Understanding the fabric of protein crystals: computational classification of biological interfaces and crystal contacts

Abstract

Modern structural biology still draws the vast majority of information from crystallography, a technique where the objects being investigated are embedded in a crystal lattice. Given the complexity and variety of those objects, it becomes fundamental to computationally assess which of the interfaces in the lattice are biologically relevant and which are simply crystal contacts. Since the mid-1990s, several approaches have been applied to obtain high-accuracy classification of crystal contacts and biological protein-protein interfaces. This review provides an overview of the concepts and main approaches to protein interface classification: thermodynamic estimation of interface stability, evolutionary approaches based on conservation of interface residues, and co-occurrence of the interface across different crystal forms. Among the three categories, evolutionary approaches offer the strongest promise for improvement, thanks to the incessant growth in sequence knowledge. Importantly, protein interface classification algorithms can also be used on multimeric structures obtained using other high-resolution techniques or for protein assembly design or validation purposes. A key issue linked to protein interface classification is the identification of the biological assembly of a crystal structure and the analysis of its symmetry. Here, we highlight the most important concepts and problems to be overcome in assembly prediction. Over the next few years, tools and concepts of interface classification will probably become more frequently used and integrated in several areas of structural biology and structural bioinformatics. Among the main challenges for the future are better addressing of weak interfaces and the application of interface classification concepts to prediction problems like protein-protein docking.

Fig. 1.

2D schematic illustration of the interface classification problem. Given (a) as a crystal lattice, any of (b–d) could be inferred with equal validity as the biological unit. Without further information, it is not clear which arrangement represents the true biological unit. This figure was inspired by a similar one by Levy and Teichmann (2013), which, in turn, was inspired by ‘Fish (N° 20)’ by M.C. Escher

Fig. 2.

Average number of contacts between chains of the lattice per PDB entry for structures solved using X-ray crystallography from 1980 to 2014. Averages for all structures solved in a particular year appear in pink (dots, solid line), cumulative averages for the whole PDB per year are shown in turquoise (triangles, dashed line). Essentially the same value for the current average number of contacts was independently obtained in an analysis of a 2012 PDB subset consisting of monomeric proteins with one chain per asymmetric unit (Carugo and Djinović-Carugo, 2012)

Fig. 3.

Protein topology and assemblies. (a) Two identical protomers coming together to form an isologous homooligomeric assembly. The black lens denotes a 2-fold axis of rotational symmetry. (b) Three identical subunits assembling to form an infinite heterologous homooligomeric assembly. (c) Six identical protomers assembling to form a closed heterologous homooligomeric assembly with 6-fold symmetry (the black hexagon). (d) A rendering of a cyclic C6 assembly (PDB ID: 4QNB). (e) A protein with dihedral D4 symmetry (PDB ID: 4OAO)