In silico approaches to identify novel myeloid cell leukemia-1 (Mcl-1) inhibitors for treatment of cancer

Myeloid cell leukemia-1 (Mcl-1) has been a validated and attractive target for cancer therapy. Over-expression of Mcl-1 in many cancers allows cancer cells to evade apoptosis and contributes to the resistance to current chemotherapeutics. Here, we identified new Mcl-1 inhibitors using a multi-step virtual screening approach. First, based on two different ligand-receptor complexes, 20 pharmacophore models were established by simultaneously using ‘Receptor-Ligand Pharmacophore Generation’ method and manual build feature method, and then carefully validated by a test database. Then, pharmacophore-based virtual screening (PB-VS) could be performed by using the 20 pharmacophore models. In addition, docking study was used to predict the possible binding poses of compounds, and the docking parameters were optimized before performing docking-based virtual screening (DB-VS). Moreover, a 3D QSAR model was established by applying the 55 aligned Mcl-1 inhibitors. The 55 inhibitors sharing the same scaffold were docked into the Mcl-1 active site before alignment, then the inhibitors with possible binding conformations were aligned. For the training set, the 3D QSAR model gave a correlation coefficient r² of 0.996; for the test set, the correlation coefficient r² was 0.812. Therefore, the developed 3D QSAR model was a good model, which could be applied for carrying out 3D QSAR-based virtual screening (QSARD-VS). After the above three virtual screening methods orderly filtering, 23 potential inhibitors with novel scaffolds were identified. Furthermore, we have discussed in detail the mapping results of two potent compounds onto pharmacophore models, 3D QSAR model, and the interactions between the compounds and active site residues.     

3D QSAR,pharmacophore and molecular docking studies of known inhibitors and designing of novel inhibitors for M18 aspartyl aminopeptidase of <Emphasis Type="Italic">Plasmodium falciparum</Emphasis>

Background

The Plasmodium falciparum M18 Aspartyl Aminopeptidase (PfM18AAP) is only aspartyl aminopeptidase which is found in the genome of P. falciparum and is essential for its survival. The PfM18AAP enzyme performs various functions in the parasite and the erythrocytic host such as hemoglobin digestion, erythrocyte invasion, parasite growth and parasite escape from the host cell. It is a valid target to develop antimalarial drugs. In the present work, we employed 3D QSAR modeling, pharmacophore modeling, and molecular docking to identify novel potent inhibitors that bind with M18AAP of P. falciparum.

Results

The PLSR QSAR model showed highest value for correlation coefficient r² (88 %) and predictive correlation coefficient (pred_r2) =0.6101 for external test set among all QSAR models. The pharmacophore modeling identified DHRR (one hydrogen donor, one hydrophobic group, and two aromatic rings) as an essential feature of PfM18AAP inhibitors. The combined approach of 3D QSAR, pharmacophore, and structure-based molecular docking yielded 10 novel PfM18AAP inhibitors from ChEMBL antimalarial library, 2 novel inhibitors from each derivative of quinine, chloroquine, 8-aminoquinoline and 10 novel inhibitors from WHO antimalarial drugs. Additionally, high throughput virtual screening identified top 10 compounds as antimalarial leads showing G-scores -12.50 to -10.45 (in kcal/mol), compared with control compounds(G-scores -7.80 to -4.70) which are known antimalarial M18AAP inhibitors (AID743024). This result indicates these novel compounds have the best binding affinity for PfM18AAP.

Conclusion

The 3D QSAR models of PfM18AAP inhibitors provided useful information about the structural characteristics of inhibitors which are contributors of the inhibitory potency. Interestingly, In this studies, we extrapolate that the derivatives of quinine, chloroquine, and 8-aminoquinoline, for which there is no specific target has been identified till date, might show the antimalarial effect by interacting with PfM18AAP.

     

Quantitative structure–activity relationship analysis using deep learning based on a novel molecular image input technique

Quantitative structure–activity relationship (QSAR) analysis uses structural, quantum chemical, and physicochemical features calculated from molecular geometry as explanatory variables predicting physiological activity. Recently, deep learning based on advanced artificial neural networks has demonstrated excellent performance in the discipline of QSAR research. While it has properties of feature representation learning that directly calculate feature values from molecular structure, the use of this potential function is limited in QSAR modeling. The present study applied this function of feature representation learning to QSAR analysis by incorporating 360° images of molecular conformations into deep learning. Accordingly, I successfully constructed a highly versatile identification model for chemical compounds that induce mitochondrial membrane potential disruption with the external validation area under the receiver operating characteristic curve of ≥0.9.     

Pharmacophore, QSAR, and ADME based semisynthesis and in vitro evaluation of ursolic acid analogs for anticancer activity

In the present work, QSAR models for predicting the activities of ursolic acid analogs against human lung (A-549) and CNS (SF-295) cancer cell lines were developed by a forward stepwise multiple linear regression method using a leave-one-out approach. The regression coefficient (r(2)) and the cross-validation regression coefficient (rCV(2)) of the QSAR model for cytotoxic activity against the human lung cancer cell line (A-549) were 0.85 and 0.80, respectively. The QSAR study indicated that the LUMO energy, ring count, and solvent-accessible surface area were strongly correlated with anticancer activity. Similarly, the QSAR model for cytotoxic activity against the human CNS cancer cell line (SF-295) also showed a high correlation (r(2) = 0.99 and rCV(2) = 0.96), and indicated that dipole vector and solvent-accessible surface area were strongly correlated with activity. Ursolic acid analogs that were predicted to be active against these cancer cell lines by the QSAR models were semisynthesized and characterized on the basis of their (1)H and (13)C NMR spectroscopic data, and were then tested in vitro against the human lung (A-549) and CNS (SF-295) cancer cell lines. The experimental results obtained agreed well with the predicted values.     

Analysis of Compound Synergy in High-Throughput Cellular Screens by Population-Based Lifetime Modeling

Despite the successful introduction of potent anti-cancer therapeutics, most of these drugs lead to only modest tumor-shrinkage or transient responses, followed by re-growth of tumors. Combining different compounds has resulted in enhanced tumor control and prolonged survival. However, methods querying the efficacy of such combinations have been hampered by limited scalability, analytical resolution, statistical feasibility, or a combination thereof. We have developed a theoretical framework modeling cellular viability as a stochastic lifetime process to determine synergistic compound combinations from high-throughput cellular screens. We apply our method to data derived from chemical perturbations of 65 cancer cell lines with two inhibitors. Our analysis revealed synergy for the combination of both compounds in subsets of cell lines. By contrast, in cell lines in which inhibition of one of both targets was sufficient to induce cell death, no synergy was detected, compatible with the topology of the oncogenically activated signaling network. In summary, we provide a tool for the measurement of synergy strength for combination perturbation experiments that might help define pathway topologies and direct clinical trials.     

Development of a robust QSAR model to predict the affinity of pyrrolidine analogs for dipeptidyl peptidase IV (DPP- IV)

QSAR analysis using multiple linear regression and partial least squares methods were conducted on a data set of 47 pyrrolidine analogs acting as DPP IV inhibitors. The QSAR models generated (both MLR and PLS) were robust with statistically significant s, F, r, r(2) and r(2) (CV) values. The analysis helped to ascertain the role of shape flexibility index, Ipso atom E-state index and electrostatic parameters like dipole moment, in determining the activity of DPP IV inhibitors. In addition to QSAR modeling, Lipinski's rule of five was also employed to check the pharmacokinetic profile of DPP IV inhibitors. Since none of the compounds violated the Lipinski's rule of five indicating that the DPP IV inhibitors reported herein have sound pharmacokinetic profile and can be considered as potential drug candidates for diabetes mellitus Type II.     

Inhibitors and promoters of tubulin polymerization: synthesis and biological evaluation of chalcones and related dienones as potential anticancer agents

A series of dihalogenated chalcones and structurally related dienones were synthesized and evaluated for their antiproliferative activity in 10 different cancer cell lines and for their effect on microtubule assembly. All compounds showed cytotoxic activity, with IC(50) values in the 5-280 μM range depending on the chalcone structure and the cell line. Five of the compounds were found to be tubulin polymerization inhibitors. In contrast, one of the compounds was found to stabilize tubulin to the same extent as the anticancer drug docetaxel. Molecular modeling suggested that the tubulin inhibitors bind to the colchicine binding site of β-tubulin while the novel tubulin stabilization agent seems to interact with the paclitaxel binding site.     

Cytotoxic effects of two organotin compounds and their mode of inflicting cell death on four mammalian cancer cells

In this report, we have tested the cytotoxicity of two organotin (OT) compounds by flow cytometry on a panel of immortalized cancer cell lines of human and murine origin. Although the OT compounds exhibited varying levels of cytotoxicity, diphenylmethyltin chloride was more toxic than 1,4-bis (diphenylchlorostannyl)p-xylene on all cell lines tested. The OT compounds were found to be highly cytotoxic to lymphoma cell lines with lower toxicity toward the HeLa cervical cancer cell line. In order to discern the mechanism by which cell death was induced, additional experiments were conducted to monitor characteristic changes consistent with apoptosis and/or necrosis. Cell lines treated with the experimental compounds indicated that there was no consistent mode of cell death induction. However, both compounds induced apoptosis in the pro-B lymphocyte cell line, NFS-70. The work presented here also demonstrates that the two OT compounds possess selective cytotoxicity against distinct transformed cell lines.     

Design,synthesis and biological evaluation of novel 3-oxo-4-oxa-5α-androst-17β-amide derivatives as dual 5α-reductase inhibitors and androgen receptor antagonists

Prostate cancer (PCa) is the second leading cause of death in men. Recently, some researches have showed that 5α-reductase inhibitors were beneficial in PCa treatment as well. In this study, a series of novel 3-oxo-4-oxa-5α-androst-17β-amide derivatives have been designed and synthesized in a more simple and convenient method. Most of the synthesized compounds displayed good 5α-reductase inhibitory activities and androgen receptor binding affinities. Their anti-proliferation activities in PC-3 and LNCaP cell lines were also evaluated and the results indicated that most of the synthesized compounds exhibited potent anti-proliferative activities. It is obvious that the androgen-dependent cell line LNCaP was much more sensitive than the androgen-independent cell line PC-3. Among all the synthesized compounds, 11d and 11k displayed the best inhibition activity with 4-fold more sensitive toward LNCaP than PC-3, which was consistent with their high affinities observed in AR binding assay. Molecular modeling studies suggested that 11k could bind to AR in a manner similar to the binding of dihydrotestosterone to AR. Compared to the finasteride, 11k showed a longer plasma half-life (4 h) and a better bioavailability. Overall, based on biological activities data, compound 11d and 11k can be identified as potential dual 5α-reductase inhibitors and AR antagonists which might be of therapeutic importance for prostate cancer treatment.     

Exploration of Novel Inhibitors for Class I Histone Deacetylase Isoforms by QSAR Modeling and Molecular Dynamics Simulation Assays

Histone deacetylases (HDAC) are metal-dependent enzymes and considered as important targets for cell functioning. Particularly, higher expression of class I HDACs is common in the onset of multiple malignancies which results in deregulation of many target genes involved in cell growth, differentiation and survival. Although substantial attempts have been made to control the irregular functioning of HDACs by employing various inhibitors with high sensitivity towards transformed cells, limited success has been achieved in epigenetic cancer therapy. Here in this study, we used ligand-based pharmacophore and 2-dimensional quantitative structure activity relationship (QSAR) modeling approaches for targeting class I HDAC isoforms. Pharmacophore models were generated by taking into account the known IC₅₀ values and experimental energy scores with extensive validations. The QSAR model having an external R² value of 0.93 was employed for virtual screening of compound libraries. 10 potential lead compounds (C1-C10) were short-listed having strong binding affinities for HDACs, out of which 2 compounds (C8 and C9) were able to interact with all members of class I HDACs. The potential binding modes of HDAC2 and HDAC8 to C8 were explored through molecular dynamics simulations. Overall, bioactivity and ligand efficiency (binding energy/non-hydrogen atoms) profiles suggested that proposed hits may be more effective inhibitors for cancer therapy.     

Discovery of novel fatty acid synthase (FAS) inhibitors based on the structure of ketoaceyl synthase (KS) domain

Development of fatty acid synthase (FAS) inhibitors has increasingly attracted much attention in recent years due to their potential therapeutic use in obesity and cancers. In this investigation, pharmacophore modeling based on the first crystal structure of human KS domain of FAS was carried out. The established pharmacophore model was taken as a 3D query for retrieving potent FAS inhibitors from the chemical database Specs. Docking study was further carried out to refine the obtained hit compounds. Finally, a total of 28 compounds were selected based on the ranking order and visual examination, which were first evaluated by a cell line-based assay. Seven compounds that have good inhibition activity against two FAS overexpressing cancer cell lines were further evaluated by an enzyme-based assay. One compound with a new chemical scaffold was found to have low micromolar inhibition potency against FAS, which has been subjected to further chemical structural modification.     

Identification of potential inhibitors for HCV NS5b of genotype 4a by combining dynamic simulation,protein–ligand interaction fingerprint, 3D pharmacophore,docking and 3D QSAR

Abstract

HCV NS5B polymerase has been one of the most attractive targets for developing new drugs for HCV infection and many drugs were successfully developed, but all of them were designed for targeting Hepatitis C Virus genotype 1 (HCV GT1). Hepatitis C virus genotype 4a (HCV GT4a) dominant in Egypt has paid less attention. Here, we describe our protocol of virtual screening in identification of novel potential potent inhibitors for HCV NS5B polymerase of GT4a using homology modeling, protein–ligand interaction fingerprint (PLIF), docking, pharmacophore, and 3D CoMFA quantitative structure activity relationship (QSAR). Firstly, a high-quality 3D model of HCV NS5B polymerase of GT4a was constructed using crystal structure of HCV NS5B polymerase of GT1 (PDB ID: 3hkw) as a template. Then, both the model and the template were simulated to compare conformational stability. PLIF was generated using five crystal structures of HCV NS5B (PDB ID: 4mia, 4mib, 4mk9, 4mka, and 4mkb), which revealed the most important residues and their interactions with the co-crystalized ligands. After that, a 3D pharmacophore model was developed from the generated PLIF data and then used as a screening filter for 17000328 drug-like zinc database compounds. 900 compounds passed the pharmacophore filter and entered the docking-based virtual screening stage. Finally, a 3D CoMFA QSAR was developed using 42 compounds as a training and 19 compounds as a test set. The 3D CoMFA QSAR was used to design and screen some potential inhibitors, these compounds were further evaluated by the docking stage. The highest ranked five hits from docking result (compounds (p1–p4) and compound q1) were selected for further analysis.

Communicated by Ramaswamy H. Sarma     

QSAR studies and pharmacophore identification for arylsubstituted cycloalkenecarboxylic acid methyl esters with affinity for the human dopamine transporter

Data from a series of 29 monoamine transport inhibitors were used to generate 2D and 3D QSAR models for their binding affinity to the human dopamine transporter (hDAT). Among the inhibitors were many non-nitrogen containing compounds. The 2D QSAR analysis resulted in the equation -logK(i)=4.00-3.93E(LUMO)-0.67E(HOMO)-3.24sigma(p), which predicted the importance of electron withdrawing groups in the aromatic moiety. However, the model failed to predict the observed poor binding of nitro-substituted compounds. In contrast, a derived 3D QSAR model was capable of predicting these more correctly.     

Novel Acylguanidine Derivatives Targeting Smoothened Induce Antiproliferative and Pro-Apoptotic Effects in Chronic Myeloid Leukemia Cells

The most relevant therapeutic approaches to treat CML rely on the administration of tyrosine kinase inhibitors (TKIs) like Imatinib, which are able to counteract the activity of Bcr-Abl protein increasing patient’s life expectancy and survival. Unfortunately, there are some issues TKIs are not able to address; first of all TKIs are not so effective in increasing survival of patients in blast crisis, second they are not able to eradicate leukemic stem cells (LSC) which represent the major cause of disease relapse, and third patients often develop resistance to TKIs due to mutations in the drug binding site. For all these reasons it’s of primary interest to find alternative strategies to treat CML. Literature shows that Hedgehog signaling pathway is involved in LSC maintenance, and pharmacological inhibition of Smoothened (SMO), one of the key molecules of the pathway, has been demonstrated to reduce Bcr-Abl positive bone marrow cells and LSC. Consequently, targeting SMO could be a promising way to develop a new treatment strategy for CML overcoming the limitations of current therapies. In our work we have tested some compounds able to inhibit SMO, and among them MRT92 appears to be a very potent SMO antagonist. We found that almost all our compounds were able to reduce Gli1 protein levels in K-562 and in KU-812 CML cell lines. Furthermore, they were also able to increase Gli1 and SMO RNA levels, and to reduce cell proliferation and induce apoptosis/autophagy in both the tested cell lines. Finally, we demonstrated that our compounds were able to modulate the expression of some miRNAs related to Hedgehog pathway such as miR-324-5p and miR-326. Being Hedgehog pathway deeply implicated in the mechanisms of CML we may conclude that it could be a good therapeutic target for CML and our compounds seem to be promising antagonists of such pathway.     

Identification and structure–activity relationships of ortho-biphenyl carboxamides as potent Smoothened antagonists inhibiting the Hedgehog signaling pathway

Ortho-biphenyl carboxamides, originally prepared as inhibitors of microsomal triglyceride transfer protein (MTP) have been identified as novel inhibitors of the Hedgehog signaling pathway. Structure–activity relationship studies for this class of compounds reduced MTP inhibitory activity and led to low nanomolar Hedgehog inhibitors. Binding assays revealed that the compounds act as antagonists of Smoothened and show cross-reactivity for both the human and mouse receptor.