De Novo Design of Foldable Proteins with Smooth Folding Funnel

Abstract

De novo sequence design of foldable proteins provides a way of investigating principles of protein architecture. We performed fully automated sequence design for a target structure having a three-helix bundle topology and synthesized the designed sequences. Our design principle is different from the conventional approach, in that instead of optimizing interactions within the target structure, we design the global shape of the protein folding funnel. This includes automated implementation of negative design by explicitly requiring higher free energy of the denatured state. The designed sequences do not have significant similarity to those of any natural proteins. The NMR and CD spectroscopic data indicated that one designed sequence has a well-defined three-dimensional structure as well as alpha-helical content consistent with the target.

Learning To Fold Proteins Using Energy Landscape Theory

“…To look at specific kinetic issues we also employed a non-additive structure based model that has a higher (and more realistic) degree of cooperativity than AWSEM now has [112]. The designed sequences chosen for the study were Top7, from the Baker group, and two sequences designed and synthesized by the Takada group [59, 50]. Top7 was designed to fold to a novel topology starting from a “sketch” of the topology and its initial sequence was generated by using fragments with consistent secondary structure [59].…”

“…The design procedure was then iterated by the Baker group using Monte Carlo based sequence design and gradient based backbone optimization for multiple rounds. The two sequences designed by the Takada group began with a target scaffold of a relaxed structure of protein G-related albumin binding domain and then sequences that were expected to fold to this structure were found by a search in sequence space motivated by two criteria inspired by landscape theory [50]. One sequence, which we call TakadaE, was designed based on a scheme that merely minimized the target structure energy over sequences, while the other sequence, TakadaZ, was designed using a T f /T g criterion.…”

Protein Folding Thermodynamics and Dynamics: Where Physics, Chemistry, and Biology Meet

“…Z-score optimization of sequences was first developed in 63 for lattice model proteins and was further extended to real proteins in 70,71 . In particular, Takada and coworkers designed novel sequences for a known protein having three-helix bundle structure 71 using the Z-score optimization as well as (for comparison) energy minimization approach with given aminoacid compositions. The authors used a simplified protein representation where aminoacids were represented as spheres.…”

Domain swapping is a consequence of minimal frustration

“…Such models have impressively reproduced the experimentally observed folding mechanism of many single-domain proteins (6,20). The quantitative form of minimal frustration of proteins has been successfully used to improve protein structure prediction energy functions (21) and for protein design (22). Because proteins carry out their function while interacting with other cellular components, one may also ask not only whether proteins have evolved to fold efficiently but also whether proteins may be optimized for selective binding.…”