A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions

By Maxim V. Shapovalov, Roland L. Dunbrack. 2011

970 citations recorded by the source corpus.

Rotamer libraries are used in protein structure determination, structure prediction, and design. The backbone-dependent rotamer library consists of rotamer frequencies and their mean dihedral angles and variances as a function of the backbone dihedral angles ϕ and ψ. Previous versions of this rotamer library were not developed with smoothness in mind, although some structure prediction and protein design methods would strongly benefit from smoothing. A new version of the backbone-dependent rotamer library has been developed using adaptive kernel density estimates for the rotamer frequencies and adaptive kernel regression for the mean dihedral angles and variances. The formulation presented allows for evaluation of the rotamer probabilities, mean angles and variances at any ϕ, ψ point, i.e. as a continuous function of ϕ and ψ. Continuous probability density estimates for the non-rotameric degrees of freedom of amides, carboxylates, and aromatic side chains have been modeled as a function of the backbone dihedral angles and rotamers of the remaining degrees of freedom. New backbone-dependent rotamer libraries at varying levels of smoothing are available from http://dunbrack.fccc.edu.

Subfields: Materials Chemistry, Molecular Biology

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Citations in the corpus

SWISS-MODEL: homology modelling of protein structures and complexes (2018, positive): “Non-conserved side-chains are modelled using the 2010 back-bone dependent rotamer library from the Dunbrack group (52).”
Scientific Benchmarks for Guiding Macromolecular Energy Function Improvement (2013, background): “The Dunbrack term in Score12 is given by where the rotamer bin, rot, which gives the probability of the rotamer, p (rot| f , c ,aa), is computed from the assigned w dihedrals, and both (cid:2) w i f , c j aa,rot ð Þ and s i ( f , c |aa,rot)arethemeasuredmean w valuesandstandard deviations for the ro”
High‐accuracy protein structure prediction in CASP14 (2021, background): “As expected from the relationship between side-chain and back-bone geometry, 29,30 the closer the geometry of the models' backbone, the more accurate were the side-chain conformations predicted (Figure 2D).”
Energy-based models for atomic-resolution protein conformations (2020, methodology): “We use the Dunbrack library (Shapovalov & Dunbrack Jr, 2011) for rotamer conﬁgurations.”
Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design (2018, methodology): “The protein backbone is held fixed throughout the protocol and sidechain conformations are sampled using a backbone-dependent rotamer library 28 .”
Chemical shift-based methods in NMR structure determination (2018, methodology): “Lastly, sidechain rotamers [61] and minor deviations from ideal values are introduced on low-resolution conformations, which undergo further refinement to reduce steric clashes, and finally to produce all-atom structural models.”
A Web Resource for Standardized Benchmark Datasets, Metrics, and Rosetta Protocols for Macromolecular Modeling and Design (2015, background): “All segment side chains and those within 10Å of the segment are modeled based on a side chain rotamer library [48] that does not include the native side chain conformations.”
Protein engineering by highly parallel screening of computationally designed variants (2016, methodology): “5 (build 2013 week 42) with the Dunbrack 2010 rotamer library (23).”
Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks (2013, methodology): “The latter prediction can be made using the 2010 backbone-dependent rotamer library of Shapovalov and Dunbrack (Shapovalov and Dunbrack 2011), using as input the φ and ψ values of any given residue obtained from TALOS-N.”
Enhancing structure prediction and design of soluble and membrane proteins with explicit solvent-protein interactions (2017, background): “Rotamers are built according to a library (developed by Dunbrack et al. (Shapovalov and Dunbrack, 2011)) of consensus amino-acid conformations recurrently observed in high-resolution experimental protein structures.”
Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity (2015, methodology): “Rotamers are generated using the Dunbrack backbone-dependent rotamer library [42].”