Computational fishing of new DNA methyltransferase inhibitors from natural products

Fragment-based discovery of new potential DNMT1 inhibitors integrating multiple pharmacophore modeling, 3D-QSAR, virtual screening, molecular docking, ADME, and molecular dynamics simulation approaches

DNA methyl transferases (DNMTs) are one of the crucial epigenetic modulators associated with a wide variety of cancer conditions. Among the DNMT isoforms, DNMT1 is correlated with bladder, pancreatic, and breast cancer, as well as acute myeloid leukemia and esophagus squamous cell carcinoma. Therefore, the inhibition of DNMT1 could be an attractive target for combating cancers and other metabolic disorders. The disadvantages of the existing nucleoside and non-nucleoside DNMT1 inhibitors are the main motive for the discovery of novel promising inhibitors. Here, pharmacophore modeling, 3D-QSAR, and e-pharmacophore modeling of DNMT1 inhibitors were performed for the large fragment database screening. The resulting fragments with high dock scores were combined into molecules. The current study revealed several constitutional pharmacophoric features that can be essential for selective DNMT1 inhibition. The fragment docking and virtual screening identified 10 final hit molecules that exhibited good binding affinities in terms of docking score, binding free energies, and acceptable ADME properties. Also, the modified lead molecules (GL1b and GL2b) designed in this study showed effective binding with DNMT1 confirmed by their docking scores, binding free energies, 3D-QSAR predicted activities and acceptable drug-like properties. The MD simulation studies also suggested that leads (GL1b and GL2b) formed stable complexes with DNMT1. Therefore, the findings of this study can provide effective information for the development/identification of novel DNMT1 inhibitors as effective anticancer agents.

Molecular Human Targets of Bioactive Alkaloid-Type Compounds from Tabernaemontana cymose Jacq

Alkaloids are a group of secondary metabolites that have been widely studied for the discovery of new drugs due to their properties on the central nervous system and their anti-inflammatory, antioxidant and anti-cancer activities. Molecular docking was performed for 10 indole alkaloids identified in the ethanol extract of Tabernaemontana cymosa Jacq. with 951 human targets involved in different diseases. The results were analyzed through the KEGG and STRING databases, finding the most relevant physiological associations for alkaloids. The molecule 5-oxocoronaridine proved to be the most active molecule against human proteins (binding energy affinity average = −9.2 kcal/mol) and the analysis of the interactions between the affected proteins pointed to the PI3K/ Akt/mTOR signaling pathway as the main target. The above indicates that indole alkaloids from T. cymosa constitute a promising source for the search and development of new treatments against different types of cancer.

Effect of Epigenetic Drug Candidate Olsalazine on the Expression of CDH1 and uPA Genes in MCF-7 Breast Cancer Cell Line

Background: A main epigenetic change in cancer is DNA methylation, which leads to the inactivation of tumor suppressor genes. Due to its reversible nature, many studies have focused on how to correct epigenetic imbalances via inhibiting DNA methyltransferases (DNMTs). Recent studies have shown that olsalazine can be a potent candidate for DNMT inhibition. Objectives: The current study aimed to assess the cytotoxic effect of olsalazine on MCF-7 cells and the expression of CDH1 and uPA, as cancer-related genes, compared to decitabine. Methods: The cytotoxicity of olsalazine and decitabine on MCF-7 cells was assessed by MTT assay. To evaluate the effect of drugs on the expression of CDH1 and uPA genes, MCF-7 cells were treated with olsalazine and decitabine in concentrations below their IC50 values. After 24 h, RNA of treated cells was extracted and then subjected to a quantitative reverse transcription-polymerase chain reaction (Q-RT-PCR). Results: The MTT assay showed that olsalazine was more toxic (IC50 = 1.75 mM) in MCF-7 cells than decitabine (IC50 = 3mM). Q-RT-PCR analysis showed that olsalazine can significantly increase uPA expression along with a non-significant increase in CDH1 expression. Meanwhile, no significant change was found in gene expression after treatment with decitabine. Conclusions: This study demonstrated that olsalazine was more cytotoxic than decitabine on MCF-7 cells. Also, compared to decitabine, olsalazine could increase the expression of CDH1 and uPA genes. It suggests that olsalazine might be more potent than decitabine in inhibiting DNMTs, although further studies are needed.

Application of Machine Learning Approaches for the Design and Study of Anticancer Drugs

BACKGROUND

Globally the number of cancer patients and deaths are continuing to increase yearly, and cancer has, therefore, become one of the world's highest causes of morbidity and mortality. In recent years, the study of anticancer drugs has become one of the most popular medical topics.

OBJECTIVE

In this review, in order to study the application of machine learning in predicting anticancer drugs activity, some machine learning approaches such as Linear Discriminant Analysis (LDA), Principal components analysis (PCA), Support Vector Machine (SVM), Random forest (RF), k-Nearest Neighbor (kNN), and Naïve Bayes (NB) were selected, and the examples of their applications in anticancer drugs design are listed.

RESULTS

Machine learning contributes a lot to anticancer drugs design and helps researchers by saving time and is cost effective. However, it can only be an assisting tool for drug design.

CONCLUSION

This paper introduces the application of machine learning approaches in anticancer drug design. Many examples of success in identification and prediction in the area of anticancer drugs activity prediction are discussed, and the anticancer drugs research is still in active progress. Moreover, the merits of some web servers related to anticancer drugs are mentioned.

Effects of Propolis and Phenolic Acids on Triple-Negative Breast Cancer Cell Lines: Potential Involvement of Epigenetic Mechanisms

Triple-negative breast cancer is an aggressive disease frequently associated with resistance to chemotherapy. Evidence supports that small molecules showing DNA methyltransferase inhibitory activity (DNMTi) are important to sensitize cancer cells to cytotoxic agents, in part, by reverting the acquired epigenetic changes associated with the resistance to therapy. The present study aimed to evaluate if chemical compounds derived from propolis could act as epigenetic drugs (epi-drugs). We selected three phenolic acids (caffeic, dihydrocinnamic, and p-coumaric) commonly detected in propolis and the (−)-epigallocatechin-3-gallate (EGCG) from green tea, which is a well-known DNA demethylating agent, for further analysis. The treatment with p-coumaric acid and EGCG significantly reduced the cell viability of four triple-negative breast cancer cell lines (BT-20, BT-549, MDA-MB-231, and MDA-MB-436). Computational predictions by molecular docking indicated that both chemicals could interact with the MTAse domain of the human DNMT1 and directly compete with its intrinsic inhibitor S-Adenosyl-l-homocysteine (SAH). Although the ethanolic extract of propolis (EEP) did not change the global DNA methylation content, by using MS-PCR (Methylation-Specific Polymerase Chain Reaction) we demonstrated that EEP and EGCG were able to partly demethylate the promoter region of RASSF1A in BT-549 cells. Also, in vitro treatment with EEP altered the RASSF1 protein expression levels. Our data indicated that some chemical compound present in the EEP has DNMTi activity and can revert the epigenetic silencing of the tumor suppressor RASSF1A. These findings suggest that propolis are a promising source for epi-drugs discovery.

In silico evaluation of pesticides as potential modulators of human DNA methyltransferases

DNA methylations are carried out by DNA methyltransferases (DNMTs) that are key enzymes during gene expression. Many chemicals, including pesticides, have shown modulation of epigenetic functions by inhibiting DNMTs. In this work, human DNMTs were evaluated as a potential target for pesticides through virtual screening of 1038 pesticides on DNMT1 (3SWR) and DNMT3A (2QRV). Molecular docking calculations for DNMTs-pesticide complexes were performed using AutoDock Vina. Binding-affinity values and contact patterns were employed as selection criteria of pesticides as virtual hits for DNMTs. The best three DNMT-pesticides complexes selected according to their high absolute affinity values (kcal/mol), for both DNMT1 and DNMT3A, were flocoumafen (-12.5; -9.9), brodifacoum (-12.4; -8.4) and difenacoum (-12.1; -8.7). These chemicals belong to second-generation rodenticides. The most frequent predicted interacting residues for DNMT1-pesticide complexes were Trp1170A, Phe1145A, Asn1578A, Arg1574A and Pro1225A; whereas for DNMT3A those were Arg271B, Lys740A, and Glu303B. These results suggest that rodenticides used for pest control are potential DNMT ligands and therefore, may modulate DNA methylations. This finding has important environmental and clinical implications, as epigenetic pathways are critical in many biochemical processes leading to diseases.

DNA methyltransferases: emerging targets for the discovery of inhibitors as potent anticancer drugs

DNA methyltransferases (DNMTs) are a conserved family of cytosine methylases with crucial roles in epigenetic regulation. They have been considered as promising therapeutic targets for the epigenetic treatment of cancer. Therefore, DNMT inhibitors (DNMTis) have attracted considerable interest in recent years for the modulation of the aberrant DNA methylation pattern in a reversible way. In this review, we provide a structure-based overview of the therapeutic importance of DNMTs against different cancer types, and then summarize recently investigated DNMTis as well as their inhibitory mechanisms, focusing on recent advances in the development of DNMTis with specificity and/or selectivity using computational approaches.

Modelling and molecular docking studies of the cytoplasmic domain of Wsc-family, full-length Ras2p, and therapeutic antifungal compounds

Saccharomyces cerevisiae, the budding yeast, must remodel initial cell shape and cell wall integrity during vegetative growth and pheromone-induced morphogenesis. The cell wall remodeling is monitored and regulated by the cell wall integrity (CWI) signaling pathway. Wsc1p, together with Wsc2p and Wsc3p, belongs to a family of highly O-glycosylated cell surface proteins that function as stress sensors of the cell wall in S. cerevisiae. These cell surface proteins have the main role of activating the CWI signaling pathway by stimulating the small G-protein Rho1p, which subsequently activates protein kinase C (Pkc1p) and a mitogen activated protein (MAP) kinase cascade that activates downstream transcription factors of stress-response genes. Wsc1p, Wsc2p, and Wsc3p possess a cytoplasmic domain where two conserved regions of the sequence have been assessed to be important for Rom2p interaction. Meanwhile, other research groups have also proposed that these transmembrane proteins could support protein-protein interactions with Ras2p. Molecular structures of the cytoplasmic domain of Wsc1p, Wsc2p and Wsc3p were generated using the standard and fully-automated ORCHESTAR procedures provided by the Sybyl-X 2.1.1 program. The tridimensional structure of full length Ras2p was also generated with Phyre2. These protein models were validated with Procheck-PDBsum and ProSA-web tools and subsequently used in docking-based modeling of protein-protein and protein-compound interfaces for extensive structural and functional characterization of their interaction. The results retrieved from STRING 10.5 suggest that the Wsc-family is involved in protein-protein interactions with each other and with Ras2p. Docking-based studies also validated the existence of protein-protein interactions mainly between Motif I (Wsc3p > Wsc1p > Wsc2p) and Ras2p, in agreement with the data provided by STRING 10.5. Additionally, it has shown that Calcofluor White preferably binds to Wsc1p (-9.5 kcal/mol), meanwhile Caspofungin binds to Wsc3p (-9.1 kcal/mol), Wsc1p (-9.1 kcal/mol) and more weakly Wsc2p (-6.9 kcal/mol). Thus, these data suggests Caspofungin as a common inhibitor for the Wsc-family. MTiOpenScreen database has provided a list of new compounds with energy scores higher than those compounds used in our docking studies, thus suggesting these new compounds have a better affinity towards the cytoplasmic domains and Ras2p. Based on these data, there are new and possibly more effective compounds that should be considered as therapeutic agents against yeast infection.

Inhibitors of DNA Methyltransferases From Natural Sources: A Computational Perspective

Naturally occurring small molecules include a large variety of natural products from different sources that have confirmed activity against epigenetic targets. In this work we review chemoinformatic, molecular modeling, and other computational approaches that have been used to uncover natural products as inhibitors of DNA methyltransferases, a major family of epigenetic targets with therapeutic interest. Examples of computational approaches surveyed in this work are docking, similarity-based virtual screening, and pharmacophore modeling. It is also discussed the chemoinformatic-guided exploration of the chemical space of naturally occurring compounds as epigenetic modulators which may have significant implications in epigenetic drug discovery and nutriepigenetics.

Copaifera of the Neotropics: A Review of the Phytochemistry and Pharmacology

The oleoresin of Copaifera trees has been widely used as a traditional medicine in Neotropical regions for thousands of years and remains a popular treatment for a variety of ailments. The copaiba resins are generally composed of a volatile oil made up largely of sesquiterpene hydrocarbons, such as β-caryophyllene, α-copaene, β-elemene, α-humulene, and germacrene D. In addition, the oleoresin is also made up of several biologically active diterpene acids, including copalic acid, kaurenoic acid, alepterolic acid, and polyalthic acid. This review presents a summary of the ecology and distribution of Copaifera species, the traditional uses, the biological activities, and the phytochemistry of copaiba oleoresins. In addition, several biomolecular targets relevant to the bioactivities have been implicated by molecular docking methods.

Research progress in modern structure of platinum complexes

Since the antitumor activity of cisplatin was discovered in 1967 by Rosenberg, platinum-based anticancer drugs have played an important role in chemotherapy in clinic. Nevertheless, platinum anticancer drugs also have caused severe side effects and cross drug resistance which limited their applications. Therefore, a significant amount of efforts have been devoted to developing new platinum-based anticancer agents with equal or higher antitumor activity but lower toxicity. Until now, a large number of platinum-based complexes have been prepared and extensively investigated in vitro and in vivo. Among them, some platinum-based complexes revealing excellent anticancer activity showed the potential to be developed as novel type of anticancer agents. In this account, we present such platinum-based anticancer complexes which owning various types of ligands, such as, amine carrier ligands, leaving groups, reactive molecule, steric hindrance groups, non-covalently binding platinum (II) complexes, Platinum(IV) complexes and polynuclear platinum complexes. Overall, platinum-based anticancer complexes reported recently years upon modern structure are emphasized.

A molecular docking study of the interactions between human transferrin and seven metallocene dichlorides

Human Transferrin (hTf) is a metal-binding protein found in blood plasma and is well known for its role in iron delivery. With only a 30% of its capacity for Fe⁺³ binding, this protein has the potential ability to transport other metal ions or organometallic compounds from the blood stream to all cell tissues. In this perspective, recent studies have described seven metallocene dichlorides (Cp₂M(IV)Cl₂, M(IV)=V, Mo, W, Nb, Ti, Zr, Hf) suitable as anticancer drugs and less secondary effects than cisplatin. However, these studies have not provided enough data to clearly explain how hTf binds and transports these organometallic compounds into the cells. Thus, a computational docking study with native apo-hTf using Sybyl-X 2.0 program was conducted to explore the binding modes of these seven Cp₂M(IV)Cl₂ after their optimization and minimization using Gaussian 09. Our model showed that the first three Cp₂M(IV)Cl₂ (M(IV)=V, Mo, W) can interact with apo-hTf on a common binding site with the amino acid residues Leu-46, Ile-49, Arg-50, Leu-66, Asp-69, Ala-70, Leu-72, Ala-73, Pro-74 and Asn-75, while the next four Cp₂M(IV)Cl₂ (M(IV)=Nb, Ti, Zr, Hf) showed different binding sites, unknown until now. A decreasing order in the total score (equal to -log Kd) was observed from these docking studies: W (5.4356), Mo (5.2692), Nb (5.1672), V (4.5973), Ti (3.6529), Zr (2.0054) and Hf (1.8811). High and significant correlation between the affinity of these seven ligands (metallocenes) for apo-hTf and their bond angles CpMCp (r=0.94, p<0.01) and Cl-M-Cl (r=0.95, p<0.01) were observed, thus indicating the important role that these bond angles can play in ligand-protein interactions. Fluorescence spectra of apo-hTf, measured at pH 7.4, had a decrease in the fluorescence emission spectrum with increasing concentration of Cp₂M(IV)Cl₂. Experimental data has a good correlation between K_A (r=0.84, p=0.027) and K_d (r=0.94, p=0.0014) values and the calculated total scores obtained from our docking experiments. In conclusion, these results suggest that the seven Cp₂M(IV)Cl₂ used for this study can interact with apo-hTf, and their affinity was directly and inversely proportional to their bond angles CpMCp and ClMCl, respectively. Our docking studies also suggest that the binding of the first three Cp₂M(IV)Cl₂ (M(IV)=V, Mo, W) to hTf could abrogate the formation of the hTf-receptor complex, and as a consequence the metallocene-hTf complex might require another transport mechanism in order to get into the cell.

Identification of potent inhibitors of DNA methyltransferase 1 (DNMT1) through a pharmacophore-based virtual screening approach

DNA methylation is an epigenetic change that results in the addition of a methyl group at the carbon-5 position of cytosine residues. DNA methyltransferase (DNMT) inhibitors can suppress tumour growth and have significant therapeutic value. However, the established inhibitors are limited in their application due to their substantial cytotoxicity. Additionally, the standard drugs for DNMT inhibition are non-selective cytosine analogues with considerable cytotoxic side-effects. In the present study, we have designed a workflow by integrating various ligand-based and structure-based approaches to discover new agents active against DNMT1. We have derived a pharmacophore model with the help of available DNMT1 inhibitors. Utilising this model, we performed the virtual screening of Maybridge chemical library and the identified hits were then subsequently filtered based on the Naïve Bayesian classification model. The molecules that have returned from this classification model were subjected to ensemble based docking. We have selected 10 molecules for the biological assay by inspecting the interactions portrayed by these molecules. Three out of the ten tested compounds have shown DNMT1 inhibitory activity. These compounds were also found to demonstrate potential inhibition of cellular proliferation in human breast cancer MDA-MB-231 cells. In the present study, we have utilized a multi-step virtual screening protocol to identify inhibitors of DNMT1, which offers a starting point to develop more potent DNMT1 inhibitors as anti-cancer agents.

Natural Products as Chemopreventive Agents by Potential Inhibition of the Kinase Domain in ErbB Receptors

Small molecules found in natural products provide therapeutic benefits due to their pharmacological or biological activity, which may increase or decrease the expression of human epidermal growth factor receptor (HER), a promising target in the modification of signaling cascades involved in excessive cellular growth. In this study, in silico molecular protein-ligand docking protocols were performed with AutoDock Vina in order to evaluate the interaction of 800 natural compounds (NPs) from the NatProd Collection (http://www.msdiscovery.com/natprod.html), with four human HER family members: HER1 (PDB: 2ITW), HER2 (PDB: 3PP0), HER3 (PDB: 3LMG) and HER4 (PDB: 2R4B). The best binding affinity values (kcal/mol) for docking pairs were obtained for HER1-podototarin (−10.7), HER2-hecogenin acetate (−11.2), HER3-hesperidin (−11.5) and HER4-theaflavin (−10.7). The reliability of the theoretical calculations was evaluated employing published data on HER inhibition correlated with in silico binding calculations. IC₅₀ values followed a significant linear relationship with the theoretical binding Affinity data for HER1 (R = 0.656, p < 0.0001) and HER2 (R = 0.543, p < 0.0001), but not for HER4 (R = 0.364, p > 0.05). In short, this methodology allowed the identification of several NPs as HER inhibitors, being useful in the discovery and design of more potent and selective anticancer drugs.

Molecular Modeling and Chemoinformatics to Advance the Development of Modulators of Epigenetic Targets: A Focus on DNA Methyltransferases

In light of the emerging field of Epi-informatics, ie, computational methods applied to epigenetic research, molecular docking, and dynamics, pharmacophore and activity landscape modeling and QSAR play a key role in the development of modulators of DNA methyltransferases (DNMTs), one of the major epigenetic target families. The increased chemical information available for modulators of DNMTs has opened up the avenue to explore the epigenetic relevant chemical space (ERCS). Herein, we discuss recent progress on the identification and development of inhibitors of DNMTs as potential epi-drugs and epi-probes that have been driven by molecular modeling and chemoinformatics methods. We also survey advances on the elucidation of their structure-activity relationships and exploration of ERCS. Finally, it is illustrated how computational approaches can be applied to identify modulators of DNMTs in food chemicals.

Discovery of antiviral molecules for dengue: In silico search and biological evaluation

BACKGROUND

Dengue disease is a global disease that has no effective treatment. The dengue virus (DENV) NS2B/NS3 protease complex is a target for designing specific antivirals due to its importance in viral replication and its high degree of conservation.

METHODS

NS2B/NS3 protease complex structural information was employed to find small molecules that are capable of inhibiting the activity of the enzyme complex. This inhibitory activity was probed with in vitro assays using a fluorescent substrate and the complex NS2B/NS3 obtained by recombinant DNA techniques. HepG2 cells infected with dengue virus serotype 2 were used to test the activity against dengue virus replication.

RESULTS

A total of 210,903 small molecules from PubChem were docked in silico to the NS2B/NS3 structure (PDB: 2FOM) to find molecules that were capable of inhibiting this protein complex. Five of the best 500 leading compounds, according to their affinity values (-11.6 and -13.5 kcal/mol), were purchased. The inhibitory protease activity on the recombinant protein and antiviral assays was tested.

CONCLUSIONS

Chemicals CID 54681617, CID 54692801 and CID 54715399 were strong inhibitors of NS2B/NS3, with IC50 values (μM) and percentages of viral titer reductions of 19.9, 79.9%; 17.5, 69.8%; and 9.1, 73.9%, respectively. Multivariate methods applied to the molecular descriptors showed two compounds that were structurally different from other DENV inhibitors.

GENERAL SIGNIFICANCE

This discovery opens new possibilities for obtaining drug candidates against Dengue virus.

Activity landscape sweeping: insights into the mechanism of inhibition and optimization of DNMT1 inhibitors

Inhibitors of DNA methyltransferases have distinct structure–activity relationships as revealed by the activity landscape sweeping study discussed in this work.