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

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

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

Development of an Optical Zn2+ Probe Based on a Single Fluorescent Protein

Various fluorescent probes have been developed to reveal the biological functions of intracellular labile Zn2+. Here, we present Green Zinc Probe (GZnP), a novel genetically encoded Zn2+ sensor design based on a single fluorescent protein (single-FP). The GZnP sensor is generated by attaching two zinc fingers (ZF) of the transcription factor Zap1 (ZF1 and ZF2) to the two ends of a circularly permuted green fluorescent protein (cpGFP). Formation of ZF folds induces interaction between the two ZFs, which induces a change in the cpGFP conformation, leading to an increase in fluorescence. A small sensor library is created to include mutations in the ZFs, cpGFP and linkers between ZF and cpGFP to improve signal stability, sensor brightness and dynamic range based on rational protein engineering, and computational design by Rosetta. Using a cell-based library screen, we identify sensor GZnP1, which demonstrates a stable maximum signal, decent brightness (QY = 0.42 at apo state), as well as specific and sensitive response to Zn2+ in HeLa cells (Fmax/Fmin = 2.6, Kd = 58 pM, pH 7.4). The subcellular localizing sensors mito-GZnP1 (in mitochondria matrix) and Lck-GZnP1 (on plasma membrane) display sensitivity to Zn2+ (Fmax/Fmin = 2.2). This sensor design provides freedom to be used in combination with other optical indicators and optogenetic tools for simultaneous imaging and advancing our understanding of cellular Zn2+ function

Normal metabolism but different physical properties of myelin from mice deficient in proteolipid protein

Proteolipid protein (PLP) is the primary protein component of CNS myelin, yet myelin from the PLPnull mouse has only minor ultrastructural abnormalities. Might compensation for a potentially unstable structure involve increased myelin synthesis and turnover? This was not the case; neither accumulation nor in vivo synthesis rates for the myelin- specific lipid cerebroside was altered in PLPnull mice relative to wild-type (wt) animals. However, the yield of myelin from PLPnull mice, assayed as levels of cerebroside, was only about 55% of wt control levels. Loss of myelin occurred during initial centrifugation of brain homogenate at 20,000g for 20 min, which is sufficient to sediment almost all myelin from wt mice. Cerebroside-containing fragments from PLPnull mice remaining in the supernatant could be sedimented by more stringent centrifugation, 100,000g for 60 min. Both the rapidly. and the more slowly sedimenting cerebroside-containing membranes banded at the 0.85/0.32 M sucrose interface of a density gradient, as did myelin from wt mice. These results suggest at least some myelin from PLPnull mice differs from wt myelin with respect to physical stability (fragmented into smaller particles during dispersion) and/or density. Alternatively, slowly sedimenting cerebroside-containing particles could be myelin precursor membranes that, lacking PLP, were retarded in their processing toward mature myelin and thus differ from mature myelin in physical properties. If this is so, recently synthesized cerebroside should be preferentially found in these "slower-sedimenting" myelin precursor fragments. Metabolic tracer experiments showed this was not the case. We conclude that PLPnull myelin is physically less stable and/or less dense than wt myelin. (C) 2003 Wiley- Liss, Inc

Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms.

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions

Development of an Optical Zn²⁺ Probe Based on a Single Fluorescent Protein

Various fluorescent probes have been developed to reveal the biological functions of intracellular labile Zn²⁺. Here, we present Green Zinc Probe (GZnP), a novel genetically encoded Zn²⁺ sensor design based on a single fluorescent protein (single-FP). The GZnP sensor is generated by attaching two zinc fingers (ZF) of the transcription factor Zap1 (ZF1 and ZF2) to the two ends of a circularly permuted green fluorescent protein (cpGFP). Formation of ZF folds induces interaction between the two ZFs, which induces a change in the cpGFP conformation, leading to an increase in fluorescence. A small sensor library is created to include mutations in the ZFs, cpGFP and linkers between ZF and cpGFP to improve signal stability, sensor brightness and dynamic range based on rational protein engineering, and computational design by Rosetta. Using a cell-based library screen, we identify sensor GZnP1, which demonstrates a stable maximum signal, decent brightness (QY = 0.42 at apo state), as well as specific and sensitive response to Zn²⁺ in HeLa cells (<i>F</i>_max/<i>F</i>_min = 2.6, <i>K</i>_d = 58 pM, pH 7.4). The subcellular localizing sensors mito-GZnP1 (in mitochondria matrix) and Lck-GZnP1 (on plasma membrane) display sensitivity to Zn²⁺ (<i>F</i>_max/<i>F</i>_min = 2.2). This sensor design provides freedom to be used in combination with other optical indicators and optogenetic tools for simultaneous imaging and advancing our understanding of cellular Zn²⁺ function