Computational Analysis of Structure-Based Interactions for Novel H₁-Antihistamines

Evaluation of Urtica dioica Phytochemicals against Therapeutic Targets of Allergic Rhinitis Using Computational Studies

Allergic rhinitis (AR) is a prevalent inflammatory condition affecting millions globally, with current treatments often associated with significant side effects. To seek safer and more effective alternatives, natural sources like Urtica dioica (UD) are being explored. However, UD's mechanism of action remains unknown. Therefore, to elucidate it, we conducted an in silico evaluation of UD phytochemicals' effects on known therapeutic targets of allergic rhinitis: histamine receptor 1 (HR1), neurokinin 1 receptor (NK1R), cysteinyl leukotriene receptor 1 (CLR1), chemoattractant receptor-homologous molecule expressed on type 2 helper T cells (CRTH2), and bradykinin receptor type 2 (BK2R). The docking analysis identified amentoflavone, alpha-tocotrienol, neoxanthin, and isorhamnetin 3-O-rutinoside as possessing a high affinity for all the receptors. Subsequently, molecular dynamics (MD) simulations were used to analyze the key interactions; the free energy of binding was calculated through Generalized Born and Surface Area Solvation (MMGBSA), and the conformational changes were evaluated. Alpha-tocotrienol exhibited a high affinity while also inducing positive conformational changes across all targets. Amentoflavone primarily affected CRTH2, neoxanthin targeted NK1R, CRTH2, and BK2R, and isorhamnetin-3-O-rutinoside acted on NK1R. These findings suggest UD's potential to treat AR symptoms by inhibiting these targets. Notably, alpha-tocotrienol emerges as a promising multi-target inhibitor. Further in vivo and in vitro studies are needed for validation.

In silico screening-based discovery of benzamide derivatives as inhibitors of Rho-associated kinase-1 (ROCK1)

As a pivotal node in modulating various cell behaviors, Rho-associated kinase-1 (ROCK1) has attracted significant attention as a promising therapeutic target in a variety of diseases. Benzamide has been widely reported as a ROCK1 inhibitors in recent years. To better understand its pharmacological properties and to explore its potential inhibitors, a series of ROCK1 inhibitors derived from N-methyl-4-(4-pyrazolidinyl) benzamides (MPBs) were investigated by using three-dimensional quantitative structure-activity relationship (3D-QSAR) models, pharmacophore models, molecular docking, and molecular dynamics (MD) simulation. The comparative Molecular Field Analysis (CoMFA) model (q2 = 0.616, R2 = 0.972, ONC = 4, and r2pred = 0.983) and the best Comparative Molecular Similarity Indices Analysis (CoMSIA) model (q2= 0.740, R2 = 0.982, ONC = 6, and r2pred = 0.824) exhibited reliable predictability with satisfactory validation parameters. In the subsequent virtual screening, VS03 and VS05 were identified to have superior predicted activities and higher docking scores, meanwhile they demonstrated to be reasonably stable in the binding pocket through MD simulations. These results provide a significant theoretical direction for the rational design and development of novel ROCK1 inhibitors.Communicated by Ramaswamy H. Sarma.

Benzoquinoline Chemical Space: A Helpful Approach in Antibacterial and Anticancer Drug Design

Benzoquinolines are used in many drug design projects as starting molecules subject to derivatization. This computational study aims to characterize e benzoquinone drug space to ease future drug design processes based on these molecules. The drug space is composed of all benzoquinones, which are active on topoisomerase II and ATP synthase. Topological, chemical, and bioactivity spaces are explored using computational methodologies based on virtual screening and scaffold hopping and molecular docking, respectively. Topological space is a geometrical space in which the elements composing it can be defined as a set of neighbors (which satisfy a particular axiom). In such space, a chemical space can be defined as the property space spanned by all possible molecules and chemical compounds adhering to a given set of construction principles and boundary conditions. In this chemical space, the potentially pharmacologically active molecules form the bioactivity space. Results show a poly-morphological chemical space that suggests distinct characteristics. The chemical space is correlated with properties such as steric energy, the number of hydrogen bonds, the presence of halogen atoms, and membrane permeability-related properties. Lastly, novel chemical compounds (such as oxadiazole methybenzamide and floro methylcyclohexane diene) with drug-like potential, active on TOPO II and ATP synthase have been identified.

Molecular Modeling of Histamine Receptors-Recent Advances in Drug Discovery

The recent developments of fast reliable docking, virtual screening and other algorithms gave rise to discovery of many novel ligands of histamine receptors that could be used for treatment of allergic inflammatory disorders, central nervous system pathologies, pain, cancer and obesity. Furthermore, the pharmacological profiles of ligands clearly indicate that these receptors may be considered as targets not only for selective but also for multi-target drugs that could be used for treatment of complex disorders such as Alzheimer's disease. Therefore, analysis of protein-ligand recognition in the binding site of histamine receptors and also other molecular targets has become a valuable tool in drug design toolkit. This review covers the period 2014-2020 in the field of theoretical investigations of histamine receptors mostly based on molecular modeling as well as the experimental characterization of novel ligands of these receptors.

In silico profiling the interaction mechanism of 2,5-diketopiperazine derivatives as oxytocin antagonists

Oxytocin plays a vital role in the occurrence of preterm birth by interacting with oxytocin receptor (OTR), and thus OTR antagonists provide effective approaches for the treatment of early birth. Presently, for purpose of exploring the structural traits affecting the antagonism potency, the up-to-date largest set of 121 2,5-diketopiperazine derivatives as OTR antagonists was subjected to ligand-based three-dimensional quantitative structure-activity (3D-QSAR) analysis applying comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. The resultant optimal CoMSIA model displays proper validity and predictability with cross-validated correlation coefficient Q² = 0.614, non-cross-validated correlation coefficient R²_ncv = 0.969 and predicted correlation coefficient R²_pre = 0.912 for the test set of compounds, respectively. In addition, docking study was carried out for further elucidating the binding modes of OTR antagonists. The final docking cavity was located among the TM2-TM7 helices of the target protein and proved to be the same as described by other scholars' researches of other type of OTR antagonists. The major amino acids forming the cavity are Q92, Q96, K116, Q119, V120, M123, G196, I201, Q295, W288, F311 and M315. Representative compound 118 forms two H-bonds with Q119 and two H-bonds with Q295, with also a π - π stacking effect with F311, respectively. Meanwhile, as a supplementary tool to study the antagonists' conformation in the binding cavity, molecular dynamics (MD) simulation was also performed to further elucidate the changes in the ligand-receptor complex. We hope that the obtained models and information may help to provide an insight into the interaction mechanism of OTR antagonists and facilitate the design and optimization of novel antagonists for preventing premature birth.

Functional G-Protein-Coupled Receptor (GPCR) Synthesis: The Pharmacological Analysis of Human Histamine H1 Receptor (HRH1) Synthesized by a Wheat Germ Cell-Free Protein Synthesis System Combined with Asolectin Glycerosomes

G-protein-coupled receptors (GPCRs) are membrane proteins distributed on the cell surface, and they may be potential drug targets. However, synthesizing GPCRs in vitro can be challenging. Recently, some cell-free protein synthesis systems have been shown to produce a large amount of membrane protein combined with chemical chaperones that include liposomes and glycerol. Liposomes containing high concentrations of glycerol are known as glycerosomes, which are used in new drug delivery systems. Glycerosomes have greater morphological stability than liposomes. Proteoglycerosomes are defined as glycerosomes that contain membrane proteins. Human histamine H₁ receptor (HRH1) is one of the most studied GPCRs. In this study, we synthesized wild-type HRH1 (WT-HRH1) proteoglycerosomes and D107A-HRH1, (in which Asp107 was replaced by Ala) in a wheat germ cell-free protein synthesis system combined with asolectin glycerosomes. The mutant HRH1 has been reported to have low affinity for the H₁ antagonist. In this study, the amount of synthesized WT-HRH1 in one synthesis reaction was 434 ± 66.6 μg (7.75 ± 1.19 × 10³pmol). The specific binding of [³H]pyrilamine to the WT-HRH1 proteoglycerosomes became saturated as the concentration of the radioligand increased. The dissociation constant (Kd) and maximum density (Bmax) of the synthesized WT-HRH1 were 9.76 ± 1.25 nM and 21.4 ± 0.936 pmol/mg protein, respectively. However, specific binding to D107A-HRH1 was reduced compared with WT-HRH1 and the binding did not become saturated. The findings of this study highlight that HRH1 synthesized using a wheat germ cell-free protein synthesis system combined with glycerosomes has the ability to bind to H₁ antagonists.

Mechanism Exploration of Arylpiperazine Derivatives Targeting the 5-HT2A Receptor by In Silico Methods

As a G-protein coupled receptor, the 5-hydroxytryptamine 2A (5-HT_2A) receptor is known for its critical role in the cognitive, behavioural and physiological functions, and thus is a primary molecular target to treat psychiatric diseases, including especially depression. With purpose to explore the structural traits affecting the inhibitory activity, currently a dataset of 109 arylpiperazine derivatives as promising 5-HT_2A antagonists was built, based on which the ligand-based three-dimensional quantitative structure-activity relationship (3D-QSAR) study by using both comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches was carried out. The resultant optimal CoMSIA model displays proper validity and predictability with cross-validated correlation coefficient Q² = 0.587, non-cross-validated correlation coefficient R²_ncv = 0.900 and predicted correlation coefficient for the test set of compounds R²_pre = 0.897, respectively. Besides, molecular docking was also conducted to investigate the binding mode between these ligands and the active site of the 5-HT_2A receptor. Meanwhile, as a docking supplementary tool to study the antagonists' conformation in the binding cavity, molecular dynamics (MD) simulation was also performed, providing further elucidation about the changes in the ligand-receptor complex. Lastly, some new molecules were also newly-designed based on the above results that are potential arylpiperazine antagonists of 5-HT_2A receptor. We hope that the present models and derived information may be of help for facilitating the optimization and design of novel potent antagonists as antidepressant drugs as well as exploring the interaction mechanism of 5-HT_2A antagonists.

Data Analysis in Chemistry and Bio-Medical Sciences

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