Modelling of third cytoplasmic loop of bovine rhodopsin by multicanonical molecular dynamics

Advances in the Development and Application of Computational Methodologies for Structural Modeling of G-Protein Coupled Receptors

BACKGROUND: Despite the large amount of experimental data accumulated in the past decade on G-protein coupled receptor (GPCR) structure and function, understanding of the molecular mechanisms underlying GPCR signaling is still far from being complete, thus impairing the design of effective and selective pharmaceuticals. OBJECTIVE: Understanding of GPCR function has been challenged even further by more recent experimental evidence that several of these receptors are organized in the cell membrane as homo- or hetero-oligomers, and that they may exhibit unique pharmacological properties. Given the complexity of these new signaling systems, researcher's efforts are turning increasingly to molecular modeling, bioinformatics and computational simulations for mechanistic insights of GPCR functional plasticity. METHODS: We review here current advances in the development and application of computational approaches to improve prediction of GPCR structure and dynamics, thus enhancing current understanding of GPCR signaling. RESULTS/CONCLUSIONS: Models resulting from use of these computational approaches further supported by experiments are expected to help elucidate the complex allosterism that propagates through GPCR complexes, ultimately aiming at successful structure-based rational drug design.

Generation of a flexible loop structural ensemble and its application to induced-fit structural changes following ligand binding

Molecular recognition is often mediated by flexible loops that have widely fluctuating structures and are sometimes disordered, but that form particular complex structures following ligand binding. In fact, many loop structures found in the PDB database are too flexible to be determined precisely. A new loop modeling method was therefore developed using force-biased multicanonical molecular dynamics with the implicit solvent model to generate an ensemble of putative loop structures with low free energy values. The method was then used to create ensembles for several flexible loops that were compared with the corresponding NMR and X-ray structures. The induced-fit structural change of dihydrofolate reductase (DHFR) was also predicted from a structural ensemble of ligand-free M20 loop conformations and successive docking simulations.

Modeling flexible loops in the dark-adapted and activated states of rhodopsin, a prototypical G-protein-coupled receptor

Conformational possibilities of flexible loops in rhodopsin, a prototypical G-protein-coupled receptor, were studied by modeling both in the dark-adapted (R) and activated (R*) states. Loop structures were built onto templates representing the R and R* states of the TM region of rhodopsin developed previously (G. V. Nikiforovich and G. R. Marshall. 2003. Biochemistry. 42:9110). Geometrical sampling and energy calculations were performed for each individual loop, as well as for the interacting intracellular loops IC1, IC2, and IC3 and the extracellular loops EC1, EC2, and EC3 mounted on the R and R* templates. Calculations revealed that the intra- and extracellular loops of rhodopsin possess low-energy structures corresponding to large conformational movements both in the R and R* states. Results of these calculations are in good agreement with the x-ray data available for the dark-adapted rhodopsin as well as with the available experimental biophysical data on the disulfide-linked mutants of rhodopsin. The calculated results are used to exemplify how the combined application of the results of independent calculations with emerging experimental data can be used to select plausible three-dimensional structures of the loops in rhodopsin.

Molecular dynamics sampling scheme realizing multiple distributions

We present a molecular-dynamics sampling scheme in which any summation of multiple arbitrarily given distributions can be realized deterministically by a certain theoretical guide. Our scheme thus provides a static view of the composition of the distributions, rather than a dynamic view in which some parameter is switched at a certain time in the simulation process. The proposed method induces the orbit to jump automatically among different phase space regions, without the use of any artificial timing parameter. In addition, the proposed method does not require an assumption that the density of states is smooth. We applied it to multiple Tsallis distributions and established a suitable series of parameter values for which the sum of the distributions allows broad sampling. Numerical simulations applied to fundamental models with multi-Tsallis distributions showed efficient sampling, characterized by an energy trajectory that was totally different from that associated with each single distribution.