Meiler Lab

Protein de-novo Folding

Methods Development
Contact Prediction BCL Align Sequence Alignment and Fold Recognition Sparse EPR Data guided Protein Structure Elucidation Jufo9D Secondary Structure and TM Span Prediction Protein Structure Prediction using Fold Templates BCL::Cluster: Clustering biological molecules with PyMOL visualization Gradient Minimization for Structure Refinement RosettaTMH
Applications
Modeling of Protein IIIA Structure Determination of DsbB using Paramagnetic Restraints Structure determination of KCNE3 using paramagnetic restraints

Protein Structure Prediction from Sparse Data

Methods Development
Protein Structure Prediction Cryo-EM Fit Cryo-EM Guided Protein Fold Elucidation Membrane Protein Structure Prediction using Sparse NMR Restraints RosettaEPR BCL::EMFitMinimize Protein Structure Prediction using SAXS Data
Applications
Modeling Rhodopsin Interaction with G-Protein and Arrestin Mechanism of Activation of the heterotrimeric G protein alpha subunit

Cheminformatics

Methods Development
Chemical Shift Prediction PharmMap Method Development for QSAR Ligand-based Virtual Screening Development of RosettaQSAR Knowledge-Based Small Molecule Conformational Sampling Novel HTS Datasets composed to benchmark ligand-based QSAR Modeling
Applications
mGluR5 Related Neurological Diseases Allosteric Modulators of Neuropeptide Y Receptors Malaria - Inhibition of beta-Hematin Crystallization in Plasmodium falciparum Rapid in silico target identification for anti-malarials

Protein-Protein Interactions

Applications
Structural Characterization of HoxA11 HIV Antibody/Antigens Interactions Antibiotics- Protein/Peptide Interfaces Antibody/Antigens Interaction

Ligand Docking

Methods Development
Rosetta Drug Design Rosetta Design Modeling Partial Covalent Interactions in Protein Ligand Interfaces RosettaLigandEnsemble Drug Design through Foldit Video Game
Applications
Structural Determinants of Antidepressant Drugs GPCR Model Building, Refinement, and Ligand Docking HIV-1 Protease Inhibitor Docking Protein-Ligand Interaction as Cancer Therapeutics

Protein Design

Applications
Evolution of TIM Barrels Chemical Basis of Ligand-Macromolecule Recognition

G-Protein Coupled Receptor (GPCR) Model Building, Refinement, and Ligand Docking

G-protein coupled receptors (GPCR) make up the largest family of proteins and also serve as targets for over 50% of drugs currently on the market. Characterizing the structure of GPCRs is therefore a valuable tool that allows for a novel approach to the development of therapeutic agents. However, because GPCRs are membrane proteins, structure determination of proteins in this family is a challenge for NMR studies, x-ray crystallography, and computational comparative modeling tools, which are often optimized for soluble proteins. Our lab is interested in developing tools specific for the structure determination of membrane proteins. Machine learning methods are being used to train bcl::align to perform sequence alignments optimized for transmembrane protein domains. In addition, the membrane protein-specific de novo folding algorithms and scoring functions in Rosetta (collectively called RosettaMembrane) provide the allow for high-resolution computational modeling of membrane proteins. These tools will be applied to our receptors of interest, mGluR5 and the human NPY4 receptor. Through diverse signaling pathways that modulate synaptic plasticity, metabotropic glutamate receptor subtype 5 (mGluR5) is involved in mammalian cognitive function and can be targeted in the development of new treatment strategies for disorders such as schizophrenia and fragile X syndrome. Agonists of the human neuropeptide Y4 (NPY4) receptor can potentially serve as therapeutics to treat obesity. Structure determination and ligand docking studies with new computational comparative modeling tools developed specifically for membrane proteins should uncover functionally important residues in these GPCRs that can be used to further drug development.

Further work involves comparative modeling of the prolactin releasing peptide receptor (PrRPR) and growth hormone secretagogue receptor (GHSR). These are also implicated in obesity and metabolic disorders. These two receptors are endogenously activated by the prolactin releasing peptide (PrRP) and ghrelin, respectively. In order to determine the structural mechanism of activation, PrRP and ghrelin were first folded de novo using Rosetta in the presence of sparse NMR data (e.g., chemical shifts and NOEs) (link to Activity of PrRP paper by DeLuca et al). In the case of PrRP, the resulting ensemble of models were docked into the PrRP receptor using Rosetta (link to Ligand mimicking paper on PrRP by Rathmann et al).

A publication concerning similar work with the ghrelin peptide is forthcoming, supplementary files and protocol are already available .

Current Project Members: Georg Kuenze , Oanh Vu
Alumni Project Members: Elizabeth Nguyen , Stephanie DeLuca Hirst , Eric Dawson , Darwin Fu

Center for Structural Biology
465 21st Ave South, BIOSCI/MRBIII
Vanderbilt University, Nashville, TN