Vaccine hesitancy and emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) escaping vaccine-induced immune responses highlight the urgency for new COVID-19 therapeutics. Engineered angiotensin-converting enzyme 2 (ACE2) proteins with augmented binding affinities for SARS-CoV-2 spike (S) protein may prove to be especially efficacious against multiple variants. Using molecular dynamics simulations and functional assays, we show that three amino acid substitutions in an engineered soluble ACE2 protein markedly augmented the affinity for the S protein of the SARS-CoV-2 WA-1/2020 isolate and multiple VOCs: B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma) and B.1.617.2 (Delta). In humanized K18-hACE2 mice infected with the SARS-CoV-2 WA-1/2020 or P.1 variant, prophylactic and therapeutic injections of soluble ACE22.v2.4-IgG1 prevented lung vascular injury and edema formation, essential features of CoV-2-induced SARS, and above all improved survival. These studies demonstrate broad efficacy in vivo of an engineered ACE2 decoy against SARS-CoV-2 variants in mice and point to its therapeutic potential.

Some Bacteroidetes and other human colonic bacteria can degrade arabinoxylans, common polysaccharides found in dietary fiber. Previous work has identified gene clusters (polysaccharide-utilization loci, PULs) for degradation of simple arabinoxylans. However, the degradation of complex arabinoxylans (containing side chains such as ferulic acid, a phenolic compound) is poorly understood. Here, we identify a PUL that encodes multiple esterases for degradation of complex arabinoxylans in Bacteroides species. The PUL is specifically upregulated in the presence of complex arabinoxylans. We characterize some of the esterases biochemically and structurally, and show that they release ferulic acid from complex arabinoxylans. Growth of four different colonic Bacteroidetes members, including Bacteroides intestinalis, on complex arabinoxylans results in accumulation of ferulic acid, a compound known to have antioxidative and immunomodulatory properties.

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The therapeutic potential of cannabinoid receptors is not fully explored due to psychoactive side effects and lack of selectivity associated with orthosteric ligands. Allosteric modulators have the potential to become selective therapeutics for cannabinoid receptors. Biochemical experiments have shown the effects of the allosteric Na+ binding on cannabinoid receptor activity. However, the Na+ coordination site and binding pathway are still unknown. Here, we perform molecular dynamic simulations to explore Na+ binding in the cannabinoid receptors, CB1 and CB2. Simulations reveal that Na+ binds to the primary binding site from different extracellular sites for CB1 and CB2. A distinct secondary Na+ coordination site is identified in CB1 that is not present in CB2. Furthermore, simulations also show that intracellular Na+ could bind to the Na+ binding site in CB1. Constructed Markov state models show that the standard free energy of Na+ binding is similar to the previously calculated free energy for other class A GPCRs.

Design of cannabinergic subtype selective ligands is challenging because of high sequence and structural similarities of cannabinoid receptors (CB1 and CB2). We hypothesize that the subtype selectivity of designed selective ligands can be explained by the ligand binding to the conformationally distinct states between cannabinoid receptors. Analysis of ~ 700 μs of unbiased simulations using Markov state models and VAMPnets identifies the similarities and distinctions between the activation mechanism of both receptors. Structural and dynamic comparisons of metastable intermediate states allow us to observe the distinction in the binding pocket volume change during CB1 and CB2 activation. Docking analysis reveals that only a few of the intermediate metastable states of CB1 show high affinity towards CB2 selective agonists. In contrast, all the CB2 metastable states show a similar affinity for these agonists. These results mechanistically explain the subtype selectivity of these agonists by deciphering the activation mechanism of cannabinoid receptors.

Cannabinoid receptors (CB1 and CB2) are important drug targets for inflammation, obesity, and other central nervous system disorders. However, due to sequence and structural similarities of the ligand binding pockets of these receptors, most of the ligands lack subtype selectivity and cause off-target side effects. CB2 selective agonists can potentially treat pain and inflammation without the psychoactive effects of CB1 agonism. We hypothesize that the subtype selectivity of designed selective ligands can be explained by ligand binding to the conformationally distinct states between CB1 and CB2. To find these conformationally distinct states, we perform 700 μs of unbiased simulations to study the activation mechanism of both the receptors in absence of ligands. The simulation datasets of two receptors were analyzed using Markov state models to identify similarities and distinctions of the major conformational changes associated with activation and allosteric communication between them. Specifically, toggle switch residue movement and its effect on receptor activation differ greatly between CB1 and CB2. Upon further analysis, we discretize the conformational ensembles of both receptors into metastable states using the neural network-based VAMPnets. Structural and dynamic comparisons of these metastable states allow us to decipher a coarse-grained view of protein activation by revealing sequential conversion between these states. Specifically, we observe the difference in the binding pocket volume of different metastable states of CB1, whereas there are minimal changes observed in the CB2. Docking analysis reveals that differential binding pocket volume leads to distinct binding poses and docking affinities of CB2 selective agonists in CB1. Only a few of the intermediate metastable states of CB1 shows high affinity towards CB2 selective agonists. On the other hand, all the CB2 metastable states show a similar affinity for CB2 selective agonists, explaining these ligands overall higher affinity towards CB2. Overall, this computational study mechanistically explains the subtype selectivity of CB2 selective ligands by deciphering the activation mechanism of cannabinoid receptors.

A robust synthesis methodology for crystallizing nanoporous single-layer graphene hosting a high density of size-selective nanopores is urgently needed to realize the true potential of two-dimensional membranes for gas separation. Currently, there are no controllable etching techniques for single-layer graphene that are self-limiting, and that can generate size-selective nanopores at a high pore-density. In this work, we simulate a unique chemical vapor deposition based crystallization of graphene on Cu(111), in the presence of an etchant, to generate a high density (>1013 cm−2) of sub-nanometer-sized, elongated nanopores in graphene. An equilibrium between the growth rate and the etching rate is obtained, and beyond a critical time, the total number of the carbon atoms and the edge carbon atoms do not change. Using an optimal first-order etching chemistry, a log-mean pore-size of 5.0 ± 1.7 (number of missing carbon atoms), and a pore-density of 3 × 1013 cm−2 was achieved. A high throughput calculation route for estimating gas selectivity from ensembles of thousands of nanopores was developed. The optimized result yielded H2/CO2, H2/N2 and H2/CH4 selectivities larger than 200, attributing to elongated pores generated by the competitive etching and growth. The approach of competitive etching during the crystal growth is quite generic and can be applied to a number of two-dimensional materials.