Classification of Multi-Domain Glycoside Hydrolases to Aid in the Enzymatic Production of Biofuels from Biomass

Biomass conversion to renewable biofuels provides an alternative to conventional fossil-fuel based transportation fuels and a means to reduce dependence on foreign oil. However, plant cell walls have evolved to be quite resistant to enzymatic deconstruction, a phenomenon generally termed biomass recalcitrance. As enzymes represent a substantial cost in biofuels production, there is significant impetus to understand and improve their efficiency in converting cell wall carbohydrates to fermentable sugars. Much research has been conducted on single free enzymes with one catalytic unit per protein and on the much larger, complexed cellulosomes with many tens of catalytic units per protein, but little work has been done on multi-domain enzymes that are an interpolation in size between free enzymes and cellulosomes. A bioinformatics study on multi-domain glycoside hydrolases was conducted to gather information on the various ways each family is found and organized in nature. GH61s, GH6s and GH7s in particular have been classified based on order of protein domain, catalytic domain, carbohydrate binding module, linker length, and origin. It is hoped that this will eventually become a complete database of multi-domain enzymes that will aid in the development of cost-effective methods of lignocellulosic biomass conversion

Computational Redesign of Protein-Protein Interactions

Computational protein modeling predicts and manipulates the biophysical properties of proteins based on their amino acid sequences. Computational protein modeling has been applied to protein-protein and protein-peptide interactions in order to develop research tools as well as protein therapeutics. The intent of our work was to address three areas of protein interface design that are of special interest due to their potential applications. Affinity maturation has been used to improve biosensors as well as potential protein therapeutics. We developed a protocol to predict point mutations that will enhance the binding affinity of protein-protein interactions. Extending this work, we evaluated a protocol designed to increase protein-peptide binding specificity. Redesigning binding specificity can be used to isolate specific protein interactions within complicated signaling networks by limiting the interactions of redesigned proteins with their wild type counterparts and other natural binding partners. Finally, the de novo design of a peptide-protein interaction, or the design of a peptide that will bind a wild type protein, could enable the creation of biosensors or therapeutics from scratch. We take a step towards this goal by redesigning a portion of a peptide backbone in the context of its wild type binding partner

Molecular Dynamics Simulation of Amyloid Beta Dimer Formation

Recent experiments with amyloid-beta (Abeta) peptide suggest that formation of toxic oligomers may be an important contribution to the onset of Alzheimer's disease. The toxicity of Abeta oligomers depends on their structure, which is governed by assembly dynamics. Due to limitations of current experimental techniques, a detailed knowledge of oligomer structure at the atomic level is missing. We introduce a molecular dynamics approach to study Abeta dimer formation: (1) we use discrete molecular dynamics simulations of a coarse-grained model to identify a variety of dimer conformations, and (2) we employ all-atom molecular mechanics simulations to estimate the thermodynamic stability of all dimer conformations. Our simulations of a coarse-grained Abeta peptide model predicts ten different planar beta-strand dimer conformations. We then estimate the free energies of all dimer conformations in all-atom molecular mechanics simulations with explicit water. We compare the free energies of Abeta(1-42) and Abeta(1-40) dimers. We find that (a) all dimer conformations have higher free energies compared to their corresponding monomeric states, and (b) the free energy difference between the Abeta(1-42) and the analogous Abeta(1-40) dimer conformation is not significant. Our results suggest that Abeta oligomerization is not accompanied by the formation of stable planar beta-strand Abeta dimers.Comment: 32 pages (preprint format), 3 figure

Computational design of second-site suppressor mutations at protein-protein interfaces

The importance of a protein-protein interaction to a signaling pathway can be established by showing that amino acid mutations that weaken the interaction disrupt signaling, and that additional mutations that rescue the interaction recover signaling. Identifying rescue mutations, often referred to as second-site suppressor mutations, controls against scenarios in which the initial deleterious mutation inactivates the protein or disrupts alternative protein-protein interactions. Here, we test a structure-based protocol for identifying second-site suppressor mutations that is based on a strategy previously described by Kortemme and Baker. The molecular modeling software Rosetta is used to scan an interface for point mutations that are predicted to weaken binding but can be rescued by mutations on the partner protein. The protocol typically identifies three types of specificity switches: knob-in-to-hole redesigns, switching hydrophobic interactions to hydrogen bond interactions, and replacing polar interactions with non-polar interactions. Computational predictions were tested with two separate protein complexes; the G-protein Gαi1 bound to the RGS14 GoLoco motif, and UbcH7 bound to the ubiquitin ligase E6AP. Eight designs were experimentally tested. Swapping a buried hydrophobic residue with a polar residue dramatically weakened binding affinities. In none of these cases were we able to identify compensating mutations that returned binding to wild type affinity, highlighting the challenges inherent in designing buried hydrogen bond networks. The strongest specificity switches were a knob-in-to-hole design (20-fold) and the replacement of a charge-charge interaction with non-polar interactions (55-fold). In two cases, specificity was further tuned by including mutations distant from the initial design

Combining different design strategies for rational affinity maturation of the MICA‐NKG2D interface

We redesigned residues on the surface of MICA, a protein that binds the homodimeric immunoreceptor NKG2D, to increase binding affinity with a series of rational, incremental changes. A fixed‐backbone RosettaDesign protocol scored a set of initial mutations, which we tested by surface plasmon resonance for thermodynamics and kinetics of NKG2D binding, both singly and in combination. We combined the best four mutations at the surface with three affinity‐enhancing mutations below the binding interface found with a previous design strategy. After curating design scores with three cross‐validated tests, we found a linear relationship between free energy of binding and design score, and to a lesser extent, enthalpy and design score. Multiple mutants bound with substantial subadditivity, but in at least one case full additivity was observed when combining distant mutations. Altogether, combining the best mutations from the two strategies into a septuple mutant enhanced affinity by 50‐fold, to 50 nM, demonstrating a simple, effective protocol for affinity enhancement.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93571/1/PRO_2115_sm_Suppinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/93571/2/2115_ftp.pd

Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi.

Anaerobic fungi (Neocallimastigomycota) are emerging non-model hosts for biotechnology due to their wealth of biomass-degrading enzymes, yet tools to engineer these fungi have not yet been established. Here, we show that the anaerobic gut fungi have the most GC depleted genomes among 443 sequenced organisms in the fungal kingdom, which has ramifications for heterologous expression of genes as well as for emerging CRISPR-based genome engineering approaches. Comparative genomic analyses suggest that anaerobic fungi may contain cellular machinery to aid in sexual reproduction, yet a complete mating pathway was not identified. Predicted proteomes of the anaerobic fungi also contain an unusually large fraction of proteins with homopolymeric amino acid runs consisting of five or more identical consecutive amino acids. In particular, threonine runs are especially enriched in anaerobic fungal carbohydrate active enzymes (CAZymes) and this, together with a high abundance of predicted N-glycosylation motifs, suggests that gut fungal CAZymes are heavily glycosylated, which may impact heterologous production of these biotechnologically useful enzymes. Finally, we present a codon optimization strategy to aid in the development of genetic engineering tools tailored to these early-branching anaerobic fungi

Structure-based Protocol for Identifying Mutations that Enhance Protein–Protein Binding Affinities

The ability to manipulate protein binding affinities is important for the development of proteins as biosensors, industrial reagents, and therapeutics. We have developed a structure-based method to rationally predict single mutations at protein-protein interfaces that enhance binding affinities. The protocol is based on the premise that increasing buried hydrophobic surface area and/or reducing buried hydrophilic surface area will generally lead to enhanced affinity if large steric clashes are not introduced and buried polar groups are not left without a hydrogen bond partner. The procedure selects affinity enhancing point mutations at the protein-protein interface using three criteria: 1) the mutation must be from a polar amino acid to a non-polar amino acid or from a non-polar amino acid to a larger non-polar amino acid, 2) the free energy of binding as calculated with the Rosetta protein modeling program should be more favorable than the free energy of binding calculated for the wild type complex and 3) the mutation should not be predicted to significantly destabilize the monomers. The Rosetta energy function emphasizes short-range interactions: steric repulsion, Van der Waals forces, hydrogen bonding, and an implicit solvation model that penalizes placing atoms adjacent to polar groups. The performance of the computational protocol was experimentally tested on two separate protein complexes; Gαi1 from the heterotrimeric G-protein system bound to the RGS14 GoLoco motif, and the E2, UbcH7, bound to the E3, E6AP from the ubiquitin pathway. 12 single-site mutations that were predicted to be stabilizing were synthesized and characterized in the laboratory. 9 of the 12 mutations successfully increased binding affinity with 5 of these increasing binding by over 1.0 kcal/mol. To further assess our approach we searched the literature for point mutations that pass our criteria and have experimentally determined binding affinities. Of the 8 mutations identified, 5 were accurately predicted to increase binding affinity, further validating the method as a useful tool to increase protein-protein binding affinities

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

Glycosylation Is Vital for Industrial Performance of Hyperactive Cellulases

In the terrestrial biosphere, biomass deconstruction is conducted by microbes employing a variety of complementary strategies, many of which remain to be discovered. Moreover, the biofuels industry seeks more efficient (and less costly) cellulase formulations upon which to launch the nascent sustainable bioenergy economy. The glycan decoration of fungal cellulases has been shown to protect these enzymes from protease action and to enhance binding to cellulose. We show here that thermal tolerant bacterial cellulases are glycosylated as well, although the types and extents of decoration differ from their Eukaryotic counterparts. Our major findings are that glycosylation of CelA is uniform across its three linker peptides and composed of mainly galactose disaccharides (which is unique) and that this glycosylation dramatically impacts the hydrolysis of insoluble substrates, proteolytic and thermal stability, and substrate binding and changes the dynamics of the enzyme. This study suggests that the glycosylation of CelA is crucial for its exceptionally high cellulolytic activity on biomass and provides the robustness needed for this enzyme to function in harsh environments including industrial settings

Design, expression and characterization of mutants of fasciculin optimized for interaction with its target, acetylcholinesterase

Predicting mutations that enhance protein–protein affinity remains a challenging task, especially for high-affinity complexes. To test our capability to improve the affinity of such complexes, we studied interaction of acetylcholinesterase with the snake toxin, fasciculin. Using the program ORBIT, we redesigned fasciculin's sequence to enhance its interactions with Torpedo californica acetylcholinesterase. Mutations were predicted in 5 out of 13 interfacial residues on fasciculin, preserving most of the polar inter-molecular contacts seen in the wild-type toxin/enzyme complex. To experimentally characterize fasciculin mutants, we developed an efficient strategy to over-express the toxin in Escherichia coli, followed by refolding to the native conformation. Despite our predictions, a designed quintuple fasciculin mutant displayed reduced affinity for the enzyme. However, removal of a single mutation in the designed sequence produced a quadruple mutant with improved affinity. Moreover, one designed mutation produced 7-fold enhancement in affinity for acetylcholinesterase. This led us to reassess our criteria for enhancing affinity of the toxin for the enzyme. We observed that the change in the predicted inter-molecular energy, rather than in the total energy, correlates well with the change in the experimental free energy of binding, and hence may serve as a criterion for enhancement of affinity in protein–protein complexes