Active site fingerprinting and pharmacophore screening strategies for the identification of dual inhibitors of protein kinase C (ΡΚCβ) and poly (ADP-ribose) polymerase-1 (PARP-1)

Pyrrole-containing hybrids as potential anticancer agents: An insight into current developments and structure-activity relationships

Cancer poses a significant threat to human health. Therefore, it is urgent to develop potent anti-cancer drugs with excellent inhibitory activity and no toxic side effects. Pyrrole and its derivatives are privileged heterocyclic compounds with significant diverse pharmacological effects. These compounds can target various aspects of cancer cells and have been applied in clinical settings or are undergoing clinical trials. As a result, pyrrole has emerged as a promising drug scaffold and has been further probed to get novel entities for the treatment of cancer. This article reviews recent research progress on anti-cancer drugs containing pyrrole. It focuses on the mechanism of action, biological activity, and structure-activity relationships of pyrrole derivatives, aiming to assist in designing and synthesizing innovative pyrrole-based anti-cancer compounds.

Epigenetic target identification strategy based on multi-feature learning

The identification of potential epigenetic targets for a known bioactive compound is essential and promising as more and more epigenetic drugs are used in cancer clinical treatment and the availability of chemogenomic data related to epigenetics increases. In this study, we introduce a novel epigenetic target identification strategy (ETI-Strategy) that integrates a multi-task graph convolutional neural network prior model and a protein-ligand interaction classification discriminating model using large-scale bioactivity data for a panel of 55 epigenetic targets. Our approach utilizes machine learning techniques to achieve an AUC value of 0.934 for the prior model and 0.830 for the discriminating model, outperforming inverse docking in predicting protein-ligand interactions. When comparing with other open-source target identification tools, it was found that only our tool was able to accurately predict all the targets corresponding to each compound. This further demonstrates the ability of our strategy to take full advantage of molecular-level information as well as protein-level information in molecular activity prediction. Our work highlights the contribution of machine learning in the identification of potential epigenetic targets and offers a novel approach for epigenetic drug discovery and development.Communicated by Ramaswamy H. Sarma.

Identification of potentially high drug-like VEGFR2/c-Met dual-target type II kinase inhibitors with symmetric skeletons based on structural screening

Vascular endothelial growth factor receptor 2 (VEGFR2) and c-Mesenchymal epithelial transition factor (c-Met) are tyrosine kinase receptors associated with the occurrence of malignant tumors. Studies have shown that inhibition of VEGFR2 promotes a feedback increase in c-Met, a mechanism linked to the emergence of resistance to VEGFR2 inhibitors. Therefore, treatment targeting both VEGFR2 and c-Met will have better application prospects. In this study, hierarchical virtual screening was performed on ZINC15, Molport and Mcule-ULTIMATE databases to identify potential VEGFR2/c-Met dual inhibitors. Firstly, the best pharmacophore model for each target was used to cross-screen the three databases, and the compounds that could match the two pharmacophore models were then retained based on the Fit Value of the respective crystal ligands. Compounds ZINC, MOL, and MLB named after their database sources were retained by binding pattern analysis and docking assessment. ADMET predictions indicated that ZINC had significantly higher oral bioavailability compared to the approved drug cabozantinib. This is likely due to ZINC's unique symmetrical backbone with less structure complexity, which may reduce the occurrence of adverse effects. Molecular dynamics simulations and binding free energy analysis showed that all three hit compounds were able to stably bind at the active site, but only ZINC could form high occupancy of hydrogen bonds with both VEGFR2 and c-Met, and also only ZINC had a higher binding free energy than crystal ligands, suggesting that ZINC was the most likely potential VEGFR2/c-Met dual-target inhibitor. This finding provides a promising starting point for the development of VEGFR2/c-Met dual-target inhibitors.Communicated by Ramaswamy H. Sarma.

Organophosphorus insecticide interacts with the pheromone-binding proteins of Athetis lepigone: Implication for olfactory dysfunction

Athetis lepigone is one of the most severe polyphagous pests, and it has developed resistance to different chemical insecticides. Insects primarily rely on the olfactory system to recognize various environmental chemicals, including xenobiotics such as insecticides. Here, we expressed two A. lepigone pheromone-binding proteins (AlepPBP2 and AlepPBP3), and observed they had higher binding affinities to phoxim than other insecticides, with Ki was 3.30 ± 0.38 μM and 3.27 ± 0.10 μM, respectively. Molecular dynamics simulation, binding mode analysis, and computational alanine scanning showed that six residues (Phe15, Phe39, Ile55, Leu65, Ile97, and Phe122) of AlepPBP2 and three residues (Phe12, Ile52, and Ile134) of AlepPBP3 maybe as potential residues that can change protein ability to bind an organophosphorus insecticide phoxim. Then, we used site-directed mutagenesis assay to mutate these residues into alanine, respectively. Subsequently, the binding assays displayed that Phe15, Phe39, and Ile97 of AlepPBP2, Phe12 and Ile134 of AlepPBP3 caused a significant decrease of AlepPBPs binding ability to phoxim, suggesting they should play crucial roles in the AlepPBPs/phoxim interactions. Our findings could further advance in using PBPs as unique targets to design and develop precise and environmentally-friendly pest control agents with high insecticidal potential using a computer-aided drug design (CADD) approach.

Key Amino Acid Residues Influencing Binding Affinities of Pheromone-Binding Protein from Athetis lepigone to Two Sex Pheromones

Athetis lepigone is a polyphagous pest found around the world that feeds on maize, wheat, and various other important crops. Although it exhibits a degree of resistance to various chemical insecticides, an effective pest-control method has not yet been developed. The sex pheromone communication system plays an essential role in the mating and reproduction of moths, in which pheromone-binding proteins (PBPs) are crucial genes. In this study, we cloned and purified the protein AlepPBP1 using an E. coli expression system and found it had a higher binding affinity to two sex pheromones of A. lepigone, namely, Z7-12:Ac and Z9-14:Ac (with K_i 0.77 ± 0.10 and 1.10 ± 0.20 μM, respectively), than to other plant volatiles. The binding-mode analysis of protein conformation with equilibrium stabilization was obtained using molecular dynamics (MD) simulation and indicated that hydrophobic interactions involving several nonpolar residues were the main driving force for the binding affinity of AlepPBP1 with sex pheromones. Computational alanine scanning (CAS) was performed to further identify key amino acid residues and validate their binding contributions. Each key residue, including Phe36, Trp37, Val52, and Phe118, was subsequently mutated into alanine using site-directed mutagenesis. Binding assays showed that the efficient binding abilities to Z7-12:Ac (F36A, W37A, and F118A) and Z9-14:Ac (F36A, W37A, V52A, and F118A) were almost lost in the mutated proteins. Our results demonstrated that these key amino acid residues are crucial for determining the binding ability of AlepPBP1 to sex pheromones. These findings provide a basis for the use of AlepPBP1 in the studies as a specific target for the development of novel behavioral antagonists with marked inhibition or mating-disruption abilities using computer-aided drug design (CADD).

The cardioprotective effect of dexrazoxane (Cardioxane) is consistent with sequestration of poly(ADP-ribose) by self-assembly and not depletion of topoisomerase 2B

Following systematic scrutiny of the evidence in support of the hypothesis that the cardioprotective mechanism of action of dexrazoxane is mediated by a 'depletion' or 'downregulation' of Top2β protein levels in heart tissue, the author concludes that this hypothesis is untenable. In seeking to understand how dexrazoxane protects the heart, the outcomes of a customised association rule learning algorithm incorporating the use of antecedent surrogate variables (CEME, 2017 McCormack Pharma) reveal a previously unknown relationship between dexrazoxane and poly(ADP-ribose) (PAR) polymer. The author shows how this previously unknown relationship explains both acute and long-term cardioprotection in patients receiving anthracyclines. In addition, as a direct inhibitor of PAR dexrazoxane has access to the epigenome and this offers a new insight into protection by dexrazoxane against doxorubicin-induced late-onset damage [McCormack K, manuscript in preparation]. Notably, through this review article, the author illustrates the practical application of probing natural language text using an association rule learning algorithm for the discovery of new and interesting associations that, otherwise, would remain lost. Historically, the use of CEME enabled the first report of the capacity of a small molecule to catalyse the hybrid self-assembly of a nucleic acid biopolymer via canonical and non-canonical, non-covalent interactions analogous to Watson Crick and Hoogsteen base pairing, respectively.

Poly(ADP-Ribose) Polymerases in Host-Pathogen Interactions, Inflammation, and Immunity

The literature review presented here details recent research involving members of the poly(ADP-ribose) polymerase (PARP) family of proteins. Among the 17 recognized members of the family, the human enzyme PARP1 is the most extensively studied, resulting in a number of known biological and metabolic roles. This review is focused on the roles played by PARP enzymes in host-pathogen interactions and in diseases with an associated inflammatory response. In mammalian cells, several PARPs have specific roles in the antiviral response; this is perhaps best illustrated by PARP13, also termed the zinc finger antiviral protein (ZAP). Plant stress responses and immunity are also regulated by poly(ADP-ribosyl)ation. PARPs promote inflammatory responses by stimulating proinflammatory signal transduction pathways that lead to the expression of cytokines and cell adhesion molecules. Hence, PARP inhibitors show promise in the treatment of inflammatory disorders and conditions with an inflammatory component, such as diabetes, arthritis, and stroke. These functions are correlated with the biophysical characteristics of PARP family enzymes. This work is important in providing a comprehensive understanding of the molecular basis of pathogenesis and host responses, as well as in the identification of inhibitors. This is important because the identification of inhibitors has been shown to be effective in arresting the progression of disease.

Hierarchical virtual screening of the dual MMP-2/HDAC-6 inhibitors from natural products based on pharmacophore models and molecular docking

The dual-target inhibitors tend to improve the response rate in treating tumors, comparing with the single-target inhibitors. Matrix metalloproteinase-2 (MMP-2) and histone deacetylase-6 (HDAC-6) are attractive targets for cancer therapy. In this study, the hierarchical virtual screening of dual MMP-2/HDAC-6 inhibitors from natural products is investigated. The pharmacophore model of MMP-2 inhibitors is built based on ligands, but the pharmacophore model of HDAC-6 inhibitors is built based on the experimental crystal structures of multiple receptor-ligand complexes. The reliability of these two pharmacophore models is validated subsequently. The hierarchical virtual screening, combining these two different pharmacophore models of MMP-2 and HDAC-6 inhibitors with molecular docking, is carried out to identify the dual MMP-2/HDAC-6 inhibitors from a database of natural products. The four potential dual MMP-2/HDAC-6 inhibitors of natural products, STOCK1 N-46177, STOCK1 N-52245, STOCK1 N-55477, and STOCK1 N-69706, are found. The studies of binding modes show that the screened four natural products can simultaneously well bind with the MMP-2 and HDAC-6 active sites by different kinds of interactions, to inhibit the MMP-2 and HDAC-6 activities. In addition, the ADMET properties of screened four natural products are assessed. These found dual MMP-2/HDAC-6 inhibitors of natural products could serve as the lead compounds for designing the new dual MMP-2/HDAC-6 inhibitors having higher biological activities by carrying out structural modifications and optimizations in the future studies.