BCL::Score—Knowledge Based Energy Potentials for Ranking Protein Models Represented by Idealized Secondary Structure Elements

Abstract

The topology of most experimentally determined protein domains is defined by the relative arrangement of secondary structure elements, i.e. α-helices and β-strands, which make up 50–70% of the sequence. Pairing of β-strands defines the topology of β-sheets. The packing of side chains between α-helices and β-sheets defines the majority of the protein core. Often, limited experimental datasets restrain the position of secondary structure elements while lacking detail with respect to loop or side chain conformation. At the same time the regular structure and reduced flexibility of secondary structure elements make these interactions more predictable when compared to flexible loops and side chains. To determine the topology of the protein in such settings, we introduce a tailored knowledge-based energy function that evaluates arrangement of secondary structure elements only. Based on the amino acid Cβ atom coordinates within secondary structure elements, potentials for amino acid pair distance, amino acid environment, secondary structure element packing, β-strand pairing, loop length, radius of gyration, contact order and secondary structure prediction agreement are defined. Separate penalty functions exclude conformations with clashes between amino acids or secondary structure elements and loops that cannot be closed. Each individual term discriminates for native-like protein structures. The composite potential significantly enriches for native-like models in three different databases of 10,000–12,000 protein models in 80–94% of the cases. The corresponding application, “BCL::ScoreProtein,” is available at www.meilerlab.org.

Iterative Molecular Dynamics–Rosetta Membrane Protein Structure Refinement Guided by Cryo-EM Densities

“…RMSDs over the backbone atoms of the generated models were calculated using the BCL::Quality algorithm 87 . Since we were not interested in starting structures that significantly deviated from the native, we only picked proteins for which we were able to generate ab initio models with RMSDs of less than ~ 5 Å to the native.…”

“…The full atom solvation score term was set to zero to implicitly account for the membrane environment. RMSD of each model was calculated using the BCL::Quality algorithm 87 . The fit-to-density score of each model was also calculated using Rosetta density-tools which provided the model-map agreement 94 .…”

Pushing the size limit of de novo structure ensemble prediction guided by sparse SDSL-EPR restraints to 200 residues: The monomeric and homodimeric forms of BAX

“…After each Monte Carlo step, models are scored using knowledge-based potentials evaluating different scoring terms like SSE packing, radius of gyration, amino acid exposure, amino acid interactions, loop closure geometry, secondary structure length and content, as well as penalizing potentials for SSE and amino acid clashes (Woetzel et al, 2012). The potential functions for each scoring term were derived from statistics over protein structures deposited in the PDB using the inverse Boltzmann relation (Equation 1) (Woetzel et al, 2012). $$E=-RT\times \ln \frac{P_{obs}}{P_{back}}$$…”

“…This normalization ensures that favorable features are assigned negative scores. The term RT is set to 1 for convenience (Woetzel et al, 2012). For example, one scoring term ( S NC ) evaluates the burial of residues.…”

“…The simplified macromolecule representations used in de novo folding simulations prohibit computation of accurate free energy differences between different conformations. Instead, the approach employed in this study uses knowledge-based energy functions to determine the likelihood of proposed protein models (Woetzel et al, 2012). In parallel, SDSL-EPR distance restraints restrict the sampling space to conformations that are in agreement with the SDSL-EPR data (Bleicken et al, 2014), thus increasing the frequency with which models in agreement with the SDSL-EPR data are sampled.…”