Molecular Dynamics Simulations of the Allosteric Modulation of the Adenosine A2A Receptor by a Mini-G Protein

The PIWI-specific insertion module helps load longer piRNAs for translational activation essential for male fertility

PIWI-clade proteins harness piRNAs of 24-33 nt in length. Of great puzzles are how PIWI-clade proteins incorporate piRNAs of different sizes and whether the size matters to PIWI/piRNA function. Here we report that a PIWI-Ins module unique in PIWI-clade proteins helps define the length of piRNAs. Deletion of PIWI-Ins in Miwi shifts MIWI to load with shorter piRNAs and causes spermiogenic failure in mice, demonstrating the functional importance of this regulatory module. Mechanistically, we show that longer piRNAs provide additional complementarity to target mRNAs, thereby enhancing the assembly of the MIWI/eIF3f/HuR super-complex for translational activation. Importantly, we identify a c.1108C>T (p.R370W) mutation of HIWI (human PIWIL1) in infertile men and demonstrate in Miwi knock-in mice that this genetic mutation impairs male fertility by altering the property of PIWI-Ins in selecting longer piRNAs. These findings reveal a critical role of PIWI-Ins-ensured longer piRNAs in fine-tuning MIWI/piRNA targeting capacity, proven essential for spermatid development and male fertility.

On the force field optimisation of [Formula: see text]-lactam cores using the force field Toolkit

When employing molecular dynamics (MD) simulations for computer-aided drug design, the quality of the used force fields is highly important. Here we present reparametrisations of the force fields for the core molecules from 9 different [Formula: see text]-lactam classes, for which we utilized the force field Toolkit and Gaussian calculations. We focus on the parametrisation of the dihedral angles, with the goal of reproducing the optimised quantum geometry in MD simulations. Parameters taken from CGenFF turn out to be a good initial guess for the multiplicity of each dihedral angle, but the key to a successful parametrisation is found to lie in the phase shifts. Based on the optimised quantum geometry, we come up with a strategy for predicting the phase shifts prior to the dihedral potential fitting. This allows us to successfully parameterise 8 out of the 11 molecules studied here, while the remaining 3 molecules can also be parameterised with small adjustments. Our work highlights the importance of predicting the dihedral phase shifts in the ligand parametrisation protocol, and provides a simple yet valuable strategy for improving the process of parameterising force fields of drug-like molecules.

Mechanical Allosteric Couplings of Redox-Induced Conformational Changes in Respiratory Complex I

We apply linear response theory to calculate mechanical allosteric couplings in respiratory complex I between the iron sulfur cluster N2, located in the catalytic cavity, and the membrane part of the enzyme, separated from it by more than 50 Å. According to our hypothesis, the redox reaction of ubiquinone in the catalytic cavity of the enzyme generates an unbalanced charge that via repulsion of the charged redox center N2 produces local mechanical stress that transmits into the membrane part of the enzyme where it induces proton pumping. Using coarse-grained simulations of the enzyme, we calculated mechanistic allosteric couplings that reveal the pathways of the mechanical transmission of the stress along the enzyme. The results shed light on the recent experimental studies where a stabilization of the enzyme with an introduced disulfide bridge resulted in the abolishing of proton pumping. Simulation of the disulfide bond action indicates a dramatic change of the mechanistic coupling pathways in line with experimental findings.

Glycosylation is key for enhancing drug recognition into spike glycoprotein of SARS-CoV-2

The emergence of COVID-19 caused by SARS-CoV-2 and its spread since 2019 represents the major public health problem worldwide nowadays, which has generated a high number of infections and deaths. The spike protein (S protein) is the most studied protein of SARS-CoV-2, and key to host-cell entry through ACE2 receptor. This protein presents a large pattern of glycosylations with important roles in immunity and infection mechanisms. Therefore, understanding key aspects of the molecular mechanisms of these structures, during drug recognition in SARS-CoV-2, may contribute to therapeutic alternatives. In this work, we explored the impact of glycosylations on the drug recognition on two domains of the S protein, the receptor-binding domain (RBD) and the N-terminal domain (NTD) through molecular dynamics simulations and computational biophysics analysis. Our results show that glycosylations in the S protein induce structural stability and changes in rigidity/flexibility related to the number of glycosylations in the structure. These structural changes are important for its biological activity as well as the correct interaction of ligands in the RBD and NTD regions. Additionally, we evidenced a roto-translation phenomenon in the interaction of the ligand with RBD in the absence of glycosylation, which disappears due to the influence of glycosylation and the convergence of metastable states in RBM. Similarly, glycosylations in NTD promote an induced fit phenomenon, which is not observed in the absence of glycosylations; this process is decisive for the activity of the ligand at the cryptic site. Altogether, these results provide an explanation of glycosylation relevance in biophysical properties and drug recognition to S protein of SARS-CoV-2, which must be considered in the rational drug development and virtual screening targeting S protein.

Molecular simulations of proteins: From simplified physical interactions to complex biological phenomena

Molecular dynamics simulation is the most popular computational technique for investigating the structural and dynamical behaviour of proteins, in search of the molecular basis of their function. Far from being a completely settled field of research, simulations are still evolving to best capture the essential features of the atomic interactions that govern a protein's inner motions. Modern force fields are becoming increasingly accurate in providing a physical description adequate to this purpose, and allow us to model complex biological systems under fairly realistic conditions. Furthermore, the use of accelerated sampling techniques is improving our access to the observation of progressively larger molecular structures, longer time scales, and more hidden functional events. In this review, the basic principles of molecular dynamics simulations and a number of key applications in the area of protein science are summarized, and some of the most important results are discussed. Examples include the study of the structure, dynamics and binding properties of 'difficult' targets, such as intrinsically disordered proteins and membrane receptors, and the investigation of challenging phenomena like hydration-driven processes and protein aggregation. The findings described provide an overall picture of the current state of this research field, and indicate new perspectives on the road ahead to the upcoming future of molecular simulations.

Allosteric Modulation of Adenosine A2A Receptors as a New Therapeutic Avenue

The therapeutic potential of targeting adenosine A_2A receptors (A_2ARs) is immense due to their broad expression in the body and central nervous system. The role of A_2ARs in cardiovascular function, inflammation, sleep/wake behaviors, cognition, and other primary nervous system functions has been extensively studied. Numerous A_2AR agonist and antagonist molecules are reported, many of which are currently in clinical trials or have already been approved for treatment. Allosteric modulators can selectively elicit a physiologic response only where and when the orthosteric ligand is released, which reduces the risk of an adverse effect resulting from A_2AR activation. Thus, these allosteric modulators have a potential therapeutic advantage over classical agonist and antagonist molecules. This review focuses on the recent developments regarding allosteric A_2AR modulation, which is a promising area for future pharmaceutical research because the list of existing allosteric A_2AR modulators and their physiologic effects is still short.

Comprehensive virtual screening of 4.8 k flavonoids reveals novel insights into allosteric inhibition of SARS-CoV-2 MPRO

SARS-CoV-2 main protease is a common target for inhibition assays due to its high conservation among coronaviruses. Since flavonoids show antiviral activity, several in silico works have proposed them as potential SARS-CoV-2 main protease inhibitors. Nonetheless, there is reason to doubt certain results given the lack of consideration for flavonoid promiscuity or main protease plasticity, usage of short library sizes, absence of control molecules and/or the limitation of the methodology to a single target site. Here, we report a virtual screening study where dorsilurin E, euchrenone a11, sanggenol O and CHEMBL2171598 are proposed to inhibit main protease through different pathways. Remarkably, novel structural mechanisms were observed after sanggenol O and CHEMBL2171598 bound to experimentally proven allosteric sites. The former drastically affected the active site, while the latter triggered a hinge movement which has been previously reported for an inactive SARS-CoV main protease mutant. The use of a curated database of 4.8 k flavonoids, combining two well-known docking software (AutoDock Vina and AutoDock4.2), molecular dynamics and MMPBSA, guaranteed an adequate analysis and robust interpretation. These criteria can be considered for future screening campaigns against SARS-CoV-2 main protease.

Valine-279 Deletion-Mutation on Arginine Vasopressin Receptor 2 Causes Obstruction in G-Protein Binding Site: A Clinical Nephrogenic Diabetes Insipidus Case and Its Sub-Molecular Pathogenic Analysis

Congenital nephrogenic diabetes insipidus (CNDI) is a genetic disorder caused by mutations in arginine vasopressin receptor 2 (AVPR2) or aquaporin 2 genes, rendering collecting duct cells insensitive to the peptide hormone arginine vasopressin stimulation for water reabsorption. This study reports a first identified AVPR2 mutation in Taiwan and demonstrates our effort to understand the pathogenesis caused by applying computational structural analysis tools. The CNDI condition of an 8-month-old male patient was confirmed according to symptoms, family history, and DNA sequence analysis. The patient was identified to have a valine 279 deletion-mutation in the AVPR2 gene. Cellular experiments using mutant protein transfected cells revealed that mutated AVPR2 is expressed successfully in cells and localized on cell surfaces. We further analyzed the pathogenesis of the mutation at sub-molecular levels via long-term molecular dynamics (MD) simulations and structural analysis. The MD simulations showed while the structure of the extracellular ligand-binding domain remains unchanged, the mutation alters the direction of dynamic motion of AVPR2 transmembrane helix 6 toward the center of the G-protein binding site, obstructing the binding of G-protein, thus likely disabling downstream signaling. This study demonstrated that the computational approaches can be powerful tools for obtaining valuable information on the pathogenesis induced by mutations in G-protein-coupled receptors. These methods can also be helpful in providing clues on potential therapeutic strategies for CNDI.

An in-silico layer-by-layer adsorption study of the interaction between Rebaudioside A and the T1R2 human sweet taste receptor: modelling and biosensing perspectives

The human sweet taste receptor (T1R2) monomer-a member of the G-protein coupled receptor family that detects a wide variety of chemically and structurally diverse sweet tasting molecules, is known to pose a significant threat to human health. Protein that lack crystal structure is a challenge in structure-based protein design. This study focused on the interaction of the T1R2 monomer with rebaudioside A (Reb-A), a steviol glycoside with potential use as a natural sweetener using in-silico and biosensing methods. Herein, homology modelling, docking studies, and molecular dynamics simulations were applied to elucidate the interaction between Reb-A and the T1R2 monomer. In addition, the electrochemical sensing of the immobilised T1R2-Reb-A complex with zinc oxide nanoparticles (ZnONPs) and graphene oxide (GO) were assessed by testing the performance of multiwalled carbon nanotube (MWCNT) as an adsorbent experimentally. Results indicate a strong interaction between Reb-A and the T1R2 receptor, revealing the stabilizing interaction of the amino acids with the Reb-A by hydrogen bonds with the hydroxyl groups of the glucose moieties, along with a significant amount of hydrophobic interactions. Moreover, the presence of the MWCNT as an anchor confirms the adsorption strength of the T1R2-Reb-A complex onto the GO nanocomposite and supported with electrochemical measurements. Overall, this study could serve as a cornerstone in the development of electrochemical immunosensor for the detection of Reb-A, with applications in the food industry.

Computational Investigations on the Binding Mode of Ligands for the Cannabinoid-Activated G Protein-Coupled Receptor GPR18

GPR18 is an orphan G protein-coupled receptor (GPCR) expressed in cells of the immune system. It is activated by the cannabinoid receptor (CB) agonist ∆⁹-tetrahydrocannabinol (THC). Several further lipids have been proposed to act as GPR18 agonists, but these results still require unambiguous confirmation. In the present study, we constructed a homology model of the human GPR18 based on an ensemble of three GPCR crystal structures to investigate the binding modes of the agonist THC and the recently reported antagonists which feature an imidazothiazinone core to which a (substituted) phenyl ring is connected via a lipophilic linker. Docking and molecular dynamics simulation studies were performed. As a result, a hydrophobic binding pocket is predicted to accommodate the imidazothiazinone core, while the terminal phenyl ring projects towards an aromatic pocket. Hydrophobic interaction of Cys251 with substituents on the phenyl ring could explain the high potency of the most potent derivatives. Molecular dynamics simulation studies suggest that the binding of imidazothiazinone antagonists stabilizes transmembrane regions TM1, TM6 and TM7 of the receptor through a salt bridge between Asp118 and Lys133. The agonist THC is presumed to bind differently to GPR18 than to the distantly related CB receptors. This study provides insights into the binding mode of GPR18 agonists and antagonists which will facilitate future drug design for this promising potential drug target.

Molecular Mechanism for Attractant Signaling to DHMA by E. coli Tsr

The attractant chemotaxis response of Escherichia coli to norepinephrine requires that it be converted to 3,4-dihydroxymandelic acid (DHMA) by the monoamine oxidase TynA and the aromatic aldehyde dehydrogenase FeaB. DHMA is sensed by the serine chemoreceptor Tsr, and the attractant response requires that at least one subunit of the periplasmic domain of the Tsr homodimer (pTsr) has an intact serine-binding site. DHMA that is generated in vivo by E. coli is expected to be a racemic mixture of the (R) and (S) enantiomers, so it has been unclear whether one or both chiral forms are active. Here, we used a combination of state-of-the-art tools in molecular docking and simulations, including an in-house simulation-based docking protocol, to investigate the binding properties of (R)-DHMA and (S)-DHMA to E. coli pTsr. Our studies computationally predicted that (R)-DHMA should promote a stronger attractant response than (S)-DHMA because of a consistently greater-magnitude piston-like pushdown of the pTsr α-helix 4 toward the membrane upon binding of (R)-DHMA than upon binding of (S)-DHMA. This displacement is caused primarily by interaction of DHMA with Tsr residue Thr156, which has been shown by genetic studies to be critical for the attractant response to L-serine and DHMA. These findings led us to separate the two chiral species and test their effectiveness as chemoattractants. Both the tethered cell and motility migration coefficient assays validated the prediction that (R)-DHMA is a stronger attractant than (S)-DHMA. Our study demonstrates that refined computational docking and simulation studies combined with experiments can be used to investigate situations in which subtle differences between ligands may lead to diverse chemotactic responses.