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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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 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.</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

Comparative Study on Separation of Diastereomers by HPLC.

Reversed (RP-HPLC) and normal phase chromatographic (NP-HPLC) separations have been developed for diastereomers ofN-acyl-1-methyl-1,2,3,4-tetrahydo-&beta;-carbolines which are acylated derivatives of simple natural &beta;-carboline alkaloids. Separations of derivatives having different acyl moieties in theO,O-diacyl-tartaric acid ester subtituent differed remarkably. Little or no resolution in either NP-HPLC or RP-HPLC could be achieved with the diacetyl-tartrate derivative. Base-line separation by RP-HPLC but no separation by NP-HPLC was possible with the bulkier and more apolar dipivaloyl derivative. Retention order of the bis-benzoylated diastereomers was reversed and separation time increased dramatically by RP-HPLC. Good separation of the medium polarity, but rigid,N-camphanyl derivative by NP-HPLC has been achieved, whereas RP-HPLC could not be used for separation of these diastereomers. Separability of different diastereomers was highly dependent on polarity and rigidity of the derivatizingN-acyl moieties. Conformational analysis by molecular mechanics and comparison of the lowest energy conformational states of the diastereomers was applied to rationalise separation-retention behaviour of stereoisomers by RP-HPLC

Investigation of genetic variants of alpha-1 acid glycoprotein by ultra-performance liquid chromatography-mass spectrometry

Genetic variants of human plasma alpha-1 acid glycoprotein (AGP) have been studied in cancer, compared with a group of healthy control. AGP has four genetic variants: AGP F1, F2, and S variants correspond to the ORM1 gene whereas AGP A corresponds to the ORM2 gene. The proportion of ORM1 and ORM2 variants were studied in plasma using a novel UPLC–MS method. Plasma total AGP level was 0.5 ± 0.2 g L−1 and the proportions of the ORM1 and ORM2 variants were 76.3 ± 8.2% and 23.7 ± 8.2%, respectively. In cancer plasma AGP levels increased fourfold and the proportion of ORM1 variants increased to 88.7 ± 6.8%. Changes in the proportion of genetic variants due to cancer were clearly significant, as shown by statistical analysis. Three different cancer types have been studied, lymphoma, melanoma, and ovarian cancer. The results did not show any difference depending on cancer type. The results indicate that, in accordance with prior expectations, the ORM1 variant is predominantly responsible for the acute-phase property of AGP