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Hezha O. Rasul SP 1 sp , Bakhtyar K. Aziz SP 1 sp , Dlzar D. Ghafour SP 2,3 sp , Arif Kivrak SP 4 sp SP 1 sp College of Medicals and Applied Sciences, Charmo University, Peshawa Street, Chamchamal, 46,023, Sulaimani, Iraq SP 2 sp College of Science, Department of Medical Laboratory Science, Komar University of Science and Technology, 46,001, Sulaimani, Iraq SP 3 sp College of Science, Chemistry Department, University of Sulaimani, 46,001, Sulaimani, Iraq SP 4 sp Eskisehir Osmangazi University, Faculty of Sciences and Arts, Department of Chemistry, Eskisehir, 26,040, Turkey Email (corresponding): hezha.rasul@charmouniversity.org The two affiliations should be corrected as follows: Hezha O. Rasul SP 1 sp , Bakhtyar K. Aziz SP 2 sp , Dlzar D. Ghafour SP 3,4 sp , Arif Kivrak SP 5 sp SP 1 sp Department of Pharmaceutical Chemistry, College of Medicals and Applied Sciences, Charmo University, Peshawa Street, Chamchamal, 46,023, Sulaimani, Iraq SP 2 sp Department of Nanoscience and Applied Chemistry, College of Medicals and Applied Sciences, Charmo University, Peshawa Street, Chamchamal, 46,023, Sulaimani, Iraq SP 3 sp Department of Medical Laboratory Science, College of Science, Komar University of Science and Technology, 46,001, Sulaimani, Iraq SP 4 sp Department of Chemistry, College of Science, University of Sulaimani, 46,001, Sulaimani, Iraq SP 5 sp Department of Chemistry, Faculty of Sciences and Arts, Eskisehir Osmangazi University, Eskisehir, 26,040, Turkey Email (corresponding): hezha.rasul@charmouniversity.org The original article has been corrected. In the published article "In silico molecular docking and dynamic simulation of eugenol compounds against breast cancer" J Mol Model 28, 17 (2022), https://doi.org/10.1007/s00894-021-05010-w" two affiliations were published incorrectly. [Extracted from the article]

One of the most common malignancies diagnosed and the leading cause of death for cancer-stricken women globally is breast cancer. The molecular subtype affects therapy options because it is a complex disorder with multiple subtypes. By concentrating on receptor activation, mTOR (mammalian target of rapamycin) can be employed as a therapeutic target. The goal of this work was to screen a number of inhibitors produced from Hibiscus rosa-sinensis for possible target to inhibit the mTOR and to determine which has the greatest affinity for the receptor. Primarily, the ionization states of the chosen compounds were predicted using the ChemAxon web platform, and their pKa values were estimated. Given the significance of interactions between proteins in the development of drugs, structure-based virtual screening was done using AutoDock Vina. Approximately 120 Hibiscus components and ten approved anti-cancer drugs, including the mTOR inhibitor everolimus, were used in the comparative analysis. By using Lipinski's rule of five to the chosen compounds, the ADMET profile and drug-likeness characteristics were further examined to assess the anti-breast cancer activity. The compounds with the highest ranked binding poses were loaded using the SeeSAR tool and the HYDE scoring to give interactive, desolvation, and visual ΔG estimation for ligand binding affinity assessment. Following, the prospective candidates underwent three replicas of 100 ns long molecular dynamics simulations, preceded with MM-GBSA binding free energy calculation. The stability of the protein–ligand complex was determined using root mean square deviation (RMSD), root mean square fluctuation (RMSF), and protein–ligand interactions. The results demonstrated that the best mTOR binding affinities were found for stigmastadienol (107), lupeol (66), and taraxasterol acetate (111), which all performed well in comparison to the control compounds. Thus, bioactive compounds isolated from Hibiscus rosa-sinensis could serve as lead molecules for the creation of potent and effective mTOR inhibitors for the breast cancer therapy. [ABSTRACT FROM AUTHOR]

Context: A bacterial biofilm is a cluster of bacterial cells embedded in a self-produced matrix of extracellular polymeric substances such as DNA, proteins, and polysaccharides. Several diseases have been reported to cause by bacterial biofilms, and difficulties in treating these infections are of concern. This work aimed to identify the inhibitor with the highest binding affinity for the receptor protein by screening various inhibitors obtained from Azorella species for a potential target to inhibit dispersin B. This work shows that azorellolide has the highest binding affinity (− 8.2 kcal/mol) among the compounds tested, followed by dyhydroazorellolide, mulinone A, and 7-acetoxy-mulin-9,12-diene which all had a binding affinity of − 8.0 kcal/mol. To the best of our knowledge, this is the first study to evaluate and contrast several diterpene compounds as antibacterial biofilm chemicals. Methods: Here, molecular modelling techniques tested 49 diterpene compounds of Azorella and six FDA-approved antibiotics medicines for antibiofilm activity. Since protein-like interactions are crucial in drug discovery, AutoDock Vina was initially employed to carry out structure-based virtual screening. The drug-likeness and ADMET properties of the chosen compounds were examined to assess the antibiofilm activity further. Lipinski's rule of five was then applied to determine the antibiofilm activity. Then, molecular electrostatic potential was used to determine the relative polarity of a molecule using the Gaussian 09 package and GaussView 5.08. Following three replica molecular dynamic simulations (using the Schrodinger program, Desmond 2019-4 package) that each lasted 100 ns on the promising candidates, binding free energy was estimated using MM-GBSA. Structural visualisation was used to test the binding affinity of each compound to the crystal structure of dispersin B protein (PDB: 1YHT), a well-known antibiofilm compound. [ABSTRACT FROM AUTHOR]

Breast cancer is the most common malignancy among women. It is a complex condition with many subtypes based on the hormone receptor. The mammalian target of the rapamycin (mTOR) pathway regulates cell survival, metabolism, growth, and protein synthesis in response to upstream signals in both normal physiological and pathological situations, primarily in cancer. The objective of this study was to screen for a potential target to inhibit the mTOR using a variety of inhibitors derived from Cichorium intybus and to identify the one with the highest binding affinity for the receptor protein. Initially, AutoDock Vina was used to perform structure-based virtual screening, as protein-like interactions are critical in drug development. For the comparative analysis, 110 components of Cichorium intybus were employed and ten FDA-approved anticancer medicines, including everolimus, an mTOR inhibitor. Further, the drug-likeness and ADMET properties were investigated to evaluate the anti-breast cancer activity by applying Lipinski's rule of five to the selected molecules. The promising candidates were then subjected to three replica molecular dynamics simulations run for 100 ns, followed by binding free energy estimation using MM-GBSA. The data were analyzed using root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), and protein–ligand interactions to determine the stability of the protein–ligand complex. Based on the results, taraxerone (98) revealed optimum binding affinities with mTOR, followed by stigmasterol (110) and rutin (104), which compared favorably to the control compounds. Subsequently, bioactive compounds derived from Cichorium intybus may serve as lead molecules for developing potent and effective mTOR inhibitors to treat breast cancer. [ABSTRACT FROM AUTHOR]

Breast cancer is one of the most severe problems, and it is the primary cause of cancer-related death in females worldwide. The adverse effects and therapeutic resistance development are among the most potent clinical issues for potent medications for breast cancer treatment. The eugenol molecules have a significant affinity for breast cancer receptors. The aim of the study has been on the eugenol compounds, which has potent actions on Erα, PR, EGFR, CDK2, mTOR, ERBB2, c-Src, HSP90, and chemokines receptors inhibition. Initially, the drug-likeness property was examined to evaluate the anti-breast cancer activity by applying Lipinski's rule of five on 120 eugenol molecules. Further, structure-based virtual screening was performed via molecular docking, as protein-like interactions play a vital role in drug development. The 3D structure of the receptors has been acquired from the protein data bank and is docked with 87 3D PubChem and ZINC structures of eugenol compounds, and five FDA-approved anti-cancer drugs using AutoDock Vina. Then, the compounds were subjected to three replica molecular dynamic simulations run of 100 ns per system. The results were evaluated using root mean square deviation (RMSD), root mean square fluctuation (RMSF), and protein–ligand interactions to indicate protein–ligand complex stability. The results confirm that Eugenol cinnamaldehyde has the best docking score for breast cancer, followed by Aspirin eugenol ester and 4-Allyl-2-methoxyphenyl cinnamate. From the results obtained from in silico studies, we propose that the selected eugenols can be further investigated and evaluated for further lead optimization and drug development. [ABSTRACT FROM AUTHOR]