Towards to potential 2-cyano-pyrimidines cathepsin-K inhibitors: An in silico design and screening research based on comprehensive application of quantitative structure–activity relationships, molecular docking and ADMET prediction

Design, synthesis and evaluation of new thiazolidin-4-ones as LPA1 receptor antagonists for breast cancer therapy

Aim: Breast cancer has been a leading cause of mortality among women worldwide in recent years. Targeting the lysophosphatidic acid (LPA)-LPA1 pathway using small molecules could improve breast cancer therapy. Materials & methods: Thiazolidin-4-ones were developed and tested on MCF-7 cancer cells, and active compounds were analyzed for their effects on apoptosis, migration angiogenesis and LPA1 protein and gene expression. Results & conclusion: Compounds TZ-4 and TZ-6 effectively reduced the migration of MCF-7 cells, and induced apoptosis. TZ-4, TZ-6, TZ-8 and TZ-14 significantly reduced the LPA1 protein, LPA1 and angiogenesis gene expression in treated MCF-7 cells. Molecular docking and molecular dynamic simulation studies reveal the ligand interactions and stability of the LPA1-ligand complex. Developed thiazolidin-4-ones showed great potential as an LPA1-targeted approach to combating breast cancer.

Novel Imidazole Phenoxyacetic Acids as Inhibitors of USP30 for Neuroprotection Implication via the Ubiquitin-Rho-110 Fluorometric Assay: Design, Synthesis, and In Silico and Biochemical Assays

USP30, a deubiquitinating enzyme family, forfeits the ubiquitination of E3 ligase and Parkin on the surface of mitochondria. Inhibition of USP30 results in mitophagy and cellular clearance. Herein, by understanding structural requirements, we discovered potential USP30 inhibitors from an imidazole series of ligands via a validated ubiquitin-rhodamine-110 fluorometric assay. A novel catalytic use of the Zn(l-proline)₂ complex for the synthesis of tetrasubstituted imidazoles was identified. Among all compounds investigated, 3g and 3f inhibited USP30 at IC₅₀ of 5.12 and 8.43 μM, respectively. The binding mode of compounds at the USP30 binding site was understood by a docking study and interactions with the key amino acids were identified. Compound 3g proved its neuroprotective efficacy by inhibiting apoptosis on SH-SY5Y neuroblastoma cells against dynorphin A (10 μM) treatment. Hence, the present study provides a new protocol to design and develop ligands against USP30, thereby offering a therapeutic strategy under conditions like kidney damage and neurodegenerative disorders including Parkinson's disease.

Advances in Engineered Three-Dimensional (3D) Body Articulation Unit Models

Indeed, the body articulation units, commonly referred to as body joints, play significant roles in the musculoskeletal system, enabling body flexibility. Nevertheless, these articulation units suffer from several pathological conditions, such as osteoarthritis (OA), rheumatoid arthritis (RA), ankylosing spondylitis, gout, and psoriatic arthritis. There exist several treatment modalities based on the utilization of anti-inflammatory and analgesic drugs, which can reduce or control the pathophysiological symptoms. Despite the success, these treatment modalities suffer from major shortcomings of enormous cost and poor recovery, limiting their applicability and requiring promising strategies. To address these limitations, several engineering strategies have been emerged as promising solutions in fabricating the body articulation as unit models towards local articulation repair for tissue regeneration and high-throughput screening for drug development. In this article, we present challenges related to the selection of biomaterials (natural and synthetic sources), construction of 3D articulation models (scaffold-free, scaffold-based, and organ-on-a-chip), architectural designs (microfluidics, bioprinting, electrospinning, and biomineralization), and the type of culture conditions (growth factors and active peptides). Then, we emphasize the applicability of these articulation units for emerging biomedical applications of drug screening and tissue repair/regeneration. In conclusion, we put forward the challenges and difficulties for the further clinical application of the in vitro 3D articulation unit models in terms of the long-term high activity of the models.

In Ovo and In Silico Evaluation of the Anti-Angiogenic Potential of Syringin

INTRODUCTION

Cancer is considered as one of the deadliest human diseases today. Angiogenesis, the propagation of new blood vessels from pre-existing vasculature, is a critical step in the progression of cancer as it is essential in the growth and metastasis of tumors. Hence, suppression of angiogenesis is a promising approach in cancer therapy. Syringin, a phenylpropanoid glycoside with a molecular formula of C17H24O9, has been found to exhibit chemopreventive effects. However, its anti-angiogenic activity and the underlying mechanism of action are still unknown.

METHODS

In this work, in ovo chorioallantoic membrane (CAM) assay has been conducted to evaluate the effect of syringin on neovascularization. Additionally, reverse molecular docking studies have been performed in order to identify the probable enzyme targets in the angiogenesis pathway.

RESULTS

Treatment with syringin showed significant dose-dependent inhibition of blood vessel length and junctions in the CAM of duck eggs; the anti-angiogenic activity of syringin at 100 µM and 200 µM is comparable with 200 µM of the positive control celecoxib. The results of reverse docking studies indicate that syringin binds the strongest to dihydrofolate reductase (DHFR) and, to some extent, with transforming growth factor-beta receptor type 1 (TGF-βR1), vascular endothelial growth factor receptor 2 (VEGFR2), and matrix metalloproteinase-2 (MMP-2). Furthermore, ADMET models revealed that syringin potentially possesses excellent pharmacokinetic and toxicity profiles.

CONCLUSION

This study demonstrates the potential of syringin as an anti-angiogenic agent and elicits further investigations to establish its application in cancer suppression.

Identification of the Active Constituents and Significant Pathways of Guizhi-Shaoyao-Zhimu Decoction for the Treatment of Diabetes Mellitus Based on Molecular Docking and Network Pharmacology

AIM AND OBJECTIVE

This study was designed to explore the active compounds and significant pathways of Guizhi-Shaoyao-Zhimu decoction (GSZD) for treating diabetes mellitus using molecular docking combined with network pharmacology.

MATERIALS AND METHODS

Chemical constituents of GSZD and diabetes-related target proteins were collected from various databases. Then, compounds were filtered by Lipinski's and Veber's rules with Discovery studio software. The "Libdock" module was used to carry out molecular docking, and LibDockScores, default cutoff values for hydrogen bonds, and van der Waals interactions were recorded. LibDockScore of the target protein and its prototype ligand was considered as the threshold, and compounds with higher LibDockScores than the threshold were regarded as the active constituents of GSZD. Cytoscape software was used to construct the herb-active molecule-target interaction network of GSZD. ClueGO and CluePedia were applied to enrich the analysis of the biological functions and pathways of GSZD.

RESULTS

A total of 275 potential active compounds with 57 possible pathways in GSZD were identified by molecular docking combined with network pharmacology. TEN, INSR, PRKAA2, and GSK3B are the four most important target proteins. Gancaonin E, 3'-(γ,γ-dimethylallyl)-kievitone, aurantiamide, curcumin and 14-O-cinnamoylneoline, could interact with more than 14 of the selected target proteins. Besides, 57 potential pathways of GSZD were identified, such as insulin signaling pathway, metabolites and energy regulation, glucose metabolic process regulation, and positive regulation of carbohydrate metabolic process, etc. Conclusion: These results showed that molecular docking combined with network pharmacology is a feasible strategy for exploring bioactive compounds and mechanisms of Chinese medicines, and GSZD can be used to effectively treat diabetes through multi-components and multi-targets & pathways.

Environmentally Friendly Fluoroquinolone Derivatives with Lower Plasma Protein Binding Rate Designed Using 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation

Comparative molecular similarity index analysis (CoMSIA) was used to establish a three-dimensional quantitative structure–activity relationship (3D-QSAR) model with structural parameters of quinolones as the independent variables and plasma protein binding rate (logf_b) as the dependent variable to predict the logf_b values of remaining quinolones in this study. In addition, the mono-substituted and bis-substituted reaction schemes that significantly influenced the plasma protein binding rate of quinolones were determined through an analysis of the 3D-QSAR contour maps. It was found that the replacement of small groups, hydrophobic groups, electronegative groups, or hydrogen bond acceptor groups at the substitution sites significantly reduce the logf_b values of quinolone derivatives. Furthermore, the mechanism of decrease in binding rate between trovafloxacin (TRO) derivatives and plasma protein was revealed qualitatively and quantitatively based on molecular docking and molecular dynamics simulation. After modification of the target molecule, 11 TRO derivatives with low plasma protein binding rates were screened (reduced by 0.50–24.18%). Compared with the target molecule, the molecular genotoxicity and photodegradability of the TRO derivatives was higher (genotoxicity increased by 4.89–21.36%, and photodegradability increased by 9.04–20.56%), and their bioconcentration was significantly lower (by 36.90–61.41%).

Partial Least Square Model (PLS) as a Tool to Predict the Diffusion of Steroids Across Artificial Membranes

One of the most challenging goals in modern pharmaceutical research is to develop models that can predict drugs’ behavior, particularly permeability in human tissues. Since the permeability is closely related to the molecular properties, numerous characteristics are necessary in order to develop a reliable predictive tool. The present study attempts to decode the permeability by correlating the apparent permeability coefficient (P_app) of 33 steroids with their properties (physicochemical and structural). The P_app of the molecules was determined by in vitro experiments and the results were plotted as Y variable on a Partial Least Squares (PLS) model, while 37 pharmacokinetic and structural properties were used as X descriptors. The developed model was subjected to internal validation and it tends to be robust with good predictive potential (R²Y = 0.902, RMSEE = 0.00265379, Q²Y = 0.722, RMSEP = 0.0077). Based on the results specific properties (logS, logP, logD, PSA and VD_ss) were proved to be more important than others in terms of drugs P_app. The models can be utilized to predict the permeability of a new candidate drug avoiding needless animal experiments, as well as time and material consuming experiments.