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- Andersson, David C., 1978-, et al.
(author)
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A multivariate approach to investigate docking parameters' effects on docking performance
- 2007
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In: Journal of chemical information and modeling. - : American Chemical Society Publications. - 1549-9596 .- 1549-960X. ; 47:4, s. 1673-1687
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Journal article (peer-reviewed)abstract
- Increasingly powerful docking programs for analyzing and estimating the strength of protein-ligand interactions have been developed in recent decades, and they are now valuable tools in drug discovery. Software used to perform dockings relies on a number of parameters that affect various steps in the docking procedure. However, identifying the best choices of the settings for these parameters is often challenging. Therefore, the settings of the parameters are quite often left at their default values, even though scientists with long experience with a specific docking tool know that modifying certain parameters can improve the results. In the study presented here, we have used statistical experimental design and subsequent regression based on root-mean-square deviation values using partial least-square projections to latent structures (PLS) to scrutinize the effects of different parameters on the docking performance of two software packages: FRED and GOLD. Protein-ligand complexes with a high level of ligand diversity were selected from the PDBbind database for the study, using principal component analysis based on 1D and 2D descriptors, and space-filling design. The PLS models showed quantitative relationships between the docking parameters and the ability of the programs to reproduce the ligand crystallographic conformation. The PLS models also revealed which of the parameters and what parameter settings were important for the docking performance of the two programs. Furthermore, the variation in docking results obtained with specific parameter settings for different protein-ligand complexes in the diverse set examined indicates that there is great potential for optimizing the parameter settings for selected sets of proteins.
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- Geschwindner, Stefan, et al.
(author)
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Characterisation of de novo mutations in the C-terminal domain of proprotein convertase subtilisin/kexin type 9.
- 2015
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In: Protein Engineering Design & Selection. - : Oxford University Press (OUP). - 1741-0126 .- 1741-0134.
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Journal article (peer-reviewed)abstract
- Proprotein convertase subtilisin/kexin type 9 (PCSK9) promotes the degradation of the hepatic low-density lipoprotein receptor (LDL-R) and is therefore a prominent therapeutic target for reducing LDL-cholesterol. The C-terminal domain of PCSK9 is unlikely to be involved in a direct extracellular interaction with the LDL-R. We probed the importance of the C-terminus for the degradation of the LDL-R by designing seven de novo mutants of PCSK9 that fill potential druggable cavities. The mutants were tested for their ability to diminish LDL uptake in human HepG2 cells and for affinity towards a calcium independent mutant of the EGF(A) domain of the human LDL-R. The later was done by a newly developed surface plasmon resonance-based assay format. We identified three mutant proteins (G517R, V610R and V644R) with decreased ability to block LDL uptake into HepG2 cells. These mutations define areas outside the direct interaction area between PCSK9 and the LDL-R that could be targeted to inhibit the PCSK9 triggered degradation of the LDL-R. We also describe the mechanistic rationalisation of the affinity changes seen with the natural occurring human D374Y (gain of function) mutation causing severe hypercholesterolaemia. The action of this mutant is due to a significantly decreased dissociation rate constant, whereas the mutation does not affect the association rate constant.
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- Lindström, Anton, 1976-, et al.
(author)
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Postprocessing of docked protein-ligand complexes using implicit solvation models
- 2011
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In: Journal of chemical information and modeling. - : American Chemical Society (ACS). - 1549-960X .- 1549-9596. ; 51:2, s. 267-282
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Journal article (peer-reviewed)abstract
- Molecular docking plays an important role in drug discovery as a tool for the structure-based design of small organic ligands for macromolecules. Possible applications of docking are identification of the bioactive conformation of a protein−ligand complex and the ranking of different ligands with respect to their strength of binding to a particular target. We have investigated the effect of implicit water on the postprocessing of binding poses generated by molecular docking using MM-PB/GB-SA (molecular mechanics Poisson−Boltzmann and generalized Born surface area) methodology. The investigation was divided into three parts: geometry optimization, pose selection, and estimation of the relative binding energies of docked protein−ligand complexes. Appropriate geometry optimization afforded more accurate binding poses for 20% of the complexes investigated. The time required for this step was greatly reduced by minimizing the energy of the binding site using GB solvation models rather than minimizing the entire complex using the PB model. By optimizing the geometries of docking poses using the GBHCT+SA model then calculating their free energies of binding using the PB implicit solvent model, binding poses similar to those observed in crystal structures were obtained. Rescoring of these poses according to their calculated binding energies resulted in improved correlations with experimental binding data. These correlations could be further improved by applying the postprocessing to several of the most highly ranked poses rather than focusing exclusively on the top-scored pose. The postprocessing protocol was successfully applied to the analysis of a set of Factor Xa inhibitors and a set of glycopeptide ligands for the class II major histocompatibility complex (MHC) Aq protein. These results indicate that the protocol for the postprocessing of docked protein−ligand complexes developed in this paper may be generally useful for structure-based design in drug discovery.
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