backbonedependent

Backbonedependent, a term often written backbone-dependent in the literature, describes an approach in structural biology and computational chemistry that conditions the prediction of side-chain conformations on the local protein backbone geometry. The idea is that the most probable orientations of amino acid side chains (rotamers) depend on the backbone dihedral angles, typically phi and psi, rather than being drawn from a single, universal distribution independent of backbone conformation.

These models are built by analyzing high-resolution protein structures to produce conditional probability distributions for each chi angle given the backbone state. The backbone is usually partitioned into bins of phi/psi values, and for each bin a set of preferred rotamer states with frequencies is learned. The resulting backbone-dependent rotamer library is then used by side-chain packing algorithms to place and refine residues during modeling and refinement.

Differences with backbone-independent libraries: backbone-independent libraries ignore backbone geometry and assign rotamer preferences in a uniform manner across all backbone conformations. Backbone-dependent libraries improve the accuracy of side-chain placement, particularly in tightly packed regions, but require accurate backbone coordinates and higher computational effort.

Applications and limitations: backbone-dependent rotamer modeling is widely used in protein structure prediction, homology modeling, refinement, and docking pipelines. Limitations include dependence on the quality and representativeness of the underlying structural data; reduced applicability for novel folds or disordered regions; and potential mismatch in cases where backbone flexibility alters rotamer preferences.

See also: rotamer library, Dunbrack library, side-chain packing, Rosetta, SCWRL, chi angles.