Quality Control of Protein Models: Directional Atomic Contact Analysis

Branden & Jones state, in Nature: 'Protein crystallography is an exacting trade, and the results may contain errors that are difficult to identify. It is the crystallographer's responsibility to make sure that incorrect protein structures do not reach the literature. ' [Branden & Jones. (1990). Nature (London), 343, 687-689. ] One of several available methods of checking structures for correctness is the evaluation of atomic contacts. From an initial hypothesis that a tom-atom interactions are the primary determinant of protein folding, any protein model can be tested for proper packing by the calculation of a contact quality index. The index is a measure of the agreement between the distributions of atoms around each residue fragment in the model and equivalent distributions derived from the database of known structures solved at high resolution. The better the agreement, the higher the contact quality index. This empirical test, which is independent of X-ray data, is applied to a series of successively refined crystal structures. In all cases, the model known or expected to be better (the one with the lower R factor) has a better contact quality index, indicating that this type of contact analysis can be used as an independent quality criterion during crystallographic refinement. Modelled proteins and predicted mutant structures can also be evaluated. Introduction Assume that, at some stage of density fitting, X-ray refinement, structure determination from two-dimensional N M R data or even protein design or structure prediction of mutants, a complete atomic model has been generated. We ask how such a model can be tested for correctness. Has the chain been correctly traced? Have all amino acid side chains been correctly placed? In crystallography, the quality of a model is expressed by an R factor. With an R factor below 20.0, it can be safely assumed that the model is essentially correct. However, some recent experiences, summarized by Branden & Jones (1990), have made clear that 0021-8898/93/010047-14506.00 at intermediate R factors, around R = 25.0 for example, there is no guarantee that the model is correct. Many indicators exist for the quality of structures. A q~-qJ plot is often very informative and real-space R-factor plots can indicate bad spots. Here an attempt is made to evaluate the correctness of models by a purely empirical, i.e. non-physical, method based on generalizations of observations recorded in the Protein Data Bank (PDB) (Bernstein et al., 1977). Contacts in known protein structures have been analysed before (Warme & Morgan, 1978; Levitt & Perutz, 1988; Singh & Thornton, 1985, 1990; Burley & Petsko, 1985, 1986; Crippen & Kuntz, 1978; Reid, Lindley & Thornton, 1985; Richmond & Richards, 1978; Tanaka & Scheraga, 1975; Miyazawa & Jernigan, 1985), but have not been satisfactorily used for predictive or analytical purposes. These studies have focused on the occurrence of residue-residue interactions, on the occurrence of a tom-a tom interactions or on the relative spatial orientation of residue-residue interactions. Here, as one partner of a contact event, a fragment of a residue without internal degrees of freedom has been taken and, as the other partner, an atom described by its chemical type. Each contact event is thus characterized by the fragment type, the atom type and the threedimensional location of the atom relative to the local frame of the fragment. The resulting database-derived distributions are used for contact quality control by comparing them with the actual distributions in the protein structures being tested for correctness. The method Fragment types The 20 amino acid types are divided into 80 fragments. These fragments are chosen so that they are as large as possible, but do not contain rotational degrees of freedom around dihedral angles. All hydrogen atoms are neglected. The largest fragment is the tryptophan double-ring system; the smallest contains only three atoms (e.g. the three consecutive atoms in the lysine side chain). Table 1 shows how this division into fragments is made. © 1993 International Union of Crystallography 48 Q U A L I T Y C O N T R O L O F P R O T E I N M O D E L S The a toms listed are Table 1. Atoms used per fragment used to superimpose fragments on the master fragment. Pr imed a toms are the so-called unique a toms that are used to score this fragment. N ' t2Y' C a All residues except Pro, Gly N' C '' C Gly N' C "' C a' C r' C 6' Pro C'Y C' O' All residues (Y C C a' Ala C-Y C ~' S y' Cys CY C a' C r (1) Asp Glu Phe His Lys Leu Met Asn Gin Arg Trp Tyr C y' O ha' O ~2' Asp C a C r' C ~ GluLysGln C °' O ~' O ~2' Glu Cfl C~'t C ~1' C d~2' C elt C -~2' C -~t P h e C a C r' N ~a' C °2' C ~x' N ~2' His C ~ C a' C r2' lle C a C ~x' C °~' lie C r C °' C ~ Lys C ~ C " N ~' Lys C r' C a~' C ~2' Leu C a C r' S ~ Met C ~ S ~' (Y' Met C r' O ~' N ~z' Asn C ~' O ~1' N e2' G in C a C ~' C ~' Arg N ~' C ~' N ~1' N '~2' Arg C ~ C ~' O ~' Ser C a' O r~' C r2' Thr Gilt Gri t C ~'2' Val C a C r' C oa' C ~2' N ~ ' C "2' C '~' C ~2' C ga' C "2' Trp C a C v C ox' C ~2' C ~x' C ~2' C ~' O "' Tyr