Combined CoMFA and CoMSIA 3D-QSAR study of benzimidazole and benzothiophene derivatives with selective affinity for the CB2 cannabinoid receptor

Motifs in Natural Products as Useful Scaffolds to Obtain Novel Benzo[d]imidazole-Based Cannabinoid Type 2 (CB2) Receptor Agonists

The endocannabinoid system (ECS) constitutes a broad-spectrum modulator of homeostasis in mammals, providing therapeutic opportunities for several pathologies. Its two main receptors, cannabinoid type 1 (CB1) and type 2 (CB2) receptors, mediate anti-inflammatory responses; however, their differing patterns of expression make the development of CB2-selective ligands therapeutically more attractive. The benzo[d]imidazole ring is considered to be a privileged scaffold in drug discovery and has demonstrated its versatility in the development of molecules with varied pharmacologic properties. On the other hand, the main psychoactive component of Cannabis sativa, delta-9-tetrahydrocannabinol (THC), can be structurally described as an aliphatic terpenoid motif fused to an aromatic polyphenolic (resorcinol) structure. Inspired by the structure of this phytocannabinoid, we combined different natural product motifs with a benzo[d]imidazole scaffold to obtain a new library of compounds targeting the CB2 receptor. Here, we synthesized 26 new compounds, out of which 15 presented CB2 binding and 3 showed potent agonist activity. SAR analysis indicated that the presence of bulky aliphatic or aromatic natural product motifs at position 2 of the benzo[d]imidazoles ring linked by an electronegative atom is essential for receptor recognition, while substituents with moderate bulkiness at position 1 of the heterocyclic core also participate in receptor recognition. Compounds 5, 6, and 16 were further characterized through in vitro cAMP functional assay, showing potent EC50 values between 20 and 3 nM, and compound 6 presented a significant difference between the EC50 of pharmacologic activity (3.36 nM) and IC50 of toxicity (30-38 µM).

Synthesis of N-acylbenzimidazoles through [4 + 1] annulation of N-arylpivalimidamides with dioxazolones

Presented herein is a novel and efficient synthesis of N-acylbenzimidazoles through an unprecedented [4 + 1] annulation of N-arylpivalimidamides with dioxazolones.

Investigating the binding mechanism of piperidinyl ureas inhibitors based on the UBC12-DCN1 interaction by 3D-QSAR, molecular docking and molecular dynamics simulations

Neddylation regulates a variety of biological processes by modulating Cullin-RING E3 ubiquitin ligases (CRLs) which is considered to be an important target for human diseases. The activation of CRLs required Cullins Neddylation, which regulated by the interaction of UBC12-DCN1 complex. Here, to investigate the structure-activity relationship and binding mechanism of 41 piperidinyl ureas inhibitors based on the UBC12-DCN1 protein-protein interaction, we carried out molecular modeling studies using three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations.Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to generate 3D-QSAR models. The results show that the best CoMFA model has q²=0.736, r²_ncv=0.978, r²_pred=0.78 (CoMFA), and the best CoMSIA model has q²=0.761, r²_ncv=0.987, r²_pred=0.86. The electrostatic, hydrophobic and H-bond donor fields play important roles in the models. Molecular docking studies predict the binding mode and the interactions between the ligand and the receptor protein. Molecular dynamics simulations results reveal that the complex of the ligand and the receptor protein are stable at 300 K. The results of MM-GBSA indicated the residues of Ile1083, Ile1086, Ala1098, Val1102, Ile1105, Gln1114, Phe1164 and Leu1184 might be the key residues during the process of inhibitors bound to DCN1. This study could provide an important theoretical basis for further developing novel inhibitors design based on UBC12-DCN1 protein-protein interaction. All the results can provide us more useful information for our further drug design. Communicated by Ramaswamy H. Sarma.

Virtual Screening of C. Sativa Constituents for the Identification of Selective Ligands for Cannabinoid Receptor 2

The selective targeting of the cannabinoid receptor 2 (CB2) is crucial for the development of peripheral system-acting cannabinoid analgesics. This work aimed at computer-assisted identification of prospective CB2-selective compounds among the constituents of Cannabis Sativa. The molecular structures and corresponding binding affinities to CB1 and CB2 receptors were collected from ChEMBL. The molecular structures of Cannabis Sativa constituents were collected from a phytochemical database. The collected records were curated and applied for the development of quantitative structure-activity relationship (QSAR) models with a machine learning approach. The validated models predicted the affinities of Cannabis Sativa constituents. Four structures of CB2 were acquired from the Protein Data Bank (PDB) and the discriminatory ability of CB2-selective ligands and two sets of decoys were tested. We succeeded in developing the QSAR model by achieving Q² 5-CV > 0.62. The QSAR models helped to identify three prospective CB2-selective molecules that are dissimilar to already tested compounds. In a complementary structure-based virtual screening study that used available PDB structures of CB2, the agonist-bound, Cryogenic Electron Microscopy structure of CB2 showed the best statistical performance in discriminating between CB2-active and non-active ligands. The same structure also performed best in discriminating between CB2-selective ligands from non-selective ligands.

Quantum mechanics and 3D-QSAR studies on thienopyridine analogues: inhibitors of IKKβ

Inhibitor of kappa B kinase subunit β (IKKβ) is a main regulator of nuclear factor kappa B (NF-κB) and has received considerable attention as an attractive therapeutic target for the treatment of lung cancer or other inflammatory disease. A group of diversified thienopyridine derivatives exhibited a wide range of biological activity was used to investigate its structural requirements by using DFT and 3D-Quantitative structure activity relationship. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were established using the experimental activity of thienopyridine derivatives. The cross-validation coefficient (q2) values for CoMFA and CoMSIA are 0.671 and 0.647 respectively, were achieved, demonstrating high predictive capability of the model. The contour analysis indicate that presence of hydrophobic and electrostatic field is highly desirable for biological activity. The results indicate that substitution of hydrophobic group with electron withdrawing effect at R4 and R6 position have more possibility to increase the biological activity of thienopyridine derivatives. Subsequently molecular docking and DFT calculation were performed to assess the potency of the compounds.

Molecular modeling studies of benzothiophene-containing derivatives as promising selective estrogen receptor downregulators: a combination of 3D-QSAR, molecular docking and molecular dynamics simulations

Selective estrogen receptor downregulators (SERDs) for the treatment of positive breast cancer can act both as estrogen alpha receptor (ERα) antagonists and degraders. In this study, the optimal antagonist models (CoMFA-A, q² = 0.660, r² = 0.996; CoMSIA-A, q² = 0.728, r² = 0.992) and degrader models (CoMFA-D, q² = 0.850, r² = 0.996; CoMSIA-D, q² = 0.719, r² = 0.995) of a series of potent benzothiophene-containing SERDs were constructed to explore the three-dimensional quantitative structure-activity relationship. Internal and external validation indicated that all models exhibited good applicability, high predictive ability and robustness. Contour maps revealed the relationships between the essential structural features and antagonistic and degradation activities. Additionally, molecular docking, molecular dynamics and free energy calculation studies were further performed to investigate the detailed binding mode. Results indicated that several key residues, ARG394, GLU353, PHE404 and ILE424, were crucial for the stability of the ligand binding domain. The hydrophobic, electrostatic and Van der Waals interactions played significant effect on the binding affinity. Finally, ten novel compounds were designed based on above findings, where the predicted activity of compound D8 was equivalent to that of the compound LSZ102. 3D-QSAR, ADMET and bioavailability predictions indicated that all designed compounds with good predicted activity, good physicochemical and bioavailability could be potential candidates for SERDs. These results and combinations of computational methods provided guidance for the rational drug design of novel potential SERDs.Communicated by Ramaswamy H. Sarma.

Three-Dimensional Quantitative Structure-Activity Relationships (3D-QSAR) on a Series of Piperazine-Carboxamides Fatty Acid Amide Hydrolase (FAAH) Inhibitors as a Useful Tool for the Design of New Cannabinoid Ligands

Fatty Acid Amide Hydrolase (FAAH) is one of the main enzymes responsible for endocannabinoid metabolism. Inhibition of FAAH increases endogenous levels of fatty acid ethanolamides such as anandamide (AEA) and thus consitutes an indirect strategy that can be used to modulate endocannabinoid tone. In the present work, we present a three-dimensional quantitative structure-activity relationships/comparative molecular similarity indices analysis (3D-QSAR/CoMSIA) study on a series of 90 reported irreversible inhibitors of FAAH sharing a piperazine-carboxamide scaffold. The model obtained was extensively validated (q² = 0.734; r² = 0.966; r²_m = 0.723). Finally, based on the information derived from the contour maps we designed a series of 10 new compounds with high predicted FAAH inhibition (predicted pIC₅₀ of the best-proposed compounds = 12.196; 12.416).

Electroacupuncture-induced cannabinoid receptor expression in repair of abducens nerve

Objective: Through the development of beagle abducens nerve injury model, taking electroacupuncture as the core and microglia as the starting point, the author investigated whether electroacupuncture can promote the repair of injured abducens nerve by cannabinoid receptor-mediated regulation of microglia activation. Methods: Healthy beagle dogs were randomly divided into five groups: sham operation group (A), injury group (B), electroacupuncture pretreatment group (C), antagonist group (D) and solvent group (E). After stimulation with electroacupuncture, the expression of cannabinoid 1 receptor (CB1R) and cannabinoid 2 receptor (CB2R) in A, B and C microglia cells was detected by Western Bolt analysis, and further the expression of CB2R in five groups was further analyzed by immunofluorescence, thereby statistical differences were analyzed. Results: Among group A, group B and group C, Western Blot analysis showed that there were no significant changes in the expression of CB1R protein after electroacupuncture [F (2, 12)=1.75, p = 0.215]. After electroacupuncture preconditioning for 15 min for 2 weeks, group C was compared with group A and group B, which showed CB2 was affected. The expression of CB2R protein was significantly increased among groups A, B and C [F (2, 12)=5189.57, p < 0.001], but there was no significant difference in the expression of CB2R protein between group A and group B (p > 0.05). The results of immunofluorescence showed that Arginse/CD11b was significantly increased in group C comparing to group A (*p < 0.001), while there was a significant increase in group E comparing to group A about Arginse/CD11b [F (4, 20)=4345.44, p < 0.001]. Conclusions: The CB2R in the cannabinoid receptor is mainly involved in the electro-acupuncture-induced neuroprotection. Electroacupuncture can promote the repair of injured abducens nerve by CB2R-mediated activation of microglia.

Molecular Modeling and Design Studies of Purine Derivatives as Novel CDK2 Inhibitors

Cyclin-dependent kinase 2 (CDK2) is a potential target for treating cancer. Purine heterocycles have attracted particular attention as the scaffolds for the development of CDK2 inhibitors. To explore the interaction mechanism and the structure–activity relationship (SAR) and to design novel candidate compounds as potential CDK2 inhibitors, a systematic molecular modeling study was conducted on 35 purine derivatives as CDK2 inhibitors by combining three-dimensional quantitative SAR (3D-QSAR), virtual screening, molecular docking, and molecular dynamics (MD) simulations. The predictive CoMFA model (q² = 0.743, rpred2 = 0.991), the CoMSIA model (q² = 0.808, rpred2 = 0.990), and the Topomer CoMFA model (q² = 0.779, rpred2 = 0.962) were obtained. Contour maps revealed that the electrostatic, hydrophobic, hydrogen bond donor and steric fields played key roles in the QSAR models. Thirty-one novel candidate compounds with suitable predicted activity (predicted pIC₅₀ > 8) were designed by using the results of virtual screening. Molecular docking indicated that residues Asp86, Glu81, Leu83, Lys89, Lys33, and Gln131 formed hydrogen bonds with the ligand, which affected activity of the ligand. Based on the QSAR model prediction and molecular docking, two candidate compounds, I13 and I60 (predicted pIC₅₀ > 8, docking score > 10), with the most potential research value were further screened out. MD simulations of the corresponding complexes of these two candidate compounds further verified their stability. This study provided valuable information for the development of new potential CDK2 inhibitors.

Design, synthesis and biological evaluation of novel zanamivir derivatives as potent neuraminidase inhibitors

Neuraminidase (NA) is an important antiviral drug target. Zanamivir is one of the most potent NA inhibitors. In this paper, a series of zanamivir derivatives as potential NA inhibitors were studied by combination of molecular modeling techniques including 3D-QSAR, molecular docking, and molecular dynamics (MD) simulation. The results show that the best CoMFA (comparative molecular field analysis) model has q² = 0.728 and r² = 0.988, and the best CoMSIA (comparative molecular similarity indices analysis) model has q² = 0.750 and r² = 0.981, respectively. The built 3D-QSAR models show significant statistical quality and excellent predictive ability. Seven new NA inhibitors were designed and predicted. 20 ns of MD simulations were carried out and their binding free energies were calculated. Two designed compounds were selected to be synthesized and biologically evaluated by NA inhibition and virus inhibition assays. One compound (IC₅₀ = 0.670 µM, SI > 149) exhibits excellent antiviral activity against A/WSN/33 H1N1, which is superior to the reference drug zanamivir (IC₅₀ = 0.873 µM, SI > 115). The theoretical and experimental results may provide reference for development of new anti-influenza drugs.

Discovery of High-Affinity Cannabinoid Receptors Ligands through a 3D-QSAR Ushered by Scaffold-Hopping Analysis

Two 3D quantitative structure–activity relationships (3D-QSAR) models for predicting Cannabinoid receptor 1 and 2 (CB₁ and CB₂) ligands have been produced by way of creating a practical tool for the drug-design and optimization of CB₁ and CB₂ ligands. A set of 312 molecules have been used to build the model for the CB₁ receptor, and a set of 187 molecules for the CB₂ receptor. All of the molecules were recovered from the literature among those possessing measured K_i values, and Forge was used as software. The present model shows high and robust predictive potential, confirmed by the quality of the statistical analysis, and an adequate descriptive capability. A visual understanding of the hydrophobic, electrostatic, and shaping features highlighting the principal interactions for the CB₁ and CB₂ ligands was achieved with the construction of 3D maps. The predictive capabilities of the model were then used for a scaffold-hopping study of two selected compounds, with the generation of a library of new compounds with high affinity for the two receptors. Herein, we report two new 3D-QSAR models that comprehend a large number of chemically different CB₁ and CB₂ ligands and well account for the individual ligand affinities. These features will facilitate the recognition of new potent and selective molecules for CB₁ and CB₂ receptors.

Docking-based 3D-QSAR and pharmacophore studies on diarylpyrimidines as non-nucleoside inhibitors of HIV-1 reverse transcriptase

Diarylpyrimidines (DAPYs), a type of effective HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs), have been considered as one of the most successful agents for treating AIDS. A number of structurally diverse DAPYs have been designed and synthesized in the past decade, and most of them exhibited potent anti-HIV-1 activities; however, the structure-activity relationships of recently reported DAPYs and their pharmacophore features that interacted with HIV-1 reverse transcriptase (RT) remain to be studied. In the present study, molecular docking studies were first performed on three novel classes of DAPYs to study their binding pattern in the HIV-1 RT. Based on the docking conformations of these DAPYs, 3D-QSAR models were constructed using CoMSIA and Topomer CoMFA methods, and pharmacophore models were also built using distance comparison technique. All selected DAPYs presented preferred U- or L-shaped conformations while being docked into the non-nucleoside inhibitor-binding pocket of the HIV-1 RT. The best CoMSIA model exhibited powerful predictivity, with satisfactory statistical parameters such as a q² of 0.572, an r² of 0.952, and an [Formula: see text] of 0.728. Contour maps of the best CoMSIA model were in accordance with those of the Topomer CoMFA model, giving the insight into the feature requirements of DAPYs for the anti-HIV-1 activity. Three potential pharmacophore models were constructed, and each of them was consisted of five hypothesis features. All results suggested that the aromatic ring on the left wing of DAPYs and the central pyrimidine ring contained key pharmacophore features for the anti-HIV-1 activity, and also indicated that the right wing of DAPYs had potential for further structural modification to improve activity. Eight novel DAPY molecules with potential anti-HIV-1 activities were designed on the basis of the obtained results. The findings in this study might provide important information for further design and development of novel HIV-1 NNRTIs.

Molecular modeling studies of quinazolinone derivatives as novel PI3Kδ selective inhibitors

The main molecular modeling method, the docking results of newly designed compoundD04and the best pharmacophore model are reported herein.