Letters in Drug Design & Discovery - Volume 18, Issue 11, 2021

Background: The p21-activated kinases 4 (PAK4) refer to a promising target for cancer treatment. Currently, a wide range of PAK4 inhibitors has been reported. Objective: The objective of this study is to study the structural requirements of quinoline derivatives as PAK4 inhibitors and to design novel PAK4 inhibitors. Methods: In the present study, a set of quinazoline PAK4 inhibitors underwent CoMFA, CoMSIA, molecular docking, as well as molecular dynamics simulations. Results: The built CoMFA (q²=0.595, r²=0.986, r² pred =0.689) and CoMSIA (q²=0.762, r²=0.984, pred=0.822) models exhibited high robustness and prominent predicting ability. As revealed from the results of molecular docking and molecular dynamics simulations, hydrogen bond and hydrophobic interactions primarily impact the affinity of PAK4 inhibitors, and Leu398 acts as an amino acid that leads to significant stabilization of the mentioned inhibitors. Moreover, the present study developed five novel molecules exhibiting high biological activity predicted and satisfactory ADME properties. Conclusion: The structural basis of PAK4 with respect to the activities of its inhibitors was revealed, which may be conducive to designing novel PAK4 inhibitors.

Background: Inhibition activity of the epigenetic readers, such as bromodomain and extra- C terminal domain protein family, is of high significance in many therapeutic applications due to their ability to regulate gene expression as well as the chromatin structure by binding to acetylysine residues. Objectives: In order to effectively and quickly determine the inhibition activity of these compounds for the desired therapeutic application, this work presents a grid search-based extreme learning machine computational intelligence method through which the inhibition activity of forty different compounds of substituted 4-phenylisoquinolinones was determined. Methods: The prediction and generalization capacity of the developed model were assessed using four different error metrics, which include root mean square error, mean absolute error, mean absolute percentage deviation, and correlation coefficient between the measured values and predicted activities. The lead compound (37), together with a kinase inhibitor, LY294002, and a bromodomain and extra-C terminal inhibitor, CPI-0610, was docked with a bromodomain-containing protein 4 bromodomain 1, 6P05. Results: The developed model performed better than the existing model with percentage improvement of 44.48%, 35.08%, 20.44%, and 1.23% on the basis of mean absolute percentage deviation, mean absolute error, root mean square error, and correlation coefficient, respectively. The lead compound has a better binding score than LY294002 and CPI-0610. Conclusion: Implementation of the developed model would help in searching for anti-inflammatory as well as anticancer agents for effective therapeutic application.

Background: Cancer is a global health burden and the leading cause of death across the world after cardiovascular disease. Objective: The objective of this work was the design, synthesis, and pharmacological evaluation of 2-phenylquinolin-4-amine derivatives as apoptosis inducers and anticancer agents. Methods: In this study, we performed ligand-based pharmacophore modeling as a promising design strategy for the design of substituted quinoline derivatives as apoptosis inducers and anticancer agents. The designed compounds were synthesized as 2-phenylquinolin-4-amine derivatives and characterized by FT-IR, ¹H-NMR, ¹³C-NMR, and Mass spectroscopy. Synthesized compounds were screened for apoptosis-inducing activity using caspase-3 activation and annexine-FITC assays, and also screened against cancer cell line (HT-29) in an antiproliferative assay. Results: Synthesized compounds 7a, and 7d demonstrated EC50 values of 6.06 and 6.69 μM in caspase-3 activation assay, respectively, and also showed late stage induction of apoptosis in annexine assay. Synthesized compounds 7a, 7d and 7i, also exhibited good antiproliferative activity with IC50 values of 8.12, 9.19, and 11.34 μM, respectively, which revealed that these are promising apoptosis inducers for the further development of new anticancer agents.

Background: Human papillomavirus (HPV) infection is the major risk factor for cervical cancer. Current prophylactic HPV vaccines provide immunity against most genital and carcinogenic HPV types. However, these vaccines failed to produce immune responses against already established HPV infections. Methods: To design a therapeutic vaccine candidate, we utilized immunoinformatics tools to design a potential multiepitope fusion construct based on L1 and E7 genes from different high- and low-risk HPV types. After determination of CD4+ and CD8+ T cell epitopes, the allergenicity, toxicity, immunogenicity, conservancy, and population coverage were analyzed for epitopes selection. Then, hemolytic probability of the selected epitopes, and molecular docking between major histocompatibility complex (MHC) and the chosen epitopes were performed by different web servers. Next, a multiepitope peptide construct consisting of 12 epitopes linked by AAY proteasomal sequence was designed. After that, physicochemical properties, solubility, secondary and tertiary structures of this construct were evaluated by bioinformatics tools. Finally, after amino acid reverse translation of the multiepitope peptide construct, expression of the L1-E7 DNA construct (pEGFP-L1-E7) was investigated in HEK-293T cells using fluorescent microscopy, flow cytometry, and western blotting. Results: Considering various parameters, the immunodominant peptides such as L1(MHC-I)- DLDQFPLGRKFLLQ, L1(MHC-II)-NQLFVTVVDTTRSTN, E7-HPV16(MHC-I)-AEPDRAHYNI VTF, E7-HPV18(MHC-I)-HGPKATVQDIVLHL, E7-HPV31(MHC-I)-KPDTSNYNIVTF, E7-HPV33 (MHC-I)-RPDGQAQPATADYYI, E7-HPV45(MHC-I)- RTLQQLFLSFV, E7-HPV16(MHC -II)-TLH EYMLDLQPETTD, E7-HPV18(MHC-II)-LRAFQQLFLNTLSFV, E7-HPV31(MHC-II)-PTLQDYVL DLQPEAT, E7-HPV33(MHC-II)-LKEYVLDLYPEPTDL and E7-HPV45(MHC-II)-LQQLFLSTLSF VCPW were determined to design the vaccine construct. The results indicated efficient expression of the L1-E7 DNA construct (74 ± 2.19%) in vitro. Moreover, the polyepitope peptide generated in the cells was detected as a clear band of ~ 50 kDa in western blotting. Conclusion: Regarding the favorable transfection efficiency of the designed L1-E7 multi-epitope construct, in vivo validation study on its therapeutic potential is underway.

Background: Diabetes mellitus is a chronic metabolic disease that constitutes a risk factor for patients infected by COVID-19. Aldose reductase (ALR2) is an enzyme that catalyzes the formation of sorbitol in the metabolism of glucose via polyols in diabetic patients and leads to a group of diabetic complications: cataracts, retinopathies, neuropathies, and nephropathies. Introduction: Inhibitors of this enzyme are therapeutic targets for the prophylaxis and treatment of these conditions. The aim of this work was to identify flavonoids isolated from medicinal plants, fruits, and vegetables as potential inhibitors of ALR2. Methods: In this study, using the MATLAB numerical computation system and the molecular descriptors implemented in the DRAGON software, a regression tree was developed, with an R² of 0.953 and adequate parameters for its fit. Results: The model was validated to take into account internal and external validation procedures. Besides, the applicability domain was determined to guarantee the reliability of the predictions. Due to its good predictive power (R² ext = 0.949), the model was used to predict the inhibition of ALR2 by flavonoids reported in dietary sources. The most promising flavonoids are Myricetin and Tricin (pIC50predicted = 7.296), which are within the application domain and meet drug-like properties for oral administration. Conclusion: Finally, we can conclude that the proposed tools are useful for the rapid and economical identification of flavonoid-based potential drug candidates against ALR2 in diabetic complications.