Structure-based and ligand-based drug design for HER 2 receptor

In silico pharmacology suggests ginger extracts may reduce stroke risks

Aberrations in cyclic adenosine monophosphate (cAMP) signaling cascade has been linked to the allergic responses that associate with the risks of stroke or cardiovascular diseases. Phosphodiesterase 4D (PDE4D) has been shown to be highly involved in cAMP regulation and is hence implied to be a potential drug target in stroke prevention. To identify potential PDE4D inhibitors from traditional Chinese medicine (TCM), we employed machine learning modeling techniques to screen a comprehensive TCM database. The multiple linear regression (MLR) and support vector machine (SVM) models constructed have correlation coefficients of 0.8234 and 0.7854 respectively. Three candidates from the ginger family were identified based on the prediction models. Molecular dynamics simulation further validated the binding stabilities of each candidate in comparison to the control inhibitor L-454560. The intermolecular distances suggested that the candidates could hinder PDE4D from binding to cAMP. Furthermore, the HypoGen validation suggested that top2, top3, and the control L-454560 mapped with the predicted pharmacophores. The results suggested that the 3 compounds identified from the ginger family were capable in inhibiting cAMP binding and hydrolysis by PDE4D. We further identified and characterized the ligand binding properties that are associated with the inhibition of PDE4D.

Protein-protein interactions: principles, techniques, and their potential role in new drug development

A vast network of genes is inter-linked through protein-protein interactions and is critical component of almost every biological process under physiological conditions. Any disruption of the biologically essential network leads to pathological conditions resulting into related diseases. Therefore, proper understanding of biological functions warrants a comprehensive knowledge of protein-protein interactions and the molecular mechanisms that govern such processes. The importance of protein-protein interaction process is highlighted by the fact that a number of powerful techniques/methods have been developed to understand how such interactions take place under various physiological and pathological conditions. Many of the key protein-protein interactions are known to participate in disease-associated signaling pathways, and represent novel targets for therapeutic intervention. Thus, controlling protein-protein interactions offers a rich dividend for the discovery of new drug targets. Availability of various tools to study and the knowledge of human genome have put us in a unique position to understand highly complex biological network, and the mechanisms involved therein. In this review article, we have summarized protein-protein interaction networks, techniques/methods of their binding/kinetic parameters, and the role of these interactions in the development of potential tools for drug designing.

The key residues of active sites on the catalytic fragment for paclitaxel interacting with poly (ADP-ribose) polymerase

Poly(ADP-ribose) polymerase (PARP) is regarded as a target protein for paclitaxel (PTX) to bind. An important issue is to identify the key residues as active sites for PTX interacting with PARP, which will help to understand the potential drug activity of PTX against cancer cells. Using docking method and MD simulation, we have constructed a refined structure of PTX docked on the catalytic function domain of PARP (PDB code: 1A26). The residues Glu327(988), Tyr246(907), Lys242(903), His165(826), Asp105(766), Gln102(763) and Gln98(759) in PARP are identified as potential sites involved in interaction with PTX according to binding energy (E(b)) between PTX and single residue calculated with B3LYP/6-31G(d,p). These residues form an active binding pocket located on the surface of the catalytic fragment, possibly interacting with the required groups of PTX leading to its activity against cancer cells. It is noted that most of the active sites make conatct with the "southern hemisphere" of PTX except for one residue, Tyr246(907), which interacts with the "northern hemisphere" of PTX. The conformation of PTX in complex with the catalytic fragment is observed as being T-shaped, similar to that complexed with β-tubulin. The total Eb of -269.9 kJ/mol represents the potent interaction between PTX and the catalytic fragment, implying that PTX can readily bind to the active pocket. The tight association of PTX with the catalytic fragment would inhibit PARP activation, suggesting a potential application of PTX as an effective antineoplastic agent.

Molecular dynamics simulation and density functional theory studies on the active pocket for the binding of paclitaxel to tubulin

Paclitaxel (PTX) is used to treat various cancers, but it also causes serious side effects and resistance. To better design similar compounds with less toxicity and more activity against drug-resistant tumors, it is important to clearly understand the PTX-binding pocket formed by the key residues of active sites on β-tubulin. Using a docking method, molecular dynamics (MD) simulation and density functional theory (DFT), we identified some residues (such as Arg278, Asp26, Asp226, Glu22, Glu27, His229, Arg369, Lys218, Ser277 and Thr276) on β-tubulin that are the active sites responsible for interaction with PTX. Another two residues, Leu371 and Gly279, also likely serve as active sites. Most of these sites contact with the "southern hemisphere" of PTX; only one key residue interacts with the "northern hemisphere" of PTX. These key residues can be divided into four groups, which serve as active compositions in the formation of an active pocket for PTX binding to β-tubulin. This active binding pocket enables a very strong interaction (the strength is predicted to be in the range of -327.8 to -365.7 kJ mol(-1)) between β-tubulin and PTX, with various orientated conformations. This strong interaction means that PTX possesses a high level of activity against cancer cells, a result that is in good agreement with the clinical mechanism of PTX. The described PTX pocket and key active residues will be applied to probe the mechanism of tumor cells resistant to PTX, and to design novel analogs with superior properties.

Potent inhibitor design against H1N1 swine influenza: structure-based and molecular dynamics analysis for M2 inhibitors from traditional Chinese medicine database

The rapid spread of influenza virus subtype H1N1 poses a great threat to million lives worldwide. To search for new anti-influenza compounds, we performed molecular docking and molecular dynamics simulation to identify potential traditional Chinese medicine (TCM) constituents that could block influenza M2 channel activity. Quinic acid, genipin, syringic acid, cucurbitine, fagarine, and methyl isoferulate all have extremely well docking results as compared to control amantadine. Further de novo drug design suggests that derivatives of genipin and methyl isoferulate could have enhanced binding affinity towards M2 channel. Selected molecular dynamics simulations of M2-derivative complexes show stable hydrogen bond interactions between the derivatives and M2 residues, Ser10 and Ala9. To our best knowledge, this is the first study on the anti-viral activity of the above listed TCM compounds.

A conformationally constrained peptidomimetic binds to the extracellular region of HER2 protein

Human epidermal growth factor receptor 2 (HER2) is a member of the human epidermal growth factor receptor kinases (other members include EGFR or HER1, HER3, and HER4) that are involved in signaling cascades for cell growth and differentiation. It is well established that HER2-mediated heterodimerization has important implications in cancer. Deregulation of signaling pathways and overexpression of HER2 is known to occur in cancer cells, indicating a role of HER2 in tumorigenesis. Therefore, blocking HER2-mediated signaling has potential therapeutic value. We have designed several peptidomimetics to inhibit HER2-mediated signaling for cell growth. One of the compounds (HERP5, Arg-beta Naph-Phe) exhibited antiproliferative activity with IC(50) values in the micromolar-to-nanomolar range in breast cancer cell lines. Binding of fluorescently labeled HERP5 to HER2 protein was evaluated by fluorescence assay, microscopy, and circular dichroism spectroscopy. Results indicated that HERP5 binds to the extracellular region of the HER2 protein. Structure of the peptidomimetic HERP5 was studied by NMR and molecular dynamics simulations. Based on these results a model was proposed for HER2-EGFR dimerization and possible blocking by HERP5 peptidomimetic using a protein-protein docking method.

TCM Database@Taiwan: the world's largest traditional Chinese medicine database for drug screening in silico

Rapid advancing computational technologies have greatly speeded up the development of computer-aided drug design (CADD). Recently, pharmaceutical companies have increasingly shifted their attentions toward traditional Chinese medicine (TCM) for novel lead compounds. Despite the growing number of studies on TCM, there is no free 3D small molecular structure database of TCM available for virtual screening or molecular simulation. To address this shortcoming, we have constructed TCM Database@Taiwan (http://tcm.cmu.edu.tw/) based on information collected from Chinese medical texts and scientific publications. TCM Database@Taiwan is currently the world's largest non-commercial TCM database. This web-based database contains more than 20,000 pure compounds isolated from 453 TCM ingredients. Both cdx (2D) and Tripos mol2 (3D) formats of each pure compound in the database are available for download and virtual screening. The TCM database includes both simple and advanced web-based query options that can specify search clauses, such as molecular properties, substructures, TCM ingredients, and TCM classification, based on intended drug actions. The TCM database can be easily accessed by all researchers conducting CADD. Over the last eight years, numerous volunteers have devoted their time to analyze TCM ingredients from Chinese medical texts as well as to construct structure files for each isolated compound. We believe that TCM Database@Taiwan will be a milestone on the path towards modernizing traditional Chinese medicine.