible conformational changes of SERT upon ligand binding were studied by MD simulations. "
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ABSTRACT: The serotonin (5-HT) transporter (SERT) plays an important role in the termination of 5-HT-mediated neurotransmission by transporting 5-HT away from the synaptic cleft and into the presynaptic neuron. In addition, SERT is the main target for antidepressant drugs, including the selective serotonin reuptake inhibitors (SSRIs). The three-dimensional (3D) structure of SERT has not yet been determined, and little is known about the molecular mechanisms of substrate binding and transport, though such information is very important for the development of new antidepressant drugs. In this study, a homology model of SERT was constructed based on the 3D structure of a prokaryotic homologous leucine transporter (LeuT) (PDB id: 2A65). Eleven tryptamine derivates (including 5-HT) and the SSRI (S)-citalopram were docked into the putative substrate binding site, and two possible binding modes of the ligands were found. To study the conformational effect that ligand binding may have on SERT, two SERT–5-HT and two SERT–(S)-citalopram complexes, as well as the SERT apo structure, were embedded in POPC lipid bilayers and comparative molecular dynamics (MD) simulations were performed. Our results show that 5-HT in the SERT–5-HTB complex induced larger conformational changes in the cytoplasmic parts of the transmembrane helices of SERT than any of the other ligands. Based on these results, we suggest that the formation and breakage of ionic interactions with amino acids in transmembrane helices 6 and 8 and intracellular loop 1 may be of importance for substrate translocation.
SERT–5-HTB binding mode
Journal of Molecular Modeling 06/2011; 18(3):1073-85. DOI:10.1007/s00894-011-1133-1 · 1.74 Impact Factor
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ABSTRACT: Robust control system analysis and design is based on an
uncertainty description, called a linear fractional transformation
(LFT), which separates the uncertain (or varying) part of the system
from the nominal system. Low-order LFT models are difficult to form for
nonlinear parameter-dependent systems. The paper presents a numerical
computational method that can be used to construct low-order LFT models
for multivariate polynomial and rational problems based on simple matrix
computations. This LFT modeling method makes current robust and linear
parameter varying (LPV) control analysis and design methods accessible
to a broad class of difficult practical problems
American Control Conference, 1998. Proceedings of the 1998; 07/1998
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