First chemical feature-based pharmacophore modeling of potent retinoidal retinoic acid metabolism blocking agents (RAMBAs): identification of novel RAMBA scaffolds

Dual role tertiary amines in photocatalytic cyclizations: towards sustainable syntheses of 1,3-dinitrogen heterocycles

A novel photocatalytic cascade has been engineered for the transformation of diketimines into 1,3-dinitrogen heterocycles, ingeniously repurposing methylamine a typically utilized sacrificial additive as a dual-function reagent, serving simultaneously as an electron donor and a methyl source. This innovation champions atom economy and underscores a commitment to sustainable chemical synthesis.

Retinol Depletion in COVID-19

Background and aims

COVID-19 has been a devastating pandemic. There are indications that vitamin A is depleted during infections. Vitamin A is important in development and immune homeostasis. It has been used successfully in measles, RSV and AIDS infections. In this study, we aimed to measure the serum retinol levels in severe COVID-19 patients to assess the importance of vitamin A in the COVID-19 pathogenesis.

Methods

The serum retinol level was measured in two groups of patients: the COVID-19 group, which consisted of 27 severe COVID-19 patients hospitalized in the intensive care unit with respiratory failure, and the control group, which consisted of 23 patients without COVID-19 symptoms.

Results

The mean serum retinol levels were 0.37 mg/L in the COVID-19 group and 0.52 mg/L in the control group. The difference between the serum retinol levels in the two groups was statistically significant. There was no significant difference in retinol levels between different ages and genders within the COVID-19 group. Comorbidity did not affect serum retinol levels.

Conclusion

The serum retinol level was significantly lower in patients with severe COVID-19, and this difference was independent of age or underlying comorbidity. Our data show that retinol and retinoic acid signaling might be important in immunopathogenesis of COVID-19.

Computational Investigation Identified Potential Chemical Scaffolds for Heparanase as Anticancer Therapeutics

Heparanase (Hpse) is an endo-β-D-glucuronidase capable of cleaving heparan sulfate side chains. Its upregulated expression is implicated in tumor growth, metastasis and angiogenesis, thus making it an attractive target in cancer therapeutics. Currently, a few small molecule inhibitors have been reported to inhibit Hpse, with promising oral administration and pharmacokinetic (PK) properties. In the present study, a ligand-based pharmacophore model was generated from a dataset of well-known active small molecule Hpse inhibitors which were observed to display favorable PK properties. The compounds from the InterBioScreen database of natural (69,034) and synthetic (195,469) molecules were first filtered for their drug-likeness and the pharmacophore model was used to screen the drug-like database. The compounds acquired from screening were subjected to molecular docking with Heparanase, where two molecules used in pharmacophore generation were used as reference. From the docking analysis, 33 compounds displayed higher docking scores than the reference and favorable interactions with the catalytic residues. Complex interactions were further evaluated by molecular dynamics simulations to assess their stability over a period of 50 ns. Furthermore, the binding free energies of the 33 compounds revealed 2 natural and 2 synthetic compounds, with better binding affinities than reference molecules, and were, therefore, deemed as hits. The hit compounds presented from this in silico investigation could act as potent Heparanase inhibitors and further serve as lead scaffolds to develop compounds targeting Heparanase upregulation in cancer.

Retinoic Acid and Its Derivatives in Skin

The retinoids are a group of compounds including vitamin A and its active metabolite all-trans-retinoic acid (ATRA). Retinoids regulate a variety of physiological functions in multiple organ systems, are essential for normal immune competence, and are involved in the regulation of cell growth and differentiation. Vitamin A derivatives have held promise in cancer treatment and ATRA is used in differentiation therapy of acute promyelocytic leukemia (APL). ATRA and other retinoids have also been successfully applied in a variety of dermatological conditions such as skin cancer, psoriasis, acne, and ichthyosis. Moreover, modulation of retinoic acid receptors and retinoid X (or rexinoid) receptors function may affect dermal cells. The studies using complex genetic models with various combinations of retinoic acid receptors (RARs) and retinoid X (or rexinoid) receptors (RXRs) indicate that retinoic acid and its derivatives have therapeutic potential for a variety of serious dermatological disorders including some malignant conditions. Here, we provide a synopsis of the main advances in understanding the role of ATRA and its receptors in dermatology.

Identification of Essential 2D and 3D Chemical Features for Discovery of the Novel Tubulin Polymerization Inhibitors

Background:

Tubulin polymerization inhibitors interfere with microtubule assembly and their functions lead to mitotic arrest, therefore they are attractive target for design and development of novel anticancer compounds.

Objective:

The proposed novel and effective structures following the use of three-dimensionalquantitative structure activity relationship (3D-QSAR) pharmacophore based virtual screening clearly demonstrate the high efficiency of this method in modern drug discovery.

Method:

Combined computational approach was applied to extract the essential 2D and 3D features requirements for higher activity as well as identify new anti-tubulin agents.

Results:

The best quantitative pharmacophore model, Hypo1, exhibited good correlation of 0.943 (RMSD=1.019) and excellent predictive power in the training set compounds. Generated model AHHHR, was well mapped to colchicine site and three-dimensional spatial arrangement of their features were in good agreement with the vital interactions in the active site. Total prediction accuracy (0.92 for training set and 0.86 for test set), enrichment factor (4.2 for training set and 4.5 for test set) and the area under the ROC curve (0.86 for training set and 0.94 for the test set), the developed model using Extended Class FingerPrints of maximum diameter 4 (ECFP_4) was chosen as the best model.

Conclusion:

Developed computational platform provided a better understanding of requirement features for colchicine site inhibitors and we believe the results of this study might be useful for the rational design and optimization of new inhibitors.

Human cytochrome P450 enzymes 5-51 as targets of drugs and natural and environmental compounds: mechanisms, induction, and inhibition - toxic effects and benefits

Cytochrome P450 (P450, CYP) enzymes have long been of interest due to their roles in the metabolism of drugs, pesticides, pro-carcinogens, and other xenobiotic chemicals. They have also been of interest due to their very critical roles in the biosynthesis and metabolism of steroids, vitamins, and certain eicosanoids. This review covers the 22 (of the total of 57) human P450s in Families 5-51 and their substrate selectivity. Furthermore, included is information and references regarding inducibility, inhibition, and (in some cases) stimulation by chemicals. We update and discuss important aspects of each of these 22 P450s and questions that remain open.

Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease

Naodesheng (NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctorius, Radix Notoginseng, and Crataegus pinnatifida, is widely applied for the treatment of cardio/cerebrovascular ischemic diseases, ischemic stroke, and sequelae of cerebral hemorrhage, etc. At present, the studies on NDS formula for Alzheimer's disease (AD) only focus on single component of this prescription, and there is no report about the synergistic mechanism of the constituents in NDS formula for the potential treatment of dementia. Therefore, the present study aimed to predict the potential targets and uncover the mechanisms of NDS formula for the treatment of AD. Firstly, we collected the constituents in NDS formula and key targets toward AD. Then, drug-likeness, oral bioavailability, and blood-brain barrier permeability were evaluated to find drug-like and lead-like constituents for treatment of central nervous system diseases. By combining the advantages of machine learning, molecular docking, and pharmacophore mapping, we attempted to predict the targets of constituents and find potential multi-target compounds from NDS formula. Finally, we built constituent-target network, constituent-target-target network and target-biological pathway network to study the network pharmacology of the constituents in NDS formula. To the best of our knowledge, this represented the first to study the mechanism of NDS formula for potential efficacy for AD treatment by means of the virtual screening and network pharmacology methods.

The in silico identification of human bile salt export pump (ABCB11) inhibitors associated with cholestatic drug-induced liver injury

Drug-induced liver injury (DILI) is one of the major causes of drug attrition and failure. Currently, there is increasing evidence that direct inhibition of the human bile salt export pump (BSEP/ABCB11) by drugs and/or metabolites is one of the most important mechanisms of cholestatic DILI. In the present study, we employ two in silico methods, random forest (RF) and the pharmacophore method, to recognize potential BSEP inhibitors that could cause cholestatic DILI, with the aim of mitigating the risk of cholestatic DILI to some extent. The RF model achieved the best prediction performance, producing AUC (area under receiver operating characteristic curve) values of 0.901, 0.929 and 0.996 for leave-one-out cross-validation, the test set and the external test set, respectively, indicating that the built RF model has a satisfactory identification ability. As a complement to the RF model, the pharmacophore model was also built and was proved to be reliable with good predictive performance based on the internal and external validation results. Further analysis indicates that hydrophobicity, molecular size and polarity are important factors that influence the inhibitory activity of BSEP. Furthermore, the two models are applied to screen FDA-approved small molecule drugs, among which the drugs with the potential risk of cholestatic DILI are reported. In conclusion, the RF and pharmacophore models that we present can be considered as integrated screening tools to indicate the potential risk of cholestatic DILI by inhibition of BSEP.

Comparison of the ligand binding site of CYP2C8 with CYP26A1 and CYP26B1: a structural basis for the identification of new inhibitors of the retinoic acid hydroxylases

The CYP26s are responsible for metabolizing retinoic acid and play an important role in maintaining homeostatic levels of retinoic acid. Given the ability of CYP2C8 to metabolize retinoic acid, we evaluated the potential for CYP2C8 inhibitors to also inhibit CYP26. In vitro assays were used to evaluate the inhibition potencies of CYP2C8 inhibitors against CYP26A1 and CYP26B1. Using tazarotenic acid as a substrate for CYP26, IC₅₀ values for 17 inhibitors of CYP2C8 were determined for CYP26A1 and CYP26B1, ranging from ∼20 nM to 100 μM, with a positive correlation observed between IC₅₀s for CYP2C8 and CYP26A1. An evaluation of IC₅₀'s versus in vivo C_max values suggests that inhibitors such as clotrimazole or fluconazole may interact with CYP26 at clinically relevant concentrations and may alter levels of retinoic acid. These findings provide insight into drug interactions resulting in elevated retinoic acid concentrations and expand upon the pharmacophore of CYP26 inhibition.

Establishment of a screening protocol for identification of aminopeptidase N inhibitors

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Two pharmacophore models have been developed.

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Virtual screening was performed by the pharmacophore models and docking.

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Six selected hits were discovered to have inhibitory activities.

Inhibitors of aminopeptidase N (APN) have been thought as potential drugs for the treatment of tumor angiogenesis, invasion and metastasis and a considerable number of APN inhibitors have been reported recently. To clarify the essential structure–activity relationship for the APN inhibitors as well as identify new potent leads against APN, pharmacophore models were established using structure- and common feature-based approaches and validated with a database of active and inactive compounds. These validated pharmacophores were then used in database screening for novel virtual leads. The hit compounds were further subjected to molecular docking studies to refine the retrieved hits. Finally, six structurally diverse compounds that showed strong interactions with the key amino acids and the zinc ion were selected for biological evaluation, where two hits showed more than 70% inhibition against APN at 60 μM concentration. The evaluation results show the potential of our screening approach in identifying APN inhibitors.

Pharmacophore modeling, virtual screening, docking and in silico ADMET analysis of protein kinase B (PKB β) inhibitors

Protein kinase B (PKB) is a key mediator of proliferation and survival pathways that are critical for cancer growth. Therefore, inhibitors of PKB are useful agents for the treatment of cancer. Herein, we describe pharmacophore-based virtual screening combined with docking study as a rational strategy for identification of novel hits or leads. Pharmacophore models of PKB β inhibitors were established using the DISCOtech and refined with GASP from compounds with IC50 values ranging from 2.2 to 246nM. The best pharmacophore model consists of one hydrogen bond acceptor (HBA), one hydrogen bond donor (HBD) site and two hydrophobic (HY) features. The pharmacophore models were validated through receiver operating characteristic (ROC) and Güner-Henry (GH) scoring methods indicated that the model-3 was statistically valuable and reliable in identifying PKB β inhibitors. Pharmacophore model as a 3D search query was searched against NCI database. Several compounds with different structures (scaffolds) were retrieved as hits. Molecules with a Qfit value of more than 95 and three other known inhibitors were docked in the active site of PKB to further explore the binding mode of these compounds. Finally in silico pharmacokinetic and toxicities were predicted for active hit molecules. The hits reported here showed good potential to be PKB β inhibitors.

Discovery of N6-phenyl-1H-pyrazolo[3,4-d]pyrimidine-3,6-diamine derivatives as novel CK1 inhibitors using common-feature pharmacophore model based virtual screening and hit-to-lead optimization

Aberrant activation of casein kinase 1 (CK1) has been demonstrated to be implicated in the pathogenesis of cancer and various central nervous system disorders. Discovery of CK1 inhibitors has thus attracted much attention in recent years. In this account, we describe the discovery of N6-phenyl-1H-pyrazolo[3,4-d]pyrimidine-3,6-diamine derivatives as novel CK1 inhibitors. An optimal common-feature pharmacophore hypothesis, termed Hypo2, was firstly generated, followed by virtual screening using Hypo2 against several chemical databases. One of the best hit compounds, N6-(4-chlorophenyl)-1H-pyrazolo[3,4-d]pyrimidine-3,6-diamine, was chosen for the subsequent hit-to-lead optimization under the guide of Hypo2, which led to the discovery of a new lead compound (1-(3-(3-amino-1H-pyrazolo[3,4-d]pyrimidin-6-ylamino)phenyl)-3-(3-chloro-4-fluorophenyl)urea) that potently inhibits CK1 with an IC(50) value of 78 nM.