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Two de novo protein design frameworks are applied to the discovery of new compstatin variants. One is based on sequence selection and fold specificity, whereas the other approach is based on sequence selection and approximate binding affinity calculations. The proposed frameworks were applied to a complex of C3c with compstatin variant E1 and new variants with improved binding affinities are predicted and experimentally validated. The computational studies elucidated key positions in the sequence of compstatin that greatly affect the binding affinity. Positions 4 and 13 were found to favor Trp, whereas positions 1, 9, and 10 are dominated by Asn, and position 11 consists mainly of Gln. A structural analysis of the C3c-bound peptide analogs is presented.

In this article, we introduce and apply our de novo protein design framework, which observes true backbone flexibility, to the redesign of human beta-defensin-2, a 41-residue cationic antimicrobial peptide of the innate immune system. The flexible design templates are generated using molecular dynamics simulations with both Generalized Born implicit solvation and explicit water molecules. These backbone templates were employed in addition to the x-ray crystal structure for designing human beta-defensin-2. The computational efficiency of our framework was demonstrated with the full-sequence design of the peptide with flexible backbone templates, corresponding to the mutation of all positions except the native cysteines.

This paper presents two novel formulations for solving the sequence selection problem in de novo protein design with highly flexible templates, each of which exhibits a crystal or NMR, structure. The first formulation applies weighted average energy parameters to incorporate information about every structure, with the weights, which are parameters dependent on a pair of C α positions and a particular distance bin, given by the probability that the distance between the two positions is found to belong to that distance bin in any of the structures. The second formulation allows the distance between the two positions considered to fall into any distance bin that all the structures span over, but imposes novel linear constraints to ensure a physically consistent structure. Both formulations were tested on redesigning Compstatin, the template of which has 21 NMR structures from the protein data bank.

Both rigid and flexible backbone design templates have been used in the numerous computational de novo peptide and protein design efforts reported so far. In this review paper, we use the type of templates (i.e., rigid or flexible) as a criterion to classify and review examples of successes in de novo protein design. For both cases of rigid and flexible templates, we briefly outline the different search methods for exploring the sequence space and quote some notable success examples for each search method. In particular, we divide the case of flexible templates into three subcategories, according to their approaches for incorporating backbone flexibility: (i) discrete rotamers on multiple backbones with fixed backbone assumption for each, (ii) discrete rotamers on a continuum backbone through algebraic parametrization, and (iii) continuum backbone template with continuous ranges of backbone angles.