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Multivariate design of molecular docking experiments: An investigation of protein-ligand interactions
Umeå University, Faculty of Science and Technology, Department of Chemistry.
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.
Keyword [en]
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
läkemedelskemi
Identifiers
URN: urn:nbn:se:umu:diva-35736ISBN: 978-91-7459-065-4 (print)OAI: oai:DiVA.org:umu-35736DiVA: diva2:349234
Public defence
2010-10-01, Naturvetarhuset, N360, Umeå universitet, Umeå, 10:00 (Swedish)
Opponent
Supervisors
Available from: 2010-09-09 Created: 2010-09-01 Last updated: 2011-03-24Bibliographically approved
List of papers
1. A multivariate approach to investigate docking parameters' effects on docking performance
Open this publication in new window or tab >>A multivariate approach to investigate docking parameters' effects on docking performance
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2007 (English)In: Journal of chemical information and modeling, ISSN 1549-9596, Vol. 47, no 4, 1673-1687 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
American Chemical Society Publications, 2007
Identifiers
urn:nbn:se:umu:diva-16146 (URN)10.1021/ci6005596 (DOI)
Available from: 2007-08-20 Created: 2007-08-20 Last updated: 2010-09-09Bibliographically approved
2. Mapping of ligand-binding cavities in proteins
Open this publication in new window or tab >>Mapping of ligand-binding cavities in proteins
2010 (English)In: Proteins: Structure, Function, and Genetics, ISSN 0887-3585, E-ISSN 1097-0134, Vol. 78, no 6, 1408-1422 p.Article in journal (Refereed) Published
Abstract [en]

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterize and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity, and charge). This approach can provide valuable information on the similarities and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterization and mapping of "orphan structures", selection of protein structures for docking studies in structure-based design, and identification of proteins for selectivity screens in drug design programs.

Place, publisher, year, edition, pages
John Wiley & Sons, Inc, 2010
Keyword
protein cavity comparison, physicochemical properties, alignment independent, SCREEN, principal component analysis, binding sites, medicinal chemistry, drug design, PCA clustering tree, bioinformatics
National Category
Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-33671 (URN)10.1002/prot.22655 (DOI)000276369700005 ()20034113 (PubMedID)
Available from: 2010-05-03 Created: 2010-05-03 Last updated: 2011-12-21Bibliographically approved
3. Design of target-tailored virtual screening experiments
Open this publication in new window or tab >>Design of target-tailored virtual screening experiments
(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
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.
Identifiers
urn:nbn:se:umu:diva-35735 (URN)
Available from: 2010-09-06 Created: 2010-09-01 Last updated: 2010-09-09Bibliographically approved
4. Design of glycopeptides used to investigate class II MHC binding and T-Cell responses associated with autoimmune arthritis
Open this publication in new window or tab >>Design of glycopeptides used to investigate class II MHC binding and T-Cell responses associated with autoimmune arthritis
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2011 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 6, no 3, e17881- p.Article in journal (Refereed) Published
Abstract [en]

The glycopeptide fragment CII259–273 from type II collagen (CII) binds to the murine Aq and human DR4 class II Major Histocompatibility Complex (MHC II) proteins, which are associated with development of murine collagen-induced arthritis (CIA) and rheumatoid arthritis (RA), respectively. It has been shown that CII259–273 can be used in therapeutic vaccination of CIA. This glycopeptide also elicits responses from T-cells obtained from RA patients, which indicates that it has an important role in RA as well. We now present a methodology for studies of (glyco)peptide-receptor interactions based on a combination of structure-based virtual screening, ligand-based statistical molecular design and biological evaluations. This methodology included the design of a CII259–273 glycopeptide library in which two anchor positions crucial for binding in pockets of Aq and DR4 were varied. Synthesis and biological evaluation of the designed glycopeptides provided novel structure-activity relationship (SAR) understanding of binding to Aq and DR4. Glycopeptides that retained high affinities for these MHC II proteins and induced strong responses in panels of T-cell hybridomas were also identified. An analysis of all the responses revealed groups of glycopeptides with different response patterns that are of high interest for vaccination studies in CIA. Moreover, the SAR understanding obtained in this study provides a platform for the design of second-generation glycopeptides with tuned MHC affinities and T-cell responses.

Place, publisher, year, edition, pages
Public Library of Science, 2011
National Category
Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-41050 (URN)10.1371/journal.pone.0017881 (DOI)21423632 (PubMedID)
Note

Vid avhandlingens utgivning manuskript med annan titel: "Design of glycopeptide chemical probes used to investigate multiresponses associated with autoimmune arthritis"

Available from: 2011-03-17 Created: 2011-03-17 Last updated: 2017-12-11Bibliographically approved

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