Investigating mushroom LMW compounds as potential Bcl-2 inhibitors: docking studies using AutoDock4

The B cell CLL/lymphoma-2 (Bcl-2) family is functionally classified as either anti-apoptotic or pro-apoptotic, and the regulation of its interactions dictates survival or commitment to apoptosis. Bcl-2 family is also implicated in a wide range of diseases. In some types of cancers, including lymphomas and epithelial cancers, protein overexpression of anti-apoptotic Bcl-2 family, such as the Bcl-2 protein is indicative of cancer in an advanced stage, with a poor prognosis and resistant to chemotherapy [1]. Several reports indicate that mushrooms have the ability to promote apoptosis in tumour cell lines, but the mechanism of action is not fully understood. Inhibition of the interaction between Bcl-2 (anti-apoptotic protein) and proapoptotic proteins could be an important step in the mechanism of mushroom induced apoptosis. Therefore, the discovery of compounds with the capacity to inhibit Bcl-2 is an ongoing research topic on cancer therapy. In this work, docking studies were performed using a dataset of 40 low molecular weight (LMW) compounds present in mushrooms. The docking software AutoDock 4 was used and docking studies were performed using 5 selected Bcl-2 crystal structures as targets. Compounds with the lowest predicted binding energy (predΔG) are expected to be the more potent inhibitors. Among the tested compounds, steroids presented the lowest predΔG with several exhibiting values below -9 kcal/mol. The results are corroborated by several reports that state that steroids induce apoptosis in several tumor cells. It is thus feasible that they might act by preventing Bcl-2 from forming complexes with the respective proapoptotic protein interaction partners, namely Bak, Bax, and Bim. Moreover, previous studies on our research group demonstrated that 48 h treatment of MCF-7 cells (breast carcinoma) with Suillus collinitus methanolic extract caused a decrease in Bcl-2, highlighting the antitumor potential of this mushroom species [2]. In conclusion, the process of apoptosis promoted by mushroom extracts may be related to the inhibition of Bcl-2 by the steroid derivatives herein studied. However, further studies are needed to confirm this hypothesis.

Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.

Toward on-the-fly quantum mechanical/molecular mechanical (QM/MM) docking: development and benchmark of a scoring function.

We address the challenges of treating polarization and covalent interactions in docking by developing a hybrid quantum mechanical/molecular mechanical (QM/MM) scoring function based on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. To benchmark this scoring function within the EADock DSS docking algorithm, we created a publicly available dataset of high-quality X-ray structures of zinc metalloproteins ( http://www.molecular-modelling.ch/resources.php ). For zinc-bound ligands (226 complexes), the QM/MM scoring yielded a substantially improved success rate compared to the classical scoring function (77.0% vs 61.5%), while, for allosteric ligands (55 complexes), the success rate remained constant (49.1%). The QM/MM scoring significantly improved the detection of correct zinc-binding geometries and improved the docking success rate by more than 20% for several important drug targets. The performance of both the classical and the QM/MM scoring functions compare favorably to the performance of AutoDock4, AutoDock4Zn, and AutoDock Vina.

Low molecular weight compounds from mushrooms as potential Bcl-2 inhibitors: docking and virtual screening studies

Mushrooms have the ability to promote apoptosis in tumor cell lines, but the mechanism of action is not quite well understood. Inhibition of the interaction between Bcl-2 and pro-apoptotic proteins could be an important step that leads to apoptosis. Therefore, the discovery of compounds with the ability to inhibit Bcl-2 is an ongoing research topic in drug discovery. In this study, we started by analyzing Bcl-2 experimental structures that are currently available in Protein Data Bank database. After analysis of the more relevant Bcl-2 structures, 4 were finally selected. An analysis of the best docking methodology was then performed using a cross-docking and re-docking approach while testing 2 docking softwares: AutoDock 4 and AutoDock Vina. Autodock4 provided the best docking results and was selected to perform a virtual screening study applied to a dataset of 40 Low Molecular Weight (LMW) compounds present in mushrooms, using the selected Bcl-2 structures as target. Results suggest that steroid are the more promising family, among the analyzed compounds, and may have the ability to interact with Bcl-2 and this way promoting tumor apoptosis. The steroids that presented lowest estimated binding energy (ΔG) were: Ganodermanondiol, Cerevisterol, Ganoderic Acid X and Lucidenic Lactone; with estimated ΔG values between -8,45 and -8,23 Kcal/mol. A detailed analysis of the docked conformation of these 4 top ranked LMW compounds was also performed and illustrates a plausible interaction between the 4 top raked steroids and Bcl-2, thus substantiating the accuracy of the predicted docked poses. Therefore, tumoral apoptosis promoted by mushroom might be related to Bcl-2 inhibition mediated by steroid family of compounds.