Eszter Hazai

Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock.

BackgroundMolecular docking methods are commonly used for predicting binding modes and energies of ligands to proteins. For accurate complex geometry and binding energy estimation, an appropriate method for calculating partial charges is essential. AutoDockTools software, the interface for preparing input files for one of the most widely used docking programs AutoDock 4, utilizes the Gasteiger partial charge calculation method for both protein and ligand charge calculation. However, it has already been shown that more accurate partial charge calculation - and as a consequence, more accurate docking- can be achieved by using quantum chemical methods. For docking calculations quantum chemical partial charge calculation as a routine was only used for ligands so far. The newly developed Mozyme function of MOPAC2009 allows fast partial charge calculation of proteins by quantum mechanical semi-empirical methods. Thus, in the current study, the effect of semi-empirical quantum-mechanical partial charge calculation on docking accuracy could be investigated.ResultsThe docking accuracy of AutoDock 4 using the original AutoDock scoring function was investigated on a set of 53 protein ligand complexes using Gasteiger and PM6 partial charge calculation methods. This has enabled us to compare the effect of the partial charge calculation method on docking accuracy utilizing AutoDock 4 software. Our results showed that the docking accuracy in regard to complex geometry (docking result defined as accurate when the RMSD of the first rank docking result complex is within 2 Å of the experimentally determined X-ray structure) significantly increased when partial charges of the ligands and proteins were calculated with the semi-empirical PM6 method.Out of the 53 complexes analyzed in the course of our study, the geometry of 42 complexes were accurately calculated using PM6 partial charges, while the use of Gasteiger charges resulted in only 28 accurate geometries. The binding affinity estimation was not influenced by the partial charge calculation method - for more accurate binding affinity prediction development of a new scoring function for AutoDock is needed.ConclusionOur results demonstrate that the accuracy of determination of complex geometry using AutoDock 4 for docking calculation greatly increases with the use of quantum chemical partial charge calculation on both the ligands and proteins.

Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein

Human P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter that confers resistance to a wide range of chemotherapeutic agents in cancer cells by active efflux of the drugs from cells. P-gp also plays a key role in limiting oral absorption and brain penetration and in facilitating biliary and renal elimination of structurally diverse drugs. Thus, identification of drugs or new molecular entities to be P-gp substrates is of vital importance for predicting the pharmacokinetics, efficacy, safety, or tissue levels of drugs or drug candidates. At present, publicly available, reliable in silico models predicting P-gp substrates are scarce. In this study, a support vector machine (SVM) method was developed to predict P-gp substrates and P-gp-substrate interactions, based on a training data set of 197 known P-gp substrates and non-substrates collected from the literature. We showed that the SVM method had a prediction accuracy of approximately 80% on an independent external validation data set of 32 compounds. A homology model of human P-gp based on the X-ray structure of mouse P-gp as a template has been constructed. We showed that molecular docking to the P-gp structures successfully predicted the geometry of P-gp-ligand complexes. Our SVM prediction and the molecular docking methods have been integrated into a free web server (http://pgp.althotas.com), which allows the users to predict whether a given compound is a P-gp substrate and how it binds to and interacts with P-gp. Utilization of such a web server may prove valuable for both rational drug design and screening.

Homology modeling of breast cancer resistance protein (ABCG2)

BCRP (also known as ABCG2, MXR, and ABC-P) is a member of the ABC family that transports a wide variety of substrates. BCRP is known to play a key role as a xenobiotic transporter. Since discovering its role in multidrug resistance, considerable efforts have been made in order to gain deeper understanding of BCRP structure and function. The recent study was aimed at predicting BCRP structure by creating a homology model. Based on sequence similarity with known structures of full-length, NB and TM domain of ABC transporters, TM, NB, and linker regions of BCRP were defined. The NB domain of BCRP was modeled using MalK as a template. Based on secondary structure prediction of BCRP and comparison of the transmembrane connecting regions of known structures of ABC transporters, the TM domain arrangement of BCRP was established and was found to resemble to that of the recently published crystal structure of Sav1866. Thus, an initial alignment of TM domain of BCRP was established using Sav1866 as a template. This alignment was subsequently refined using constrains derived from secondary structure and TM predictions and the final model was built. Finally, the complete homodimer ABCG2 model was generated using Sav1866 as template. Furthermore, known ligands of BCRP were docked to our model in order to define possible binding sites. The results of molecular dockings of known BCRP substrates to the BCRP model were in agreement with recently published experimental data indicating multiple binding sites in BCRP.

Identification of a polyoxometalate inhibitor of the DNA binding activity of Sox2.

Aberrant expression of transcription factors is a frequent cause of disease, yet drugs that modulate transcription factor protein-DNA interactions are presently unavailable. To this end, the chemical tractability of the DNA binding domain of the stem cell inducer and oncogene Sox2 was explored in a high-throughput fluorescence anisotropy screen. The screening revealed a Dawson polyoxometalate (K(6)[P(2)Mo(18)O(62)]) as a direct and nanomolar inhibitor of the DNA binding activity of Sox2. The Dawson polyoxometalate (Dawson-POM) was found to be selective for Sox2 and related Sox-HMG family members when compared to unrelated paired and zinc finger DNA binding domains. [(15)N,(1)H]-Transverse relaxation optimized spectroscopy (TROSY) experiments coupled with docking studies suggest an interaction site of the POM on the Sox2 surface that enabled the rationalization of its inhibitory activity. The unconventional molecular scaffold of the Dawson-POM and its inhibitory mode provides strategies for the development of drugs that modulate transcription factors.

Natural product inspired antibacterial tetramic acid libraries with dual enzyme inhibition

The application of natural product inspired synthesis has identified novel antibacterial tetramic acids which exhibit wide ranging antibacterial activity, and which provide potential lead structures for antibacterial drug discovery. Their phenotypic activity appears to correlate with action at two enzymes, UPPS and RNAP, which operate in independent metabolic pathways. SAR maps and identification of their relevant binding sites by molecular modelling has been achieved, and characterisation of the most active compounds suggests that these systems offer potential for topical antibiotics but that for oral and injectable use further optimisation is required.

Predicting substrates of the human breast cancer resistance protein using a support vector machine method

BackgroundHuman breast cancer resistance protein (BCRP) is an ATP-binding cassette (ABC) efflux transporter that confers multidrug resistance in cancers and also plays an important role in the absorption, distribution and elimination of drugs. Prediction as to if drugs or new molecular entities are BCRP substrates should afford a cost-effective means that can help evaluate the pharmacokinetic properties, efficacy, and safety of these drugs or drug candidates. At present, limited studies have been done to develop in silico prediction models for BCRP substrates.In this study, we developed support vector machine (SVM) models to predict wild-type BCRP substrates based on a total of 263 known BCRP substrates and non-substrates collected from literature. The final SVM model was integrated to a free web server.ResultsWe showed that the final SVM model had an overall prediction accuracy of ~73% for an independent external validation data set of 40 compounds. The prediction accuracy for wild-type BCRP substrates was ~76%, which is higher than that for non-substrates. The free web server (http://bcrp.althotas.com) allows the users to predict whether a query compound is a wild-type BCRP substrate and calculate its physicochemical properties such as molecular weight, logP value, and polarizability.ConclusionsWe have developed an SVM prediction model for wild-type BCRP substrates based on a relatively large number of known wild-type BCRP substrates and non-substrates. This model may prove valuable for screening substrates and non-substrates of BCRP, a clinically important ABC efflux drug transporter.

Association of cytochrome P450 enzymes is a determining factor in their catalytic activity

Previously, our laboratory demonstrated that one cytochrome P450 isoenzyme can influence the catalytic properties of another P450 isoenzyme when combined in a reconstituted system. Moreover, our data and that of other investigators indicate that P450 interaction is required for catalytic activity even when one isoenzyme is present. The goal of the current study was to examine the possible mechanism of these interactions in more detail. Analyzing recently published X-ray data of microsomal P450 enzymes and protein docking studies, four types of dimer formations of P450 enzymes were examined in more detail. In case of two dimer types, the aggregating partner was shown to contribute to NADPH cytochrome P450 reductase (CPR) binding-a flavoprotein whose interaction with P450 is required for expressing P450 functional activity of the neighboring P450 moiety. Thus, it was shown that dimerization of P450 enzymes might result in an altered affinity towards the CPR. Two dimer types were shown to exist only in the presence of a substrate, while the other two types exist also without a substrate present. The molecular basis was established for the fact that the presence of a substrate and other P450 enzymes simultaneously determine the catalytic activity. Furthermore, a kinetic model was improved describing the catalytic activity of P450 enzymes as a function of CPR concentration based on equilibrium between different supramolecular organizations of P450 enzymes. This model was successfully applied in order to explain our experimental data and that of other investigators.

In silico description of differential enantioselectivity in methoxychlor O-demethylation by CYP2C enzymes

Methoxychlor undergoes metabolism by cytochrome P450 (CYP) enzymes forming a chiral mono-phenolic derivative (Mono-OH-M) as main metabolite. In the current study, members of the CYP2C family were examined for their chiral preference in Mono-OH-M formation. CYP2C9 and CYP2C19 possessed high enantioselectivity favoring the formation of S-Mono-OH-M; CYP2C3 showed no enantioselectivity, whereas CYP2C5 slightly favored the formation of R-Mono-OH-M. Molecular modeling calculations were utilized in order to explain the observed differences in chiral preference of CYP2C enzymes. Molecular docking calculations could describe neither the existence of chiral preference in metabolism, nor the enantiomer which is preferentially formed. Molecular dynamic calculations were also carried out and were found to be useful for accurate description of chiral preference in biotransformation of methoxychlor by CYP2C enzymes. An in silico model capable of predicting chiral preference in cytochrome P450 enzymes in general can be developed based on the analysis of the stability and rigidity parameters of interacting partners during molecular dynamic simulation.

Inhibition of hypoxia-inducible factor 1 with acriflavine sensitizes hypoxic tumor cells to photodynamic therapy with zinc phthalocyanine-encapsulating cationic liposomes

Photodynamic therapy (PDT) is a tumor treatment modality in which a tumorlocalized photosensitizer is excited with light, which results in local production of reactive oxygen species, destruction of tumor vasculature, tumor hypoxia, tumor cell death, and induction of an anti-tumor immune response. However, pre-existing tumor hypoxia may desensitize tumors to PDT by activating the hypoxia-inducible factor 1 (HIF-1) survival pathway. Therefore, we hypothesized that inhibition of HIF-1 with acriflavine (ACF) would exacerbate cell death in human epidermoid carcinoma (A431) cells. PDT of A431 tumor cells was performed using newly developed and optimized PEGylated cationic liposomes containing the photosensitizer zinc phthalocyanine (ZnPC). Molecular docking revealed that ACF binds to the dimerization domain of HIF-1α, and confocal microscopy confirmed translocation of ACF from the cytosol to the nucleus under hypoxia. HIF-1 was stabilized in hypoxic, but not normoxic, A431 cells following PDT. Inhibition of HIF-1 with ACF increased the extent of PDT-induced cell death under hypoxic conditions and reduced the expression of the HIF-1 target genes VEGF, PTGS2, and EDN1. Moreover, co-encapsulation of ACF in the aqueous core of ZnPC-containing liposomes yielded an adjuvant effect on PDT efficacy that was comparable to non-encapsulated ACF. In conclusion, HIF-1 contributes to A431 tumor cell survival following PDT with liposomal ZnPC. Inhibition of HIF-1 with free or liposomal ACF improves PDT efficacy.

A detailed study of antibacterial 3-acyltetramic acids and 3-acylpiperidine-2,4-diones.

Inspired by the core fragment of antibacterial natural products such as streptolydigin, 3‐acyltetramic acids and 3‐acylpiperidine‐2,4‐diones have been synthesised from the core heterocycle by direct acylation with the substituted carboxylic acids using a strategy which permits ready access to a structurally diverse compound library. The antibacterial activity of these systems has been established against a panel of Gram‐positive and Gram‐negative bacteria, with activity mostly against the former, which in some cases is very potent. Data consistent with modes of action against undecaprenylpyrophosphate synthase (UPPS) and/or RNA polymerase (RNAP) for a small subset of the library has been obtained. The most active compounds have been shown to exhibit binding at known binding sites of streptolydigin and myxopyronin at UPPS and RNAP. These systems offer potential for their antibacterial activity, and further demonstrate the use of natural products as biologically validated starting points for drug discovery.