On average, an approved drug today costs $2–3 billion and takes over ten years to develop 1 . In part, this is due to expensive and time-consuming wet-lab experiments, poor initial hit compounds, and the high attrition rates in the (pre-)clinical phases. Structure-based virtual screening (SBVS) has the potential to mitigate these problems. With SBVS, the quality of the hits improves with the number of compounds screened 2 . However, despite the fact that large compound databases exist, the ability to carry out large-scale SBVSs on computer clusters in an accessible, efficient, and flexible manner has remained elusive. Here we designed VirtualFlow, a highly automated and versatile open-source platform with perfect scaling behaviour that is able to prepare and efficiently screen ultra-large ligand libraries of compounds. VirtualFlow is able to use a variety of the most powerful docking programs. Using VirtualFlow, we have prepared the largest and freely available ready-to-dock ligand library available, with over 1.4 billion commercially available molecules. To demonstrate the power of VirtualFlow, we screened over 1 billion compounds and discovered a small molecule inhibitor (iKeap1) that engages KEAP1 with nanomolar affinity ( K d = 114 nM) and disrupts the interaction between KEAP1 and the transcription factor NRF2. We also identified a set of structurally diverse molecules that bind to KEAP1 with submicromolar affinity. This illustrates the potential of VirtualFlow to access vast regions of the chemical space and identify binders with high affinity for target proteins.

SARS-CoV-2 related proteins were targeted in ultra-large in silico screens. Multiple functional sites on individual target proteins were screened. 17 virus-related targets, 45 screens, and 50 billion docking instances were covered. Conservation in some target sites means hits could exhibit pancoronavirus function. Screening results are available as an interactive web resource and for download.

SARS-CoV-2 precipitates respiratory distress by infection of airway epithelial cells and is often accompanied by acute kidney injury. We report that Kidney Injury Molecule-1/T cell immunoglobulin mucin domain 1 (KIM-1/TIM-1) is expressed in lung and kidney epithelial cells in COVID-19 patients and is a receptor for SARS-CoV-2. Human and mouse lung and kidney epithelial cells express KIM-1 and endocytose nanoparticles displaying the SARS-CoV-2 spike protein (virosomes). Uptake was inhibited both by anti-KIM-1 antibodies and by TW-37, our newly discovered inhibitor of KIM-1-mediated endocytosis. Enhanced KIM-1 expression by human kidney tubuloids increased uptake of virosomes. KIM-1 positive cells express less angiotensin-converting enzyme 2 (ACE2), the well-known receptor for SARS-CoV-2. Using microscale thermophoresis, the EC50 for KIM-1-SARS-CoV-2 spike protein, and receptor binding domain (RBD) interactions, were 19 and 10 nM respectively. Thus KIM-1 is an alternative receptor to ACE2 for SARS-CoV-2. KIM-1 targeted therapeutics may prevent and/or treat COVID-19.

Elaborate control mechanisms of intracellular triacylglycerol (TAG) breakdown are critically involved in the maintenance of energy homeostasis. Hypoxia-inducible lipid droplet-associated protein (HILPDA)/hypoxia-inducible gene-2 (Hig-2) has been shown to affect intracellular TAG levels, yet, the underlying molecular mechanisms are unclear. Here, we show that HILPDA inhibits adipose triglyceride lipase (ATGL), the enzyme catalyzing the first step of intracellular TAG hydrolysis. HILPDA shares structural similarity with G0/G1 switch gene 2 (G0S2), an established inhibitor of ATGL. HILPDA inhibits ATGL activity in a dose-dependent manner with an IC50 value of ∼2 μM. ATGL inhibition depends on the direct physical interaction of both proteins and involves the N-terminal hydrophobic region of HILPDA and the N-terminal patatin domain-containing segment of ATGL. Finally, confocal microscopy combined with Förster resonance energy transfer-fluorescence lifetime imaging microscopy analysis indicated that HILPDA and ATGL colocalize and physically interact intracellularly. These findings provide a rational biochemical explanation for the tissue-specific increased TAG accumulation in HILPDA-overexpressing transgenic mouse models.

Monoglyceride lipases (MGLs) are a group of α/β-hydrolases that catalyze the hydrolysis of monoglycerides (MGs) into free fatty acids and glycerol. This reaction serves different physiological functions, namely in the last step of phospholipid and triglyceride degradation, in mammalian endocannabinoid and arachidonic acid metabolism, and in detoxification processes in microbes. Previous crystal structures of MGLs from humans and bacteria revealed conformational plasticity in the cap region of this protein and gave insight into substrate binding. In this study, we present the structure of a MGL from Saccharomyces cerevisiae called Yju3p in its free form and in complex with a covalently bound substrate analog mimicking the tetrahedral intermediate of MG hydrolysis. These structures reveal a high conservation of the overall shape of the MGL cap region and also provide evidence for conformational changes in the cap of Yju3p. The complex structure reveals that, despite the high structural similarity, Yju3p seems to have an additional opening to the substrate binding pocket at a different position compared to human and bacterial MGL. Substrate specificities towards MGs with saturated and unsaturated alkyl chains of different lengths were tested and revealed highest activity towards MG containing a C18:1 fatty acid.

<p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), previously known as 2019 novel coronavirus (2019-nCoV), has spread rapidly across the globe, creating an unparalleled global health burden and spurring a deepening economic crisis. As of July 7th, 2020, almost seven months into the outbreak, there are no approved vaccines and few treatments available. Developing drugs that target multiple points in the viral life cycle could serve as a strategy to tackle the current as well as future coronavirus pandemics. Here we leverage the power of our recently developed <i>in silico</i> screening platform, VirtualFlow, to identify inhibitors that target SARS-CoV-2. VirtualFlow is able to efficiently harness the power of computing clusters and cloud-based computing platforms to carry out ultra-large scale virtual screens. In this unprecedented structure-based multi-target virtual screening campaign, we have used VirtualFlow to screen an average of approximately 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets in the cloud. In addition to targeting the active sites of viral enzymes, we also target critical auxiliary sites such as functionally important protein-protein interaction interfaces. This multi-target approach not only increases the likelihood of finding a potent inhibitor, but could also help identify a collection of anti-coronavirus drugs that would retain efficacy in the face of viral mutation. Drugs belonging to different regimen classes could be combined to develop possible combination therapies, and top hits that bind at highly conserved sites would be potential candidates for further development as coronavirus drugs. Here, we present the top 200 <i>in silico</i> hits for each target site. While in-house experimental validation of some of these compounds is currently underway, we want to make this array of potential inhibitor candidates available to researchers worldwide in consideration of the pressing need for fast-tracked drug development.</p>

Phospho-lipid bilayer nanodiscs have gathered much scientific interest as a stable and tunable membrane mimetic for the study of membrane proteins. Until recently the size of the nanodiscs that could be produced was limited to ∼ 16 nm. Recent advances in nanodisc engineering such as covalently circularized nanodiscs (cND) and DNA corralled nanodiscs (DCND) have opened up the possibility of engineering nanodiscs of size up to 90 nm. This enables widening the application of nanodiscs from single membrane proteins to investigating large protein complexes and biological processes such as virus-membrane fusion and synaptic vesicle fusion. Another aspect of exploiting the large available surface area of these novel nanodiscs could be to engineer more realistic membrane mimetic systems with features such as membrane asymmetry and curvature. In this review, we discuss the recent technical developments in nanodisc technology leading to construction of large nanodiscs and examine some of the implicit applications.

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