Protein tunnels are essential in transporting small molecules into the active sites of enzymes. Tunnels' geometrical and physico-chemical properties influence the transport process. The tunnels are attractive hot spots for protein engineering and drug development. However, studying the ligand binding and unbinding using experimental techniques is challenging, while in silico methods come with their limitations, especially in the case of resource-demanding virtual screening pipelines. Caver Web 1.2 is a new version of the web server combining the capabilities for the detection of protein tunnels with the calculation of the ligand trajectories. The new version of the Caver Web server was expanded with the ability to fetch novel ligands from the Integrated Database of Small Molecules and with the fully automated virtual screening pipeline allowing for the fast evaluation of the predefined set of over 4,300 currently approved drugs. The virtual screening pipeline is accompanied by a comprehensive user interface, making it a viable service for the broader spectrum of companies and the academic user community. The web server is freely available for academic use at https://loschmidt.chemi.muni.cz/caverweb.

• Klíčová slova
• CIF, Crystallographic Information File, CSA, Catalytic Site Atlas, Caver, CaverDock, Channel, FDA, U.S. Food and Drug Administration, FDA-approved drug, IDSM, Integrated Database of Small Molecules, PDB, Protein Data Bank, Tunnel, Virtual screening, Web,
• Publikační typ
• časopisecké články MeSH

Steroid anticancer drugs are the focus of numerous scientific research efforts. Due to their high cytotoxic effects against tumor cells, some natural or synthetic steroid compounds seem to be promising for the treatment of different classes of cancer. In the present study, fourteen novel O-alkylated oxyimino androst-4-ene derivatives were synthesized from isomerically pure 3E-oximes, using different alkylaminoethyl chlorides. Their in vitro cytotoxic activity was evaluated against eight human cancer cell lines, as well as against normal fetal lung (MRC-5) and human foreskin (BJ) fibroblasts, to test the efficiency and selectivity of the compounds. Most derivatives displayed strong activity against malignant melanoma (G-361), lung adenocarcinoma (A549) and colon adenocarcinoma (HT-29) cell lines. Angiogenesis was assessed in vitro using migration scratch and tube formation assays on HUVEC cells, where partial inhibition of endothelial cell migration was observed for the 17α-(pyridin-2-yl)methyl 2-(morpholin-4-yl)ethyl derivative. Among the compounds that most impaired the growth of lung cancer A549 cells, the (17E)-(pyridin-2-yl)methylidene derivative bearing a 2-(pyrrolidin-1-yl)ethyl substituent induced significant apoptosis in these cells. In combination with low cytotoxicity toward normal MRC-5 cells, this molecule stands out as a good candidate for further anticancer studies. In addition, in vitro investigations against cytochrome P450 enzymes revealed that certain compounds can bind selectively in the active sites of human steroid hydroxylases CYP7, CYP17A1, CYP19A1 or CYP21A2, which could be important for the development of novel activity modulators of these enzymes and identification of possible side effects.

• Publikační typ
• časopisecké články MeSH

Protein tunnels and channels are attractive targets for drug design. Drug molecules that block the access of substrates or release of products can be efficient modulators of biological activity. Here, we demonstrate the applicability of a newly developed software tool CaverDock for screening databases of drugs against pharmacologically relevant targets. First, we evaluated the effect of rigid and flexible side chains on sets of substrates and inhibitors of seven different proteins. In order to assess the accuracy of our software, we compared the results obtained from CaverDock calculation with experimental data previously collected with heat shock protein 90α. Finally, we tested the virtual screening capabilities of CaverDock with a set of oncological and anti-inflammatory FDA-approved drugs with two molecular targets-cytochrome P450 17A1 and leukotriene A4 hydrolase/aminopeptidase. Calculation of rigid trajectories using four processors took on average 53 min per molecule with 90% successfully calculated cases. The screening identified functional tunnels based on the profile of potential energies of binding and unbinding trajectories. We concluded that CaverDock is a sufficiently fast, robust, and accurate tool for screening binding/unbinding processes of pharmacologically important targets with buried functional sites. The standalone version of CaverDock is available freely at https://loschmidt.chemi.muni.cz/caverdock/ and the web version at https://loschmidt.chemi.muni.cz/caverweb/.

• Klíčová slova
• binding, channel, docking, inhibitors, substrates, tunnel, unbinding, virtual screening,
• Publikační typ
• časopisecké články MeSH

Targeted therapy is a promising approach for treatment of neuroblastoma as evident from the large number of targeting agents employed in clinical practice today. In the absence of known crystal structures, researchers rely on homology modeling to construct template-based theoretical structures for drug design and testing. Here, we discuss three candidate cell surface proteins that are suitable for homology modeling: human norepinephrine transporter (hNET), anaplastic lymphoma kinase (ALK), and neurotrophic tyrosine kinase receptor 2 (NTRK2 or TrkB). When choosing templates, both sequence identity and structure quality are important for homology modeling and pose the first of many challenges in the modeling process. Homology modeling of hNET can be improved using template models of dopamine and serotonin transporters instead of the leucine transporter (LeuT). The extracellular domains of ALK and TrkB are yet to be exploited by homology modeling. There are several idiosyncrasies that require direct attention throughout the process of model construction, evaluation and refinement. Shifts/gaps in the alignment between the template and target, backbone outliers and side-chain rotamer outliers are among the main sources of physical errors in the structures. Low-conserved regions can be refined with loop modeling method. Residue hydrophobicity, accessibility to bound metals or glycosylation can aid in model refinement. We recommend resolving these idiosyncrasies as part of "good modeling practice" to obtain highest quality model. Decreasing physical errors in protein structures plays major role in the development of targeting agents and understanding of chemical interactions at the molecular level.

• Klíčová slova
• anaplastic lymphoma kinase, homology modeling, neuroblastoma, neurotrophic tyrosine kinase receptor, norepinephrine transporter, targeted therapy,
• Publikační typ
• časopisecké články MeSH