Improving the quality of NMR and crystallographic protein structures by means of a conformational database potential derived from structure databases

Abstract

A new conformational database potential involving dihedral angle relationships in databases of high-resolution highly refined protein crystal structures is presented as a method for improving the quality of structures generated from NMR data. The rationale for this procedure is based on the observation that uncertainties in the description of the nonbonded contacts present a key limiting factor in the attainable accuracy of protein NMR structures and that the nonbonded interaction terms presently used have poor discriminatory power between highand low-probability local conformations. The idea behind the conformational database potential is to restrict sampling during simulated annealing refinement to conformations that are likely to be energetically possible by effectively limiting the choices of dihedral angles to those that are known to be physically realizable. In this manner, the variability in the structures produced by this method is primarily a function of the experimental restraints, rather than an artifact of a poor nonbonded interaction model. We tested this approach with the experimental NMR data (comprising an average of about 30 restraints per residue and consisting of interproton distances, torsion angles, 'JHNa coupling constants, and I3C chemical shifts) used previously to calculate the solution structure of reduced human thioredoxin (Qin J, Clore GM, Gronenborn AM, 1994, Structure 2503-522). Incorporation of the conformational database potential into the target function used for refinement (which also includes terms for the experimental restraints, covalent geometry, and nonbonded interactions in the form of either a repulsive, repulsive-attractive, or 6-12 Lennard-Jones potential) results in a significant improvement in various quantitative measures of quality (Ramachandran plot, side-chain torsion angles, overall packing). This is achieved without compromising the agreement with the experimental restraints and the deviations from idealized covalent geometry that remain within experimental error, and the agreement between calculated and observed ' H chemical shifts that provides an independent NMR parameter of accuracy. The method is equally applicable to crystallographic refinement, and should be particular useful during the early stages of either an NMR or crystallographic structure determination and in cases where relatively few experimental restraints can be derived from the measured data (due, for example, to broad lines in the NMR spectra or to poorly diffracting crystals).Keywords: conformational databases; NMR; protein structure determination; refinement; X-rayThe determination and refinement of a protein structure by NMR or crystallography depends on the minimization of a target function (Etot) comprising the experimental restraints (E,,,), and two groups of a priori restraints consisting of covalent geometry (Ecou) and nonbonded interactions (Enb) (Jack &

Comprehensive structural and dynamical view of an unfolded protein from the combination of single-molecule FRET, NMR, and SAXS

“…Structural ensembles of urea-denatured ubiquitin were calculated by the program X-PLOR-NIH, version 2.39 (64), using protocols described previously (21) with standard X-PLOR force fields including a conformational database potential for torsion angles and repulsive-only van der Waals terms (54). The ensemble calculations used experimental restraints in different combinations derived from 419 RDCs (nine different types) and 256 PREs published previously (20,21) that were supplemented by 71 backbone 3 J HNHα -couplings (40) and SAXS data (38).…”

p53 and TFIIEα share a common binding site on the Tfb1/p62 subunit of TFIIH

“…The structures of TFIIE␣ 336 -439 were calculated with the program CNS by using a combination of torsion angle and Cartesian dynamics (33) and starting from one extended structure with standard geometry. The protocol used the conformational database potential derived from structural databases (34).…”

Smooth statistical torsion angle potential derived from a large conformational database via adaptive kernel density estimation improves the quality of NMR protein structures

“…For instance, rotamer libraries can be used to fit side chain conformations to electron density, 5,6 and statistical potentials derived from database torsion angle distributions can supplement experimental restraints derived from NMR data. Driven by the relative sparseness of NMR data, the latter application was introduced more than 15 years ago 7 and is at the center of this study. Statistical torsion angle potentials can be succinctly described as follows.…”