Recent Insights from Molecular Dynamics Simulations for G Protein-Coupled Receptor Drug Discovery

Impact of aging on the GABAB receptor-mediated connectome

GABA B receptors (GABABRs) are heterodimeric seven-transmembrane receptors that interact with a range of proteins and form large protein complexes on cholesterol-rich membrane microdomains. As the brain ages, membrane cholesterol levels exhibit alterations, although it remains unclear how these changes impact protein-protein interactions and downstream signaling. Herein, we studied the structural bases for the interaction between GABABR and the KCC2 transporter, including their protein expression and distribution, and we compared data between young and aged rat cerebella. Also, we analyzed lipid profiles for both groups, and we used molecular dynamics simulations on three plasma membrane systems with different cholesterol concentrations, to further explore the GABABR-transporter interaction. Based on our results, we report that a significant decrease in GABAB2 subunit expression occurs in the aged rat cerebella. After performing a comparative co-immunoprecipitation analysis, we confirm that GABABR and KCC2 form a protein complex in adult and aged rat cerebella, although their interaction levels are reduced substantially as the cerebellum ages. On the other hand, our lipid analyses reveal a significant increase in cholesterol and sphingomyelin levels of the aged cerebella. Finally, we used the Martini coarse-grained model to conduct molecular dynamics simulations, from which we observed that membrane cholesterol concentrations can dictate whether the GABABR tail domains physically establish G protein-independent contacts with a transporter, and the timing when those associations eventually occur. Taken together, our findings illustrate how age-related alterations in membrane cholesterol levels affect protein-protein interactions, and how they could play a crucial role in regulating GABABR's interactome-mediated signaling.

Significance Statement

This study elucidates age-related changes in cerebellar GABAB receptors (GABABRs), KCC2, and plasma membrane lipids, shedding light on mechanisms underlying neurological decline. Molecular dynamics simulations reveal how membrane lipids influence protein-protein interactions, offering insights into age-related neurodegeneration. The findings underscore the broader impact of cerebellar aging on motor functions, cognition, and emotional processing in the elderly. By elucidating plasma membrane regulation and GABAergic dynamics, this research lays the groundwork for understanding aging-related neurological disorders and inspires further investigation into therapeutic interventions.

N-substituted tetrahydro-beta-carboline as mu-opioid receptors ligands: in silico study; molecular docking, ADMET and molecular dynamics approach

Manipulating intracellular signals by interaction with transmembranal G-protein-coupled receptors (GPCRs) is the way of action of more than 30% of available medicines. Designing molecules against GPCRs is most challenging due to their flexible binding orthosteric and allosteric pockets, a property that lead to different mode and extent of activation of intracellular mediators. Here, in the current study we aimed to design N-substituted tetrahydro-beta-carbolines (THβC's) targeting Mu Opioid Receptors (MORs). We performed ligand docking study for reference and designed compounds against active and inactive states of MOR, as well as the active state bound to intracellular mediator of Gi. The reference compounds include 40 known agonists and antagonists, while the designed compounds include 25,227 N-substituted THβC analogues. Out of the designed compounds, 15 compounds were comparatively having better extra precision (XP) Gscore and were analyzed for absorption, distribution, metabolism, and excretion-toxicity (ADMET) properties, drug-likness, and molecular dynamic (MD) simulation. The results showed that N-substituted tetrahydro-beta-carbolines with and without C6-methoxy group substitutions (THBC/6MTHBC) analogues of A1/B1 and A9/B9 have relatively acceptable affinity and within pocket-stability toward MOR compared to the reference compounds of morphine (agonist) and naloxone (antagonist). Moreover, the designed analogues interact with key residue within the binding pocket of Asp 147 that is reported to be involved in receptor activation. In conclusion, the designed THBC analogues represent a good starting point for designing opioid receptor ligands other than morphinan scaffold, that have good synthetic accessibility which promotes feasible structural manipulation to tailor pharmacological effects with minimal side effects.

Determinants of Neutral Antagonism and Inverse Agonism in the β2-Adrenergic Receptor

Free-energy profiles for the activation/deactivation of the β2-adrenergic receptor (ADRB2) with neutral antagonist and inverse agonist ligands have been determined with well-tempered multiple-walker (MW) metadynamics simulations. The inverse agonists carazolol and ICI118551 clearly favor single inactive conformational minima in both the binary and ternary ligand-receptor-G-protein complexes, in accord with the inverse-agonist activity of the ligands. The behavior of neutral antagonists is more complex, as they seem also to affect the recruitment of the G-protein. The results are analyzed in terms of the conformational states of the well-known microswitches that have been proposed as indicators of receptor activity.

Trajectory maps: molecular dynamics visualization and analysis

Molecular dynamics simulations generate trajectories that depict system's evolution in time and are analyzed visually and quantitatively. Commonly conducted analyses include RMSD, Rgyr, RMSF, and more. However, those methods are all limited by their strictly statistical nature. Here we present trajectory maps, a novel method to analyze and visualize protein simulation courses intuitively and conclusively. By plotting protein's backbone movements during the simulation as a heatmap, trajectory maps provide new tools to directly visualize protein behavior over time, compare multiple simulations, and complement established methods. A user-friendly Python application developed for this purpose is presented, alongside detailed documentation for easy usage and implementation. The method's validation is demonstrated on three case studies. Considering its benefits, trajectory maps are expected to adopt broad application in obtaining and communicating meaningful results of protein molecular dynamics simulations in many associated fields such as biochemistry, structural biology, pharmaceutical research etc.

Molecular Dynamics as a Tool for Virtual Ligand Screening

Rational drug design is essential for new drugs to emerge, especially when the structure of a target protein or nucleic acid is known. To that purpose, high-throughput virtual ligand screening campaigns aim at discovering computationally new binding molecules or fragments to modulate particular biomolecular interactions or biological activities, related to a disease process. The structure-based virtual ligand screening process primarily relies on docking methods which allow predicting the binding of a molecule to a biological target structure with a correct conformation and the best possible affinity. The docking method itself is not sufficient as it suffers from several and crucial limitations (lack of full protein flexibility information, no solvation and ion effects, poor scoring functions, and unreliable molecular affinity estimation).At the interface of computer techniques and drug discovery, molecular dynamics (MD) allows introducing protein flexibility before or after a docking protocol, refining the structure of protein-drug complexes in the presence of water, ions, and even in membrane-like environments, describing more precisely the temporal evolution of the biological complex and ranking these complexes with more accurate binding energy calculations. In this chapter, we describe the up-to-date MD, which plays the role of supporting tools in the virtual ligand screening (VS) process.Without a doubt, using docking in combination with MD is an attractive approach in structure-based drug discovery protocols nowadays. It has proved its efficiency through many examples in the literature and is a powerful method to significantly reduce the amount of required wet experimentations (Tarcsay et al, J Chem Inf Model 53:2990-2999, 2013; Barakat et al, PLoS One 7:e51329, 2012; De Vivo et al, J Med Chem 59:4035-4061, 2016; Durrant, McCammon, BMC Biol 9:71-79, 2011; Galeazzi, Curr Comput Aided Drug Des 5:225-240, 2009; Hospital et al, Adv Appl Bioinforma Chem 8:37-47, 2015; Jiang et al, Molecules 20:12769-12786, 2015; Kundu et al, J Mol Graph Model 61:160-174, 2015; Mirza et al, J Mol Graph Model 66:99-107, 2016; Moroy et al, Future Med Chem 7:2317-2331, 2015; Naresh et al, J Mol Graph Model 61:272-280, 2015; Nichols et al, J Chem Inf Model 51:1439-1446, 2011; Nichols et al, Methods Mol Biol 819:93-103, 2012; Okimoto et al, PLoS Comput Biol 5:e1000528, 2009; Rodriguez-Bussey et al, Biopolymers 105:35-42, 2016; Sliwoski et al, Pharmacol Rev 66:334-395, 2014).

The World of GPCR dimers - Mapping dopamine receptor D2 homodimers in different activation states and configuration arrangements

G protein-coupled receptors (GPCRs) are known to dimerize, but the molecular and structural basis of GPCR dimers is not well understood. In this study, we developed a computational framework to generate models of symmetric and asymmetric GPCR dimers using different monomer activation states and identified their most likely interfaces with molecular details. We chose the dopamine receptor D2 (D2R) homodimer as a case study because of its biological relevance and the availability of structural information. Our results showed that transmembrane domains 4 and 5 (TM4 and TM5) are mostly found at the dimer interface of the D2R dimer and that these interfaces have a subset of key residues that are mostly nonpolar from TM4 and TM5, which was in line with experimental studies. In addition, TM2 and TM3 appear to be relevant for D2R dimers. In some cases, the inactive configuration is unaffected by the partnered protomer, whereas in others, the active protomer adopts the properties of an inactive receptor. Additionally, the β-arrestin configuration displayed the properties of an active receptor in the absence of an agonist, suggesting that a switch to another meta-state during dimerization occurred. Our findings are consistent with the experimental data, and this method can be adapted to study heterodimers and potentially extended to include additional proteins such as G proteins or β-arrestins. In summary, this approach provides insight into the impact of the conformational status of partnered protomers on the overall quaternary GPCR macromolecular structure and dynamics.

Identification of Dietary Bioflavonoids as Potential Inhibitors against KRAS G12D Mutant—Novel Insights from Computer-Aided Drug Discovery

The KRAS G12D mutation is very frequent in many cancers, such as pancreatic, colon and lung, and has remained undruggable for the past three decades, due to its smooth surface and lack of suitable pockets. Recent small pieces of evidence suggest that targeting the switch I/II of KRAS G12D mutant could be an efficient strategy. Therefore, in the present study, we targeted the switch I (residues 25–40) and switch II (residues 57–76) regions of KRAS G12D with dietary bioflavonoids in comparison with the reference KRAS SI/II inhibitor BI-2852. Initially, we screened 925 bioflavonoids based on drug-likeness properties, and ADME properties and selected 514 bioflavonoids for further studies. Molecular docking resulted in four lead bioflavonoids, namely 5-Dehydroxyparatocarpin K (L1), Carpachromene (L2), Sanggenone H (L3), and Kuwanol C (L4) with binding affinities of 8.8 Kcal/mol, 8.64 Kcal/mol, 8.62 Kcal/mol, and 8.58 Kcal/mol, respectively, in comparison with BI-2852 (−8.59 Kcal/mol). Further steered-molecular dynamics, molecular-dynamics simulation, toxicity, and in silico cancer-cell-line cytotoxicity predictions significantly support these four lead bioflavonoids as potential inhibitors of KRAS G12D SI/SII inhibitors. We finally conclude that these four bioflavonoids have potential inhibitory activity against the KRAS G12D mutant, and are further to be studied in vitro and in vivo, to evaluate their therapeutic potential and the utility of these compounds against KRAS G12D mutated cancers.

Interactions between curcumin and human salt-induced kinase 3 elucidated from computational tools and experimental methods

Natural products are widely used for treating mitochondrial dysfunction-related diseases and cancers. Curcumin, a well-known natural product, can be potentially used to treat cancer. Human salt-induced kinase 3 (SIK3) is one of the target proteins for curcumin. However, the interactions between curcumin and human SIK3 have not yet been investigated in detail. In this study, we studied the binding models for the interactions between curcumin and human SIK3 using computational tools such as homology modeling, molecular docking, molecular dynamics simulations, and binding free energy calculations. The open activity loop conformation of SIK3 with the ketoenol form of curcumin was the optimal binding model. The I72, V80, A93, Y144, A145, and L195 residues played a key role for curcumin binding with human SIK3. The interactions between curcumin and human SIK3 were also investigated using the kinase assay. Moreover, curcumin exhibited an IC₅₀ (half-maximal inhibitory concentration) value of 131 nM, and it showed significant antiproliferative activities of 9.62 ± 0.33 µM and 72.37 ± 0.37 µM against the MCF-7 and MDA-MB-23 cell lines, respectively. This study provides detailed information on the binding of curcumin with human SIK3 and may facilitate the design of novel salt-inducible kinases inhibitors.

Evodiamine and Rutaecarpine as Potential Anticancer Compounds: A Combined Computational Study

Evodiamine (EVO) and rutaecarpine (RUT) are the main active compounds of the traditional Chinese medicinal herb Evodia rutaecarpa. Here, we fully optimized the molecular geometries of EVO and RUT at the B3LYP/6-311++G (d, p) level of density functional theory. The natural population analysis (NPA) charges, frontier molecular orbitals, molecular electrostatic potentials, and the chemical reactivity descriptors for EVO and RUT were also investigated. Furthermore, molecular docking, molecular dynamics simulations, and the analysis of the binding free energies of EVO and RUT were carried out against the anticancer target topoisomerase 1 (TOP1) to clarify their anticancer mechanisms. The docking results indicated that they could inhibit TOP1 by intercalating into the cleaved DNA-binding site to form a TOP1−DNA−ligand ternary complex, suggesting that they may be potential TOP1 inhibitors. Molecular dynamics (MD) simulations evaluated the binding stability of the TOP1−DNA−ligand ternary complex. The calculation of binding free energy showed that the binding ability of EVO with TOP1 was stronger than that of RUT. These results elucidated the structure−activity relationship and the antitumor mechanism of EVO and RUT at the molecular level. It is suggested that EVO and RUT may be potential compounds for the development of new anticancer drugs.

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard "lock and key" paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.

Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation

GPCRs (G-protein coupled receptors) are the largest family of drug targets and share a conserved structure. Binding sites are unknown for many important GPCR ligands due to the difficulties of GPCR recombinant expression, biochemistry, and crystallography. We describe our approach, ConDockSite, for predicting ligand binding sites in class A GPCRs using combined information from surface conservation and docking, starting from crystal structures or homology models. We demonstrate the effectiveness of ConDockSite on crystallized class A GPCRs such as the beta2 adrenergic and A2A adenosine receptors. We also demonstrate that ConDockSite successfully predicts ligand binding sites from high-quality homology models. Finally, we apply ConDockSite to predict the ligand binding sites on a structurally uncharacterized GPCR, GPER, the G-protein coupled estrogen receptor. Most of the sites predicted by ConDockSite match those found in other independent modeling studies. ConDockSite predicts that four ligands bind to a common location on GPER at a site deep in the receptor cleft. Incorporating sequence conservation information in ConDockSite overcomes errors introduced from physics-based scoring functions and homology modeling.

Molecular Dynamics Simulations in Designing DARPins as Phosphorylation-Specific Protein Binders of ERK2

Extracellular signal-regulated kinases 1 and 2 (ERK1/2) play key roles in promoting cell survival and proliferation through the phosphorylation of various substrates. Remarkable antitumour activity is found in many inhibitors that act upstream of the ERK pathway. However, drug-resistant tumour cells invariably emerge after their use due to the reactivation of ERK1/2 signalling. ERK1/2 inhibitors have shown clinical efficacy as a therapeutic strategy for the treatment of tumours with mitogen-activated protein kinase (MAPK) upstream target mutations. These inhibitors may be used as a possible strategy to overcome acquired resistance to MAPK inhibitors. Here, we report a class of repeat proteins-designed ankyrin repeat protein (DARPin) macromolecules targeting ERK2 as inhibitors. The structural basis of ERK2-DARPin interactions based on molecular dynamics (MD) simulations was studied. The information was then used to predict stabilizing mutations employing a web-based algorithm, MAESTRO. To evaluate whether these design strategies were successfully deployed, we performed all-atom, explicit-solvent molecular dynamics (MD) simulations. Two mutations, Ala → Asp and Ser → Leu, were found to perform better than the original sequence (DARPin E40) based on the associated energy and key residues involved in protein-protein interaction. MD simulations and analysis of the data obtained on these mutations supported our predictions.

Dasatinib-SIK2 Binding Elucidated by Homology Modeling, Molecular Docking, and Dynamics Simulations

Salt-inducible kinases (SIKs) are calcium/calmodulin-dependent protein kinase (CAMK)-like (CAMKL) family members implicated in insulin signal transduction, metabolic regulation, inflammatory response, and other processes. Here, we focused on SIK2, which is a target of the Food and Drug Administration (FDA)-approved pan inhibitor N-(2-chloro-6-methylphenyl)-2-(6-(4-(2-hydroxyethyl)piperazin-1-yl)-2-methylpyrimidin-4-ylamino)thiazole-5-carboxamide (dasatinib), and constructed four representative SIK2 structures by homology modeling. We investigated the interactions between dasatinib and SIK2 via molecular docking, molecular dynamics simulation, and binding free energy calculation and found that dasatinib showed strong binding affinity for SIK2. Binding free energy calculations suggested that the modification of various dasatinib regions may provide useful information for drug design and to guide the discovery of novel dasatinib-based SIK2 inhibitors.

Exploring the putative mechanism of allosteric modulations by mixed-action kappa/mu opioid receptor bitopic modulators

The modulation and selectivity mechanisms of seven mixed-action kappa opioid receptor (KOR)/mu opioid receptor (MOR) bitopic modulators were explored. Molecular modeling results indicated that the 'message' moiety of seven bitopic modulators shared the same binding mode with the orthosteric site of the KOR and MOR, whereas the 'address' moiety bound with different subdomains of the allosteric site of the KOR and MOR. The 'address' moiety of seven bitopic modulators bound to different subdomains of the allosteric site of the KOR and MOR may exhibit distinguishable allosteric modulations to the binding affinity and/or efficacy of the 'message' moiety. Moreover, the 3-hydroxy group on the phenolic moiety of the seven bitopic modulators induced selectivity to the KOR over the MOR.

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.

How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs

G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.