Steroidal 5α-Reductase Inhibitors: A Comparative 3D-QSAR Study Review

Iridium Acylnitrenoid-Initiated Biomimetic Cascade Cyclizations: Stereodefined Access to Polycyclic δ-Lactams

Ring-fused azacyclic compounds are important building units in the synthesis of biorelevant natural products, pharmaceutical agents, and molecular materials. Herein, we present a new approach to these condensed azacycles by a biomimetic cascade cyclization of arylalkenyl dioxazolones. This cascade reaction was found to proceed with excellent stereoselectivity and a high functional group tolerance. The substrate scope of arylalkenyl dioxazolones turned out to be highly flexible and extendable to additional terminating subunits, such as heteroaryl and alkynyl moieties. This biomimetic cyclization was elucidated to be initiated by an intramolecular transfer of the in situ generated electrophilic Ir-acylnitrenoid to the tethered olefinic double bond, leading to a key N-acylaziridine intermediate, which is in turn reacted with pendant (hetero)arenes or alkynes in a highly regio- and stereoselective manner to produce ring-fused azacyclic compounds.

Studies on the bioactivities and molecular mechanism of antioxidant peptides by 3D-QSAR, in vitro evaluation and molecular dynamic simulations

Two novel effective antioxidative tripeptides GWY and QWY were designed based on 3D-QSAR models. Their activities were confirmed by an improved TEAC assay. The experimental results showed that GWY and QWY possessed good antioxidant activity, equaling 3.32 mM TE and 2.97 mM TE respectively. This indicated that 3D-QSAR models possessed significant predictive capacity for drug design. In addition, molecular docking and molecular dynamics simulation were applied to reveal the potential molecular mechanism of antioxidant peptides. The result showed that GWY and QWY could enhance the stability of Keap1 by interacting with the key residues Arg415, Arg483, Arg380 and Ser555 in the active sites. Interestingly, the key residues were exactly the binding site of Nrf2 in the active pocket of Keap1. Thus, GWY and QWY could compete with Nrf2 for binding to Keap1. This demonstrated that the new tripeptides might have the ability to activate the signaling pathway Keap1-Nrf2-ARE and improve the antioxidant defense system of the body as well.

Novel and Predictive QSAR Model for Steroidal and Nonsteroidal 5α- Reductase Type II Inhibitors

AIMS AND OBJECTIVE

In this study, a novel quantitative structure activity relationship (QSAR) model has been developed for inhibitors of human 5-alpha reductase type II, which are used to treat benign prostate hypertrophy (BPH).

METHODS

The dataset consisted of 113 compounds-mainly nonsteroidal-with known inhibitory concentration. Then 3D structures of compounds were optimized and molecular structure descriptors were calculated. The stepwise multiple linear regression was used to select descriptors encoding the inhibitory activity of the compounds. Multiple linear regression (MLR) was used to build up the linear QSAR model.

RESULTS

The results obtained revealed that the descriptors which best describe the activity were atom type electropological state, carbon type, radial distribution function (RDF), barysz matrix and molecular linear free energy relation. The suggested model could achieve satisfied square correlation coefficient of R² = 0.72, higher than of many previous studies, indicating its superiority. Rigid validation criteria were met using external data with Q² ˃ 0.5 and R² = 0.75, reflecting the predictive power of the model.

CONCLUSION

The QSAR model was applied for screening botanical components of herbal preparations used to treat BPH, and could predict the activity of some, among others, making reasonable attribution to the proposed effect of these preparations. Gamma tocopherol was found to be an active inhibitor, in consistence with many previous studies, anticipating the power of this model in the prediction of new candidate molecules and suggesting further investigations.

A Comprehension into Target Binding and Spatial Fingerprints of Noscapinoid Analogues as Inhibitors of Tubulin

BACKGROUND

Owing to its potential to interfere in microtubule dynamics in the mitotic phase of cell cycle and selectively induce apoptosis in cancer cells without affecting normal cells, noscapine and its synthetic analogues have been investigated by other research groups in different cell lines for their capability to be used as anti-cancer agents.

OBJECTIVE

The present study is focused on the investigation of the mode of binding of noscapinoids with tubulin, prediction of target binding affinities and mapping of their spatial fingerprints (shape and electrostatic).

METHODS

Molecular docking assisted alignment based 3D-QSAR was used on a dataset (43 molecules) having an inhibitory activity (IC₅₀ = 1.2-250 μM) against human lymphoblast (CEM) cell line.

RESULTS AND CONCLUSION

Key amino acid residues of target tubulin were mapped for the binding of most potent noscapine analogue (Compound 11) and were compared with noscapine. Spatial fingerprints of noscapinoids for favorable tubulin inhibitory activity were generated and are proposed herewith for further pharmacophoric amendments of noscapine analogues to design and develop novel potent noscapine based anti-cancer agents that may enter into drug development pipeline.

Design and development of novel focal adhesion kinase (FAK) inhibitors using Monte Carlo method with index of ideality of correlation to validate QSAR

Quantitative structure-activity relationship (QSAR) modelling of 55 focal adhesion kinase (FAK) (EC 2.7.10.2) inhibitors of triazinic nature was performed using the Monte Carlo method. The QSAR models were designed by CORAL software, and optimal descriptors were calculated with the simplified molecular input line entry system (SMILES). Four splits were made from the triazinic derivative data by random division into training, invisible training, calibration and validation sets. The QSAR results from these four random splits were robust, very simple, predictive and reliable. The best statistical parameters of the validation set (r² = 0.8398 and Q² = 0.7722) for the QSAR equation for split 3 with IIC = 0.9127 were obtained. The predictive potential of QSAR models of FAK inhibitors was explored by applying the index of ideality of correlation (IIC), which is a new criterion for the prediction of the potential for quantitative structure-property activity relationships (QSPRs/QSARs). The present method follows OECD principles.

Construction of a Quantitative Structure Activity Relationship (QSAR) Model to Predict the Absorption of Cephalosporins in Zebrafish for Toxicity Study

Cephalosporins are beta-lactam antibiotics that are widely used in China. Five generations of cephalosporins have been introduced in clinical practice to date; moreover, some new candidates are also undergoing clinical evaluations. To improve the success rates of new drug development, we need to have a comprehensive understanding about the relationship between the structure of cephalosporins and the toxicity that it induces at an early stage. In the cephalosporins toxicity study using zebrafish, the drug absorption is a key point. In this study, we determined the absorption of cephalosporins in zebrafish during toxicity test. The internal concentrations of 19 cephalosporins in zebrafish were determined using a developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. Furthermore, a quantitative structure-activity relationship (QSAR) model was established by multilinear regression; moreover, it was used to predict the absorption of cephalosporins in zebrafish. During leave-one-out cross-validation, a satisfactory performance was obtained with a predictive ability (q ²) of 0.839. The prediction ability of the model was further confirmed when the predictive ability (q ²) was 0.859 in external prediction. The best QSAR model, which was based on five molecular descriptors, exhibited a promising predictive performance and robustness. In experiments involving drug toxicity, the developed QSAR model was used to estimate internal concentrations of cephalosporins. Thus, the toxicity results were correlated with the internal concentration of the drug within the larvae. The developed model served as a new powerful tool in zebrafish toxicity tests.

2D-QSAR and 3D-QSAR simulations for the reaction rate constants of organic compounds in ozone-hydrogen peroxide oxidation

Synergistic oxidation of ozone (O₃) and hydrogen peroxide (H₂O₂) is an effective water treatment for the elimination of organic pollutants. In this study, 23 organic compounds were conducted to study the reaction rate constants during O₃-H₂O₂ oxidation. Then, two- and three-dimensional quantitative structure-activity relationship (QSAR) models were established to investigate the factors influencing the reaction rate constants by using multiple linear regression method and comparative molecular similarity index analysis (CoMSIA) method, respectively. Both of the two models showed good performance on predicting the reaction rate constants, the associated statistical indices of 2D-QSAR and 3D-QSAR models were R² = 0.898 and 0.952, q² = 0.841 and 0.951, Q_ext² = 0.968 and 0.970, respectively. But varied in the influence factors, as for the 2D-QSAR model, three quantum chemical parameters, included dipole moment, the largest change of charge in each atom during the nucleophilic attack, the maximum positive partial charge on a hydrogen atom linked with a carbon atom affected the reaction rate. While in the 3D-QSAR model, the electrostatic field played the most important role in evaluating the reaction rate with the contribution of 35.8%, followed by hydrogen bond acceptor and hydrophobic fields with the contribution of 24.9% and 23.2%, respectively. These two models provided predictive tools to study the influencing factors for the degradation of organics and might potentially be applied for estimating the removal properties of unknown organics in O₃-H₂O₂ oxidation process.

Homology Modeling of 5-alpha-Reductase 2 Using Available Experimental Data

5-Alpha-reductase 2 is an interesting pharmaceutical target for the treatment of several diseases, including prostate cancer, benign prostatic hyperplasia, male pattern baldness, acne, and hirsutism. One of the main approaches in computer aided drug design is structure-based drug discovery. However, the experimental 3D structure of 5-alpha-reductase 2 is not available at present. Therefore, a homology modeling method and molecular dynamics simulation were used to develop a reliable model of 5-alpha-reductase 2 for inhibitor pose prediction and virtual screening. Despite the low sequence identity between the target and template sequences, a useful 3D model of 5-alpha-reductase 2 was generated by the inclusion of experimental data.

Design, synthesis and biological evaluation of novel androst-3,5-diene-3-carboxylic acid derivatives as inhibitors of 5α-reductase type 1 and 2

5α-Reductase is a key enzyme responsible for dihydrotestosterone biosynthesis and has been recognized as an important target for discovering new drugs against benign prostatic hyperplasia (BPH). In this study, a series of novel steroidal androst-3,5-diene-3-carboxylic acids have been designed and synthesized. Biological evaluations were performed on their 5α-reductase inhibitory activities by both in vitro enzyme inhibition assay and in vivo by prostate weighing method. Results showed that most of them displayed excellent 5α-reductase inhibitory potency. Detailed evaluation indicated that most of the compounds displayed slightly higher inhibition potency towards type 2 isozyme. Among all the compounds, 16a was found to be the most potential inhibitor with the IC₅₀ of 0.25μM and 0.13μM against type 1 and 2 isozymes respectively. In vivo 5a-reductase inhibitory evaluation of 16a also showed a more significant reduction effect (p<0.001) in rat prostate weight than epristeride. Furthermore, the results of in silico ADME study indicated that compound 16a exhibited good pharmacokinetic properties. Thus, 16a could serve as promising lead candidates for further study.

Antiproliferative, Cytotoxic, and Apoptotic Activity of Steroidal Oximes in Cervicouterine Cell Lines

Steroidal sapogenins have shown antiproliferative effects against several tumor cell lines; and their effects on human cancer cells are currently under study. Changes in the functionality on the steroidal structure make it possible to modify the biological activity of compounds. Herein, we report the synthesis and in vitro antitumor activity of two steroidal oxime compounds on cervical cancer cells. These derivatives were synthesized from the steroidal sapogenin diosgenin in good yields. The in vitro assays show that the steroidal oximes show significant antiproliferative activity compared to the one observed for diosgenin. Cell proliferation, cell death, and the cytotoxic effects were determined in both cervical cancer cells and human lymphocytes. The cancer cells showed apoptotic morphology and an increased presence of active caspase-3, providing the notion of a death pathway in the cell. Significantly, the steroidal oximes did not exert a cytotoxic effect on lymphocytes.

Identification of the Structural Features of Guanine Derivatives as MGMT Inhibitors Using 3D-QSAR Modeling Combined with Molecular Docking

DNA repair enzyme O⁶-methylguanine-DNA methyltransferase (MGMT), which plays an important role in inducing drug resistance against alkylating agents that modify the O⁶ position of guanine in DNA, is an attractive target for anti-tumor chemotherapy. A series of MGMT inhibitors have been synthesized over the past decades to improve the chemotherapeutic effects of O⁶-alkylating agents. In the present study, we performed a three-dimensional quantitative structure activity relationship (3D-QSAR) study on 97 guanine derivatives as MGMT inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Three different alignment methods (ligand-based, DFT optimization-based and docking-based alignment) were employed to develop reliable 3D-QSAR models. Statistical parameters derived from the models using the above three alignment methods showed that the ligand-based CoMFA (Q_cv² = 0.672 and R_ncv² = 0.997) and CoMSIA (Q_cv² = 0.703 and R_ncv² = 0.946) models were better than the other two alignment methods-based CoMFA and CoMSIA models. The two ligand-based models were further confirmed by an external test-set validation and a Y-randomization examination. The ligand-based CoMFA model (Q_ext² = 0.691, R_pred² = 0.738 and slope k = 0.91) was observed with acceptable external test-set validation values rather than the CoMSIA model (Q_ext² = 0.307, R_pred² = 0.4 and slope k = 0.719). Docking studies were carried out to predict the binding modes of the inhibitors with MGMT. The results indicated that the obtained binding interactions were consistent with the 3D contour maps. Overall, the combined results of the 3D-QSAR and the docking obtained in this study provide an insight into the understanding of the interactions between guanine derivatives and MGMT protein, which will assist in designing novel MGMT inhibitors with desired activity.

Molecular modeling studies, synthesis and biological evaluation of dabigatran analogues as thrombin inhibitors

In this work, 48 thrombin inhibitors based on the structural scaffold of dabigatran were analyzed using a combination of molecular modeling techniques. We generated three-dimensional quantitative structure-activity relationship (3D-QSAR) models based on three alignments for both comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) to highlight the structural requirements for thrombin protein inhibition. In addition to the 3D-QSAR study, Topomer CoMFA model also was established with a higher leave-one-out cross-validation q(2) and a non-cross-validation r(2), which suggest that the three models have good predictive ability. The results indicated that the steric, hydrophobic and electrostatic fields play key roles in QSAR model. Furthermore, we employed molecular docking and re-docking simulation explored the binding relationship of the ligand and the receptor protein in detail. Molecular docking simulations identified several key interactions that were also indicated through 3D-QSAR analysis. On the basis of the obtained results, two compounds were designed and predicted by three models, the biological evaluation in vitro (IC50) demonstrated that these molecular models were effective for the development of novel potent thrombin inhibitors.