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Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease causing dementia and poses significant health risks to middle-aged and elderly people. Brain magnetic resonance imaging (MRI) is the most widely used diagnostic method for AD. However, it is challenging to collect sufficient brain imaging data with high-quality annotations. Weakly supervised learning (WSL) is a machine learning technique aimed at learning effective feature representation from limited or low-quality annotations. In this paper, we propose a WSL-based deep learning (DL) framework (ADGNET) consisting of a backbone network with an attention mechanism and a task network for simultaneous image classification and image reconstruction to identify and classify AD using limited annotations. The ADGNET achieves excellent performance based on six evaluation metrics (Kappa, sensitivity, specificity, precision, accuracy, F1-score) on two brain MRI datasets (2D MRI and 3D MRI data) using fine-tuning with only 20% of the labels from both datasets. The ADGNET has an F1-score of 99.61% and sensitivity is 99.69%, outperforming two state-of-the-art models (ResNext WSL and SimCLR). The proposed method represents a potential WSL-based computer-aided diagnosis method for AD in clinical practice.
Unc-51-like kinase 4 (ULK4) is a pseudokinase that has been linked to the development of several diseases. Even though sequence motifs required for ATP binding in kinases are lacking, ULK4 still tightly binds ATP and the presence of the cofactor is required for structural stability of ULK4. Here we present a high-resolution structure of a ULK4-ATPγS complex revealing a highly unusual ATP binding mode in which the lack of the canonical VAIK motif lysine is compensated by K39, located N-terminal to αC. Evolutionary analysis suggests that degradation of active site motifs in metazoan ULK4 has co-occurred with an ULK4 specific activation loop, which stabilizes the C-helix. In addition, cellular interaction studies using BioID and biochemical validation data revealed high confidence interactors of the pseudokinase and armadillo repeat domains. Many of the identified ULK4 interaction partners were centrosomal and tubulin associated proteins and several active kinases suggesting new roles for ULK4.
Highlights: Structure of the ULK4 ATP complex reveals a unique ATP binding mode.
Disease associated mutations modulate ATP binding and ULK4 stability
Degradation of active site motifs co-occurred in evolution with an ULK4 specific activation loop
BioID suggests a role of ULK4 regulating centrosomal and cytoskeletal functions,
MKK7 (MEK7) is a key regulator of the JNK stress signaling pathway and targeting MKK7 has been proposed as a chemotherapeutic strategy. Detailed understanding of the MKK7 structure and factors that impact its activity is therefore of critical importance. Here, we present a comprehensive set of MKK7 crystal structures revealing insights into catalytic domain plasticity and the role of the N-terminal regulatory helix, conserved in all MAP2Ks, mediating kinase activation. Crystal structures harboring this regulatory helix revealed typical structural features of active kinase, providing exclusively a first model of the MAP2K active state. A small molecule screening campaign yielded multiple scaffolds, including type-II irreversible inhibitors a binding mode that has not been reported previously. We also observed an unprecedented allosteric pocket located in the N-terminal lobe for the approved drug ibrutinib. Collectively, our structural and functional data expand and provide alternative targeting strategies for this important MAP2K kinase.
Selectivity remains a challenge for ATP-mimetic kinase inhibitors, an issue that may be overcome by targeting unique residues or binding pockets. However, to date only few strategies have been developed. Here we identify that bulky residues located N-terminal to the DFG motif (DFG-1) represent an opportunity for designing highly selective inhibitors with unexpected binding modes. We demonstrate that several diverse inhibitors exerted selective, noncanonical binding modes that exclusively target large hydrophobic DFG-1 residues present in many kinases including PIM, CK1, DAPK, and CLK. By use of the CLK family as a model, structural and biochemical data revealed that the DFG-1 valine controlled a noncanonical binding mode in CLK1, providing a rationale for selectivity over the closely related CLK3 which harbors a smaller DFG-1 alanine. Our data suggest that targeting the restricted back pocket in the small fraction of kinases that harbor bulky DFG-1 residues offers a versatile selectivity filter for inhibitor design.
Selectivity remains a challenge for ATP-mimetic kinase inhibitors, an issue that may be overcome by targeting unique residues or binding pockets. However, to date only few strategies have been developed. Here we identify that bulky residues located N-terminal to the DFG motif (DFG-1) represent an opportunity for designing highly selective inhibitors with unexpected binding modes. We demonstrate that several diverse inhibitors exerted selective, non-canonical binding modes that exclusively target large hydrophobic DFG-1 residues present in many kinases including PIM, CK1, DAPK and CLK. Using the CLK family as a model, structural and biochemical data revealed that the DFG-1 valine controlled a non-canonical binding mode in CLK1, providing a rational for selectivity over the closely-related CLK3 which harbors a smaller DFG-1 alanine. Our data suggests that targeting the restricted back pocket in the small fraction of kinases that harbor bulky DFG-1 residues offers a versatile selectivity filter for inhibitor design.
Single-particle electron cryo-microscopy (cryoEM) has undergone a `resolution revolution' that makes it possible to characterize megadalton (MDa) complexes at atomic resolution without crystals. To fully exploit the new opportunities in molecular microscopy, new procedures for the cloning, expression and purification of macromolecular complexes need to be explored. Macromolecular assemblies are often unstable, and invasive construct design or inadequate purification conditions and sample-preparation methods can result in disassembly or denaturation. The structure of the 2.6 MDa yeast fatty acid synthase (FAS) has been studied by electron microscopy since the 1960s. Here, a new, streamlined protocol for the rapid production of purified yeast FAS for structure determination by high-resolution cryoEM is reported. Together with a companion protocol for preparing cryoEM specimens on a hydrophilized graphene layer, the new protocol yielded a 3.1 Å resolution map of yeast FAS from 15 000 automatically picked particles within a day. The high map quality enabled a complete atomic model of an intact fungal FAS to be built.
Modular polyketide synthases (PKSs) produce complex, bioactive secondary metabolites in assembly line-like multistep reactions. Longstanding efforts to produce novel, biologically active compounds by recombining intact modules to new modular PKSs have mostly resulted in poorly active chimeras and decreased product yields. Recent findings demonstrate that the low efficiencies of modular chimeric PKSs also result from rate limitations in the transfer of the growing polyketide chain across the non-cognate module:module interface and further processing of the non-native polyketide substrate by the ketosynthase (KS) domain. In this study, we aim at disclosing and understanding the low efficiency of chimeric modular PKSs and at establishing guidelines for modular PKSs engineering. To do so, we work with a bimodular PKS testbed and systematically vary substrate specificity, substrate identity, and domain:domain interfaces of the KS involved reactions. We observe that KS domains employed in our chimeric bimodular PKSs are bottlenecks with regards to both substrate specificity as well as interaction with the ACP. Overall, our systematic study can explain in quantitative terms why early oversimplified engineering strategies based on the plain shuffling of modules mostly failed and why more recent approaches show improved success rates. We moreover identify two mutations of the KS domain that significantly increased turnover rates in chimeric systems and interpret this finding in mechanistic detail.
The ongoing pandemic caused by the Betacoronavirus SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) demonstrates the urgent need of coordinated and rapid research towards inhibitors of the COVID-19 lung disease. The covid19-nmr consortium seeks to support drug development by providing publicly accessible NMR data on the viral RNA elements and proteins. The SARS-CoV-2 genome encodes for approximately 30 proteins, among them are the 16 so-called non-structural proteins (Nsps) of the replication/transcription complex. The 217-kDa large Nsp3 spans one polypeptide chain, but comprises multiple independent, yet functionally related domains including the viral papain-like protease. The Nsp3e sub-moiety contains a putative nucleic acid-binding domain (NAB) with so far unknown function and consensus target sequences, which are conceived to be both viral and host RNAs and DNAs, as well as protein-protein interactions. Its NMR-suitable size renders it an attractive object to study, both for understanding the SARS-CoV-2 architecture and drugability besides the classical virus’ proteases. We here report the near-complete NMR backbone chemical shifts of the putative Nsp3e NAB that reveal the secondary structure and compactness of the domain, and provide a basis for NMR-based investigations towards understanding and interfering with RNA- and small-molecule-binding by Nsp3e.
Fragment-based screening has evolved as a remarkable approach within the drug discovery process both in the industry and academia. Fragment screening has become a more structure-based approach to inhibitor development, but also towards development of pathway-specific clinical probes. However, it is often witnessed that the availability, immediate and long-term, of a high quality fragment-screening library is still beyond the reach of most academic laboratories. Within iNEXT (Infrastructure for NMR, EM and X-rays for Translational research), a EU-funded Horizon 2020 program, a collection of 782 fragments were assembled utilizing the concept of “poised fragments” with the aim to facilitate downstream synthesis of ligands with high affinity by fragment ligation. Herein, we describe the analytical procedure to assess the quality of this purchased and assembled fragment library by NMR spectroscopy. This quality assessment requires buffer solubility screening, comparison with LC/MS quality control and is supported by state-of-the-art software for high throughput data acquisition and on-the-fly data analysis. Results from the analysis of the library are presented as a prototype of fragment progression through the quality control process.
The current pandemic situation caused by the Betacoronavirus SARS-CoV-2 (SCoV2) highlights the need for coordinated research to combat COVID-19. A particularly important aspect is the development of medication. In addition to viral proteins, structured RNA elements represent a potent alternative as drug targets. The search for drugs that target RNA requires their high-resolution structural characterization. Using nuclear magnetic resonance (NMR) spectroscopy, a worldwide consortium of NMR researchers aims to characterize potential RNA drug targets of SCoV2. Here, we report the characterization of 15 conserved RNA elements located at the 5′ end, the ribosomal frameshift segment and the 3′-untranslated region (3′-UTR) of the SCoV2 genome, their large-scale production and NMR-based secondary structure determination. The NMR data are corroborated with secondary structure probing by DMS footprinting experiments. The close agreement of NMR secondary structure determination of isolated RNA elements with DMS footprinting and NMR performed on larger RNA regions shows that the secondary structure elements fold independently. The NMR data reported here provide the basis for NMR investigations of RNA function, RNA interactions with viral and host proteins and screening campaigns to identify potential RNA binders for pharmaceutical intervention.