Binding site hotspot map of PI3Kα and mTOR in the presence of selective and dual ATP-competitive inhibitors.

The PI3K/Akt/mTOR signaling pathway plays a pivotal role in cellular metabolism, growth and survival. PI3Kα hyperactivation impairs downstream signaling, including mTOR regulation, and are linked to poor prognosis and refractory cancer treatment. To support multi-target drug discovery, we took advantage from existing PI3Kα and mTOR crystallographic structures to map similarities and differences in their ATP-binding pockets in the presence of selective or dual inhibitors. Molecular dynamics and MM/PBSA calculations were employed to study the binding profile and identify the relative contribution of binding site residues. Our analysis showed that while varying parameters of solute and solvent dielectric constant interfered in the absolute binding free energy, it had no effect in the relative per residue contribution. In all complexes, the most important interactions were observed within 3-3.5 Å from inhibitors, responding for ∼75-100% of the total calculated interaction energy. While closest residues are essential for the strength of the binding of all ligands, more distant residues seem to have a larger impact on the binding of the dual inhibitor, as observed for PI3Kα residues Phe934, Lys802 and Asp805 and, mTOR residues Leu2192, Phe2358, Leu2354, Lys2187 and Tyr2225. A detailed description of individual residue contribution in the presence of selective or dual inhibitors is provided as an effort to improve the understanding of molecular mechanisms controlling multi-target inhibition. This work provides key information to support further studies seeking the rational design of potent PI3K/mTOR dual inhibitors for cancer treatment.Communicated by Ramaswamy H. Sarma.

Bioinformatic Analysis of Two TOR (Target of Rapamycin)-Like Proteins Encoded by Entamoeba histolytica Revealed Structural Similarities with Functional Homologs.

The target of rapamycin (TOR), also known as FKBP-rapamycin associated protein (FRAP), is a protein kinase belonging to the PIKK (phosphatidylinositol 3-kinase (PI3K)-related kinases) family. TOR kinases are involved in several signaling pathways that control cell growth and proliferation. Entamoeba histolytica, the protozoan parasite that causes human amoebiasis, contains two genes encoding TOR-like proteins: EhFRAP and EhTOR2. To assess their potential as drug targets to control the cell proliferation of E. histolytica, we studied the structural features of EhFRAP and EhTOR2 using a biocomputational approach. The overall results confirmed that both TOR amoebic homologs share structural similarities with functional TOR kinases, and show inherent abilities to form TORC complexes and participate in protein-protein interaction networks. To our knowledge, this study represents the first in silico characterization of the structure-function relationships of EhFRAP and EhTOR2.

Network Pharmacology Uncovers Anticancer Activity of Mammea-Type Coumarins from Calophyllum brasiliense.

Mammea-type coumarins are a particular type of secondary metabolites biosynthesized by the tropical rainforest tree Calophyllum Brasiliense, which is distributed from South America to Mexico. Particularly, mammea A/BA and A/BB (alone or as a mixture) possess biological properties such as cytotoxic and antitumoral activities, however, most of its molecular targets remain unknown. In this context, novel bioinformatic approaches, such as network pharmacology analysis, have been successfully used in herbal medicine to accelerate research in this field, and the support of experimental validations has been shown to be quite robust. In the present study, we performed a network pharmacology analysis to assess the possible molecular biological networks that interact with mammea A/BA and A/BB. Moreover, we validated the most relevant networks experimentally in vitro on K562 cancer cells. The results of the network pharmacology analysis indicate that mammea A/BA and A/BB interacts with cell death, PI3K/AKT, MAPK, Ras, and cancer pathways. The in vitro model shows that mammea A/BA and A/BB induce apoptosis through the overexpression of the proapoptotic proteins Bax and Bak, disrupt the autophagic flux as seen by the cytosolic accumulation of LC3-II and p62, disrupting the mitochondria ultrastructure and concomitantly increase the intracellular calcium concentration. Additionally, docking analysis predicted a possible interaction with a rapamycin-binding domain of mTOR. In conclusion, we validated network pharmacology analysis and report, for the first time, that mammea A/BA and A/BB coumarins induce apoptosis through the inhibition of the autophagic flux, possibly interacting with mTOR.

Searching for potential mTOR inhibitors: Ligand-based drug design, docking and molecular dynamics studies of rapamycin binding site.

The PI3K/Akt/mTOR pathway is an important intracellular signaling pathway in cell cycle regulation and its dysregulation is associated with various types of diseases. mTOR (mechanistic or mammalian target of rapamycin) is the main enzyme that performs intermediate control of the signaling pathway through a phosphotransfer process. The classical inhibition of the mTOR pathway is effected by rapamycin and its analogous blocking allosterically the catalytic phosphorylation site, avoiding the deleterious side effects induced by ATP-competitive inhibitors. We employed ligand-based drug design strategies such as pharmacophore searching and analysis, molecular docking, absorption, distribution, metabolism, excretion and toxicity (ADMETox) properties filtering, and molecular dynamics to select potential molecules to become non-ATP competitive inhibitors of the mTOR complex. According to our findings, we propose eight novel potential mTOR inhibitors with similar or better properties than the classic inhibitor complex, rapamycin.

New potential inhibitors of mTOR: a computational investigation integrating molecular docking, virtual screening and molecular dynamics simulation.

The mTOR (mammalian or mechanistic Target Of Rapamycin), a complex metabolic pathway that involves multiple steps and regulators, is a major human metabolic pathway responsible for cell growth control in response to multiple factors and that is dysregulated in various types of cancer. The classical inhibition of the mTOR pathway is performed by rapamycin and its analogs (rapalogs). Considering that rapamycin binds to an allosteric site and performs a crucial role in the inhibition of the mTOR complex without causing the deleterious side effects common to ATP-competitive inhibitors, we employ ligand-based drug design strategies, such as virtual screening methodology, computational determination of ADME/Tox properties of selected molecules, and molecular dynamics in order to select molecules with the potential to become non-ATP-competitive inhibitors of the mTOR enzymatic complex. Our findings suggest five novel potential mTOR inhibitors, with similar or better properties than the classic inhibitor complex, rapamycin.

Ligand-receptor affinities computed by an adapted linear interaction model for continuum electrostatics and by protein conformational averaging.

Accurate calculations of free energies involved in small-molecule binding to a receptor are challenging. Interactions between ligand, receptor, and solvent molecules have to be described precisely, and a large number of conformational microstates has to be sampled, particularly for ligand binding to a flexible protein. Linear interaction energy models are computationally efficient methods that have found considerable success in the prediction of binding free energies. Here, we parametrize a linear interaction model for implicit solvation with coefficients adapted by ligand and binding site relative polarities in order to predict ligand binding free energies. Results obtained for a diverse series of ligands suggest that the model has good predictive power and transferability. We also apply implicit ligand theory and propose approximations to average contributions of multiple ligand-receptor poses built from a protein conformational ensemble and find that exponential averages require proper energy discrimination between plausible binding poses and false-positives (i.e., decoys). The linear interaction model and the averaging procedures presented can be applied independently of each other and of the method used to obtain the receptor structural representation.