Rosetta Structure Prediction
In the Meiler Lab, we have long-term experience in the usage and development of methods to tackle the structural prediction of biomolecules, their dynamics and how they interact with molecular partners. Although dramatic advances have recently been made in machine-learning prediction of structure from sequence, biophysical approaches are still fundamental to investigate challenging aspects of biomolecular components. In the subsections are listed a number of relevant methods we helped develop or that have been extensively applied in our research; these include data-driven modeling of protein conformational changes, comparative modeling, glycan and loop modeling, protein-protein, protein-RNA and flexible peptide docking.
Comparative Modeling
Despite the limitations of homology modeling in protein structure prediction with respect to recently developed machine learning methodologies, comparative modeling of antibodies and antigen-docking has ...
de novo Protein Modeling
De novo protein folding is a very difficult problem in structural biology. This technique works to predict protein tertiary structure from its amino acid sequence. This is done in cases where there is no template structure available ...
Protein-Protein Interactions
Many proteins carry out their functional role acting as parts of protein assemblies. The assembly of the correct biological complex strongly depends upon specific protein-protein interactions (PPIs) that are often ...
Glycan Modeling
Glycan modeling is performed with the Carbohydrate framework within the Rosetta suite. Existing glycan structures can be sampled to find the more stable conformations, or glycan chains can be ...
Loop Modeling
The conformational heterogeneity and flexibility of loops makes computational prediction a challenging task. Experimental data is also sparse as the dynamic nature of loops makes full resolution ...
Protein-RNA Modeling
Fragment Assembly of RNA with Full Atom Refinement (FARFAR) is a framework within the Rosetta suite that can produce de novo or homologous RNA structure models and has been improved ...
Flexible Peptide Docking
Docking flexible peptides upon to a potential binding partner is performed with the Flexible Peptide Docking (FlexPepDock) framework of the Rosetta software suite. Starting from a peptide sequence and an approximate location of the binding site, ...
Conformational Changes
Despite great advances in experimental methods for protein structure determination, the unambiguous characterization of multiple conformational states remains a challenge. Difficulties primarily arise from the huge range of structures that ...
EPR Based Modeling
We have an extensive track record of designing methodologies for modeling protein structures using sparse data collected by electron paramagnetic resonance (EPR) spectroscopy. Our work principally focuses on ...