QSAR studies and design of new analogs of vitamin E with enhanced antiproliferative activity on MCF-7 breast cancer cells

QSAR modeling for cytotoxicity of sulfur-containing Shikonin oxime derivatives targeting HCT-15, MGC-803, BEL-7402, and MCF-7 cell lines

Targeting cancer cells through drug-based treatment or combination therapy protocols involving chemical compounds can be challenging due to multiple factors, including their resistance to bioactive compounds and the potential of drugs to damage healthy cells. This study aims to investigate the relationship between the structure of novel sulfur-containing shikonin oxime compounds and the corresponding cytotoxicity against four cancer types, namely colon, gastric, liver, and breast cancers, through computational chemistry tools. This investigation is suggested to help build insights into how the structure of the compounds influences their activity and understand the mechanisms behind it and subsequently might be used in multi-cancer drug design process to propose novel optimized compounds that potentially exhibit the desired activity. The findings showed that the cytotoxic activity against the four cancer types was accurately predictable (R2 > 0.7, NRMSE <20%) by a combination of search and machine learning algorithms, based on the information on the structure of the compounds, including their lipophilicity, surface area, and volume. Overall, this study is supposed to play a crucial role in effective multi-cancer drug design in cancer research areas.

Tocotrienol isoforms: The molecular mechanisms underlying their effects in cancer therapy and their implementation in clinical trials

Tocotrienols are found in a variety of natural sources, like rice bran, annatto seeds and palm oil, and have been shown to have several health-promoting properties, particularly against chronic diseases such as cancer. The incidence of cancer is rapidly increasing around the world, not only a result of continued aging and population growth, but also due to the adoption of aspects of the Western lifestyle, such as high-fat diets and low-physical activity. The literature provides strong evidence that tocotrienols are able to inhibit the growth of various cancers, including breast, lung, ovarian, prostate, liver, brain, colon, myeloma and pancreatic cancers. These findings, along with the reported safety profile of tocotrienols in healthy human volunteers, encourage further research into these compounds' potential use in cancer prevention and treatment. The current review provided detailed information about the molecular mechanisms of action of different tocotrienol isoforms in various cancer models and evaluated the potential therapeutic effects of different vitamin E analogues on important cancer hallmarks, such as cellular proliferation, apoptosis, angiogenesis and metastasis. MEDLINE/PubMed and Scopus databases were used to identify recently published articles that investigated the anticancer effects of vitamin E derivatives in various types of cancer in vitro and in vivo along with clinical evidence of adjuvant chemopreventive benefits. Following an overview of pre-clinical studies, we describe several completed and ongoing clinical trials that are paving the way for the successful implementation of tocotrienols in cancer chemotherapy.

3D-QSAR modeling and molecular docking studies on a series of 2, 4, 5-trisubstituted imidazole derivatives as CK2 inhibitors

Protein case in kinase II alpha subunit (CK2) plays an imperative function in treating cancer disease. Herein, we have performed a three-dimensional quantitative structure activity relationship (3D-QSAR), and molecular docking analysis on a novel series of 2, 4, 5-trisubstituted imidazole derivatives in order to design potent kinase II alpha subunit (CK2) inhibitors. The 3D-QSAR methods such as comparative molecular similarity indexes analysis (COMSIA), and the comparative molecular field analysis (COMFA) were investigate using twenty-four molecules of 2, 4, 5-trisubstituted imidazole derivatives as anticancer agent. The best COMFA and COMSIA models exhibit excellent Q2 values of 0.66 and 0.75 and R2 values of 0.98 and 0.99 respectively. To check the validity of the selected COMFA and COMSIA models, a variety of validation tests were utilized: Internal validation analyses, and externally validation beside Y-randomization according to the principles of the Organization for Economic Co-operation and Development (OECD), and the Golbraikh and Tropsha's criteria for the validation of 3D-QSAR models. The proposed models for COMFA and COMSIA analysis have been successful. The developed models, indicating that they were reliable for activity prediction. Based on the preceding results, we designed several new potent molecules. Such outcome can proffer helpful theoretical references for future experimental studies.Communicated by Ramaswamy H. Sarma.

A simple and robust model to predict the inhibitory activity of α-glucosidase inhibitors through combined QSAR modeling and molecular docking techniques

Quantitative structure-activity relationships (QSAR) and molecular docking studies have been performed on a series of 35 α-glucosidase inhibitory derivatives. The QSAR models have been developed by genetic algorithm-multiple linear regression (GA-MLR) and least squares-support vector machine (LS-SVM) methods to correlate the conformational descriptors to the inhibitory activity. The obtained models with 5 descriptors were validated and illustrated to be statistically significant. They had desirable prediction based on squared correlation coefficient (R²), cross-validated correlation coefficient (Q²), root-mean-squares error (RMSE) and Fisher (F) parameters (R² = 0.951, Q² = 0.931, RMSE = 0.121, and F = 114.629 for GA-MLR model, and R² = 0.989, Q² = 0.987, RMSE = 0.056 and F = 543.754 for LS-SVM model). The crucial descriptor named DELS was explored to have the highest correlation with the inhibitory activity and thus has been chosen to build a simple model. The QSAR model developed with this mono-descriptor showed appropriate results of the predicted model using LS-SVM method (R² = 0.888, Q² = 0.872, RMSE = 0.185 and F = 221.459). Also, molecular docking which focuses on the interaction between ligands and α-glucosidase in the protein active site considered different binding positions to find the best binding mode. It helped the QSAR study to propose more comprehensive details of the compounds structures and was used to design more active compounds. The most active designed compound had a high inhibitory activity of 9.22 that can be proposed for the treatment of diabetes type 2.

Effect of Breast Cancer Treatment on Dietary Vitamin Intake Levels

Breast cancer is the most common tumor among women, representing the second cause of cancer deaths in women. Treatment with chemotherapy negatively interferes with nutritional status. The intake of vitamins before, during and after treatment in a pilot cohort of women with non-invasive breast cancer (type I, II) treated at the Valencian Institute of Oncology (IVO) is evaluated. A 3-day anthropometric and nutritional assessment was performed using the DIAL program. Nutritional intake is compared with the values of Estimated Average Requirements (EAR) and Dietary Reference Intake (DRI) provided by the United States Department of Agriculture (USDA) and the European Food Safety Authority (EFSA). There is an overall decrease in vitamin intake during treatment which worsens at the end of said treatment. The decrease is significant in the case of vitamins B₂ (p = 0.006), B₃ (p = 0.042), B₅ (p = 0.001), and B₈ (p = 0.021). The relative risk during and after treatment increases with respect to the reference timeframe, before treatment. Deficit risks are statistically significant in the case of vitamins B₅ (p = 0.001), B₈ (p = 0.001) and B₁₂ (p = 0.001). Decreased vitamin intake during treatment suggests a negative change in the patients’ dietary behaviors during this time. Nutritional intervention and support may be beneficial to optimize overall dietary intake and maintain compliance with EAR and DRI for patients during a time in which adequate nutrition is important.

Quantitative structure-activity relationships of xanthen-3-one and xanthen-1,8-dione derivatives and design of new compounds with enhanced antiproliferative activity on HeLa cervical cancer cells

Xanthene derivatives have become a group of molecules of great importance in discovering of new anticancer drugs. Recent studies of our group performed on xanthen-3-one and xanthen-1,8-dione derivatives have shown their antiproliferative activity on HeLa cervical cell lines. Obtained IC₅₀ values together with calculated molecular descriptors were subjected to Quantitative Structure-Activity Relationship (QSAR) study in order to identify the most relevant molecular features responsible for the observed antiproliferative activity of compounds. Partial least square statistical method and the same training and test set were used to obtain statistical parameters for internal and external validation in 2D- and 3D-QSAR study. The obtained QSAR models have shown next results: 2D-QSAR: R² = 0.741, Q² = 0.792, R²_pred = 0.875 and 3D-QSAR: R² = 0.951, Q² = 0.830, R²_pred = 0.769. Based on the performed QSAR analysis and calculated ADMET properties, novel xanthene derivatives with enhanced antiproliferative activity were designed. Communicated by Ramaswamy H. Sarma.

In silico studies of novel pyrazole-furan and pyrazole-pyrrole carboxamide as fungicides against Sclerotinia sclerotiorum

Background

Pyrazole-furan and pyrazole-pyrrole moiety are among the molecular structures that were found to have an extensive range of applications in the field of medicine and agrochemical due to their wide spectrum of biological activities. These include antimicrobial activity, anti-glaucoma activity, ocular hypertension activity, and antifungal activity.

Results

An in silico study was carried out on 37 compounds of pyrazole-furan and pyrazole-pyrrole carboxamide derivatives against Sclerotinia sclerotiorum. Using Spartan 14 software, optimization of the compounds was performed at the DFT/B3LYP/6-31G* quantum mechanical method. PaDEL descriptor software was used to calculate the molecular descriptors, and a Generic Function Approximation (GFA) was employed to generate the model. Out of four models generated, model 1 was found to be the optimal and has the following statistical parameters; R2 = 0.83485, R2adj = 0.793563, cross-validated R2 = 0.74037, and external R2 = 0.58479. Molecular docking study was carried out between the antifungal compounds, and the binding site of S. sclerotiorum (PDB CODE 2X2S) in which compound 7 was identified to have the highest binding energy of − 7.5kcal/mol. This compound “7” has a strong affinity with the macromolecular target point of the S. sclerotiorum (2x2s), producing H-bond and as well as the hydrophobic interaction at target point of the amino acid residue. Considering compound 7 as our scaffold, four (4) more potent compounds (7a, 7b, 7c, and 7d) were designed using optimization method of structure-based designed which have the following docking score, − 7.7, − 7.8, − 7.7, and − 7.7kcal/mol.

Conclusion

Statistical analyses including variance inflation factor (VIF), mean effect (ME), and applicability domain were conducted on the model. Considering an interpretation of the descriptors given in the discussion, the QSAR model provided an idea of ligand-based design while the molecular docking gave an insight on structure-based design of the new compounds with better activity against S. sclerotiorum in which four (4) compounds 7a, 7b, 7c, and 7d were designed and discovered to be of high quality and have greater binding affinity compared to the one obtained from the literature (compound 7).

In silico Methods for Design of Kinase Inhibitors as Anticancer Drugs

Rational drug design implies usage of molecular modeling techniques such as pharmacophore modeling, molecular dynamics, virtual screening, and molecular docking to explain the activity of biomolecules, define molecular determinants for interaction with the drug target, and design more efficient drug candidates. Kinases play an essential role in cell function and therefore are extensively studied targets in drug design and discovery. Kinase inhibitors are clinically very important and widely used antineoplastic drugs. In this review, computational methods used in rational drug design of kinase inhibitors are discussed and compared, considering some representative case studies.

Rational Drug Design of Antineoplastic Agents Using 3D-QSAR, Cheminformatic, and Virtual Screening Approaches

Background:

Computer-Aided Drug Design has strongly accelerated the development of novel antineoplastic agents by helping in the hit identification, optimization, and evaluation.

Results:

Computational approaches such as cheminformatic search, virtual screening, pharmacophore modeling, molecular docking and dynamics have been developed and applied to explain the activity of bioactive molecules, design novel agents, increase the success rate of drug research, and decrease the total costs of drug discovery. Similarity, searches and virtual screening are used to identify molecules with an increased probability to interact with drug targets of interest, while the other computational approaches are applied for the design and evaluation of molecules with enhanced activity and improved safety profile.

Conclusion:

In this review are described the main in silico techniques used in rational drug design of antineoplastic agents and presented optimal combinations of computational methods for design of more efficient antineoplastic drugs.

Molecular Mechanisms of Action of Tocotrienols in Cancer: Recent Trends and Advancements

Tocotrienols, found in several natural sources such as rice bran, annatto seeds, and palm oil have been reported to exert various beneficial health promoting properties especially against chronic diseases, including cancer. The incidence of cancer is rapidly increasing around the world not only because of continual aging and growth in global population, but also due to the adaptation of Western lifestyle behaviours, including intake of high fat diets and low physical activity. Tocotrienols can suppress the growth of different malignancies, including those of breast, lung, ovary, prostate, liver, brain, colon, myeloma, and pancreas. These findings, together with the reported safety profile of tocotrienols in healthy human volunteers, encourage further studies on the potential application of these compounds in cancer prevention and treatment. In the current article, detailed information about the potential molecular mechanisms of actions of tocotrienols in different cancer models has been presented and the possible effects of these vitamin E analogues on various important cancer hallmarks, i.e., cellular proliferation, apoptosis, angiogenesis, metastasis, and inflammation have been briefly analyzed.

Identification of potential tubulin polymerization inhibitors by 3D-QSAR, molecular docking and molecular dynamics

View of the correlation between experimental and predicted pIC₅₀c values, and the compound 22c docked into the binding site of 3UT5.