Insights into the structural requirements of farnesyltransferase inhibitors as potential anti-tumor agents based on 3D-QSAR CoMFA and CoMSIA models

Cytotoxicity Evaluation of Dimethoxy and Trimethoxy Indanonic Spiroisoxazolines Against Cancerous Liver Cells

Background:

3'-(3,4-dimethoxyphenyl)-4'-(4-(methylsulfonyl)phenyl)-4'H-spiro [indene-2,5'-isoxazol]-1(3H)-one and 4'-(4-(methylsulfonyl)phenyl)-3'-(3,4,5-trimethoxyphenyl)- 4'H-spiro[indene-2,5'-isoxazol]-1(3H)-one compounds containing indanonic spiroisoxazoline core are widely known for their antiproliferative activities and investigation of tubulin binding modes.

Objective:

To evaluate the cytotoxicity effect of Dimethoxy and Trimethoxy Indanonic Spiroisoxazolines against HepG2 cancerous liver cell line and to perform a comparison with other known anti-liver cancer drugs.

Methods:

The evaluation of cytotoxicity of dimethoxy and trimethoxy indanonic spiroisoxazoline compounds, Oxaliplatin, Doxorubicin, 5-fluorouracil and Cisplatin against HepG2 (hepatocellular liver carcinoma) cell line has been performed using MTT assay and analyzed by GraphPad PRISM software (version 8.0.2).

Results:

Potent cytotoxicity effects against HepG2 cell line, comparable to Cisplatin (IC50= 0.047±0.0045 µM), Oxaliplatin (IC50= 0.0051µM), Doxorubicin (IC50= 0.0014µM) and 5- fluorouracil (IC50= 0.0089 µM), were shown by both dimethoxy (IC50= 0.059±0.012 µM) and trimethoxy (IC50= 0.086±0.019 µM) indanonic spiroisoxazoline compounds.

Conclusion:

In vitro biological evaluations revealed that dimethoxy and trimethoxy indanonic spiroisoxazoline compounds are good candidates for the development of new anti-liver cancer agents.

Design, Synthesis and Biological Evaluation of Novel Piperazinone Derivatives as Cytotoxic Agents

Purpose: In this study, a series of piperazin-2-one derivatives were prepared through bioisosteric substitution of the imidazole ring of L-778,123 (imidazole-containing FTase inhibitor) and rearrangement of groups based on the tipifarnib structure. Final compounds were evaluated for their cytotoxic activities on cancer and normal cell lines by MTT assay. Methods: Methyl α-bromophenylacetic acid and 1-(3-chlorophenyl) piperazin-2-one were synthesized using previously described methods. Methyl 2-(4-chlorophenyl)-2-(4-(3- chlorophenyl)-3-oxopiperazin-1-yl) acetate was prepared by reaction between these two compounds in presence of potassium carbonate. Finally, methoxy group of ester was substituted by various amines such as guanidine, thiourea, urea and hydrazide. The synthesized compounds were tested for their cytotoxicity against colon cancer (HT-29) and lung cancer (A549) cell lines as well as MRC-5 (normal fetal lung fibroblasts) cells as a healthy cell line using MTT colorimetric assay method. Results: Replacement of imidazole moiety with guanidine, thiourea, and hydrazide could increase cytotoxicity toward all three cell lines. Some substituents, such as amine, urea, and hydroxylamine exhibited significant cytotoxicity (<500 µM) but lower than L-778,123 as standard compound. Hydroxyl and methoxy substituents did not show significant cytotoxicity. Imidazole substituent group revealed cytotoxicity similar to L-778,123 All compounds showed lower cytotoxic activity against normal cell lines compared with cancer cell lines. Conclusion: It seems the electron density of substituted groups and rearrangement of groups may significantly increase cytotoxic activity.

2D-QSAR study of some 2,5-diaminobenzophenone farnesyltransferase inhibitors by different chemometric methods

Quantitative structure activity relationship (QSAR) models can be used to predict the activity of new drug candidates in early stages of drug discovery. In the present study, the information of the ninety two 2,5-diaminobenzophenone-containing farnesyltranaferase inhibitors (FTIs) were taken from the literature. Subsequently, the structures of the molecules were optimized using Hyperchem software and molecular descriptors were obtained using Dragon software. The most suitable descriptors were selected using genetic algorithms-partial least squares and stepwise regression, where exhibited that the volume, shape and polarity of the FTIs are important for their activities. The two-dimensional QSAR models (2D-QSAR) were obtained using both linear methods (multiple linear regression) and non-linear methods (artificial neural networks and support vector machines). The proposed QSAR models were validated using internal validation method. The results showed that the proposed 2D-QSAR models were valid and they can be used for prediction of the activities of the 2,5-diaminobenzophenone-containing FTIs. In conclusion, the 2D-QSAR models (both linear and non-linear) showed good prediction capability and the non-linear models were exhibited more accuracy than the linear models.

Comparison of Cytotoxic Activity of L778123 as a Farnesyltranferase Inhibitor and Doxorubicin against A549 and HT-29 Cell Lines

PURPOSE

Farnesyltransferase (FTase) is a zinc-dependent enzyme that adds a farnesyl group to the Ras proteins. L778, 123 is a potent peptidomimetic imidazole-containing FTase inhibitor.

METHODS

L778123 was synthesized according to known methods and evaluated alone and in combination with doxorubicin against A549 (adenocarcinomic human alveolar basal epithelial cells) and HT29 (human colonic adenocarcinoma) cell lines by MTT assay.

RESULTS

L778123 showed weak cytotoxic activity with IC50 of 100 and 125 for A549 and HT-29 cell lines, respectively. The combination of doxorubicin and L778123 can decrease IC50 of doxorubicin in both cell lines significantly.

CONCLUSION

It can be concluded that L778, 123 can be a good agent for combination therapy.

Synthesis and Cytotoxicity Evaluation of Some Novel 1-(3-Chlorophenyl)piperazin-2-one Derivatives Bearing Imidazole Bioisosteres

A series of substituted 3-chlorophenylpiperazinone derivatives were synthesised using L-778123 (an imidazole-containing FTase inhibitor) as a model by bioisosteric replacement of the imidazole ring. The final compounds were evaluated against two human cancer cell lines including A549 (lung cancer) and HT-29 (colon cancer) by MTT assay. The results showed that substitution of imidazole ring with 1-amidinourea, semicarbazide, and thiobiuret led to improvement of cytotoxic activity against both cell lines.

Development of highly predictive 3D-QSAR CoMSIA models for anthraquinone and acridone derivatives as telomerase inhibitors targeting G-quadruplex DNA telomere

G-quadruplex structures of DNA represent a potentially useful target for anticancer drugs. Telomerase enzyme, involved in immortalization of cancer cells is inhibited by stabilization of G-quadruplex at the ends of chromosomes. Anthraquinone and acridone derivatives are promising G-quadruplex ligands as telomerase inhibitors. So far, optimization of these ligands remained hampered due to the lack of creditable quantitative structure-activity relationships. To understand the structural basis of anthraquinone and acridone derivatives, a predictive 3D-QSAR model has been developed for the first time for telomerase inhibitory activity of G4 ligands, employing comparative molecular similarity indices analysis (CoMSIA). Considering the proposition that the basic nitrogens in these compounds should exist in protonated form at physiological pH the protonated forms of the reported compounds were analyzed and investigated. The QSAR model from conformational template Conf1 exhibited best correlative and predictive properties. The actual predictive abilities of the QSAR model were thoroughly validated through an external validation test set of compounds. The statistics indicate a significantly high prediction power of the best model (r(2), 0.721), supporting the proposed molecular mechanism of DNA G-quadruplex ligands.

Self-organizing molecular field analysis on pregnane derivatives as human steroidal 5alpha-reductase inhibitors

Normal growth and development of human prostate is regulated by the androgens which balances cell proliferation and apoptosis. Testosterone (T) and dihydrotestosterone (DHT) are the two key androgens that stimulate most of the androgen action in prostate. Testosterone is converted to DHT by the membrane bound NADPH-dependent 5alpha-reductase enzyme. As a consequence of the important observation that progesterone and deoxycortisone inhibits the synthesis of DHT by competing with 4-en-3-one function of the testosterone for the 5alpha-reductase enzyme a number of pregnane derivatives were synthesized and have been reported as inhibitors of human 5alpha-reductase enzyme. Due to lack of information on the crystal structure of human 5alpha-reductase, ligand-based 3D-QSAR study has been performed on pregnane derivatives using self-organizing molecular field analysis (SOMFA) for rationalizing the molecular properties and human 5alpha-reductase inhibitory activities. The statistical results having good cross-validated r(cv)(2) (0.881), non-cross-validated r(2) (0.893) and F-test value (175.527), showed satisfied predictive ability r(pred)(2) (0.777). Analysis of SOMFA models through electrostatic and shape grids provide useful information for the design and optimization of steroidal structure as novel human 5alpha-reductase inhibitors.

Three-dimensional quantitative structure-farnesyltransferase inhibition analysis for some diaminobenzophenones

A 3D-QSAR investigation of 95 diaminobenzophenone yeast farnesyltransferase (FT) inhibitors selected from the work of Schlitzer et al. showed that steric, electrostatic, and hydrophobic properties play key roles in the bioactivity of the series. A CoMFA/CoMSIA combined model using the steric and electrostatic fields of CoMFA together with the hydrophobic field of CoMSIA showed significant improvement in prediction compared with the CoMFA steric and electrostatic fields model. The similarity of the 3D-QSAR field maps for yeast FT inhibition activity (from this work) and for antimalarial activity data (from previous work) and the correlation between those activities are discussed.

Imidazole-containing farnesyltransferase inhibitors: 3D quantitative structure-activity relationships and molecular docking

One of the most promising anticancer and recent antimalarial targets is the heterodimeric zinc-containing protein farnesyltransferase (FT). In this work, we studied a highly diverse series of 192 Abbott-initiated imidazole-containing compounds and their FT inhibitory activities using 3D-QSAR and docking, in order to gain understanding of the interaction of these inhibitors with FT to aid development of a rational strategy for further lead optimization. We report several highly significant and predictive CoMFA and CoMSIA models. The best model, composed of CoMFA steric and electrostatic fields combined with CoMSIA hydrophobic and H-bond acceptor fields, had r (2) = 0.878, q (2) = 0.630, and r (pred) (2) = 0.614. Docking studies on the statistical outliers revealed that some of them had a different binding mode in the FT active site based on steric bulk and available active site space, explaining why the predicted activities differed from the experimental activities.

Development of predictive 3D-QSAR CoMFA and CoMSIA models for beta-aminohydroxamic acid-derived tumor necrosis factor-alpha converting enzyme inhibitors

A three-dimensional quantitative structure-activity relationship study was performed on a series of beta-aminohydroxamic acid-derived tumor necrosis factor-alpha converting enzyme inhibitors employing comparative molecular field analysis and comparative molecular similarity indices analysis techniques to investigate the structural requirements for the inhibitors, and derive a predictive model that could be used for the design of novel tumor necrosis factor-alpha converting enzyme inhibitors. log P was used as an additional descriptor in the comparative molecular field analysis analysis to study the effects of lipophilic parameters on activity. Inclusion of log P did not improve the models significantly. The statistically significant model was established with 45 molecules, which were validated by a test set of 11 compounds. Ligand molecular superimposition on the template structure was performed by the atom-/shape-based root mean square fit and database alignment methods. Docked conformer based alignment (V) yielded the best predictive comparative molecular field analysis model = 0.673, = 0.860, F-value = 86.073, predictive r (2) = 0.642, with two components, standard error of prediction = 0.394 and standard error of estimates = 0.243 while the comparative molecular similarity indices analysis model yielded = 0.635, = 0.858, F-value = 84.451, predictive r (2) = 0.441 with three components, standard error of prediction = 0.393 and standard error of estimates = 0.245. The contour maps obtained from three-dimensional quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular field analysis models exhibited good external predictivity as compared with that of comparative molecular similarity indices analysis models. The model generated through comparative molecular field analysis was validated with the IK-682. The data generated from this study may guide our efforts in designing and predicting the tumor necrosis factor-alpha converting enzyme inhibitory activity of novel molecules.

3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.