DexDesign: an 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. 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 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 inhibitors. We also provide an implementation of DexDesign in the free and open source computational protein design software OSPREY.

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.

Impact of State Stroke Systems of Care Laws on Stroke Outcomes.

Since 2003, 38 US states and Washington, DC have adopted legislation and/or regulations to strengthen stroke systems of care (SSOCs). This study estimated the impact of SSOC laws on stroke outcomes. We used a coded legal dataset of 50 states and DC SSOC laws (years 2003-2018), national stroke accreditation information (years 1997-2018), data from the Healthcare Cost and Utilization Project (years 2012-2018), and National Vital Statistics System (years 1979-2019). We applied a natural experimental design paired with longitudinal modeling to estimate the impact of having one or more SSOC policies in effect on outcomes. On average, states with one or more SSOC policies in effect achieved better access to primary stroke centers (PSCs) than expected without SSOC policies (ranging from 2.7 to 8.0 percentage points (PP) higher), lower inpatient hospital costs (USD 610-1724 less per hospital stay), lower age-adjusted stroke mortality (1.0-1.6 fewer annual deaths per 100,000), a higher proportion of stroke patients with brain imaging results within 45 min of emergency department arrival (3.6-5.0 PP higher), and, in some states, lower in-hospital stroke mortality (5 fewer deaths per 1000). Findings were mixed for some outcomes and there was limited evidence of model fit for others. No effect was observed in racial and/or rural disparities in stroke mortality.

Predicting Affinity Through Homology (PATH): Interpretable Binding Affinity Prediction with Persistent Homology.

Accurate binding affinity prediction is crucial to structure-based drug design. Recent work used computational topology to obtain an effective representation of protein-ligand interactions. Although persistent homology encodes geometric features, previous works on binding affinity prediction using persistent homology employed uninterpretable machine learning models and failed to explain the underlying geometric and topological features that drive accurate binding affinity prediction. In this work, we propose a novel, interpretable algorithm for protein-ligand binding affinity prediction. Our algorithm achieves interpretability through an effective embedding of distances across bipartite matchings of the protein and ligand atoms into real-valued functions by summing Gaussians centered at features constructed by persistent homology. We name these functions internuclear persistent contours (IPCs) . Next, we introduce persistence fingerprints , a vector with 10 components that sketches the distances of different bipartite matching between protein and ligand atoms, refined from IPCs. Let the number of protein atoms in the protein-ligand complex be n , number of ligand atoms be m , and ω ≈ 2.4 be the matrix multiplication exponent. We show that for any 0 < ε < 1, after an 𝒪 ( mn log( mn )) preprocessing procedure, we can compute an ε -accurate approximation to the persistence fingerprint in 𝒪 ( m log 6 ω ( m/" )) time, independent of protein size. This is an improvement in time complexity by a factor of 𝒪 (( m + n ) 3 ) over any previous binding affinity prediction that uses persistent homology. We show that the representational power of persistence fingerprint generalizes to protein-ligand binding datasets beyond the training dataset. Then, we introduce PATH , Predicting Affinity Through Homology, an interpretable, small ensemble of shallow regression trees for binding affinity prediction from persistence fingerprints. We show that despite using 1,400-fold fewer features, PATH has comparable performance to a previous state-of-the-art binding affinity prediction algorithm that uses persistent homology features. Moreover, PATH has the advantage of being interpretable. Finally, we visualize the features captured by persistence fingerprint for variant HIV-1 protease complexes and show that persistence fingerprint captures binding-relevant structural mutations. The source code for PATH is released open-source as part of the osprey protein design software package.

Improved HIV-1 neutralization breadth and potency of V2-apex antibodies by in silico design.

Broadly neutralizing antibodies (bNAbs) against HIV can reduce viral transmission in humans, but an effective therapeutic will require unusually high breadth and potency of neutralization. We employ the OSPREY computational protein design software to engineer variants of two apex-directed bNAbs, PGT145 and PG9RSH, resulting in increases in potency of over 100-fold against some viruses. The top designed variants improve neutralization breadth from 39% to 54% at clinically relevant concentrations (IC80 < 1 µg/mL) and improve median potency (IC80) by up to 4-fold over a cross-clade panel of 208 strains. To investigate the mechanisms of improvement, we determine cryoelectron microscopy structures of each variant in complex with the HIV envelope trimer. Surprisingly, we find the largest increases in breadth to be a result of optimizing side-chain interactions with highly variable epitope residues. These results provide insight into mechanisms of neutralization breadth and inform strategies for antibody design and improvement.

Disruptor: Computational identification of oncogenic mutants disrupting protein-protein and protein-DNA interactions.

We report an Osprey-based computational protocol to prospectively identify oncogenic mutations that act via disruption of molecular interactions. It is applicable to analyse both protein-protein and protein-DNA interfaces and it is validated on a dataset of clinically relevant mutations. In addition, it is used to predict previously uncharacterised patient mutations in CDK6 and p16 genes, which are experimentally confirmed to impair complex formation.

Discovery, characterization, and redesign of potent antimicrobial thanatin orthologs from Chinavia ubica and Murgantia histrionica targeting E. coli LptA.

Podisus maculiventris thanatin has been reported as a potent antimicrobial peptide with antibacterial and antifungal activity. Its antibiotic activity has been most thoroughly characterized against E. coli and shown to interfere with multiple pathways, such as the lipopolysaccharide transport (LPT) pathway comprised of seven different Lpt proteins. Thanatin binds to E. coli LptA and LptD, thus disrupting the LPT complex formation and inhibiting cell wall synthesis and microbial growth. Here, we performed a genomic database search to uncover novel thanatin orthologs, characterized their binding to E. coli LptA using bio-layer interferometry, and assessed their antimicrobial activity against E. coli. We found that thanatins from Chinavia ubica and Murgantia histrionica bound tighter (by 3.6- and 2.2-fold respectively) to LptA and exhibited more potent antibiotic activity (by 2.1- and 2.8-fold respectively) than the canonical thanatin from P. maculiventris. We crystallized and determined the LptA-bound complex structures of thanatins from C. ubica (1.90 Å resolution), M. histrionica (1.80 Å resolution), and P. maculiventris (2.43 Å resolution) to better understand their mechanism of action. Our structural analysis revealed that residues A10 and I21 in C. ubica and M. histrionica thanatin are important for improving the binding interface with LptA, thus overall improving the potency of thanatin against E. coli. We also designed a stapled variant of thanatin that removes the need for a disulfide bond but retains the ability to bind LptA and antibiotic activity. Our discovery presents a library of novel thanatin sequences to serve as starting scaffolds for designing more potent antimicrobial therapeutics.

What does high value care for musculoskeletal conditions mean and how do you apply it in practice? A consensus statement from a research network of physiotherapists in New South Wales, Australia.

OBJECTIVES: To develop a physiotherapist-led consensus statement on the definition and provision of high-value care for people with musculoskeletal conditions. DESIGN: We performed a three-stage study using Research And Development/University of California Los Angeles Appropriateness Method methodology. We reviewed evidence about current definitions through a rapid literature review and then performed a survey and interviews with network members to gather consensus. Consensus was finalised in a face-to-face meeting. SETTING: Australian primary care. PARTICIPANTS: Registered physiotherapists who are members of a practice-based research network (n=31). RESULTS: The rapid review revealed two definitions, four domains of high value care and seven themes of high-quality care. Online survey responses (n=26) and interviews (n=9) generated two additional high-quality care themes, a definition of low-value care, and 21 statements on the application of high value care. Consensus was reached for three working definitions (high value, high-quality and low value care), a final model of four high value care domains (high-quality care, patient values, cost-effectiveness, reducing waste), nine high-quality care themes and 15 statements on application. CONCLUSION: High value care for musculoskeletal conditions delivers most value for the patient, and the clinical benefits outweigh the costs to the individual or system providing the care. High-quality care is evidence based, effective and safe care that is patient-centred, consistent, accountable, timely, equitable and allows easy interaction with healthcare providers and healthcare systems.

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.

Protocol for predicting drug-resistant protein mutations to an ERK2 inhibitor using RESISTOR.

Prospective predictions of drug-resistant protein mutants could improve the design of therapeutics less prone to resistance. Here, we describe RESISTOR, an algorithm that uses structure- and sequence-based criteria to predict resistance mutations. We demonstrate the process of using RESISTOR to predict ERK2 mutants likely to arise in melanoma ablating the efficacy of the ERK1/2 inhibitor SCH779284. RESISTOR is included in the free and open-source computational protein design software OSPREY. For complete details on the use and execution of this protocol, please refer to Guerin et al..1.

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.

Resistor: An algorithm for predicting resistance mutations via Pareto optimization over multistate protein design and mutational signatures.

Resistance to pharmacological treatments is a major public health challenge. Here, we introduce Resistor-a structure- and sequence-based algorithm that prospectively predicts resistance mutations for drug design. Resistor computes the Pareto frontier of four resistance-causing criteria: the change in binding affinity (ΔKa) of the (1) drug and (2) endogenous ligand upon a protein's mutation; (3) the probability a mutation will occur based on empirically derived mutational signatures; and (4) the cardinality of mutations comprising a hotspot. For validation, we applied Resistor to EGFR and BRAF kinase inhibitors treating lung adenocarcinoma and melanoma. Resistor correctly identified eight clinically significant EGFR resistance mutations, including the erlotinib and gefitinib "gatekeeper" T790M mutation and five known osimertinib resistance mutations. Furthermore, Resistor predictions are consistent with BRAF inhibitor sensitivity data from both retrospective and prospective experiments using KinCon biosensors. Resistor is available in the open-source protein design software OSPREY.

RESISTOR: A New OSPREY Module to Predict Resistance Mutations.

Computational, in silico prediction of resistance-conferring escape mutations could accelerate the design of therapeutics less prone to resistance. This article describes how to use the Resistor algorithm to predict escape mutations. Resistor employs Pareto optimization on four resistance-conferring criteria-positive and negative design, mutational probability, and hotspot cardinality-to assign a Pareto rank to each prospective mutant. It also predicts the mechanism of resistance, that is, whether a mutant ablates binding to a drug, strengthens binding to the endogenous ligand, or a combination of these two factors, and provides structural models of the mutants. Resistor is part of the free and open-source computational protein design software OSPREY.

"Myths and Facts" Education Is Comparable to "Facts Only" for Recall of Back Pain Information but May Improve Fear-Avoidance Beliefs: An Embedded Randomized Trial.

OBJECTIVE: To assess the effectiveness of patient education with "myths and facts" versus "facts only" on recall of back pain information and fear-avoidance beliefs in patients with chronic low back pain (LBP). DESIGN: Randomized Study Within A Trial. METHODS: One hundred fifty-two participants with chronic LBP were included. Participants allocated to the "facts only" group received an information sheet with 6 LBP facts, whereas those allocated to the "myths and facts" group received the same information sheet, with each myth refuted by its respective fact. The primary outcome was a correct recall of back pain facts, and the secondary outcome was the physical activity component of the Fear-Avoidance Beliefs Questionnaire (FABQ-PA), 2 weeks after the provision of the information sheet. RESULTS: There was no evidence of a difference in the proportion of participants with a correct recall between the "myths and facts" and "facts only" groups (odds ratio = 0.98; 95% confidence interval [CI]: 0.48, 1.99) and no significant difference in FABQ-PA mean scores between groups (-1.58; 95% CI: -3.77, 0.61). Sensitivity analyses adjusted for prognostic factors showed no difference in information recall but a larger difference in FABQ-PA scores (-2.3; 95% CI: -4.56, -0.04). CONCLUSION: We found no overall difference in the recall of back pain information for patients provided with "myths and facts" compared with that for patients provided with "facts only" and a slight reduction in fear-avoidance beliefs for physical activity using "myths and facts" compared with that using "facts only," but the meaningfulness of this result is uncertain. J Orthop Sports Phys Ther 2022;52(9):586-594. Epub: 9 July 2022. doi:10.2519/jospt.2022.10989.

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.

A Literature Review of Productivity Loss Associated with Hypertension in the United States.

A literature review of peer-reviewed articles published 2000-2019 was conducted to determine the types and extent of hypertension-associated productivity loss among adults in the United States. All monetary outcomes were standardized to 2019 $ by using the Employment Cost Index. Twenty-seven articles met the inclusion criteria. Nearly half of the articles (12 articles) presented monetary outcomes of productivity loss. Absenteeism (14 articles) and presenteeism (8 articles) were most frequently assessed. Annual absenteeism was estimated to cost more than $11 billion, nationally controlling for sociodemographic characteristics. The annual additional costs per person were estimated at $63 for short-term disability, $72-$330 for absenteeism, and $53-$156 for presenteeism, controlling for participant characteristics; and may be as high as $2362 for absenteeism and presenteeism when considered in combination. The annual additional time loss per person was estimated as 1.3 days for absenteeism, controlling for common hypertension comorbidities, including stroke and diabetes; and 15.6 days for work and home productivity loss combined, controlling for sociodemographic characteristics. The loss from absenteeism alone might be more than 20% of the total medical expenditure of hypertension. Although the differences in estimation methods and study populations make it challenging to synthesize the costs across the studies, this review provides detailed information on the various types of productivity loss. In addition, the ways in which methods could be standardized for future research are discussed. Accounting for the costs from productivity loss can help public health officials, health insurers, employers, and researchers better understand the economic burden of hypertension.

The Cost of Cancer: The Association of Financial and Cancer-Related Stress on Maladaptive Coping Styles in Families with a Cancer Diagnosis.

According to the American Cancer Society (2020), it is estimated that 1.8 million new cancer diagnoses will occur in 2019 in the United States. Due to the frequency of cancer diagnoses and the increasing costs of treatment, financial stress is common among cancer patients. Guided by the Family Systems Illness Model (FSI), a cross-sectional study of individuals and family members where there was an active cancer diagnosis (n = 53) was conducted. The study utilized structural equation modeling to examine the impact of cancer stress and financial stress on maladaptive family coping mechanisms, and in turn, their effect on family communication and satisfaction. Findings indicate individuals with higher financial stress reported greater cancer stress. In turn, individuals with higher cancer stress, reported higher rigidity in their family coping which was associated with less family satisfaction. Additionally, as individuals reported greater family disengagement and chaos, lower levels of family communication and satisfaction were found. These findings provide evidence to the complex stresses experienced by cancer patients and their families. Therapeutic implications of how emotionally focused therapy may support these families dealing with a cancer diagnosis are discussed.

An assessment of non-communicable disease mortality among adults in Eastern Uganda, 2010-2016.

BACKGROUND: There is a dearth of studies assessing non-communicable disease (NCD) mortality within population-based settings in Uganda. We assessed mortality due to major NCDs among persons ≥ 30 years in Eastern Uganda from 2010 to 2016. METHODS: The study was carried out at the Iganga-Mayuge health and demographic surveillance site in the Iganga and Mayuge districts of Eastern Uganda. Information on cause of death was obtained through verbal autopsies using a structured questionnaire to conduct face-face interviews with carers or close relatives of the deceased. Physicians assigned likely cause of death using ICD-10 codes. Age-adjusted mortality rates were calculated using direct method, with the average population across the seven years of the study (2010 to 2016) as the standard. Age categories of 30-40, 41-50, 51-60, 61-70, and ≥ 71 years were used for standardization. RESULTS: A total of 1,210 deaths among persons ≥ 30 years old were reported from 2010 to 2016 (50.7% among women). Approximately 53% of all deaths were due to non-communicable diseases, 31.8% due to communicable diseases, 8.2% due to injuries, and 7% due to maternal-related deaths or undetermined causes. Cardiovascular diseases accounted for the largest proportion of NCD deaths in each year, and women had substantially higher cardiovascular disease mortality rates compared to men. Conversely, women had lower diabetes mortality rates than men for five of the seven years examined. CONCLUSIONS: Non-communicable diseases are major causes of death among adults in Iganga and Mayuge; and cardiovascular diseases and diabetes are leading causes of NCD deaths. Efforts are needed to tackle NCD risk factors and provide NCD care to reduce associated burden and premature mortality.

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.