Structure based prediction of a novel GPR120 antagonist based on pharmacophore screening and molecular dynamics simulations

Free fatty acid receptors beyond fatty acids: A computational journey to explore peptides as possible binders of GPR120

Free fatty acids receptors, with members among G protein-coupled receptors (GPCRs), are crucial for biological signaling, including the perception of the so called "fatty taste". In recent years, GPR120, a protein belonging to the GPCR family, drew attention as an interesting pharmacological target to cope with obesity, satiety and diabetes. Apart from long chain fatty acids, which are GPR120 natural agonists, other synthetic molecules were identified as agonists expanding the chemical space of GPR120's ligands. In this scenario, we unveiled peptides as possible GPR120 binders toward a better understanding of this multifaceted and relevant target. This study analyzed a virtual library collecting 531 441 low-polar hexapeptides, providing mechanistic insights on the GPR120 activation and further extending the possible chemical space of GPR120 agonists. The computational pipeline started with a narrow filtering of hexapeptides based on their chemical similarity with known GPR120 agonists. The best hits were tested through docking studies, molecular dynamics and umbrella sampling simulations, which pointed to G[I,L]FGGG as a promising GPR120 agonist sequence. The presence of both peptides in food-related proteins was thoroughly assessed, revealing they may occur in mushrooms, food-grade bacteria and rice. Simulations on the counterparts with D-amino acids were also performed. Umbrella sampling simulations described that GdIFGGG may have a better interaction compared to its all-L counterpart (-13 kCal/mol ΔG and -6 kCal/mol ΔG, respectively). Overall, we obtained a predictive model to better understand the underpinning mechanism of GPR120-hexapeptides interaction, hierarchizing novel potential agonist peptides for further analysis and describing promising food sources worth of further dedicated investigations.

Sunset Yellow protects against oxidative damage and exhibits chemoprevention in chemically induced skin cancer model

Skin cancer and other skin-related inflammatory pathologies are rising due to heightened exposure to environmental pollutants and carcinogens. In this context, natural products and repurposed compounds hold promise as novel therapeutic and preventive agents. Strengthening the skin's antioxidant defense mechanisms is pivotal in neutralizing reactive oxygen species (ROS) and mitigating oxidative stress. Sunset Yellow (SY) exhibits immunomodulatory characteristics, evidenced by its capacity to partially inhibit the secretion of proinflammatory cytokines, regulate immune cell populations, and modulate the activation of lymphocytes. This study aimed to investigate the antioxidant and anti-genotoxic properties of SY using in-silico, in vitro, and physiochemical test systems, and to further explore its potential role in 7,12-dimethylbenz(a) anthracene (DMBA)/ 12-o-tetradecanoylphorbol-13-acetate (TPA)-induced two-stage skin carcinogenesis. In vitro experiments showed that pre-treatment of SY significantly enhanced the cell viability of HaCaT cells when exposed to tertiary-Butyl Hydrogen Peroxide (tBHP). This increase was accompanied by reduced ROS levels, restoration of mitochondrial membrane potential, and notable reduction in DNA damage in (SY + tBHP) treated cells. Mechanistic investigations using DPPH chemical antioxidant activity test and potentiometric titrations confirmed SY's antioxidant properties, with a standard reduction potential (E o ) of 0.211 V. Remarkably, evaluating the effect of topical application of SY in DMBA/TPA-induced two-step skin carcinogenesis model revealed dose-dependent decreases in tumor latency, incidence, yield, and burden over 21-weeks. Furthermore, computational analysis and experimental validations identified GSK3β, KEAP1 and EGFR as putative molecular targets of SY. Collectively, our findings reveal that SY enhances cellular antioxidant defenses, exhibits anti-genotoxic effects, and functions as a promising chemopreventive agent.

A high-throughput structural dynamics approach for identification of potential agonists of FFAR4 for type 2 diabetes mellitus therapy

Diabetes mellitus is a metabolic disorder that persists as a global threat to the world. A G-protein coupled receptor (GPCR), free fatty acid receptor 4 (FFAR4), has emerged as a potential target for type 2 diabetes mellitus (T2DM) and obesity-related disorders. The current study has investigated the FFAR4, deploying 3-dimensional structure modeling, molecular docking, machine learning, and high-throughput virtual screening methods to unravel the receptor's crucial and non-crucial binding site residues. We screened four lakh compounds and shortlisted them based on binding energy, stereochemical considerations, non-bonded interactions, and pharmacokinetic profiling. Out of the screened compounds, four compounds were selected for ligand-bound simulations. The molecular dynamic simulations were carried out for 1µs for native FFAR4 and 500 ns each for complexes of FFAR4 with compound 1, compound 2, compound 3, and compound 4. Our findings showed that in addition to reported binding site residues ARG99, ARG183, and VAL98 in known agonists like TUG-891, the amino acids ARG22, ARG24, THR23, TRP305, and GLU43 were also critical binding site residues. These amino acids impart stability to the FFAR4 complexes and contribute to the stronger binding affinity of the compounds. The study also indicated that aromatic residues like PHE211 are crucial for recognizing the active site's pi-pi and C-C double bonds. Since FFAR4 is a membrane protein, the simulation studies give an insight into the mechanisms of the crucial protein-lipid and lipid-water interactions. The analysis of the molecular dynamics trajectories showed all four compounds as potential hit molecules that can be developed further into potential agonists for T2DM therapy. Amongst the four compounds, compound 4 showed relatively better binding affinity, stronger non-bonded interactions, and a stable complex.Communicated by Ramaswamy H. Sarma.

In Silico Identification of New Anti-SARS-CoV-2 Main Protease (Mpro) Molecules with Pharmacokinetic Properties from Natural Sources Using Molecular Dynamics (MD) Simulations and Hierarchical Virtual Screening

Infectious agents such as SARS-CoV, MERS-CoV, and SARS-CoV-2 have emerged in recent years causing epidemics with high mortality rates. The quick development of novel therapeutic compounds is required in the fight against such pathogenic agents. Unfortunately, the traditional drug development methods are time-consuming and expensive. In this study, computational algorithms were utilized for virtual screening of a library of natural compounds in the ZINC database for their affinity towards SARS-CoV-2 Mpro. Compounds such as cinanserin, nelfinavir, baicalin, baicalein, candesartan cilexetil, chloroquine, dipyridamole, and hydroxychloroquine have the ability to prevent SARS-CoV-2 Mpro from facilitating COVID 19 infection; thus, they treat COVID 19. However, these drugs majorly act to reduce the symptoms of the disease. No anti-viral drug against COVID 19 virus infection has been discovered and approved. Therefore, this study sought to explore natural inhibitors of SARS-CoV-2 Mpro to develop a pharmacophore model for virtual screening of natural compounds in the ZINC database as potential candidates for SARS-CoV-2 Mpro inhibitors and as therapeutic molecules against COVID 19. This study undertook in silico methods to identify the best anti-viral candidates targeting SAR-CoV-2 Mpro from natural sources in the ZINC database. Initially, reported anti-SARS-CoV-2 Mpro molecules were integrated into designing a pharmacophore model utilizing PharmaGist. Later, the pharmacophore model was loaded into ZINCPHARMER and screened against the ZINC database to identify new probable drug candidates. The root means square deviation (RMSD) values of the potential drug candidates informed the selection of some of them, which were docked with SARS-CoV-2 Mpro to comprehend their interactions. From the molecular docking results, the top four candidates (ZINC000254823011, ZINC000072307130, ZINC000013627512, and ZINC000009418994) against SARS-CoV-2 Mpro, with binding energies ranging from –8.2 kcal/mol to –8.6 kcal/mol, were examined for their oral bioavailability and other pharmacokinetic properties. Consequently, ZINC000072307130 emerged as the only orally bioavailable drug candidate with desirable pharmacokinetic properties. This candidate drug was used to perform MD simulations, and the outcomes revealed that ZINC000072307130 formed a stable complex with the viral main protease. Consequently, ZINC000072307130 emerges as a potential anti-SARS-CoV-2 Mpro inhibitor for the production of new COVID 19 drugs.

Molecular docking and identification of G-protein-coupled receptor 120 (GPR120) agonists as SARS COVID-19 MPro inhibitors

COVID-19 has become a pandemic, and any new drug for treating the disease could save millions of lives. Several drugs already in use for other diseases and medical conditions are repurposed for treating COVID-19 in an attempt to find treatment for the disease without spending research time on ADME TOX and other studies on side effects. In this exercise, the drugs repurposed are from antiviral, antibiotics, antiviral for HIV and HCV, anti-cancer, natural medicines, etc. Possible repurposing anti-diabetic GPR-120 agonists used as for SAR-CoV-2 is attempted in the study by carrying out docking of 68 GPR-120 agonists. Ten of these compounds were found to have docking scores −8.3 to −8.0, and the best docking score was observed for an arylsulfonamide and a biarylpropanoic acid belonging to GPR120 agonists previously evaluated for the treatment of type II diabetes. These GPR120 agonists could serve as start point for novel inhibitors for the discovery of drugs to treat COVID-19.

Delineating the conformational landscape and intrinsic properties of the angiotensin II type 2 receptor using a computational study

As a key regulator for the renin-angiotensin system, a class A G protein-coupled receptor (GPCR), AngII type 2 receptor (AT₂R), plays a pivotal role in the homeostasis of the cardiovascular system. Compared with other GPCRs, AT₂R has a unique antagonist-bound conformation and its mechanism is still an enigma. Here, we applied combined dynamic and evolutional approaches to investigate the conformational space and intrinsic properties of AT₂R. With molecular dynamic simulations, Markov State Models, and statistics coupled analysis, we captured the conformational landscape of AT₂R and identified its uniquity from both dynamical and evolutional viewpoints. A cryptic pocket was also discovered in the intermediate state during conformation transitions. These findings offer a deeper understanding of the AT₂R mechanism at an atomic level and provide hints for the design of novel AT₂R modulators.

Autopromotion of K-Ras4B Feedback Activation Through an SOS-Mediated Long-Range Allosteric Effect

The Ras-specific guanine nucleotide exchange factors Son of Sevenless (SOS) regulates Ras activation by converting inactive GDP-bound to active GTP-bound states. The catalytic activity of Ras is further allosterically regulated by GTP−Ras bound to a distal site through a positive feedback loop. To address the mechanism underlying the long-range allosteric activation of the catalytic K-Ras4B by an additional allosteric GTP–Ras through SOS, we employed molecular dynamics simulation of the K-Ras4B^G13D•SOS^cat complex with and without an allosteric GTP-bound K-Ras4B^G13D. We found that the binding of an allosteric GTP−K-Ras4B^G13D enhanced the affinity between the catalytic K-Ras4B^G13D and SOS^cat, forming a more stable conformational state. The peeling away of the switch I from the nucleotide binding site facilitated the dissociation of GDP, thereby contributing to the increased nucleotide exchange rate. The community networks further showed stronger edge connection upon allosteric GTP−K-Ras4B^G13D binding, which represented an increased interaction between catalytic K-Ras4B^G13D and SOS^cat. Moreover, GTP−K-Ras4B^G13D binding transmitted allosteric signaling pathways though the Cdc25 domain of SOS that enhanced the allosteric regulatory from the K-Ras4B^G13D allosteric site to the catalytic site. This study may provide an in-depth mechanism for abnormal activation and allosteric regulation of K-Ras4B^G13D.

Delineating the activation mechanism and conformational landscape of a class B G protein-coupled receptor glucagon receptor

Class B G protein-coupled receptors (GPCRs) are important targets in the treatment of metabolic syndrome and diabetes. Although multiple structures of class B GPCRs-G protein complexes have been elucidated, the detailed activation mechanism of the receptors remains unclear. Here, we combine Gaussian accelerated molecular dynamics simulations and Markov state models (MSM) to investigate the activation mechanism of a canonical class B GPCR, human glucagon receptor-GCGR, including the negative allosteric modulator-bound inactive state, the agonist glucagon-bound active state, and both glucagon- and Gs-bound fully active state. The free-energy landscapes of GCGR show the conformational ensemble consisting of three activation-associated states: inactive, active, and fully active. The structural analysis indicates the high dynamics of GCGR upon glucagon binding with both active and inactive conformations in the ensemble. Significantly, the H8 and TM6 exhibits distinct features from the inactive to the active states. The additional simulations demonstrate the role of H8 in the recruitment of Gs. Gs binding presents a crucial function of stabilizing the glucagon binding site and MSM highlights the absolute requirement of Gs to help the GCGR reach the fully active state. Together, our results reveal the detailed activation mechanism of GCGR from the view of conformational dynamics.