Difficult Targets Research Articles

Targeting the cryptic sites: NMR-based strategy to improve protein druggability by controlling the conformational equilibrium.

Cryptic ligand binding sites, which are not evident in the unligated structures, are beneficial in tackling with difficult but attractive drug targets, such as protein-protein interactions (PPIs). However, cryptic sites have thus far not been rationally pursued in the early stages of drug development. Here, we demonstrated by nuclear magnetic resonance that the cryptic site in Bcl-xL exists in a conformational equilibrium between the open and closed conformations under the unligated condition. While the fraction of the open conformation in the unligated wild-type Bcl-xL is estimated to be low, F143W mutation that is distal from the ligand binding site can substantially elevate the population. The F143W mutant showed a higher hit rate in a phage-display peptide screening, and the hit peptide bound to the cryptic site of the wild-type Bcl-xL. Therefore, by controlling the conformational equilibrium in the cryptic site, the opportunity to identify a PPI inhibitor could be improved.

The Role of Frontoparietal Cortex across the Functional Stages of Visual Search

Areas in frontoparietal cortex have been shown to be active in a range of cognitive tasks and have been proposed to play a key role in goal-driven activities (Dosenbach, N. U. F., Fair, D. A., Miezin, F. M., Cohen, A. L., Wenger, K. K., Dosenbach, R. A. T., et al. Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences, U.S.A., 104, 11073-11078, 2007; Duncan, J. The multiple-demand (MD) system of the primate brain: Mental programs for intelligent behavior. Trends in Cognitive Sciences, 14, 172-179, 2010). Here, we examine the role this frontoparietal system plays in visual search. Visual search, like many complex tasks, consists of a sequence of operations: target selection, stimulus-response (SR) mapping, and response execution. We independently manipulated the difficulty of target selection and SR mapping in a novel visual search task that involved identical stimulus displays. Enhanced activity was observed in areas of frontal and parietal cortex during both difficult target selection and SR mapping. In addition, anterior insula and ACC showed preferential representation of SR-stage information, whereas the medial frontal gyrus, precuneus, and inferior parietal sulcus showed preferential representation of target selection-stage information. A connectivity analysis revealed dissociable neural circuits underlying visual search. We hypothesize that these circuits regulate distinct mental operations associated with the allocation of spatial attention, stimulus decisions, shifts of task set from selection to SR mapping, and SR mapping. Taken together, the results show frontoparietal involvement in all stages of visual search and a specialization with respect to cognitive operations.

Endoscope-Assisted Contralateral Perimedian Supracerebellar Suprapineal Approach to Third Ventricle Surface of the Thalamus: 3-Dimensional Operative Video.

In managing thalamic gliomas, total surgical removal is the most effective way of increasing overall survival. However, the thalamus is a difficult target because of surrounding neurovascular structures. According to the lesion's size/location/growth pattern, relation to neighboring structures, and surgeon's experience, most thalamic lesions can be reached through one of the 4 free surfaces: lateral ventricle, velar, cisternal, and third ventricle surfaces of the thalamus (3VsT).1-3 Approaching the thalamic lesions through the lateral side disrupts the integrity of internal capsule and corona radiata; thus, we never prefer this approach. For the removal of the lesions on the 3VsT, a transcallosal approach can be considered, but with this approach, we cannot reach 3VsT without harming the velar surface. In this 3-dimensional video, we demonstrate an endoscope-assisted contralateral perimedian supracerebellar suprapineal (CPeSS) approach to a glioma on the 3VsT. The patient, a 49-yr-old man, had progressive dizziness for a month. With the patient in a semisitting position, total resection was achieved via the endoscope-assisted CPeSS approach. This approach is entirely transcisternal-transventricular and is a natural route to the 3VsT. Although the route is longer than the ipsilateral approach, it requires no retraction and provides more direct and wider visualization. It allows complete visualization of the lateral border of the lesion. A perimedian approach also avoids the major tentorial bridging veins, which are mostly at the midline. High-definition neuroendoscope was a great adjunct that helped to visualize residual tumors at hidden corners. We suggest this approach for thalamic lesions on the third ventricle surface of the thalamus. The patient consented to the publication of his images and a written consent was obtained.

Multimodal small-molecule screening for human prion protein binders

Prion disease is a rapidly progressive neurodegenerative disorder caused by misfolding and aggregation of the prion protein (PrP), and there are currently no therapeutic options. PrP ligands could theoretically antagonize prion formation by protecting the native protein from misfolding or by targeting it for degradation, but no validated small-molecule binders have been discovered to date. We deployed a variety of screening methods in an effort to discover binders of PrP, including 19F-observed and saturation transfer difference (STD) NMR spectroscopy, differential scanning fluorimetry (DSF), DNA-encoded library selection, and in silico screening. A single benzimidazole compound was confirmed in concentration-response, but affinity was very weak (Kd > 1 mm), and it could not be advanced further. The exceptionally low hit rate observed here suggests that PrP is a difficult target for small-molecule binders. Whereas orthogonal binder discovery methods could yield high-affinity compounds, non-small-molecule modalities may offer independent paths forward against prion disease.

Firn Clutter Constraints on the Design and Performance of Orbital Radar Ice Sounders

Radar sounding is a powerful tool for constraining subglacial conditions, which influence the mass balance of polar ice sheets and their contributions to global sea-level rise. A satellite-based radar sounder, such as those successfully demonstrated at Mars, would offer unprecedented spatial and temporal coverage of the subsurface. However, airborne sounding studies suggest that poorly constrained radar scattering in polar firn may produce performance-limiting clutter for terrestrial orbital sounders. We develop glaciologically constrained electromagnetic models of radar interactions in firn, test them against in situ data and multifrequency airborne radar observations, and apply the only model we find to be consistent with observation to assess the implications of firn clutter for orbital sounder system design. Our results show that in the very high-frequency (VHF) and ultrahigh-frequency (UHF) bands, radar interactions in the firn are dominated by quasi-specular reflections at the interfaces between layers of different densities and that off-nadir backscatter is likely the result of small-scale roughness in the subsurface density profiles. As a result, high frequency (HF) or low VHF center frequencies offer a significant advantage in near-surface clutter suppression compared to the UHF band. However, the noise power is the dominant constraint in all bands, so the near-surface clutter primarily constrains the extent to which the transmit power, pulselength, or antenna gain can be engineered to improve the signal-to-noise ratio. Our analysis suggests that the deep interior of terrestrial ice sheets is a difficult target for orbital sounding, which may require optimizations in azimuth processing and cross-track clutter suppression which complement existing requirements for sounding at the margins.

Characterization of Diabetic and Non-Diabetic Foot Ulcers Using Single-Cell RNA-Sequencing.

Background: Recent advances in high-throughput single-cell sequencing technologies have led to their increasingly widespread adoption for clinical applications. However, challenges associated with tissue viability, cell yield, and delayed time-to-capture have created unique obstacles for data processing. Chronic wounds, in particular, represent some of the most difficult target specimens, due to the significant amount of fibrinous debris, extracellular matrix components, and non-viable cells inherent in tissue routinely obtained from debridement. Methods: Here, we examined the feasibility of single cell RNA sequencing (scRNA-seq) analysis to evaluate human chronic wound samples acquired in the clinic, subjected to prolonged cold ischemia time, and processed without FACS sorting. Wound tissue from human diabetic and non-diabetic plantar foot ulcers were evaluated using an optimized 10X Genomics scRNA-seq platform and analyzed using a modified data pipeline designed for low-yield specimens. Cell subtypes were identified informatically and their distributions and transcriptional programs were compared between diabetic and non-diabetic tissue. Results: 139,000 diabetic and non-diabetic wound cells were delivered for 10X capture after either 90 or 180 min of cold ischemia time. cDNA library concentrations were 858.7 and 364.7 pg/µL, respectively, prior to sequencing. Among all barcoded fragments, we found that 83.5% successfully aligned to the human transcriptome and 68% met the minimum cell viability threshold. The average mitochondrial mRNA fraction was 8.5% for diabetic cells and 6.6% for non-diabetic cells, correlating with differences in cold ischemia time. A total of 384 individual cells were of sufficient quality for subsequent analyses; from this cell pool, we identified transcriptionally-distinct cell clusters whose gene expression profiles corresponded to fibroblasts, keratinocytes, neutrophils, monocytes, and endothelial cells. Fibroblast subpopulations with differing fibrotic potentials were identified, and their distributions were found to be altered in diabetic vs. non-diabetic cells. Conclusions: scRNA-seq of clinical wound samples can be achieved using minor modifications to standard processing protocols and data analysis methods. This simple approach can capture widespread transcriptional differences between diabetic and non-diabetic tissue obtained from matched wound locations.

Abstract 527: Isolation of large and diverse monoclonal antibody panels against the multipass membrane protein targets Kv1.3, P2X7, and Claudin 18.2

Abstract Monoclonal antibodies (MAbs) are a well-established treatment approach in oncology and other diseases. Nevertheless, multipass membrane proteins are largely inaccessible as MAb targets due to their poor expression, membrane-dependent structure, small extracellular regions, and high sequence conservation between humans and rodents. Integral Molecular's MPS Antibody Discovery platform specifically addresses each of these challenges. Using this platform, we have isolated large and diverse panels of functional (agonist/antagonist) MAbs against targets including Claudin 18.2 and the ion channels P2X7 and Kv1.3. A key feature that enables the success of the platform is the use of divergent species for immunization. Chickens are immunized with a combination of DNA and Lipoparticles (high-concentration membrane proteins) to obtain high-titer immune responses against the native membrane protein. Our optimized phage-display protocols allow the isolation of large panels of MAbs against diverse epitopes. The MPS Antibody Discovery platform offers the potential for discovering MAbs against difficult targets in cancer with a success rate over 95%. Citation Format: Lewis J. Stafford, Sharon Willis, Joseph Rucker, Benjamin Doranz, Ross Chambers. Isolation of large and diverse monoclonal antibody panels against the multipass membrane protein targets Kv1.3, P2X7, and Claudin 18.2 [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 527.

Crosslinguistic influence and L2 grammar learning: Proposed replications of Ellis and Sagarra (2011) and Tolentino and Tokowicz (2014)

AbstractInvestigations of crosslinguistic effects in second language acquisition (SLA) have contributed rich understandings about the ways in which prior language knowledge and experience can influence additional language learning. Building on this work, one recent line of research has examined the extent to which SLA findings about crosslinguistic influence can be used to improve L2 learning, indicating that explicit instruction tailored to address the nature of the crosslinguistic learning problem can benefit L2 performance. At the same time, however, this line of inquiry is relatively novel and under-researched. The aim of this paper, therefore, is to suggest further research which might advance knowledge and understanding about the ways in which explicit instruction can facilitate second language (L2) learning of crosslinguistically difficult target features. To this end, I lay the ground for a series of close replications designed to understand the role of prior language knowledge and experience in L2 learning: Ellis and Sagarra (2011) and Tolentino and Tokowicz (2014). These studies were selected because they are grounded in empirical SLA research and SLA theory. In addition, the selected studies facilitate replication because they have either (i) made their data collection materials available in digital repositories or (ii) have robustly described their design and provided the stimuli used.

CnnAlpha: Protein disordered regions prediction by reduced amino acid alphabets and convolutional neural networks.

Intrinsically disordered regions (IDR) play an important role in key biological processes and are closely related to human diseases. IDRs have great potential to serve as targets for drug discovery, most notably in disordered binding regions. Accurate prediction of IDRs is challenging because their genome wide occurrence and a low ratio of disordered residues make them difficult targets for traditional classification techniques. Existing computational methods mostly rely on sequence profiles to improve accuracy which is time consuming and computationally expensive. This article describes an ab initio sequence-only prediction method-which tries to overcome the challenge of accurate prediction posed by IDRs-based on reduced amino acid alphabets and convolutional neural networks (CNNs). We experiment with six different 3-letter reduced alphabets. We argue that the dimensional reduction in the input alphabet facilitates the detection of complex patterns within the sequence by the convolutional step. Experimental results show that our proposed IDR predictor performs at the same level or outperforms other state-of-the-art methods in the same class, achieving accuracy levels of 0.76 and AUC of 0.85 on the publicly available Critical Assessment of protein Structure Prediction dataset (CASP10). Therefore, our method is suitable for proteome-wide disorder prediction yielding similar or better accuracy than existing approaches at a faster speed.

Isotopically Enriched 192Os Target Preparation using the Electron-gun Beam Method at Target Preparation Laboratory, Daresbury, UK.

In this work, we have discussed a novel electron gun beam method used for the preparation of an Osmium foil sample at Daresbury Target Preparatory Laboratory, UK, which was used during the 192Os(18O, 16O)194Os 2 neutron transfer reaction at IFIN-HH Bucharest. The successful measurement of gamma energies associated with the 194Os isotopic nucleus recorded from the experiment with the high resolution HPGe detectors from this clean target of 192Os showed that this method has proven very efficient in preparing the most difficult osmium target which other methods like the sputtering, thermal evaporation could not get it prepared due to the high melting point of about 3000 0C found in the Osmium foil.

Cryo-EM analysis of a membrane protein embedded in the liposome

Membrane proteins (MPs) used to be the most difficult targets for structural biology when X-ray crystallography was the mainstream approach. With the resolution revolution of single-particle electron cryo-microscopy (cryo-EM), rapid progress has been made for structural elucidation of isolated MPs. The next challenge is to preserve the electrochemical gradients and membrane curvature for a comprehensive structural elucidation of MPs that rely on these chemical and physical properties for their biological functions. Toward this goal, here we present a convenient workflow for cryo-EM structural analysis of MPs embedded in liposomes, using the well-characterized AcrB as a prototype. Combining optimized proteoliposome isolation, cryo-sample preparation on graphene grids, and an efficient particle selection strategy, the three-dimensional (3D) reconstruction of AcrB embedded in liposomes was obtained at 3.9 Å resolution. The conformation of the homotrimeric AcrB remains the same when the surrounding membranes display different curvatures. Our approach, which can be widely applied to cryo-EM analysis of MPs with distinctive soluble domains, lays out the foundation for cryo-EM analysis of integral or peripheral MPs whose functions are affected by transmembrane electrochemical gradients or/and membrane curvatures.

Current pivotal strategies leading a difficult target protein to a sample suitable for crystallographic analysis.

Crystallographic structural analysis is an essential method for the determination of protein structure. However, crystallization of a protein of interest is the most difficult process in the analysis. The process is often hampered during the sample preparation, including expression and purification. Even after a sample has been purified, not all candidate proteins crystallize. In this mini-review, the current methodologies used to overcome obstacles encountered during protein crystallization are sorted. Specifically, the strategy for an effective crystallization is compared with a pipeline where various expression hosts and constructs, purification and crystallization conditions, and crystallization chaperones as target-specific binder proteins are assessed by a precrystallization screening. These methodologies are also developed continuously to improve the process. The described methods are useful for sample preparation in crystallographic analysis and other structure determination techniques, such as cryo-electron microscopy.

Learning, Generalization, and Scalability of Abstract Myoelectric Control.

Motor learning-based methods offer an alternative paradigm to machine learning-based methods for controlling upper-limb prosthetics. Within this paradigm, the patterns of muscular activity used for control can differ from those which control biological limbs. Practice expedites the learning of these new, functional patterns of muscular activity. We envisage that these methods can result in enhanced control without increasing device complexity. However, key questions about training protocols, generalisation and scalability of motor learning-based methods have remained. In this work, we pursue three objectives: 1) to validate the motor learning-based abstract myoelectric control approach with people with upper-limb difference for the first time; 2) to test whether, after training, participants can generalize their learning to tasks of increased difficulty; and 3) to show that abstract myoelectric control scales with additional input signals, offering a larger control range. In three experiments, 25 limb-intact participants and 8 people with a limb difference (congenital and acquired) experienced a motor learning-based myoelectric controlled interface. We show that participants with upper-limb difference can learn to control the interface and that performance increases with experience. Across experiments, participant performance on easier lower target density tasks generalized to more difficult higher target density tasks. A proof-of-concept study demonstrates that learning-based control scales with additional myoelectric channels. Our results show that human motor learning-based approaches can enhance the number of distinct outputs from the musculature, thereby increasing the functionality of prosthetic hands and providing a viable alternative to machine learning.

Abstract 20: Targeting difficult targets with lysine-covalent ligands: Expanding the druggable space for covalent drugs

Abstract Oncology drugs osimertinib, ibrutinib, neratinib, and afatinib have all been approved in very recent years by the FDA, and all target a cysteine that is present in proximity to the binding site of their respective targets. More recently, Amgen reported on AMG 510 as a first-in-class investigational drug designed to selectively and irreversibly target the KRAS G12C protein. These drugs rely on acrylamides moieties strategically incorporated in their chemical structures to selectively and efficiently react with binding site cysteine residues. Obviously, the approach is limited to drug targets that present a cysteine residue in proximity to the binding site, which often is not the case. This druggable target space for covalent drugs is called the Cysteinome. My laboratory has been developing and applying novel strategies aimed at deriving potent, selective, cell-permeable, and efficacious covalent therapeutics by designing agents that can selectively react with lysine residues (1,2). The approach relies on introducing stable aryl-fluorosulfates or sulfonyl-fluorides in drug leads to selectively and efficiently react with lysine residues. Because lysines are more ubiquitously found within the binding pocket of the target oncogenes, the approach defines a much larger target space for covalent drugs: the Lysinome. In addition, I will demonstrate that the approach is amenable also to tackle difficult targets such as those involving protein-protein interactions (PPIs). Hence, our work widens the available target space beyond cysteine and also allows the development of novel drug candidates against PPIs, which represent an untapped large class of therapeutic targets in oncology. Examples will include potent and selective Lys-covalent agents targeting antiapoptotic proteins in the IAP and Bcl-2 families of proteins, including particularly exciting, yet to be published results.

Allele-Specific Prevention of Nonsense-Mediated Decay in Cystic Fibrosis Using Homology-Independent Genome Editing

Nonsense-mediated decay (NMD) is a major pathogenic mechanism underlying a diversity of genetic disorders. Nonsense variants tend to lead to more severe disease phenotypes and are often difficult targets for small molecule therapeutic development as a result of insufficient protein production. The treatment of cystic fibrosis (CF), an autosomal recessive disease caused by mutations in the CFTR gene, exemplifies the challenge of therapeutically addressing nonsense mutations in human disease. Therapeutic development in CF has led to multiple, highly successful protein modulatory interventions, yet no targeted therapies have been approved for nonsense mutations. Here, we have designed a CRISPR-Cas9-based strategy for the targeted prevention of NMD of CFTR transcripts containing the second most common nonsense variant listed in CFTR2, W1282X. By introducing a deletion of the downstream genic region following the premature stop codon, we demonstrate significantly increased protein expression of this mutant variant. Notably, in combination with protein modulators, genome editing significantly increases the potentiated channel activity of W1282X-CFTR in human bronchial epithelial cells. Furthermore, we show how the outlined approach can be modified to permit allele-specific editing. The described approach can be extended to other late-occurring nonsense mutations in the CFTR gene or applied as a generalized approach for gene-specific prevention of NMD in disorders where a truncated protein product retains full or partial functionality.

Role of Mesenchymal Stem Cells in Counteracting Oxidative Stress-Related Neurodegeneration.

Neurodegenerative diseases include a variety of pathologies such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, amyotrophic lateral sclerosis, and so forth, which share many common characteristics such as oxidative stress, glycation, abnormal protein deposition, inflammation, and progressive neuronal loss. The last century has witnessed significant research to identify mechanisms and risk factors contributing to the complex etiopathogenesis of neurodegenerative diseases, such as genetic, vascular/metabolic, and lifestyle-related factors, which often co-occur and interact with each other. Apart from several environmental or genetic factors, in recent years, much evidence hints that impairment in redox homeostasis is a common mechanism in different neurological diseases. However, from a pharmacological perspective, oxidative stress is a difficult target, and antioxidants, the only strategy used so far, have been ineffective or even provoked side effects. In this review, we report an analysis of the recent literature on the role of oxidative stress in Alzheimer’s and Parkinson’s diseases as well as in amyotrophic lateral sclerosis, retinal ganglion cells, and ataxia. Moreover, the contribution of stem cells has been widely explored, looking at their potential in neuronal differentiation and reporting findings on their application in fighting oxidative stress in different neurodegenerative diseases. In particular, the exposure to mesenchymal stem cells or their secretome can be considered as a promising therapeutic strategy to enhance antioxidant capacity and neurotrophin expression while inhibiting pro-inflammatory cytokine secretion, which are common aspects of neurodegenerative pathologies. Further studies are needed to identify a tailored approach for each neurodegenerative disease in order to design more effective stem cell therapeutic strategies to prevent a broad range of neurodegenerative disorders.

Hypertemporal Imaging Capability of UAS Improves Photogrammetric Tree Canopy Models

Small uncrewed aerial systems (UASs) generate imagery that can provide detailed information regarding condition and change if the products are reproducible through time. Densified point clouds form the basic information for digital surface models and orthorectified mosaics, so variable dense point reconstruction will introduce uncertainty. Eucalyptus trees typically have sparse and discontinuous canopies with pendulous leaves that present a difficult target for photogrammetry software. We examine how spectral band, season, solar azimuth, elevation, and some processing settings impact completeness and reproducibility of dense point clouds for shrub swamp and Eucalyptus forest canopy. At the study site near solar noon, selecting near infrared camera increased projected tree canopy fourfold, and dense point features more than 2 m above ground were increased sixfold compared to red spectral bands. Near infrared (NIR) imagery improved projected and total dense features two- and threefold, respectively, compared to default green band imagery. The lowest solar elevation captured (25°) consistently improved canopy feature reconstruction in all spectral bands. Although low solar elevations are typically avoided for radiometric reasons, we demonstrate that these conditions improve the detection and reconstruction of complex tree canopy features in natural Eucalyptus forests. Combining imagery sets captured at different solar elevations improved the reproducibility of dense point clouds between seasons. Total dense point cloud features reconstructed were increased by almost 10 million points (20%) when imagery used was NIR combining solar noon and low solar elevation imagery. It is possible to use agricultural multispectral camera rigs to reconstruct Eucalyptus tree canopy and shrub swamp by combining imagery and selecting appropriate spectral bands for processing.

Automation reliability, human–machine system performance, and operator compliance: A study with airport security screeners supported by automated explosives detection systems for cabin baggage screening

Using a simulated X-ray screening task, we tested 122 airport security screeners working with the support of explosives detection systems for cabin baggage screening (EDSCB) as low-level automation. EDSCB varied systematically on three automation reliability measures: accuracy, d', and positive predictive value (PPV). Results showed that when unaided performance was high, operator confidence was high, and automation provided only small benefits. When unaided performance was lower, operator confidence was lower, and automation with higher d' provided large benefits. Operator compliance depended on the PPV of automation: We found lower compliance for lower PPV. Automation with a high false alarm rate of 20% and a low PPV of .3 resulted in operators ignoring about one-half of the true automation alarms on difficult targets—a strong cry-wolf effect. Our results suggest that automation reliability described by d' and PPV is more valid than using accuracy alone. When the PPV is below .5, operators should receive clear instructions on how to respond to automation alarms.

Crystalizing Structured RNAs Using a Surface‐Entropy‐Reduced Fab as a Crystallization Chaperone

Our lab studies the molecular mechanisms of regulatory RNAs elements by determining their atomic resolution structure using x‐ray crystallography. However, RNA crystallization presents many challenges. One strategy to meet these challenges is the use of a protein chaperone to assist RNA crystallization. Antibody fragments (Fabs) provide one type of crystallization chaperone, and we have used these successfully for RNA crystallization in two ways. In one approach, a Fab‐binding‐RNA epitope is grafted into the RNA of interest to create a binding site for the cognate Fab crystallization chaperone. To improve this method, I performed surface entropy reduction on the Fab framework to make a version of our crystallization chaperone that is more suited to well‐ordered crystal packing. Using structural analysis software as a guide, I made twelve surface‐entropy‐reduced (SER) mutant versions of the Fab framework, in which patches of bulky, flexible residues are mutated to alanine. To test the performance of these mutants, I carried out crystallization trials of their complexes with the yjdF RNA, a novel bacterial riboswitch that binds to aza‐aromatic compounds. The wild type Fab (wt BL3‐6) and many of the mutants were able to crystalize with the riboswitch and gave diffraction datasets with 3.5 – 3 angstrom resolution range, and the structure is currently being solved. Using the mutants, I have also crystalized a second RNA target, PEMV2, which is a viral cap‐independent‐translation‐element. This RNA crystalized with wild type but could only diffract to 2.75 angstrom resolution with the aid of a mutant. I am in the process of solving this structure which will give valuable hints to the mechanism of action of this class of viral cap‐independent‐translation‐elements. As I refine this crystallization chaperone technology, I will also apply it to a notoriously difficult crystallization target, domain V of the human polio virus IRES.Support or Funding InformationNIH, HHMI, The University of Chicago

Resolution of Inflammation and Gut Repair in IBD: Translational Steps Towards Complete Mucosal Healing.

Despite significant recent therapeutic advances, complete mucosal healing remains a difficult treatment target for many patients with inflammatory bowel diseases (IBD) to achieve. Our review focuses on the translational concept of promoting resolution of inflammation and repair as a necessary adjunctive step to reach this goal. We explore the roles of inflammatory cell apoptosis and efferocytosis to promote resolution, the new knowledge of gut monocyte-macrophage populations and their secreted prorepair mediators, and the processes of gut epithelial repair and regeneration to bridge this gap. We discuss the need and rationale for this vision and the tangible steps toward integrating proresolution therapies in IBD.