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Objective: Endometriosis is a common benign disease in women of reproductive age. Qu's formula (QUF) is a patented Chinese herbal medicine for treating endometriosis that has been proven to be effective in treating and preventing the recurrence of endometriosis. This study is aimed to discover its molecular mechanism and to explore the potential drug targets. Methods: A QUF target and endometriosis-related gene set was identified by the Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) databases and five disease-gene databases. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed, and a protein–protein interaction (PPI) network was established to discover the potential mechanism. MalaCards was searched for targets and signaling pathways related to endometriosis, and the search results were also used to identify the key factors in QUF. Molecular docking was performed to visualize the interactions between the effective molecules and proteins encoded by critical genes. Cell experiments and molecular dynamics (MD) simulations were used to further validate the therapeutic effects of the active compounds in QUF on endometriosis. Results: A compound-target network with 117 nodes (94 genes and 23 active compounds) and 224 edges was generated. The results of GO and KEGG analyses indicated that QUF could act by regulating the immune response, apoptosis and proliferation, oxidative stress, and angiogenesis. VEGFA, CXCL8, CCL2, IL1B and PTGS2 were selected for molecular docking analysis from two critical subnetworks with high correlation scores in MalaCards, and the active compounds of QUF had binding potential and high affinity for them. The mRNA expression levels of CCL2, IL1B and PTGS2 significantly decreased after treatment with quercetin. MD simulations showed that the combinations of quercetin and these proteins were relatively stable. Conclusion: The network pharmacological strategy integrates molecular docking to unravel the molecular mechanism by which QUF protects against endometriosis. Our findings not only confirm the clinical effectiveness of QUF but also provide a foundation for further experimental study. [ABSTRACT FROM AUTHOR]

Protein tyrosine phosphatase 1B (PTP1B) is an intracellular non-receptor phosphatase that is implicated in signal transduction of insulin and leptin pathways, thus PTP1B is considered as potential target for treating type II diabetes and obesity. The present article is an attempt to formulate the three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling of a series of compounds possessing PTP1B inhibitory activities using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The optimum template ligand-based models are statistically significant with great CoMFA (R 2 cv  = 0.600, R 2 pred  = 0.6760) and CoMSIA (R 2 cv  = 0.624, R 2 pred  = 0.8068) values. Molecular docking was employed to elucidate the inhibitory mechanisms of this series of compounds against PTP1B. In addition, the CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of PTP1B active site. The knowledge of structure-activity relationship and ligand-receptor interactions from 3D-QSAR model and molecular docking will be useful for better understanding the mechanism of ligand-receptor interaction and facilitating development of novel compounds as potent PTP1B inhibitors. [ABSTRACT FROM AUTHOR]

DNA gyrase B (GyrB) plays a critical role in DNA replication, repair, recombination, and transcription and has become an attractive target for a number of antibacterial agents. In the present work, to better comprehend the structure–activity relationship and mechanism of action of novel series of GyrB inhibitors, a theoretical study of three-dimensional-quantitative structure–activity relationship (3D-QSAR), molecular docking, molecular dynamics (MD) simulations, and binding free energy analysis were performed. The results showed that CoMFA (R2 cv = 0.591, R2 pred = 0.7698) and CoMSIA (R2 cv = 0.629, R2 pred = 0.6848) models possessed robust stability and predictability. The derived contour maps of steric, electrostatic, and hydrogen bond donor field further displayed the modified information of these inhibitors. Molecular docking was further conducted to provide the initial binding conformation for MD simulations. Subsequently, MD simulations were applied to explore the key amino acids and binding modes at the active site. The binding free energy decomposition analysis further indicates that the residues Ile54, Glu55, Arg83, Ala85, Val86 and Thr128 are essential for the high selectivity of inhibitors. Overall, these results would serve as a significant guideline for the discovery and design of novel GyrB inhibitors. [ABSTRACT FROM AUTHOR]

Selective thyroid hormone receptor β (TRβ) binding over TRα is an important requirement for improved therapeutic profile of TRβ agonists. Since selective compounds might be tolerated at doses that lead to complete binding without side effects, thus a selectivity study is valuable. Initially, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were developed on a series of agonists of TRβ and TRα, respectively. These models produced statistically significant results: TRβ-CoMFA ( R cv 2 , R pred 2 : 0.634, 0.6825), TRβ-CoMSIA ( R cv 2 , R pred 2 : 0.711, 0.5622), TRα-CoMFA ( R cv 2 , R pred 2 : 0.602, 0.5384) and TRα-CoMSIA ( R cv 2 , R pred 2 : 0.674, 0.5078). These cross-validated results suggest that the developed models have excellent internal and external predictability and consistency. To further explore the origin of the selectivity at the amino acid residue level, the comparison between molecular docking and contour maps was conducted, it is revealed that steric, electrostatic and hydrogen bonding interactions play critical roles on selectivity; and Arg316, Arg282, Asn331, His435 for TRβ, Arg228, Arg262, Ser277, His381 for TRα are the significant residues, an in-depth comparative investigation suggests that the single different amino acid Asn331/Ser277 in the ligand binding pocket mainly introduce the ligand selectivity. All these analyses provide valuable information for better understand the mechanism of ligand–receptor interaction and facilitate structural modifications of the agonists to increase activity and selectivity. [ABSTRACT FROM AUTHOR]

Src homology 2 (SH2)-containing protein tyrosine phosphatase 2 (SHP2) as a major phosphatase would affect the development of tumors by regulating several cellular processes, and is a significant potential target for cancer treatment. In the present work, a series of pyridine derivatives possessing a wide range of inhibitory activity was employed to investigate the structural requirements by developing three dimensional quantitative structure–activity relationship (3D-QSAR) models using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. The results show that CoMFA (R2 cv = 0.646, R2 pred = 0.5587) and CoMSIA (R2 cv = 0.777, R2 pred = 0.7131) have excellent stability and predictability. The relationship between the inhibitory activity and structure of the inhibitors was analyzed by the derived contour maps. Furthermore, the QSAR models were validated by molecular docking and molecular dynamics simulations, which were also applied to reveal the potential molecular mechanism of these inhibitors. It was found that Arg110, Asn216, Thr218, Thr252 and Pro490 play a crucial role in stabilizing the inhibitors. Additionally, MM/PBSA calculations provided the binding free energy were also conducted to explain the discrepancy of binding activities. Overall, the outcomes of this work could provide useful information and theoretical guidance for the development of novel and potent SHP2 inhibitors. [ABSTRACT FROM AUTHOR]

Abstract: Glycogen synthase kinase-3 beta (GSK3β) plays an important role in a diverse number of regulatory pathways by phosphorylation of several different cellular targets and its inhibitors have been evaluated as promising drug candidates. In this work, 192 3-aryl-4-(arylhydrazono)-1H-pyrazol-5-one analogs (AHP) and indazoles (ID) derivatives possessing selective binding affinity for GSK3β kinase were studied using the 3D-QSAR/CoMFA/CoMSIA methodologies. The obtained CoMFA/CoMSIA models exhibit both good internal and external predictive abilities, i.e., for AHP derivatives and for ID analogs. Of paramount interest is the observation derived from the combination of molecular dynamics and molecular docking studies that Val135 and Asp133 are responsible for the binding recognition for AHP molecules, while residues Val135 and Pro136 are mainly involved in the specific ligand–kinase interactions for ID analogs. The developed models are seeking to be helpful for the rational design of novel potent GSK3β inhibitors. [Copyright &y& Elsevier]

Abstract: CDK2 (cyclin-dependent kinase 2) is an attractive target for therapeutic intervention in cancer. In this work, quantitative structure–activity relationship (QSAR), molecular docking, and molecular dynamics (MD) studies were performed on three sets of 155 CDK2 inhibitors. The obtained models exhibit good predictive capability in both internal and external validations (q 2 =0.73, for 6, 6-dimethyl pyrrolo [3,4-c]pyrazoles analogs, q 2 =0.62, for imidazole pyrimidine amides analogs and q 2 =0.56, for 4-(pyrazol-4-yl)-pyrimidines analogs). Furthermore, a comparison between 3D-contour map, docking and MD simulation explore in detail the binding modes and the key structural features impacting the interaction of each series of inhibitors with the CDK2 enzyme, which should be useful to aid the designing of new inhibitors with CDK2 improved biological response. [Copyright &y& Elsevier]

Focal adhesion kinase (FAK) is a promising target for developing more effective anticancer drugs. To better understand the structure-activity relationships and mechanism of actions of FAK inhibitors, a molecular modeling study using 3D-QSAR, molecular docking, molecular dynamics simulations, and binding free energy analysis were conducted. Two types of satisfactory 3D-QSAR models were generated, comprising the CoMFA model (R2 cv = 0.528, R2 pred = 0.7557) and CoMSIA model (R2 cv = 0.757, R2 pred = 0.8362), for predicting the inhibitory activities of novel inhibitors. The derived contour maps indicate structural characteristics for substituents on the template. Molecular docking, molecular dynamic simulations and binding free energy calculations further reveal that the binding of inhibitors to FAK is mainly contributed from hydrophobic, electrostatic and hydrogen bonding interactions. In addition, some key residues (Arg14, Glu88, Cys90, Arg138, Asn139, Leu141, and Leu155) responsible for ligand-receptor binding are highlighted. All structural information obtained from 3D-QSAR models and molecular dynamics is consist with the available experimental activities. All the results will facilitate the optimization of this series of FAK inhibitors with higher inhibitory activities. [ABSTRACT FROM AUTHOR]

Dityrosine is the product of oxidation that has been linked to a number of serious pathological conditions. Evidence indicates that high amounts of dityrosine exist in oxidized milk powders and some milk related foodstuffs, further reducing the nutritional value of oxidized proteins. Therefore, we hypothesize that some receptors related to special diseases would be targets for dityrosine. However, the mechanisms of the interaction of dityrosine with probable targets are still unknown. In the present work, an inverse virtual screening approach was performed to screen possible novel targets for dityrosine. Molecular docking studies were performed on a panel of targets extracted from the potential drug target database (PDTD) to optimize and validate the screening results. Firstly, two different conformations cis- and trans- were found for dityrosine during minimization. Moreover, Tubulin (αT) (−11.0 kcal/mol) was identified as a target for cis-dityrosine (CDT), targets including αT (−11.2 kcal/mol) and thyroid hormone receptor beta-1 (−10.7 kcal/mol) presented high binding affinities for trans-dityrosine (TDT). Furthermore, in order to provide binding complexes with higher precision, the three docked systems were further refined by performing thermo dynamic simulations. A series of techniques for searching for the most stable binding pose and the calculation of binding free energy are elaborately provided in this work. The major interactions between these targets and dityrosine were hydrophobic, electrostatic and hydrogen bonding. The application of inverse virtual screening method may facilitate the prediction of unknown targets for known ligands, and direct future experimental assays. [ABSTRACT FROM AUTHOR]