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- Jacobsson, Micael, 1975-
(author)
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Structure-Based Virtual Screening : New Methods and Applications in Infectious Diseases
- 2008
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Doctoral thesis (other academic/artistic)abstract
- A drug discovery project typically starts with a pharmacological hypothesis: that the modulation of a specific molecular biological mechanism would be beneficial in the treatment of the targeted disease. In a small-molecule project, the next step is to identify hits, i.e. molecules that can effect this modulation. These hits are subsequently expanded into hit series, which are optimised with respect to pharmacodynamic and pharmacokinetic properties, through medicinal chemistry. Finally, a drug candidate is clinically developed into a new drug. This thesis concerns the use of structure-based virtual screening in the hit identification phase of drug discovery.Structure-based virtual screening involves using the known 3D structure of a target protein to predict binders, through the process of docking and scoring. Docking is the prediction of potential binding poses, and scoring is the prediction of the free energy of binding from those poses. Two new methodologies, based on post-processing of scoring results, were developed and evaluated using model systems. Both methods significantly increased the enrichment of true positives. Furthermore, correlation was observed between scores and simple molecular properties, and identified as a source of false positives in structure-based virtual screening.Two target proteins, Mycobacterium tuberculosis ribose-5-phosphate isomerase, a potential drug target in tuberculosis, and Plasmodium falciparum spermidine synthase, a potential drug target in malaria, were subjected to docking and virtual screening. Docking of substrates and products of ribose-5-phosphate isomerase led to hypotheses on the role of individual residues in the active site. Additionally, virtual screening was used to predict 48 potential inhibitors, but none was confirmed as an inhibitor or binder to the target enzyme. For spermidine synthase, structure-based virtual screening was used to predict 32 potential active-site binders. Seven of these were confirmed to bind in the active site.
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| 2. |
- Lindgren, Cecilia, 1988-
(author)
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Design strategies for new drugs targeting multicomponent systems : focusing on class II MHC proteins and acetylcholinesterase
- 2017
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Doctoral thesis (other academic/artistic)abstract
- The field of medicinal chemistry is constantly evolving. Aided by advances within techniques as well as knowledge of biological systems, increasingly complex targets and drugs can be considered. This thesis includes two projects focusing on the design of drugs targeting multicomponent systems, referring to systems for which multiple components must be considered during the drug design process.In the first project, the long-term goal is to develop a vaccine against the autoimmune disease rheumatoid arthritis (RA). The cause of RA is unknown, but it is genetically linked to expression of class II MHC proteins that present antigens to T-cell receptors (TCRs), responsible for initiating an immune response. A glycopeptide fragment, CII259–273, from type II collagen has shown promising results as a vaccine against arthritis resembling RA in mice. CII259–273 binds to the class II MHC protein followed by presentation to the TCR, forming a multicomponent system.We have used molecular dynamics (MD) simulations to study the effect that modifications of CII259–273 have on the multicomponent system. Non-native amino acids and amide bond isosteres have been introduced. This has demonstrated the importance of retaining the backbone conformation of CII259–273, as well as the hydrogen bonds formed to the backbone. The ability to introduce such modifications would be of value to affect the potency towards the MHC protein, and prevent degradation of the glycopeptide. The studies have revealed a multicomponent system that is highly sensitive to even small modifications that can affect the dynamics of the entire complex.In the second project, the long-term goal is to develop a broad-spectrum antidote against nerve agents. Nerve agents are extremely toxic compounds that act by covalently inhibiting the enzyme acetylcholinesterase (AChE), which is essential for termination of nerve signalling. A major limitation of current antidotes is that their efficiency is dependent on the type of nerve agent. A broad-spectrum antidote must be able to bind to the multicomponent system consisting of AChE covalently inhibited by different nerve agents. It will then act by performing a nucleophilic attack on the nerve agent adduct, thus breaking the covalent bond to AChE.We have used statistical molecular design (SMD) and quantitative structure-activity relationship (QSAR) modelling to identify a fragment with a potency for AChE inhibited by different nerve agents. A nucleophilic component able to restore the enzyme to the active form was thereafter introduced. This resulted in a functional reactivator, efficient for multiple nerve agents. Furthermore, the mechanism of reactivation has been investigated through structural studies, enabled by a combination of X-ray crystallography and molecular modelling. A high flexibility of the reactivator, as well as the ability to bind to AChE in multiple conformations, are defined as important properties for a broad-spectrum antidote.
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| 3. |
- Lindh, Martin, 1981-
(author)
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Computational Modelling in Drug Discovery : Application of Structure-Based Drug Design, Conformal Prediction and Evaluation of Virtual Screening
- 2017
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Doctoral thesis (other academic/artistic)abstract
- Structure-based drug design and virtual screening are areas of computational medicinal chemistry that use 3D models of target proteins. It is important to develop better methods in this field with the aim of increasing the speed and quality of early stage drug discovery.The first part of this thesis focuses on the application of structure-based drug design in the search for inhibitors for the protein 1-deoxy-D-xylulose-5-phosphate reductoisomerase (DXR), one of the enzymes in the DOXP/MEP synthetic pathway. This pathway is found in many bacteria (such as Mycobacterium tuberculosis) and in the parasite Plasmodium falciparum.In order to evaluate and improve current virtual screening methods, a benchmarking data set was constructed using publically available high-throughput screening data. The exercise highlighted a number of problems with current data sets as well as with the use of publically available high-throughput screening data. We hope this work will help guide further development of well designed benchmarking data sets for virtual screening methods.Conformal prediction is a new method in the computer-aided drug design toolbox that gives the prediction range at a specified level of confidence for each compound. To demonstrate the versatility and applicability of this method we derived models of skin permeability using two different machine learning methods; random forest and support vector machines.
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