Characterization of binding kinetics and intracellular signaling of new psychoactive substances targeting cannabinoid receptor using transition-based reweighting method.

New psychoactive substances (NPS) targeting cannabinoid receptor 1 pose a significant threat to society as recreational abusive drugs that have pronounced physiological side effects. These greater adverse effects compared to classical cannabinoids have been linked to the higher downstream ß-arrestin signaling. Thus, understanding the mechanism of differential signaling will reveal important structure-activity relationship essential for identifying and potentially regulating NPS molecules. In this study, we simulate the slow (un)binding process of NPS MDMB-Fubinaca and classical cannabinoid HU-210 from CB1 using multi-ensemble simulation to decipher the effects of ligand binding dynamics on downstream signaling. The transition-based reweighing method is used for the estimation of transition rates and underlying thermodynamics of (un)binding processes of ligands with nanomolar affinities. Our analyses reveal major interaction differences with transmembrane TM7 between NPS and classical cannabinoids. A variational autoencoder-based approach, neural relational inference (NRI), is applied to assess the allosteric effects on intracellular regions attributable to variations in binding pocket interactions. NRI analysis indicate a heightened level of allosteric control of NPxxY motif for NPS-bound receptors, which contributes to the higher probability of formation of a crucial triad interaction (Y7.53-Y5.58-T3.46) necessary for stronger ß-arrestin signaling. Hence, in this work, MD simulation, data-driven statistical methods, and deep learning point out the structural basis for the heightened physiological side effects associated with NPS, contributing to efforts aimed at mitigating their public health impact.

Distinct activation mechanisms regulate subtype selectivity of Cannabinoid receptors.

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.

Activation mechanism of the human Smoothened receptor.

Smoothened (SMO) is a membrane protein of the class F subfamily of G protein-coupled receptors (GPCRs) and maintains homeostasis of cellular differentiation. SMO undergoes conformational change during activation, transmitting the signal across the membrane, making it amenable to bind to its intracellular signaling partner. Receptor activation has been studied at length for class A receptors, but the mechanism of class F receptor activation remains unknown. Agonists and antagonists bound to SMO at sites in the transmembrane domain (TMD) and the cysteine-rich domain have been characterized, giving a static view of the various conformations SMO adopts. Although the structures of the inactive and active SMO outline the residue-level transitions, a kinetic view of the overall activation process remains unexplored for class F receptors. We describe SMO's activation process in atomistic detail by performing 300 µs of molecular dynamics simulations and combining it with Markov state model theory. A molecular switch, conserved across class F and analogous to the activation-mediating D-R-Y motif in class A receptors, is observed to break during activation. We also show that this transition occurs in a stage-wise movement of the transmembrane helices: TM6 first, followed by TM5. To see how modulators affect SMO activity, we simulated agonist and antagonist-bound SMO. We observed that agonist-bound SMO has an expanded hydrophobic tunnel in SMO's core TMD, whereas antagonist-bound SMO shrinks this tunnel, further supporting the hypothesis that cholesterol travels through a tunnel inside Smoothened to activate it. In summary, this study elucidates the distinct activation mechanism of class F GPCRs and shows that SMO's activation process rearranges the core TMD to open a hydrophobic conduit for cholesterol transport.

Reconciling membrane protein simulations with experimental DEER spectroscopy data.

Spectroscopy experiments are crucial to study membrane proteins for which traditional structure determination methods still prove challenging. Double electron-electron resonance (DEER) spectroscopy experiments provide protein residue-pair distance distributions that are indicative of their conformational heterogeneity. Atomistic molecular dynamics (MD) simulations are another tool that have been proven to be vital to study the structural dynamics of membrane proteins such as to identify inward-open, occluded, and outward-open conformations of transporter membrane proteins, among other partially open or closed states of the protein. Yet, studies have reported that there is no direct consensus between the distributional data from DEER experiments and MD simulations, which has challenged validation of structures obtained from long-timescale simulations and using simulations to design experiments. Current coping strategies for comparisons rely on heuristics, such as mapping the nearest matching peaks between two ensembles or biased simulations. Here we examine the differences in residue-pair distance distributions arising due to the choice of membranes around the protein and covalent modification of a pair of residues to nitroxide spin labels in DEER experiments. Through comparing MD simulations of two proteins, PepTSo and LeuT-both of which have been characterized using DEER experiments previously-we show that the proteins' dynamics are similar despite the choice of the detergent micelle as a membrane mimetic in DEER experiments. On the other hand, covalently modified residues show slight local differences in their dynamics and a huge divergence when the oxygen atom pair distances between spin labeled residues are measured rather than protein backbone distances. Given the computational expense associated with pairwise MTSSL labeled MD simulations, we examine the use of biased simulations to explore the conformational dynamics of the spin labels only to reveal that such simulations alter the underlying protein dynamics. Our study identifies the main cause for the mismatch between DEER experiments and MD simulations and will accelerate the development of potential mitigation strategies to improve the match.

Mechanistic origin of partial agonism of tetrahydrocannabinol for cannabinoid receptors.

Cannabinoid receptor 1 (CB1) is a therapeutically relevant drug target for controlling pain, obesity, and other central nervous system disorders. However, full agonists and antagonists of CB1 have been reported to cause serious side effects in patients. Therefore, partial agonists have emerged as a viable alternative as they can mitigate overstimulation and side effects. One of the key bottlenecks in the design of partial agonists, however, is the lack of understanding of the molecular mechanism of partial agonism itself. In this study, we examine two mechanistic hypotheses for the origin of partial agonism in cannabinoid receptors and predict the mechanistic basis of partial agonism exhibited by Δ9-Tetrahydrocannabinol (THC) against CB1. In particular, we inspect whether partial agonism emerges from the ability of THC to bind in both agonist and antagonist-binding poses or from its ability to only partially activate the receptor. We used extensive molecular dynamics simulations and Markov state modeling to capture the THC binding in both antagonist and agonist-binding poses in the CB1 receptor. Furthermore, we predict that binding of THC in the agonist-binding pose leads to rotation of toggle switch residues and causes partial outward movement of intracellular transmembrane helix 6 (TM6). Our simulations also suggest that the alkyl side chain of THC plays a crucial role in determining partial agonism by stabilizing the ligand in the agonist and antagonist-like poses within the pocket. Taken together, this study provides important insights into the mechanistic origin of the partial agonism of THC.

Engineered ACE2 decoy mitigates lung injury and death induced by SARS-CoV-2 variants.

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.

Distinct Binding Mechanisms for Allosteric Sodium Ion in Cannabinoid Receptors.

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.

Degradation of complex arabinoxylans by human colonic Bacteroidetes.

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.

A detailed model and Monte Carlo simulation for predicting DIP genome length distribution in baculovirus infection of insect cells.

Baculoviruses have enormous potential for use as biopesticides to control insect pest populations without the adverse environmental effects posed by the widespread use of chemical pesticides. However, continuous baculovirus production is susceptible to DNA mutation and the subsequent production of defective interfering particles (DIPs). The amount of DIPs produced and their genome length distribution are of great interest not only for baculoviruses but for many other DNA and RNA viruses. In this study, we elucidate this aspect of virus replication using baculovirus as an example system and both experimental and modeling studies. The existing mathematical models for the virus replication process consider DIPs as a lumped quantity and do not consider the genome length distribution of the DIPs. In this study, a detailed population balance model for the cell-virus culture is presented, which predicts the genome length distribution of the DIP population along with their relative proportion. The model is simulated using the kinetic Monte Carlo algorithm, and the results agree well with the experimental results. Using this model, a practical strategy to maintain the DIP fraction to near to its maximum and minimum limits has been demonstrated.

Engineered High-Affinity ACE2 Peptide Mitigates ARDS and Death Induced by Multiple SARS-CoV-2 Variants.

Vaccine hesitancy and continuing emergence of SARS-CoV-2 variants of concern that may escape vaccine-induced immune responses highlight the urgent need for effective COVID-19 therapeutics. Monoclonal antibodies used in the clinic have varying efficacies against distinct SARS-CoV-2 variants; thus, there is considerable interest in engineered ACE2 peptides with augmented binding affinities for SARS-CoV-2 Spike protein. These could have therapeutic benefit against multiple viral variants. Using molecular dynamics simulations, we show how three amino acid substitutions in an engineered soluble ACE2 peptide (sACE2 2 .v2.4-IgG1) markedly increase affinity for the SARS-CoV-2 Spike (S) protein. We demonstrate high binding affinity to S protein of the early SARS-CoV-2 WA-1/2020 isolate and also to multiple variants of concern: B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), and B.1.617.2 (Delta) SARS-CoV-2 variants. In humanized K18-hACE2 mice, prophylactic and therapeutic administration of sACE2 2 .v2.4-IgG1 peptide prevented acute lung vascular endothelial injury and lung edema (essential features of ARDS) and significantly improved survival after infection by SARS-CoV-2 WA-1/2020 as well as P.1 variant of concern. These studies demonstrate for the first time broad efficacy in vivo of an ACE2 decoy peptide against multiple SARS-CoV-2 variants and point to its therapeutic potential.

Crystallization of gas-selective nanoporous graphene by competitive etching and growth: a modeling study.

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.