Protein structural motifs in prediction and design

Abstract

The Protein Data Bank (PDB) has been an integral resource for shaping our fundamental understanding of protein structure and for the advancement of such applications as protein design and structure prediction. Over the years, information from the PDB has been used to generate models ranging from specific structural mechanisms to general statistical potentials. With accumulating structural data, it has become possible to mine for more complete and complex structural observations, deducing more accurate generalizations. Motif libraries, which capture recurring structural features along with their sequence preferences, have exposed modularity in the structural universe and found successful application in various problems of structural biology. Here we summarize recent achievements in this arena, focusing on subdomain level structural patterns and their applications to protein design and structure prediction, and suggest promising future directions as the structural database continues to grow.

Figure 1

Decomposition of protein structure space into motif libraries has revealed considerable modularity across the structural hierarchy, providing useful insights for protein design and structure prediction applications. Shown are six recent examples of motif libraries, each covering local-backbone and secondary (L/S), super-secondary (SS), or higher-order (HO) structural information to different extents (black, gray, or missing checkmarks in the structural coverage table correspond to detailed, sparse, or low coverage). Shown on the bottom are examples of uses of each motif library in either design or prediction/modeling applications (examples denoted by references).