G Protein-Coupled Receptors - Modeling and Simulation by Marta Filizola

Author:Marta Filizola
Language: eng
Format: epub
Publisher: Springer Netherlands, Dordrecht

6.4.2 Combining CG Representation and Biased MD to Investigate GPCR Dimerization

By combining the MARTINI reduced representation of the system with biased MD techniques, it has been possible to make predictions about the relative strength of dimers formed at different interfaces in an explicit membrane environment.

We pioneered the use of a free energy approach to characterize oligomerization of GPCRs. Two studies of dimerization of the DOP receptor were performed using established methodologies, firstly umbrella sampling, from which we derived the PMF of a dimerization event (Provasi et al. 2010), and secondly, a metadynamics study in which we established the most favorable orientation of the individual protomers involved in different dimeric arrangements (Johnston et al. 2011), i.e. comprised of different contact interfaces, of the DOP receptor. The computational results of this study compared favorably with inferences from cysteine crosslinking experiments, supporting the role of specific residues at the interfaces.

To characterize dimerization for the DOP receptor, we performed biased MD simulations of a CG representation of a homo-dimeric arrangement of this receptor in an explicitly CG represented, POPC:10 % cholesterol-water environment. Since these studies were conducted prior to the crystallographic solution of the opioid receptor structures in 2012 (Wu et al. 2012; Granier et al. 2012; Thompson et al. 2012; Manglik et al. 2012), an all-atom structural model of the DOP receptor protomer from Mus musculus, was generated by homology modeling, using the crystal structure of the B2AR at 2.4 Å resolution (PDB ID: 2RH1) (Cherezov et al. 2007) in MODELLER 9v3 (Eswar et al. 2007), using the same strategy we recently reported in the literature for the human DOP receptor (Provasi et al. 2009). The loop regions were built ab initio using ROSETTA 2.2 (Wang et al. 2007). A pair of the resultant DOP receptor models was placed facing one another at a putative symmetrical interface, involving residue 4.58, inferred from cysteine cross-linking data on this and other GPCRs (see e.g. Guo et al. 2005, 2008).

In an effort to improve the stability of the secondary structure of the CG representation of the receptor, we combined an elastic network model (ENM) with the MARTINI CG representation, using a method developed and termed ELNEDIN by Periole and colleagues (2009). ENMs are ideally suited to preserve the secondary or tertiary structure of biomolecules, since they are structure derived, and therefore introduce an intrinsic bias toward the structure upon which they are established. In a novel extension to the ELNEDIN method, we applied a secondary-structure-dependent construct to models of the DOP receptor dimer (Provasi et al. 2010). The strength of the force constant for the harmonic restraint, KSPRING, was determined by the secondary structure of each of the residues. If the residue was determined to have a defined secondary structure (by DSSP (Kabsch and Sander 1983)), e.g. α-helix as in the case of the TM regions of the DOP receptor, then a force constant of KSPRING = 1,000 kJ/mol/nm2 was applied. For a sequence of >2 residues with undefined secondary structure (e.g. coil, bend, or turn), a force constant of KSPRING = 250 kJ/mol/nm2 was applied.

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