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1.  A Rotamer Library to Enable Modeling and Design of Peptoid Foldamers 
Peptoids are a family of synthetic oligomers composed of N-substituted glycine units. Along with other “foldamer” systems, peptoid oligomer sequences can be predictably designed to form a variety of stable secondary structures. It is not yet evident if foldamer design can be extended to reliably create tertiary structure features that mimic more complex biomolecular folds and functions. Computational modeling and prediction of peptoid conformations will likely play a critical role in enabling complex biomimetic designs. We introduce a computational approach to provide accurate conformational and energetic parameters for peptoid side chains needed for successful modeling and design. We find that peptoids can be described by a “rotamer” treatment, similar to that established for proteins, in which the peptoid side chains display rotational isomerism to populate discrete regions of the conformational landscape. Because of the insufficient number of solved peptoid structures, we have calculated the relative energies of side-chain conformational states to provide a backbone-dependent (BBD) rotamer library for a set of 54 different peptoid side chains. We evaluated two rotamer library development methods that employ quantum mechanics (QM) and/or molecular mechanics (MM) energy calculations to identify side-chain rotamers. We show by comparison to experimental peptoid structures that both methods provide an accurate prediction of peptoid side chain placements in folded peptoid oligomers and at protein interfaces. We have incorporated our peptoid rotamer libraries into ROSETTA, a molecular design package previously validated in the context of protein design and structure prediction.
PMCID: PMC4227732  PMID: 24823488
2.  Adding Diverse Noncanonical Backbones to Rosetta: Enabling Peptidomimetic Design 
PLoS ONE  2013;8(7):e67051.
Peptidomimetics are classes of molecules that mimic structural and functional attributes of polypeptides. Peptidomimetic oligomers can frequently be synthesized using efficient solid phase synthesis procedures similar to peptide synthesis. Conformationally ordered peptidomimetic oligomers are finding broad applications for molecular recognition and for inhibiting protein-protein interactions. One critical limitation is the limited set of design tools for identifying oligomer sequences that can adopt desired conformations. Here, we present expansions to the ROSETTA platform that enable structure prediction and design of five non-peptidic oligomer scaffolds (noncanonical backbones), oligooxopiperazines, oligo-peptoids, -peptides, hydrogen bond surrogate helices and oligosaccharides. This work is complementary to prior additions to model noncanonical protein side chains in ROSETTA. The main purpose of our manuscript is to give a detailed description to current and future developers of how each of these noncanonical backbones was implemented. Furthermore, we provide a general outline for implementation of new backbone types not discussed here. To illustrate the utility of this approach, we describe the first tests of the ROSETTA molecular mechanics energy function in the context of oligooxopiperazines, using quantum mechanical calculations as comparison points, scanning through backbone and side chain torsion angles for a model peptidomimetic. Finally, as an example of a novel design application, we describe the automated design of an oligooxopiperazine that inhibits the p53-MDM2 protein-protein interaction. For the general biological and bioengineering community, several noncanonical backbones have been incorporated into web applications that allow users to freely and rapidly test the presented protocols ( This work helps address the peptidomimetic community's need for an automated and expandable modeling tool for noncanonical backbones.
PMCID: PMC3712014  PMID: 23869206
3.  Computational Design of the Sequence and Structure of a Protein-Binding Peptide 
The de novo design of protein-binding peptides is challenging, because it requires identifying both a sequence and a backbone conformation favorable for binding. We used a computational strategy that iterates between structure and sequence optimization to redesign the C-terminal portion of the RGS14 GoLoco motif peptide so that it adopts a new conformation when bound to Gαi1. An X-ray crystal structure of the redesigned complex closely matches the computational model, with a backbone RMSD of 1.1 Å.
PMCID: PMC3081598  PMID: 21388199
4.  Rational Design of Temperature-Sensitive Alleles Using Computational Structure Prediction 
PLoS ONE  2011;6(9):e23947.
Temperature-sensitive (ts) mutations are mutations that exhibit a mutant phenotype at high or low temperatures and a wild-type phenotype at normal temperature. Temperature-sensitive mutants are valuable tools for geneticists, particularly in the study of essential genes. However, finding ts mutations typically relies on generating and screening many thousands of mutations, which is an expensive and labor-intensive process. Here we describe an in silico method that uses Rosetta and machine learning techniques to predict a highly accurate “top 5” list of ts mutations given the structure of a protein of interest. Rosetta is a protein structure prediction and design code, used here to model and score how proteins accommodate point mutations with side-chain and backbone movements. We show that integrating Rosetta relax-derived features with sequence-based features results in accurate temperature-sensitive mutation predictions.
PMCID: PMC3166291  PMID: 21912654
5.  Computational design of a PAK1 binding protein 
Journal of molecular biology  2010;400(2):257-270.
We describe a computational protocol, called DDMI, for redesigning scaffold proteins to bind to a specified region on a target protein. The DDMI protocol is implemented within the Rosetta molecular modeling program and uses rigid-body docking, sequence design, and gradient-based minimization of backbone and side chain torsion angles to design low energy interfaces between the scaffold and target protein. Iterative rounds of sequence design and conformational optimization were needed to produce models that have calculated binding energies that are similar to binding energies calculated for native complexes. We also show that additional conformation sampling with molecular dynamics can be iterated with sequence design to further lower the computed energy of the designed complexes. To experimentally test the DDMI protocol we redesigned the human hyperplastic discs protein to bind to the kinase domain of p21-activated kinase 1 (PAK1). Six designs were experimentally characterized. Two of the designs aggregated and were not characterized further. Of the remaining four designs, three bound to the PAK1 with affinities tighter than 350 μM. The tightest binding design, named Spider Roll, bound with an affinity of 100 μM. NMR –based structure prediction of Spider Roll based on backbone and 13Cβ chemical shifts using the program CS-ROSETTA indicated that the architecture of human hyperplastic discs protein is preserved. Mutagenesis studies confirmed that Spider Roll binds the target patch on PAK1. Additionally, Spider Roll binds to full length PAK1 in its activated state, but does not bind PAK1 when it forms an auto-inhibited conformation that blocks the Spider Roll target site. Subsequent NMR characterization of the binding of Spider Roll to PAK1 revealed a comparably small binding `on-rate' constant (<< 105 M−1 s−1). The ability to rationally design the site of novel protein-protein interactions is an important step towards creating new proteins that are useful as therapeutics or molecular probes.
PMCID: PMC2903434  PMID: 20460129
Computational protein design; protein-protein interactions; protein docking; Rosetta molecular modeling program; NMR; CS-ROSETTA
6.  Structural and Functional Studies of A. oryzae Cutinase: Enhanced Thermostability and Hydrolytic Activity of Synthetic Ester and Polyester Degradation 
Journal of the American Chemical Society  2009;131(43):15711-15716.
Cutinases are responsible for hydrolysis of the protective cutin lipid polyester matrix in plants and thus have been exploited for hydrolysis of small molecule esters and polyesters. Here we explore the reactivity, stability, and structure of Aspergillus oryzae cutinase and compare it to the well-studied enzyme from Fusarium solani. Two critical differences are highlighted in the crystallographic analysis of the A. oryzae structure: (i) an additional disulfide bond and (ii) a topologically favored catalytic triad with a continuous and deep groove. These structural features of A. oryzae cutinase are proposed to result in improved hydrolytic activity and altered substrate specificity profile, enhanced thermostability and remarkable reactivity towards the degradation of the synthetic polyester, polycaprolactone. The results presented here provide insight into engineering new cutinase-inspired biocatalysts with tailor-made properties.
PMCID: PMC2796240  PMID: 19810726
A. oryzae; cutinase; hydrolysis; substrate specificity; thermostability; disulfide bond; polyester degradation

Results 1-6 (6)