Chiral evasion and stereospecific antifolate resistance in Staphylococcus aureus.

Antimicrobial resistance presents a significant health care crisis. The mutation F98Y in Staphylococcus aureus dihydrofolate reductase (SaDHFR) confers resistance to the clinically important antifolate trimethoprim (TMP). Propargyl-linked antifolates (PLAs), next generation DHFR inhibitors, are much more resilient than TMP against this F98Y variant, yet this F98Y substitution still reduces efficacy of these agents. Surprisingly, differences in the enantiomeric configuration at the stereogenic center of PLAs influence the isomeric state of the NADPH cofactor. To understand the molecular basis of F98Y-mediated resistance and how PLAs' inhibition drives NADPH isomeric states, we used protein design algorithms in the osprey protein design software suite to analyze a comprehensive suite of structural, biophysical, biochemical, and computational data. Here, we present a model showing how F98Y SaDHFR exploits a different anomeric configuration of NADPH to evade certain PLAs' inhibition, while other PLAs remain unaffected by this resistance mechanism.

Factors associated with caretakers' knowledge, attitude, and practices in the management of pneumonia for children aged five years and below in rural Uganda.

BACKGROUND: Efforts aimed at reducing morbidity and mortality associated with pneumonia in children aged five years and below largely depend on caretakers. This study aimed to assess the factors associated with knowledge, attitudes, and practices of caretakers regarding pneumonia. METHODS: This was a cross-sectional study carried out within Iganga and Mayuge health and demographic surveillance site (IMHDSS) cohort in Eastern Uganda. Caretakers of children under the age of five years were assessed for knowledge, attitudes, and practices using a set of indicators. The caretaker characteristics as determinants for knowledge, attitude, and practices in relation to pneumonia management were assessed for association. Logistic regression was used to assess the factors associated with caretaker knowledge, attitudes and practices. RESULTS: A total of 649 caretakers of children five years and below of age were interviewed. Caretakers knew pneumonia as one of the childhood diseases, but were less knowledgeable about its transmission, signs and symptoms, risk factors and treatment. Overall, 28% had good knowledge, 36% had moderate knowledge and 35% had poor knowledge. The caretaker attitude was good for more than a half of the respondents (57%), while majority reported good practices (74.1%). Older age (OR = 1.63, 95% CI (1.05-2.51)), Tertiary education (OR = 4.92, 95% CI (2.5-9.65)), being married (OR = 1.82, 95% CI (1.05-3.15)) were associated with having good knowledge. Age above 35 years (aOR = 1.48, 95% CI (1.03-2.11)), and main source of livelihood were associated with good attitude and lastly being female (OR = 2.3, 95% CI (1.23-4.37)), being a Muslim (aOR = 0.5, 95% CI (0.35-0.75)), and being a farmer (OR = 0.5, 95% CI (0.33-0.85)) were associated with being a good caretaker practice. CONCLUSIONS: The caretakers of children five years and below, have relatively adequate knowledge about the signs and symptoms of pneumonia, risk factors and treatment measures. Higher education, being married, and being a salary earner were associated with better knowledge about pneumonia, while being female, being a Muslim, and being a peasant farmer were associated with good practice. Targeted interventions to equip caretakers with relevant and adequate skills and knowledge for lower-income and less educated caretakers, considering cultural and religious beliefs about childhood pneumonia identification and management are required.

Meaningful coproduction with clinicians: establishing a practice-based research network with physiotherapists in regional Australia.

BACKGROUND: The disconnect between research and clinical practice leads to research evidence that is often not useful for clinical practice. Practice-based research networks are collaborations between researchers and clinicians aimed at coproducing more useful research. Such networks are rare in the physiotherapy field. We aimed to describe (i) clinicians' motivations behind, and enablers to, participating in a network, (ii) the process of network establishment and (iii) research priorities for a practice-based network of physiotherapists in the Hunter Region of New South Wales (NSW), Australia that supports research coproduction. METHODS: We describe the methods and outcomes of the three steps we used to establish the network. Step 1 involved consultation with local opinion leaders and a formative evaluation to understand clinicians' motivations behind, and enablers to, participating in a network. Step 2 involved establishment activities to generate a founding membership group and codesign a governance model. Step 3 involved mapping clinical problems through a workshop guided by systems thinking theory with local stakeholders and prioritizing research areas. RESULTS: Through formative evaluation focus groups, we generated five key motivating themes and three key enablers for physiotherapists' involvement in the network. Establishment activities led to a founding membership group (n = 29, 67% from private practice clinics), a network vision and mission statement, and a joint governance group (9/13 [70%] are private practice clinicians). Our problem-mapping and prioritization process led to three clinically relevant priority research areas with the potential for significant change in practice and patient outcomes. CONCLUSIONS: Clinicians are motivated to break down traditional siloed research generation and collaborate with researchers to solve a wide array of issues with the delivery of care. Practice-based research networks have promise for both researchers and clinicians in the common goal of improving patient outcomes.

Physiotherapists' opinions, barriers, and enablers to providing evidence-based care: a mixed-methods study.

BACKGROUND: Physiotherapists deliver evidence-based guideline recommended treatments only half of the time to patients with musculoskeletal conditions. Physiotherapists' behaviour in clinical practice are influenced by many cognitive, social, and environmental factors including time and financial pressures. Many initiatives aimed at improving physiotherapists' uptake of evidence-based care have failed to appreciate the context involved in clinical decisions and clinical practice. Therefore, we aimed to describe: i) opinions toward evidence; ii) how evidence is accessed; iii) factors influencing evidence access; iv) factors influencing evidence application, for physiotherapists working in regional areas. METHODS: We used a mixed-methods study with online survey and focus groups. We included registered physiotherapists in the survey and physiotherapists practising in regional New South Wales in the focus groups. Quantitative and qualitative data were used to inform all research objectives. We used eight domains of the Transtheoretical Domains Framework to design survey questions. We analysed quantitative and qualitative data in parallel, then integrated both sources through by developing a matrix while considering the Transtheoretical Domains Framework domains to generate themes. RESULTS: Fifty-seven physiotherapists participated in the study (survey only n = 41; focus group only n = 8; both survey and focus group n = 8). Participants reported that evidence was important, but they also considered patient expectations, colleagues' treatment choices, and business demands in clinical decision making. Physiotherapists reported they access evidence on average 30 minutes or less per week. Competing demands like business administration tasks are barriers to accessing evidence. Participants reported that patient expectations were a major barrier to applying evidence in practice. Environmental and systemic factors, like funding structures or incentives for evidence-based care, and social factors, like lacking or having a culture of accountability and mentorship, were reported as both barriers and enablers to evidence application. CONCLUSIONS: This study provides context to physiotherapists' opinion, access, and application of evidence in clinical practice. Physiotherapists' provision of evidence-based care may be improved by enhancing structural support from workplaces to access and apply evidence and exploring discrepancies between physiotherapists' perceptions of patient expectations and actual patient expectations.

Novel, provable algorithms for efficient ensemble-based computational protein design and their application to the redesign of the c-Raf-RBD:KRas protein-protein interface.

The K* algorithm provably approximates partition functions for a set of states (e.g., protein, ligand, and protein-ligand complex) to a user-specified accuracy ε. Often, reaching an ε-approximation for a particular set of partition functions takes a prohibitive amount of time and space. To alleviate some of this cost, we introduce two new algorithms into the osprey suite for protein design: fries, a Fast Removal of Inadequately Energied Sequences, and EWAK*, an Energy Window Approximation to K*. fries pre-processes the sequence space to limit a design to only the most stable, energetically favorable sequence possibilities. EWAK* then takes this pruned sequence space as input and, using a user-specified energy window, calculates K* scores using the lowest energy conformations. We expect fries/EWAK* to be most useful in cases where there are many unstable sequences in the design sequence space and when users are satisfied with enumerating the low-energy ensemble of conformations. In combination, these algorithms provably retain calculational accuracy while limiting the input sequence space and the conformations included in each partition function calculation to only the most energetically favorable, effectively reducing runtime while still enriching for desirable sequences. This combined approach led to significant speed-ups compared to the previous state-of-the-art multi-sequence algorithm, BBK*, while maintaining its efficiency and accuracy, which we show across 40 different protein systems and a total of 2,826 protein design problems. Additionally, as a proof of concept, we used these new algorithms to redesign the protein-protein interface (PPI) of the c-Raf-RBD:KRas complex. The Ras-binding domain of the protein kinase c-Raf (c-Raf-RBD) is the tightest known binder of KRas, a protein implicated in difficult-to-treat cancers. fries/EWAK* accurately retrospectively predicted the effect of 41 different sets of mutations in the PPI of the c-Raf-RBD:KRas complex. Notably, these mutations include mutations whose effect had previously been incorrectly predicted using other computational methods. Next, we used fries/EWAK* for prospective design and discovered a novel point mutation that improves binding of c-Raf-RBD to KRas in its active, GTP-bound state (KRasGTP). We combined this new mutation with two previously reported mutations (which were highly-ranked by osprey) to create a new variant of c-Raf-RBD, c-Raf-RBD(RKY). fries/EWAK* in osprey computationally predicted that this new variant binds even more tightly than the previous best-binding variant, c-Raf-RBD(RK). We measured the binding affinity of c-Raf-RBD(RKY) using a bio-layer interferometry (BLI) assay, and found that this new variant exhibits single-digit nanomolar affinity for KRasGTP, confirming the computational predictions made with fries/EWAK*. This new variant binds roughly five times more tightly than the previous best known binder and roughly 36 times more tightly than the design starting point (wild-type c-Raf-RBD). This study steps through the advancement and development of computational protein design by presenting theory, new algorithms, accurate retrospective designs, new prospective designs, and biochemical validation.

Minimal NMR distance information for rigidity of protein graphs.

Nuclear Magnetic Resonance (NMR) experiments provide distances between nearby atoms of a protein molecule. The corresponding structure determination problem is to determine the 3D protein structure by exploiting such distances. We present a new order on the atoms of the protein, based on information from the chemistry of proteins and NMR experiments, which allows us to formulate the problem as a combinatorial search. Additionally, this order tells us what kind of NMR distance information is crucial to understand the cardinality of the solution set of the problem and its computational complexity.

OSPREY 3.0: Open-source protein redesign for you, with powerful new features.

We present osprey 3.0, a new and greatly improved release of the osprey protein design software. Osprey 3.0 features a convenient new Python interface, which greatly improves its ease of use. It is over two orders of magnitude faster than previous versions of osprey when running the same algorithms on the same hardware. Moreover, osprey 3.0 includes several new algorithms, which introduce substantial speedups as well as improved biophysical modeling. It also includes GPU support, which provides an additional speedup of over an order of magnitude. Like previous versions of osprey, osprey 3.0 offers a unique package of advantages over other design software, including provable design algorithms that account for continuous flexibility during design and model conformational entropy. Finally, we show here empirically that osprey 3.0 accurately predicts the effect of mutations on protein-protein binding. Osprey 3.0 is available at http://www.cs.duke.edu/donaldlab/osprey.php as free and open-source software. © 2018 Wiley Periodicals, Inc.

CATS (Coordinates of Atoms by Taylor Series): protein design with backbone flexibility in all locally feasible directions.

MOTIVATION: When proteins mutate or bind to ligands, their backbones often move significantly, especially in loop regions. Computational protein design algorithms must model these motions in order to accurately optimize protein stability and binding affinity. However, methods for backbone conformational search in design have been much more limited than for sidechain conformational search. This is especially true for combinatorial protein design algorithms, which aim to search a large sequence space efficiently and thus cannot rely on temporal simulation of each candidate sequence. RESULTS: We alleviate this difficulty with a new parameterization of backbone conformational space, which represents all degrees of freedom of a specified segment of protein chain that maintain valid bonding geometry (by maintaining the original bond lengths and angles and ω dihedrals). In order to search this space, we present an efficient algorithm, CATS, for computing atomic coordinates as a function of our new continuous backbone internal coordinates. CATS generalizes the iMinDEE and EPIC protein design algorithms, which model continuous flexibility in sidechain dihedrals, to model continuous, appropriately localized flexibility in the backbone dihedrals ϕ and ψ as well. We show using 81 test cases based on 29 different protein structures that CATS finds sequences and conformations that are significantly lower in energy than methods with less or no backbone flexibility do. In particular, we show that CATS can model the viability of an antibody mutation known experimentally to increase affinity, but that appears sterically infeasible when modeled with less or no backbone flexibility. AVAILABILITY AND IMPLEMENTATION: Our code is available as free software at https://github.com/donaldlab/OSPREY_refactor . CONTACT: mhallen@ttic.edu or brd+ismb17@cs.duke.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A critical analysis of computational protein design with sparse residue interaction graphs.

Protein design algorithms enumerate a combinatorial number of candidate structures to compute the Global Minimum Energy Conformation (GMEC). To efficiently find the GMEC, protein design algorithms must methodically reduce the conformational search space. By applying distance and energy cutoffs, the protein system to be designed can thus be represented using a sparse residue interaction graph, where the number of interacting residue pairs is less than all pairs of mutable residues, and the corresponding GMEC is called the sparse GMEC. However, ignoring some pairwise residue interactions can lead to a change in the energy, conformation, or sequence of the sparse GMEC vs. the original or the full GMEC. Despite the widespread use of sparse residue interaction graphs in protein design, the above mentioned effects of their use have not been previously analyzed. To analyze the costs and benefits of designing with sparse residue interaction graphs, we computed the GMECs for 136 different protein design problems both with and without distance and energy cutoffs, and compared their energies, conformations, and sequences. Our analysis shows that the differences between the GMECs depend critically on whether or not the design includes core, boundary, or surface residues. Moreover, neglecting long-range interactions can alter local interactions and introduce large sequence differences, both of which can result in significant structural and functional changes. Designs on proteins with experimentally measured thermostability show it is beneficial to compute both the full and the sparse GMEC accurately and efficiently. To this end, we show that a provable, ensemble-based algorithm can efficiently compute both GMECs by enumerating a small number of conformations, usually fewer than 1000. This provides a novel way to combine sparse residue interaction graphs with provable, ensemble-based algorithms to reap the benefits of sparse residue interaction graphs while avoiding their potential inaccuracies.

Protein design algorithms predict viable resistance to an experimental antifolate.

Methods to accurately predict potential drug target mutations in response to early-stage leads could drive the design of more resilient first generation drug candidates. In this study, a structure-based protein design algorithm (K* in the OSPREY suite) was used to prospectively identify single-nucleotide polymorphisms that confer resistance to an experimental inhibitor effective against dihydrofolate reductase (DHFR) from Staphylococcus aureus. Four of the top-ranked mutations in DHFR were found to be catalytically competent and resistant to the inhibitor. Selection of resistant bacteria in vitro reveals that two of the predicted mutations arise in the background of a compensatory mutation. Using enzyme kinetics, microbiology, and crystal structures of the complexes, we determined the fitness of the mutant enzymes and strains, the structural basis of resistance, and the compensatory relationship of the mutations. To our knowledge, this work illustrates the first application of protein design algorithms to prospectively predict viable resistance mutations that arise in bacteria under antibiotic pressure.

Structure of an HIV-1-neutralizing antibody target, the lipid-bound gp41 envelope membrane proximal region trimer.

The membrane proximal external region (MPER) of HIV-1 glycoprotein (gp) 41 is involved in viral-host cell membrane fusion. It contains short amino acid sequences that are binding sites for the HIV-1 broadly neutralizing antibodies 2F5, 4E10, and 10E8, making these binding sites important targets for HIV-1 vaccine development. We report a high-resolution structure of a designed MPER trimer assembled on a detergent micelle. The NMR solution structure of this trimeric domain, designated gp41-M-MAT, shows that the three MPER peptides each adopt symmetric α-helical conformations exposing the amino acid side chains of the antibody binding sites. The helices are closely associated at their N termini, bend between the 2F5 and 4E10 epitopes, and gradually separate toward the C termini, where they associate with the membrane. The mAbs 2F5 and 4E10 bind gp41-M-MAT with nanomolar affinities, consistent with the substantial exposure of their respective epitopes in the trimer structure. The traditional structure determination of gp41-M-MAT using the Xplor-NIH protocol was validated by independently determining the structure using the DISCO sparse-data protocol, which exploits geometric arrangement algorithms that guarantee to compute all structures and assignments that satisfy the data.

Fast search algorithms for computational protein design.

One of the main challenges in computational protein design (CPD) is the huge size of the protein sequence and conformational space that has to be computationally explored. Recently, we showed that state-of-the-art combinatorial optimization technologies based on Cost Function Network (CFN) processing allow speeding up provable rigid backbone protein design methods by several orders of magnitudes. Building up on this, we improved and injected CFN technology into the well-established CPD package Osprey to allow all Osprey CPD algorithms to benefit from associated speedups. Because Osprey fundamentally relies on the ability of A* to produce conformations in increasing order of energy, we defined new A* strategies combining CFN lower bounds, with new side-chain positioning-based branching scheme. Beyond the speedups obtained in the new A*-CFN combination, this novel branching scheme enables a much faster enumeration of suboptimal sequences, far beyond what is reachable without it. Together with the immediate and important speedups provided by CFN technology, these developments directly benefit to all the algorithms that previously relied on the DEE/ A* combination inside Osprey* and make it possible to solve larger CPD problems with provable algorithms.

Improved energy bound accuracy enhances the efficiency of continuous protein design.

Flexibility and dynamics are important for protein function and a protein's ability to accommodate amino acid substitutions. However, when computational protein design algorithms search over protein structures, the allowed flexibility is often reduced to a relatively small set of discrete side-chain and backbone conformations. While simplifications in scoring functions and protein flexibility are currently necessary to computationally search the vast protein sequence and conformational space, a rigid representation of a protein causes the search to become brittle and miss low-energy structures. Continuous rotamers more closely represent the allowed movement of a side chain within its torsional well and have been successfully incorporated into the protein design framework to design biomedically relevant protein systems. The use of continuous rotamers in protein design enables algorithms to search a larger conformational space than previously possible, but adds additional complexity to the design search. To design large, complex systems with continuous rotamers, new algorithms are needed to increase the efficiency of the search. We present two methods, PartCR and HOT, that greatly increase the speed and efficiency of protein design with continuous rotamers. These methods specifically target the large errors in energetic terms that are used to bound pairwise energies during the design search. By tightening the energy bounds, additional pruning of the conformation space can be achieved, and the number of conformations that must be enumerated to find the global minimum energy conformation is greatly reduced.

Systematic solution to homo-oligomeric structures determined by NMR.

Protein structure determination by NMR has predominantly relied on simulated annealing-based conformational search for a converged fold using primarily distance constraints, including constraints derived from nuclear Overhauser effects, paramagnetic relaxation enhancement, and cysteine crosslinkings. Although there is no guarantee that the converged fold represents the global minimum of the conformational space, it is generally accepted that good convergence is synonymous to the global minimum. Here, we show such a criterion breaks down in the presence of large numbers of ambiguous constraints from NMR experiments on homo-oligomeric protein complexes. A systematic evaluation of the conformational solutions that satisfy the NMR constraints of a trimeric membrane protein, DAGK, reveals 9 distinct folds, including the reported NMR and crystal structures. This result highlights the fundamental limitation of global fold determination for homo-oligomeric proteins using ambiguous distance constraints and provides a systematic solution for exhaustive enumeration of all satisfying solutions.

Fast gap-free enumeration of conformations and sequences for protein design.

Despite significant successes in structure-based computational protein design in recent years, protein design algorithms must be improved to increase the biological accuracy of new designs. Protein design algorithms search through an exponential number of protein conformations, protein ensembles, and amino acid sequences in an attempt to find globally optimal structures with a desired biological function. To improve the biological accuracy of protein designs, it is necessary to increase both the amount of protein flexibility allowed during the search and the overall size of the design, while guaranteeing that the lowest-energy structures and sequences are found. DEE/A*-based algorithms are the most prevalent provable algorithms in the field of protein design and can provably enumerate a gap-free list of low-energy protein conformations, which is necessary for ensemble-based algorithms that predict protein binding. We present two classes of algorithmic improvements to the A* algorithm that greatly increase the efficiency of A*. First, we analyze the effect of ordering the expansion of mutable residue positions within the A* tree and present a dynamic residue ordering that reduces the number of A* nodes that must be visited during the search. Second, we propose new methods to improve the conformational bounds used to estimate the energies of partial conformations during the A* search. The residue ordering techniques and improved bounds can be combined for additional increases in A* efficiency. Our enhancements enable all A*-based methods to more fully search protein conformation space, which will ultimately improve the accuracy of complex biomedically relevant designs.

Enhanced potency of a broadly neutralizing HIV-1 antibody in vitro improves protection against lentiviral infection in vivo.

UNLABELLED: Over the past 5 years, a new generation of highly potent and broadly neutralizing HIV-1 antibodies has been identified. These antibodies can protect against lentiviral infection in nonhuman primates (NHPs), suggesting that passive antibody transfer would prevent HIV-1 transmission in humans. To increase the protective efficacy of such monoclonal antibodies, we employed next-generation sequencing, computational bioinformatics, and structure-guided design to enhance the neutralization potency and breadth of VRC01, an antibody that targets the CD4 binding site of the HIV-1 envelope. One variant, VRC07-523, was 5- to 8-fold more potent than VRC01, neutralized 96% of viruses tested, and displayed minimal autoreactivity. To compare its protective efficacy to that of VRC01 in vivo, we performed a series of simian-human immunodeficiency virus (SHIV) challenge experiments in nonhuman primates and calculated the doses of VRC07-523 and VRC01 that provide 50% protection (EC50). VRC07-523 prevented infection in NHPs at a 5-fold lower concentration than VRC01. These results suggest that increased neutralization potency in vitro correlates with improved protection against infection in vivo, documenting the improved functional efficacy of VRC07-523 and its potential clinical relevance for protecting against HIV-1 infection in humans. IMPORTANCE: In the absence of an effective HIV-1 vaccine, alternative strategies are needed to block HIV-1 transmission. Direct administration of HIV-1-neutralizing antibodies may be able to prevent HIV-1 infections in humans. This approach could be especially useful in individuals at high risk for contracting HIV-1 and could be used together with antiretroviral drugs to prevent infection. To optimize the chance of success, such antibodies can be modified to improve their potency, breadth, and in vivo half-life. Here, knowledge of the structure of a potent neutralizing antibody, VRC01, that targets the CD4-binding site of the HIV-1 envelope protein was used to engineer a next-generation antibody with 5- to 8-fold increased potency in vitro. When administered to nonhuman primates, this antibody conferred protection at a 5-fold lower concentration than the original antibody. Our studies demonstrate an important correlation between in vitro assays used to evaluate the therapeutic potential of antibodies and their in vivo effectiveness.

An efficient parallel algorithm for accelerating computational protein design.

MOTIVATION: Structure-based computational protein design (SCPR) is an important topic in protein engineering. Under the assumption of a rigid backbone and a finite set of discrete conformations of side-chains, various methods have been proposed to address this problem. A popular method is to combine the dead-end elimination (DEE) and A* tree search algorithms, which provably finds the global minimum energy conformation (GMEC) solution. RESULTS: In this article, we improve the efficiency of computing A* heuristic functions for protein design and propose a variant of A* algorithm in which the search process can be performed on a single GPU in a massively parallel fashion. In addition, we make some efforts to address the memory exceeding problem in A* search. As a result, our enhancements can achieve a significant speedup of the A*-based protein design algorithm by four orders of magnitude on large-scale test data through pre-computation and parallelization, while still maintaining an acceptable memory overhead. We also show that our parallel A* search algorithm could be successfully combined with iMinDEE, a state-of-the-art DEE criterion, for rotamer pruning to further improve SCPR with the consideration of continuous side-chain flexibility. AVAILABILITY: Our software is available and distributed open-source under the GNU Lesser General License Version 2.1 (GNU, February 1999). The source code can be downloaded from http://www.cs.duke.edu/donaldlab/osprey.php or http://iiis.tsinghua.edu.cn/∼compbio/software.html.

Managing the Risk of Occupational Allergy in the Enzyme Detergent Industry.

Enzyme proteins have potential to cause occupational allergy/asthma. Consequently, as users of enzymes in formulated products, detergents manufacturers have implemented a number of control measures to ensure that the hazard does not translate into health effects in the workforce. To that end, trade associations have developed best practice guidelines which emphasize occupational hygiene and medical monitoring as part of an effective risk management strategy. The need for businesses to recognize the utility of this guidance is reinforced by reports where factories which have failed to follow good industrial hygiene practices have given rise to incidences of occupational allergy. In this article, an overview is provided of how the industry guidelines are actually implemented in practice and what experience is to be derived therefrom. Both medical surveillance and air monitoring practices associated with the implementation of industry guidelines at approximately 100 manufacturing facilities are examined. The data show that by using the approaches described for the limitation of exposure, for the provision of good occupational hygiene and for the active monitoring of health, the respiratory allergenic risk associated with enzyme proteins can be successfully managed. This therefore represents an approach that could be recommended to other industries contemplating working with enzymes.

DexDesign: A new OSPREY-based algorithm for designing de novo D-peptide inhibitors.

With over 270 unique occurrences in the human genome, peptide-recognizing PDZ domains play a central role in modulating polarization, signaling, and trafficking pathways. Mutations in PDZ domains lead to diseases such as cancer and cystic fibrosis, making PDZ domains attractive targets for therapeutic intervention. D-peptide inhibitors offer unique advantages as therapeutics, including increased metabolic stability and low immunogenicity. Here, we introduce DexDesign, a novel OSPREY-based algorithm for computationally designing de novo D-peptide inhibitors. DexDesign leverages three novel techniques that are broadly applicable to computational protein design: the Minimum Flexible Set, K*-based Mutational Scan, and Inverse Alanine Scan, which enable exponential reductions in the size of the peptide sequence search space. We apply these techniques and DexDesign to generate novel D-peptide inhibitors of two biomedically important PDZ domain targets: CAL and MAST2. We introduce a new framework for analyzing de novo peptides-evaluation along a replication/restitution axis-and apply it to the DexDesign-generated D-peptides. Notably, the peptides we generated are predicted to bind their targets tighter than their targets' endogenous ligands, validating the peptides' potential as lead therapeutic candidates. We provide an implementation of DexDesign in the free and open source computational protein design software OSPREY.