Among the milestones that we were able to accomplish under the auspices of continued NIH funding over the past 10 years are the design, testing, and implementation of innovative computational strategies to build improved molecular models of G Protein-Coupled Receptors (GPCRs) and to study, more efficiently, the conformational plasticity and dynamical nature of liganded or unliganded, single or interacting, receptors within their natural lipid environment. In particular, we pioneered the use of enhanced, molecular dynamics (MD)-based computational strategies in combination with either atomistic or coarse-grained (CG) system representations to improve dynamic molecular models of GPCR molecular recognition, activation, and oligomerization, with the ultimate goal of elucidating receptor allostery and functional selectivity for successful use in rational drug design. In particular, we were able: (i) to obtain reliable models of ligand-bound conformations of GPCRs that do not require very long and computationally inefficient standard MD simulations, (ii) to establish a possible molecular basis for the functional selectivity of GPCRs through the prediction of ligand-specific conformations, and (iii) to advance current understanding of the role of oligomerization in receptor function through the generation of novel testable hypotheses of specific mutations that could eventually be used to modulate receptor function (see section 2, below). While the specific computational methods we explored are not new from an algorithmic standpoint, we developed some distinctive combinations of such methods, and showed in recent publications that they are indeed able to generate ligand-specific conformations of both isolated and interacting, inactive and active, GPCRs that are consistent with experimental data. Notably, the methodologies we developed represent fundamental tools that can be generalized to other transmembrane receptors, as well as broadly to other proteins.
Among the various GPCRs, we have devoted special attention to opioid receptors, which are important drug targets for pain management, drug abuse/addiction, and mood disorders. We have a long history of work on these GPCR subtypes, having contributed over the past 15 years to several structural and mechanistic insights into their pharmacology and signaling. Most recently, we have focused on their dynamics, seeking answers to questions like: How does an opioid drug bind to his receptor? How can sodium ions modulate opioid receptor activity? What are the likely interfaces of opioid receptor homodimers?
Provasi, D., Bortolato A., Filizola, M. “Exploring Molecular Mechanisms of Ligand Recognition by Opioid Receptors with Metadynamics.” Biochemistry (2009) 48 (42): 10020-10029.
Filizola M. & Devi, L.A. “How opioid drugs bind to receptors” Nature (2012) 485, 314-7.
Johnston, J.M., Aburi, M., Provasi, D., Bortolato, A., Urizar, E., Lambert, N.A., Javitch, J.A., Filizola, M. “Making Structural Sense of Dimerization Interfaces of Delta Opioid Receptor Homodimers”, Biochemistry (2011) 50(10):1682-1690
Shang, Y., LeRouzic, V., Schneider, S., Bisignano, P., Pasternak, G.W., Filizola, M. “Mechanistic Insights into the Allosteric Modulation of Opioid Receptors by Sodium Ions” Biochemistry (2014) 53(31):5140-9.
Mobarec, J.C., Sanchez, R., and Filizola, M. “Modern Homology Modeling of G-Protein Coupled Receptors: Which Structural Template to Use?” Journal of Medicinal Chemistry (2009) 52 (16), 5207-5216.
Provasi, D., Camacho-Artacho, M., Negri, A., Mobarec, J.C., Filizola, M. “Ligand-Induced Modulation of the Free-Energy Landscape of G Protein-Coupled Receptors Explored by Adaptive Biasing Techniques.” PLOS Computational Biology (2011) 7(10):e1002193.
Provasi, D. & Filizola, M. “Putative Active States of a Prototypic G-Protein Coupled Receptor from Biased Molecular Dynamics.”Biophysical Journal (2010) 19(10):2347-2355.
Schneider, S., Provasi, D. & Filizola, M. “The Dynamic Process of Drug-GPCR Binding at Either Orthosteric or Allosteric Sites Evaluated by Metadynamics” Methods in Molecular Biology (2015) in press.