A General Computational Approach for Repeat Protein Design

Abstract

Repeat proteins have considerable potential for use as modular binding reagents or biomaterials in biomedical and nanotechnology applications. Here we describe a general computational method for building idealized repeats that integrates available family sequences and structural information with Rosetta de novo protein design calculations. Idealized designs from six different repeat families were generated and experimentally characterized; 80% of the proteins were expressed and soluble and more than 40% were folded and monomeric with high thermal stability. Crystal structures determined for members of three families are within 1 Å root-mean-square deviation to the design models. The method provides a general approach for fast and reliable generation of stable modular repeat protein scaffolds.

Computationally Designed Armadillo Repeat Proteins for Modular Peptide Recognition

“…Internal repeats were constrained to adopt the same primary sequence, side-chain, and backbone conformations by using symmetric sequence design and conformation sampling during all modeling moves. Symmetric structure prediction [18] and design has been used extensively in Rosetta [11] yielding atomic-accuracy predictions for large homomeric oligomers, designed cage-like assemblies or repeat proteins [12][13][14][15][19][20][21]. Our calculations were restricted to three internal repeats and two capping repeats.…”

“…Using this template, the relative orientations between subsequent repeats were extracted and imposed as symmetric modeling constraints during backbone and side chain sampling simulations using the Rosetta software suite [11]. Similar design protocols have been used for the computational design of repeat proteins, first with sequence and structural information obtained from natural repeat protein families [12,13] and then for de novo designed repeat proteins with open [14] and closed [15] architectures. Using such approaches, typically >50% of the designed constructs can be expressed as soluble, folded, monomeric proteins and determined structures agree well with the design models (typical RMSD of Cα atoms 0.5 -2.5 Å).…”

Designed protein reveals structural determinants of extreme kinetic stability

“…We demonstrate a high level of design success for ThreeFoil as evidenced by its: (i) reversible, cooperative, two-state (un)folding; and (ii) well folded and functional native structure which has high solubility and monodispersity, well diffracting crystals, and great resistance against H/D exchange (1), denaturation by chaotropes and detergent, and degradation by protease. Although the rational design of proteins with desired structure and function remains a great challenge and often require multiple cycles of design and/or selection to improve them, successes in designing both structures and/or functions, including ones not observed in nature, have been increasing (3,4,6,8,9,18,49,50). These results demonstrate the increasing understanding of fundamental principles and utility of computational protein design.…”

“…These results demonstrate the increasing understanding of fundamental principles and utility of computational protein design. Recently, there have been multiple reports of success for common folds based on repeated structural elements, including relatively high success rates and stabilities for various helix-containing elongated repeat proteins (18,51) and toroidal or globular superfolds (1-3, 7, 16, 17, 19). The great diversity of sequences observed for these symmetric protein structures may reflect an inherent capacity for stability, foldability and functionality that is especially amenable to both evolution and design (22).…”

“…Internal structural symmetry, resulting from the repetition of smaller elements of structure, is very common in natural proteins, with ∼20% of all protein folds (22) and the majority of the most populated globular protein folds (superfolds) (21) containing internal structural symmetry. Recent design successes, for helical proteins (5, 6), repeat proteins (18,20,23) and symmetric superfolds (1,2,7,16,17,19,(24)(25)(26) recommend the simplification of the design process by using repetitive/symmetric folds as a particularly effective strategy.…”