Zsolt Bikádi

BACKGROUND: Molecular 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. RESULTS: The 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 A 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. CONCLUSION: Our 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.

The human breast cancer resistance protein (BCRP/ABCG2) is the second member of the G subfamily of the large ATP-binding cassette (ABC) transporter superfamily. BCRP was initially discovered in multidrug resistant breast cancer cell lines where it confers resistance to chemotherapeutic agents such as mitoxantrone, topotecan and methotrexate by extruding these compounds out of the cell. BCRP is capable of transporting non-chemotherapy drugs and xenobiotiocs as well, including nitrofurantoin, prazosin, glyburide, and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine. BCRP is frequently detected at high levels in stem cells, likely providing xenobiotic protection. BCRP is also highly expressed in normal human tissues including the small intestine, liver, brain endothelium, and placenta. Therefore, BCRP has been increasingly recognized for its important role in the absorption, elimination, and tissue distribution of drugs and xenobiotics. At present, little is known about the transport mechanism of BCRP, particularly how it recognizes and transports a large number of structurally and chemically unrelated drugs and xenobiotics. Here, we review current knowledge of structure and function of this medically important ABC efflux drug transporter.

For the first time, an interaction between the non-toxic, cancer chemopreventive agent curcumin and both natural and synthetic DNA duplexes has been demonstrated by using circular dichroism (CD) and absorption spectroscopy techniques. Upon addition of curcumin to calf thymus DNA, poly(dG-dC).poly(dG-dC) and poly(dA-dT).poly(dA-dT) solutions, an intense positive induced CD band centered around 460-470 nm was observed depending on the actual pH and Na+ ion concentration of the medium; no CD signal was obtained, however, with single stranded poly(dC). Interaction of curcumin with calf thymus DNA was observed already at pH 6.5 in contrast with poly(dG-dC).poly(dG-dC) which induces no extrinsic Cotton effect above a pH value of 5. The protonated, Hoogsteen base-paired structure of poly(dG-dC).poly(dG-dC) is necessary for curcumin binding while the alternating AT-rich polymer formed complexes with curcumin only at certain Na+ concentrations. Evaluation of the spectral data and molecular modeling calculations suggested that curcumin, this dietary polyphenolic compound binds in the minor groove of the double helix. The mechanism of the induced CD activity, the effects of the pH and Na+ ions on the ligand binding and conformation of the double helix are discussed in detail. As well as being an essentially new phenolic minor groove binder agent curcumin is also a promising molecular probe to study biologically important, pH and cation induced conformational polymorphisms of nucleic acids.

MOTIVATION: Human serum albumin (HSA), the most abundant plasma protein is well known for its extraordinary binding capacity for both endogenous and exogenous substances, including a wide range of drugs. Interaction with the two principal binding sites of HSA in subdomain IIA (site 1) and in subdomain IIIA (site 2) controls the free, active concentration of a drug, provides a reservoir for a long duration of action and ultimately affects the ADME (absorption, distribution, metabolism, and excretion) profile. Due to the continuous demand to investigate HSA binding properties of novel drugs, drug candidates and drug-like compounds, a support vector machine (SVM) model was developed that efficiently predicts albumin binding. Our SVM model was integrated to a free, web-based prediction platform (http://albumin.althotas.com). Automated molecular docking calculations for prediction of complex geometry are also integrated into the web service. The platform enables the users (i) to predict if albumin binds the query ligand, (ii) to determine the probable ligand binding site (site 1 or site 2), (iii) to select the albumin X-ray structure which is complexed with the most similar ligand and (iv) to calculate complex geometry using molecular docking calculations. Our SVM model and the potential offered by the combined use of in silico calculation methods and experimental binding data is illustrated.