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Design of target-tailored virtual screening experiments
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Howard Hughes Institute, Department of Biochemistry and Molecular Biophysics, Center for Computational Biology and Bioinformatics, Columbia University..
Umeå University, Faculty of Science and Technology, Department of Chemistry.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Discovering molecules with a desired biological function is one of the great challenges in drug research. To discover new lead molecules, in silico virtual screens (VS) are often conducted, in which databases of molecules are screened for potential binders to a specific protein, using molecular docking. The choice of docking software and parameter settings within the software can significantly influence the outcome of a VS. In this study, we have applied chemometric methods such as DoE, principal component analysis (PCA) and partial least-square projections to latent structure (PLS) to simulated VS experiments to find and compare suitable conditions for performing VS against six protein targets selected from the DUD databases. The docking parameters in FRED, and scoring functions in both FRED and GOLD docking software, were varied according to a statistical experimental design and a PLS model was calculated to correlate the experimental setup to the VS outcome. The study revealed that the choice of scoring function has the greatest influence on VS outcome, and that other parameters have varying influence, depending on the protein target. We also found that substantial bias can be introduced by the lack of variation of molecule properties in the databases used in the screening. The results indicate that docking experiments should be tailored to the protein target in order to obtain satisfactory VS results and that our methodology provides a suitable approach for such tailoring.

Keyword [en]
Virtual screening, design of experiments, DOE, principal component analysis, PCA, partial least squares, PLS, docking, angiotensin-converting enzyme, ACE, Acetylcholinesterase, AChE, cyclin-dependent kinase 2, CDK2, fibroblast growth factor receptor 1, FGFr1, coagulation factor Xa, FXa, trypsin, receiver operating characteristics, enrichment factor directory of useful decoys, DUD.
URN: urn:nbn:se:umu:diva-35735OAI: diva2:346553
Available from: 2010-09-06 Created: 2010-09-01 Last updated: 2010-09-09Bibliographically approved
In thesis
1. Multivariate design of molecular docking experiments: An investigation of protein-ligand interactions
Open this publication in new window or tab >>Multivariate design of molecular docking experiments: An investigation of protein-ligand interactions
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

To be able to make informed descicions regarding the research of new drug molecules (ligands), it is crucial to have access to information regarding the chemical interaction between the drug and its biological target (protein). Computer-based methods have a given role in drug research today and, by using methods such as molecular docking, it is possible to investigate the way in which ligands and proteins interact. Despite the acceleration in computer power experienced in the last decades many problems persist in modelling these complicated interactions. The main objective of this thesis was to investigate and improve molecular modelling methods aimed to estimate protein-ligand binding. In order to do so, we have utilised chemometric tools, e.g. design of experiments (DoE) and principal component analysis (PCA), in the field of molecular modelling. More specifically, molecular docking was investigated as a tool for reproduction of ligand poses in protein 3D structures and for virtual screening. Adjustable parameters in two docking software were varied using DoE and parameter settings were identified which lead to improved results. In an additional study, we explored the nature of ligand-binding cavities in proteins since they are important factors in protein-ligand interactions, especially in the prediction of the function of newly found proteins. We developed a strategy, comprising a new set of descriptors and PCA, to map proteins based on their cavity physicochemical properties. Finally, we applied our developed strategies to design a set of glycopeptides which were used to study autoimmune arthritis. A combination of docking and statistical molecular design, synthesis and biological evaluation led to new binders for two different class II MHC proteins and recognition by a panel of T-cell hybridomas. New and interesting SAR conclusions could be drawn and the results will serve as a basis for selection of peptides to include in in vivo studies.

Place, publisher, year, edition, pages
Umeå: Umeå universitet. Kemiska institutionen, 2010
Molecular docking, chemometrics, multivariate analysis, principal component analysis, PCA, design of experiments, DoE, partial least-square projections to latent structures, PLS, scoring functions, ligand-binding cavity, major histocompatibility complex, MHC, glycopeptide, T-cell.
National Category
Medicinal Chemistry
Research subject
urn:nbn:se:umu:diva-35736 (URN)978-91-7459-065-4 (ISBN)
Public defence
2010-10-01, Naturvetarhuset, N360, Umeå universitet, Umeå, 10:00 (Swedish)
Available from: 2010-09-09 Created: 2010-09-01 Last updated: 2011-03-24Bibliographically approved

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Andersson, David C.Linusson Jonsson, Anna
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