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

Trauma-Informed Measurement-Based Care for Children: Implementation in Diverse Treatment Settings

Ongoing and comprehensive assessment is a critical part of the implementation of evidence-based care; yet, most providers fail to routinely incorporate measurement into their clinical practice. Few studies have focused on the complex application of routine assessment or measurement-based care (MBC) with children. This pilot examined the acceptability, appropriateness, adoptability, and feasibility of an MBC effort, the Clinical Improvement through Measurement Initiative (CIMI), across several child-serving settings (e.g., community mental health center, residential treatment facility). CIMI includes a comprehensive mental health assessment protocol and combines a mobile technology platform with implementation support. Survey and focus group information, assessing implementation constructs and outcomes, was collected from 44 clinicians and staff. Overall, participants agreed that the implementation process and technology were acceptable, appropriate, and feasible for use in child mental health and that CIMI can be used to guide case conceptualization, facilitate treatment planning, and monitor outcomes. Strategies that supported the implementation process were identified as were recommendations to enhance adoption. Significant differences were observed by Community versus Specialized settings with respect to feasibility and appropriateness, likely because of factors associated with inner setting (climate, compatibility), outer setting (patient needs), and the phase of implementation achieved by sites. Implications and recommendations for tailoring MBC implementation by characteristics related to setting are discussed. MBC across child service settings are discussed in the context of implementation frameworks. (PsycInfo Database Record (c) 2020 APA, all rights reserved)

G Protein Mono-ubiquitination by the Rsp5 Ubiquitin Ligase*S⃞

Emerging evidence suggests that ubiquitination serves as a protein trafficking signal in addition to its well characterized role in promoting protein degradation. The yeast G protein α subunit Gpa1 represents a rare example of a protein that undergoes both mono- and poly-ubiquitination. Whereas mono-ubiquitinated Gpa1 is targeted to the vacuole, poly-ubiquitinated Gpa1 is directed instead to the proteasome. Here we investigate the structural requirements for mono- and poly-ubiquitination of Gpa1. We find that variants of Gpa1 engineered to be unstable are more likely to be poly-ubiquitinated and less likely to be mono-ubiquitinated. In addition, mutants that cannot be myristoylated are no longer mono-ubiquitinated but are still polyubiquitinated. Finally, we show that the ubiquitin ligase Rsp5 is necessary for Gpa1 mono-ubiquitination in vivo and that the purified enzyme is sufficient to catalyze Gpa1 mono-ubiquitination in vitro. Taken together, these data indicate that mono- and poly-ubiquitination have distinct enzyme and substrate recognition requirements; whereas poly-ubiquitination targets misfolded protein for degradation, a distinct ubiquitination apparatus targets the fully mature, fully myristoylated G protein for mono-ubiquitination and delivery to the vacuole