Identification of Cys255 in HIF‐1α as a novel site for development of covalent inhibitors of HIF‐1α/ARNT PasB domain protein–protein interaction

The heterodimer HIF‐1α (hypoxia inducible factor)/HIF‐β (also known as ARNT‐aryl hydrocarbon nuclear translocator) is a key mediator of cellular response to hypoxia. The interaction between these monomer units can be modified by the action of small molecules in the binding interface between their C‐terminal heterodimerization (PasB) domains. Taking advantage of the presence of several cysteine residues located in the allosteric cavity of HIF‐1α PasB domain, we applied a cysteine‐based reactomics “hotspot identification” strategy to locate regions of HIF‐1α PasB domain critical for its interaction with ARNT. COMPOUND 5 was identified using a mass spectrometry‐based primary screening strategy and was shown to react specifically with Cys255 of the HIF‐1α PasB domain. Biophysical characterization of the interaction between PasB domains of HIF‐1α and ARNT revealed that covalent binding of COMPOUND 5 to Cys255 reduced binding affinity between HIF‐1α and ARNT PasB domains approximately 10‐fold. Detailed NMR structural analysis of HIF‐1α‐PasB‐COMPOUND 5 conjugate showed significant local conformation changes in the HIF‐1α associated with key residues involved in the HIF‐1α/ARNT PasB domain interaction as revealed by the crystal structure of the HIF‐1α/ARNT PasB heterodimer. Our screening strategy could be applied to other targets to identify pockets surrounding reactive cysteines suitable for development of small molecule modulators of protein function.     

A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2

As part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated. We use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create ‘COVID-secure’ workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics. The progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels. In the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread.     

Modeling tumor invasion and metastasis in Drosophila

Conservation of major signaling pathways between humans and flies has made Drosophila a useful model organism for cancer research. Our understanding of the mechanisms regulating cell growth, differentiation and development has been considerably advanced by studies in Drosophila. Several recent high profile studies have examined the processes constraining the metastatic growth of tumor cells in fruit fly models. Cell invasion can be studied in the context of an in vivo setting in flies, enabling the genetic requirements of the microenvironment of tumor cells undergoing metastasis to be analyzed. This Perspective discusses the strengths and limitations of Drosophila models of cancer invasion and the unique tools that have enabled these studies. It also highlights several recent reports that together make a strong case for Drosophila as a system with the potential for both testing novel concepts in tumor progression and cell invasion, and for uncovering players in metastasis.