Targeted transcriptional downregulation of MYC using epigenomic controllers demonstrates antitumor activity in hepatocellular carcinoma models.

Dysregulation of master regulator c-MYC (MYC) plays a central role in hepatocellular carcinoma (HCC) and other cancers but remains an elusive target for therapeutic intervention. MYC expression is epigenetically modulated within naturally occurring DNA loop structures, Insulated Genomic Domains (IGDs). We present a therapeutic approach using an epigenomic controller (EC), a programmable epigenomic mRNA medicine, to precisely modify MYC IGD sub-elements, leading to methylation of MYC regulatory elements and durable downregulation of MYC mRNA transcription. Significant antitumor activity is observed in preclinical models of HCC treated with the MYC-targeted EC, as monotherapy or in combination with tyrosine kinase or immune checkpoint inhibitors. These findings pave the way for clinical development of MYC-targeting epigenomic controllers in HCC patients and provide a framework for programmable epigenomic mRNA therapeutics for cancer and other diseases.

A Financial Incentives Program to Promote Smoking Cessation Among Recently Hospitalized Individuals: Feasibility and Acceptability Study.

BACKGROUND: Hospitalization is an opportunity to engage underserved individuals in tobacco treatment who may not otherwise have access to it. Tobacco treatment interventions that begin during hospitalization and continue for at least 1 postdischarge month are effective in promoting smoking cessation. However, there is low usage of postdischarge tobacco treatment services. Financial incentives for smoking cessation are an intervention in which participants receive incentives, such as cash payments or vouchers for goods, to encourage individuals to stop smoking or to reward individuals for maintaining abstinence. OBJECTIVE: We sought to determine the feasibility and acceptability of a novel postdischarge financial incentive intervention that uses a smartphone application paired to measurements of exhaled carbon monoxide (CO) concentration levels to promote smoking cessation in individuals who smoke cigarettes. METHODS: We collaborated with Vincere Health, Inc. to tailor their mobile application that uses facial recognition features, a portable breath test CO monitor, and smartphone technology to deliver financial incentives to a participant's digital wallet after the completion of each CO test. The program includes 3 racks. Track 1: Noncontingent incentives for conducting CO tests. Track 2: Combination of noncontingent and contingent incentives for CO levels <10 parts per million (ppm). Track 3: Contingent incentives only for CO levels <10 ppm. After obtaining informed consent, we pilot-tested the program from September to November 2020 with a convenience sample of 33 hospitalized individuals at Boston Medical Center, a large safety-net hospital in New England. Participants received text reminders to conduct CO tests twice daily for 30 days postdischarge. We collected data on engagement, CO levels, and incentives earned. We measured feasibility and acceptability quantitatively and qualitatively at 2 and 4 weeks. RESULTS: Seventy-six percent (25/33) completed the program and 61% (20/33) conducted at least 1 breath test each week. Seven patients had consecutive CO levels <10 ppm during the last 7 days of the program. Engagement with the financial incentive intervention as well as in-treatment abstinence was highest in Track 3 that delivered financial incentives contingent on CO levels <10 ppm. Participants reported high program satisfaction and that the intervention helped motivate smoking cessation. Participants suggested increasing program duration to at least 3 months and adding supplemental text messaging to increase motivation to stop smoking. CONCLUSIONS: Financial incentives paired to measurements of exhaled CO concentration levels is a novel smartphone-based tobacco cessation approach that is feasible and acceptable. Future studies should examine the efficacy of the intervention after it is refined to add a counseling or text-messaging component.

Drugging the epigenome in the age of precision medicine.

BACKGROUND: Modulating the epigenome has long been considered a potential opportunity for therapeutic intervention in numerous disease areas with several approved therapies marketed, primarily for cancer. Despite the overall promise of early approaches, however, these drugs have been plagued by poor pharmacokinetic and safety/tolerability profiles due in large part to off-target effects and a lack of specificity. RESULTS: Recently, there has been marked progress in the field on a new generation of epigenomic therapies which address these challenges directly by targeting defined loci with highly precise, durable, and tunable approaches. Here, we review the promise and pitfalls of epigenetic drug development to date and provide an outlook on recent advances and their promise for future therapeutic applications. CONCLUSIONS: Novel therapeutic modalities leveraging epigenetics and epigenomics with increased precision are well positioned to advance the field and treat patients across disease areas in the coming years.

A mixed methods study to inform and evaluate a longitudinal nurse practitioner/community health worker intervention to address social determinants of health and chronic obstructive pulmonary disease self-management.

BACKGROUND: Individuals with low socioeconomic status experience higher prevalence and worse outcomes of chronic obstructive pulmonary disease (COPD). We undertook a quality improvement initiative at our safety net hospital in which a nurse practitioner (NP)/community health worker (CHW) team followed patients with COPD, frequent admissions, and unmet SDOH needs from hospitalization through one month post-discharge. We report our mixed methods approach to inform development and preliminary evaluation of this intervention. METHODS: We first assessed characteristics of patients admitted with COPD in 2018 (n = 1811), performing multivariable logistic regression to identify factors associated with ≥ 2 admissions per year. We then tested a standardized tool to screen for unmet SDOH needs in a convenience sample of 51 frequently hospitalized patients with COPD. From January-July 2019, we pilot tested the NP/CHW intervention with 57 patients, reviewed NP/CHW logs, and conducted qualitative interviews with 16 patient participants to explore impressions of the intervention. RESULTS: Patients with Medicaid insurance, mental health disorders, cardiac disease, and substance use disorder had increased odds of having ≥ 2 admissions. COPD severity, comorbidities, and unmet SDOH needs made COPD self-management challenging. Seventy-four percent of frequently admitted patients with COPD completing SDOH screening had unmet SDOH needs. Patients perceived that the NP/CHW intervention addressed these barriers by connecting them to resources and providing emotional support. CONCLUSIONS: Many patients with COPD admitted at our safety-net hospital experience unmet SDOH needs that impede COPD self-management. A longitudinal NP/CHW intervention to address unmet SDOH needs following discharge appears feasible and acceptable.

Rapid Cycle Evaluation and Adaptation of an Inpatient Tobacco Treatment Service at a U.S. Safety-Net Hospital.

Background: To address disparities in smoking rates, our safety-net hospital implemented an inpatient tobacco treatment intervention: an "opt-out" electronic health record (EHR)-based Best Practice Alert + order-set, which triggers consultation to a Tobacco Treatment Consult (TTC) service for all hospitalized patients who smoke cigarettes. We report on development, implementation, and adaptation of the intervention, informed by a pre-implementation needs assessment and two rapid-cycle evaluations guided by the Consolidated Framework for Implementation Research (CFIR) and Expert Recommendations for Implementing Change (ERIC) compilation. Methods: We identified stakeholders affected by implementation and conducted a local needs assessment starting 6 months-pre-launch. We then conducted two rapid-cycle evaluations during the first 6 months post-implementation. The CFIR informed survey and interview guide development, data collection, assessment of barriers and facilitators, and selection of ERIC strategies to implement and adapt the intervention. Results: Key themes were: (1) Understanding the hospital's priority to improving tobacco performance metrics was critical in gaining leadership buy-in (CFIR Domain: Outer setting; Construct: External Policy and Incentives). (2) CFIR-based rapid-cycle evaluations allowed us to recognize implementation challenges early and select ERIC strategies clustering into 3 broad categories (conducting needs assessment; developing stakeholder relationships; training and educating stakeholders) to make real-time adaptations, creating an acceptable clinical workflow. (3) Minimizing clinician burden allowed the successful implementation of the TTC service. (4) Demonstrating improved 6-month quit rates and tobacco performance metrics were key to sustaining the program. Conclusions: Rapid-cycle evaluations to gather pre-implementation and early-implementation data, focusing on modifiable barriers and facilitators, allowed us to develop and refine the intervention to improve acceptability, adoption, and sustainability, enabling us to improve tobacco performance metrics in a short timeline. Future directions include spreading rapid-cycle evaluations to promote implementation of inpatient tobacco treatment programs to other settings and assessing long-term sustainability and return on investment of these programs.

Effectiveness of an Opt-Out Electronic Heath Record-Based Tobacco Treatment Consult Service at an Urban Safety Net Hospital.

BACKGROUND: To address the burden of tobacco use in underserved populations, our safety net hospital developed a tobacco treatment intervention consisting of an "opt-out" electronic health record-based best practice alert + order set, which triggers consultation to an inpatient tobacco treatment consult (TTC) service for all hospitalized smokers. RESEARCH QUESTION: We sought to understand if the intervention would increase patient-level outcomes (receipt of tobacco treatment during hospitalization and at discharge; 6-month smoking abstinence) and improve hospital-wide performance on tobacco treatment metrics. DESIGN AND METHODS: We conducted two retrospective quasi-experimental analyses to examine effectiveness of the TTC service. Using a pragmatic design and multivariable logistic regression, we compared patient-level outcomes of receipt of nicotine replacement therapy and 6-month quit rates between smokers seen by the service (n = 505) and eligible smokers not seen because of time constraints (n = 680) between July 2016 and December 2016. In addition, we conducted an interrupted time series analysis to examine the effect of the TTC service on hospital-level performance measures, comparing reported Joint Commission measure rates for inpatient (Tob-2) and postdischarge (Tob-3) tobacco treatment preimplementation (January 2015-June 2016) vs postimplementation (July 2016-December 2017) of the intervention. RESULTS: Compared with inpatient smokers not seen by the TTC service, smokers seen by the TTC service had higher odds of receiving nicotine replacement during hospitalization (260 of 505 [51.5%] vs 244 of 680 [35.9%]; adjusted ORs [AOR], 1.93 [95% CI, 1.5-2.45]) and at discharge (164 of 505 [32.5%] vs 84 of 680 [12.4%]; AOR, 3.41 [95% CI, 2.54-4.61]), as well as higher odds of 6-month smoking abstinence (75 of 505 [14.9%] vs 68 of 680 [10%]; AOR, 1.48 [95% CI, 1.03-2.12]). Hospital-wide, the intervention was associated with a change in slope trends for Tob-3 (P < .01), but not for Tob-2. INTERPRETATION: The "opt-out" electronic health record-based TTC service at our large safety net hospital was effective at improving both patient-level outcomes and hospital-level performance metrics, and could be implemented at other safety net hospitals that care for hard-to-reach smokers.

Feasibility, Acceptability, and Adoption of an Inpatient Tobacco Treatment Service at a Safety-Net Hospital: A Mixed-Methods Study.

Rationale: Hospitalization is an opportunity to engage smokers who may not seek tobacco treatment. Our safety-net hospital developed and implemented an inpatient intervention consisting of an "opt-out" electronic health record-based Best Practice Alert (BPA)+order-set, designed to trigger referral to the Tobacco Treatment Consult (TTC) service (a team staffed by tobacco treatment specialists) for all hospitalized smokers, regardless of motivation to quit.Objectives: We performed a sequential explanatory mixed-methods study to evaluate the feasibility, acceptability, and adoption of the TTC service.Methods: Among all admissions of adult "current smokers" between July 2016 and June 2017, we calculated the percentage of patients whose clinicians accepted the order-set (through a simple "order" click), thus generating the TTC referral. We then determined the extent of clinician follow-through of TTC recommendations for prescribing nicotine replacement therapy among 1,651 consecutive smokers seen by the TTC service. Finally, we conducted qualitative interviews with inpatient clinicians (n = 25) to understand their rationale for adoption or nonuse of the TTC intervention, including perceived usefulness, barriers to adoption, and strategies to improve the utility of the service.Results: Clinicians accepted the TTC order-set for 4,100 out of 6,598 "current smokers" (62.1%) for whom the BPA fired, typically after initially deferring the BPA. Rates of acceptance significantly differed across clinical services (range: 8% [obstetrics-gynecology] to 82.2% [cardiology]; P < 0.00001). A chart review showed that 43.5% (719/1,651) of the patients seen by the TTC service desired outpatient nicotine replacement therapy, but only half of these patients (48.8%; 351/719) received a discharge prescription from the inpatient team. Clinicians expressed that they valued the TTC service, but that BPA fatigue, time constraints, competing priorities, and poor communication with the TTC service were barriers to using the service and following recommendations. Clinicians suggested strategies to address barriers to the use of tobacco treatment interventions during hospitalization and after discharge.Conclusions: Implementing a large-scale "opt-out" tobacco treatment service for hospitalized smokers at a safety-net hospital is feasible and acceptable, but suffers from inconsistent adoption due to a variety of clinician barriers. System-level changes are needed to increase uptake and sustain inpatient tobacco treatment interventions to promote smoking cessation.

A distant trophoblast-specific enhancer controls HLA-G expression at the maternal-fetal interface.

HLA-G, a nonclassical HLA molecule uniquely expressed in the placenta, is a central component of fetus-induced immune tolerance during pregnancy. The tissue-specific expression of HLA-G, however, remains poorly understood. Here, systematic interrogation of the HLA-G locus using massively parallel reporter assay (MPRA) uncovered a previously unidentified cis-regulatory element 12 kb upstream of HLA-G with enhancer activity, Enhancer L Strikingly, clustered regularly-interspaced short palindromic repeats (CRISPR)/Cas9-mediated deletion of this enhancer resulted in ablation of HLA-G expression in JEG3 cells and in primary human trophoblasts isolated from placenta. RNA-seq analysis demonstrated that Enhancer L specifically controls HLA-G expression. Moreover, DNase-seq and chromatin conformation capture (3C) defined Enhancer L as a cell type-specific enhancer that loops into the HLA-G promoter. Interestingly, MPRA-based saturation mutagenesis of Enhancer L identified motifs for transcription factors of the CEBP and GATA families essential for placentation. These factors associate with Enhancer L and regulate HLA-G expression. Our findings identify long-range chromatin looping mediated by core trophoblast transcription factors as the mechanism controlling tissue-specific HLA-G expression at the maternal-fetal interface. More broadly, these results establish the combination of MPRA and CRISPR/Cas9 deletion as a powerful strategy to investigate human immune gene regulation.

Experimental and mathematical analysis of in vitro Pitavastatin hepatic uptake across species.

1. To investigate the non-linear kinetics of in vitro hepatocyte uptake across species, the OATP substrate Pitavastatin was used as a probe. 2. Experiments were conducted at AstraZeneca (Alderley Park, Macclesfield) using freshly isolated rat, dog and human hepatocytes, utilising the "oil spin" methodology described by Hassen et al. (1996). Very few mechanistic models have previously been used to characterise the uptake process. 3. Here two candidate pharmacokinetic non-linear compartmental models are proposed. Both models have been shown to be structurally identifiable and distinghishable previously, which establishes that all unknown parameters could be identified from the experimental observations available and that input/output relationships for both the candidate models were structurally different. 4. A kinetic modelling software package, FACSIMILE (MCPA Software, Faringdon, UK), was used to obtain numerical solutions for the system equations and for parameter estimation. Model fits gave good agreement with the in vitro data and suggest the current widely accepted assumption that the rate of diffusion across the hepatocyte cell membrane is the same at both 4 °C and 37 °C is not valid, at least for Pitavastatin. Although this finding has already been proposed, this is the first time it is comprehensively debunked using statistical testing.

Simultaneous alignment and folding of protein sequences.

Accurate comparative analysis tools for low-homology proteins remains a difficult challenge in computational biology, especially sequence alignment and consensus folding problems. We present partiFold-Align, the first algorithm for simultaneous alignment and consensus folding of unaligned protein sequences; the algorithm's complexity is polynomial in time and space. Algorithmically, partiFold-Align exploits sparsity in the set of super-secondary structure pairings and alignment candidates to achieve an effectively cubic running time for simultaneous pairwise alignment and folding. We demonstrate the efficacy of these techniques on transmembrane ß-barrel proteins, an important yet difficult class of proteins with few known three-dimensional structures. Testing against structurally derived sequence alignments, partiFold-Align significantly outperforms state-of-the-art pairwise and multiple sequence alignment tools in the most difficult low-sequence homology case. It also improves secondary structure prediction where current approaches fail. Importantly, partiFold-Align requires no prior training. These general techniques are widely applicable to many more protein families (partiFold-Align is available at http://partifold.csail.mit.edu/ ).

MARIS: method for analyzing RNA following intracellular sorting.

Transcriptional profiling is a key technique in the study of cell biology that is limited by the availability of reagents to uniquely identify specific cell types and isolate high quality RNA from them. We report a Method for Analyzing RNA following Intracellular Sorting (MARIS) that generates high quality RNA for transcriptome profiling following cellular fixation, intracellular immunofluorescent staining and FACS. MARIS can therefore be used to isolate high quality RNA from many otherwise inaccessible cell types simply based on immunofluorescent tagging of unique intracellular proteins. As proof of principle, we isolate RNA from sorted human embryonic stem cell-derived insulin-expressing cells as well as adult human ß cells. MARIS is a basic molecular biology technique that could be used across several biological disciplines.

Differentiated human stem cells resemble fetal, not adult, ß cells.

Human pluripotent stem cells (hPSCs) have the potential to generate any human cell type, and one widely recognized goal is to make pancreatic ß cells. To this end, comparisons between differentiated cell types produced in vitro and their in vivo counterparts are essential to validate hPSC-derived cells. Genome-wide transcriptional analysis of sorted insulin-expressing (INS(+)) cells derived from three independent hPSC lines, human fetal pancreata, and adult human islets points to two major conclusions: (i) Different hPSC lines produce highly similar INS(+) cells and (ii) hPSC-derived INS(+) (hPSC-INS(+)) cells more closely resemble human fetal ß cells than adult ß cells. This study provides a direct comparison of transcriptional programs between pure hPSC-INS(+) cells and true ß cells and provides a catalog of genes whose manipulation may convert hPSC-INS(+) cells into functional ß cells.

Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape.

We describe protein interaction quantitation (PIQ), a computational method for modeling the magnitude and shape of genome-wide DNase I hypersensitivity profiles to identify transcription factor (TF) binding sites. Through the use of machine-learning techniques, PIQ identified binding sites for >700 TFs from one DNase I hypersensitivity analysis followed by sequencing (DNase-seq) experiment with accuracy comparable to that of chromatin immunoprecipitation followed by sequencing (ChIP-seq). We applied PIQ to analyze DNase-seq data from mouse embryonic stem cells differentiating into prepancreatic and intestinal endoderm. We identified 120 and experimentally validated eight 'pioneer' TF families that dynamically open chromatin. Four pioneer TF families only opened chromatin in one direction from their motifs. Furthermore, we identified 'settler' TFs whose genomic binding is principally governed by proximity to open chromatin. Our results support a model of hierarchical TF binding in which directional and nondirectional pioneer activity shapes the chromatin landscape for population by settler TFs.

Design and optimization of pyrazinecarboxamide-based inhibitors of diacylglycerol acyltransferase 1 (DGAT1) leading to a clinical candidate dimethylpyrazinecarboxamide phenylcyclohexylacetic acid (AZD7687).

A new series of pyrazinecarboxamide DGAT1 inhibitors was designed to address the need for a candidate drug with good potency, selectivity, and physical and DMPK properties combined with a low predicted dose in man. Rational design and optimization of this series led to the discovery of compound 30 (AZD7687), which met the project objectives for potency, selectivity, in particular over ACAT1, solubility, and preclinical PK profiles. This compound showed the anticipated excellent pharmacokinetic properties in human volunteers.

A global sampling approach to designing and reengineering RNA secondary structures.

The development of algorithms for designing artificial RNA sequences that fold into specific secondary structures has many potential biomedical and synthetic biology applications. To date, this problem remains computationally difficult, and current strategies to address it resort to heuristics and stochastic search techniques. The most popular methods consist of two steps: First a random seed sequence is generated; next, this seed is progressively modified (i.e. mutated) to adopt the desired folding properties. Although computationally inexpensive, this approach raises several questions such as (i) the influence of the seed; and (ii) the efficiency of single-path directed searches that may be affected by energy barriers in the mutational landscape. In this article, we present RNA-ensign, a novel paradigm for RNA design. Instead of taking a progressive adaptive walk driven by local search criteria, we use an efficient global sampling algorithm to examine large regions of the mutational landscape under structural and thermodynamical constraints until a solution is found. When considering the influence of the seeds and the target secondary structures, our results show that, compared to single-path directed searches, our approach is more robust, succeeds more often and generates more thermodynamically stable sequences. An ensemble approach to RNA design is thus well worth pursuing as a complement to existing approaches. RNA-ensign is available at http://csb.cs.mcgill.ca/RNAensign.

STITCHER: Dynamic assembly of likely amyloid and prion ß-structures from secondary structure predictions.

The supersecondary structure of amyloids and prions, proteins of intense clinical and biological interest, are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Previous work has demonstrated that probability-based prediction of discrete ß-strand pairs can offer insight into these structures. Here, we devise a system of energetic rules that can be used to dynamically assemble these discrete ß-strand pairs into complete amyloid ß-structures. The STITCHER algorithm progressively 'stitches' strand-pairs into full ß-sheets based on a novel free-energy model, incorporating experimentally observed amino-acid side-chain stacking contributions, entropic estimates, and steric restrictions for amyloidal parallel ß-sheet construction. A dynamic program computes the top 50 structures and returns both the highest scoring structure and a consensus structure taken by polling this list for common discrete elements. Putative structural heterogeneity can be inferred from sequence regions that compose poorly. Predictions show agreement with experimental models of Alzheimer's amyloid beta peptide and the Podospora anserina Het-s prion. Predictions of the HET-s homolog HET-S also reflect experimental observations of poor amyloid formation. We put forward predicted structures for the yeast prion Sup35, suggesting N-terminal structural stability enabled by tyrosine ladders, and C-terminal heterogeneity. Predictions for the Rnq1 prion and alpha-synuclein are also given, identifying a similar mix of homogenous and heterogeneous secondary structure elements. STITCHER provides novel insight into the energetic basis of amyloid structure, provides accurate structure predictions, and can help guide future experimental studies.

Discovery, optimisation and in vivo evaluation of novel GPR119 agonists.

GPR119 is increasingly seen as an attractive target for the treatment of type II diabetes and other elements of the metabolic syndrome. During a programme aimed at developing agonists of the GPR119 receptor, we identified compounds that were potent with reduced hERG liabilities, that had good pharmacokinetic properties and that displayed excellent glucose-lowering effects in vivo. However, further profiling in a GPR119 knock-out (KO) mouse model revealed that the biological effects were not exclusively due to GPR119 agonism, highlighting the value of transgenic animals in drug discovery programs.

Efficient traversal of beta-sheet protein folding pathways using ensemble models.

Molecular dynamics (MD) simulations can now predict ms-timescale folding processes of small proteins; however, this presently requires hundreds of thousands of CPU hours and is primarily applicable to short peptides with few long-range interactions. Larger and slower-folding proteins, such as many with extended ß-sheet structure, would require orders of magnitude more time and computing resources. Furthermore, when the objective is to determine only which folding events are necessary and limiting, atomistic detail MD simulations can prove unnecessary. Here, we introduce the program tFolder as an efficient method for modelling the folding process of large ß-sheet proteins using sequence data alone. To do so, we extend existing ensemble ß-sheet prediction techniques, which permitted only a fixed anti-parallel ß-barrel shape, with a method that predicts arbitrary ß-strand/ß-strand orientations and strand-order permutations. By accounting for all partial and final structural states, we can then model the transition from random coil to native state as a Markov process, using a master equation to simulate population dynamics of folding over time. Thus, all putative folding pathways can be energetically scored, including which transitions present the greatest barriers. Since correct folding pathway prediction is likely determined by the accuracy of contact prediction, we demonstrate the accuracy of tFolder to be comparable with state-of-the-art methods designed specifically for the contact prediction problem alone. We validate our method for dynamics prediction by applying it to the folding pathway of the well-studied Protein G. With relatively very little computation time, tFolder is able to reveal critical features of the folding pathways which were only previously observed through time-consuming MD simulations and experimental studies. Such a result greatly expands the number of proteins whose folding pathways can be studied, while the algorithmic integration of ensemble prediction with Markovian dynamics can be applied to many other problems.

Opposing effects of glutamine and asparagine govern prion formation by intrinsically disordered proteins.

Sequences rich in glutamine (Q) and asparagine (N) residues often fail to fold at the monomer level. This, coupled to their unusual hydrogen-bonding abilities, provides the driving force to switch between disordered monomers and amyloids. Such transitions govern processes as diverse as human protein-folding diseases, bacterial biofilm assembly, and the inheritance of yeast prions (protein-based genetic elements). A systematic survey of prion-forming domains suggested that Q and N residues have distinct effects on amyloid formation. Here, we use cell biological, biochemical, and computational techniques to compare Q/N-rich protein variants, replacing Ns with Qs and Qs with Ns. We find that the two residues have strong and opposing effects: N richness promotes assembly of benign self-templating amyloids; Q richness promotes formation of toxic nonamyloid conformers. Molecular simulations focusing on intrinsic folding differences between Qs and Ns suggest that their different behaviors are due to the enhanced turn-forming propensity of Ns over Qs.

A method for probing the mutational landscape of amyloid structure.

MOTIVATION: Proteins of all kinds can self-assemble into highly ordered ß-sheet aggregates known as amyloid fibrils, important both biologically and clinically. However, the specific molecular structure of a fibril can vary dramatically depending on sequence and environmental conditions, and mutations can drastically alter amyloid function and pathogenicity. Experimental structure determination has proven extremely difficult with only a handful of NMR-based models proposed, suggesting a need for computational methods. RESULTS: We present AmyloidMutants, a statistical mechanics approach for de novo prediction and analysis of wild-type and mutant amyloid structures. Based on the premise of protein mutational landscapes, AmyloidMutants energetically quantifies the effects of sequence mutation on fibril conformation and stability. Tested on non-mutant, full-length amyloid structures with known chemical shift data, AmyloidMutants offers roughly 2-fold improvement in prediction accuracy over existing tools. Moreover, AmyloidMutants is the only method to predict complete super-secondary structures, enabling accurate discrimination of topologically dissimilar amyloid conformations that correspond to the same sequence locations. Applied to mutant prediction, AmyloidMutants identifies a global conformational switch between Aß and its highly-toxic 'Iowa' mutant in agreement with a recent experimental model based on partial chemical shift data. Predictions on mutant, yeast-toxic strains of HET-s suggest similar alternate folds. When applied to HET-s and a HET-s mutant with core asparagines replaced by glutamines (both highly amyloidogenic chemically similar residues abundant in many amyloids), AmyloidMutants surprisingly predicts a greatly reduced capacity of the glutamine mutant to form amyloid. We confirm this finding by conducting mutagenesis experiments. AVAILABILITY: Our tool is publically available on the web at http://amyloid.csail.mit.edu/. CONTACT: lindquist_admin@wi.mit.edu; bab@csail.mit.edu.