Activity of diverse chalcones against several targets: statistical analysis of a high-throughput virtual screen of a custom chalcone library
- Authors: Sarron, Arthur F D
- Date: 2020
- Subjects: Acetophenone , Benzaldehyde , Ketones , Pyruvate kinase , Drug development , Aromatic compounds , Heat shock proteins
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/116028 , vital:34291
- Description: Chalcone family molecules are well known to have therapeutic proprieties (anti-inflammatory, anti-microbial or anti-cancer, etc). However the mechanism of action in some cases is not well known. A virtual library of this family of compounds was constructed using custom scripts, based on the aldol condensation, and this library was modified further to analogues by expansion of the α,β-unsaturated ketone linker. Acetophenone and benzaldehyde derivatives which are available and purchasable were used as a base to design the chalcone virtual library. 8063 chalcones were constructed and geometrically optimized with Gaussian 09. Their physicochemical characteristics linked to the Lipinski rules were analyzed with Knime and CDK. The entire library was after docked against several targets including HIV-1 integrase, MRSA pyruvate kinase, HSP90, COX-1, COX-2, ALR2, MAOA, MAOB, acetylcholinesterase, butyrylcholinesterase and PLA2. With the exception of MAOA, which does not have a crystal structure ligand, all dockings were validated by redocking the original ligand provided by the literature. These targets are known in the literature to be inhibited by chalcone-derivatives. However, specificity of the particular known chalcone inhibitors to the particular targets is not known. To this end the performance of the generated chalcone library against the list of targets was of interest. The binding energy of ligand-protein complexes was generally good across the library. Statistical analysis including principal component analysis and hierarchical clustering analysis were made in order to investigate for any physical/chemical characteristics which might explain what chalcone features affect the binding energy of the ligand-protein complexes. The spherical polar coordinates defining the orientation of the binding poses were also calculated and used in the statistical analysis. The statistical analysis has allowed us to hypothesize the importance of these radial distances and the polar angles of key atoms in the chalcones in binding to the pyruvate kinase crystal structure. This was validated by the docking of another small library of compound models in which the α,β-unsaturated ketone chain of the chalcone was replaced by incrementally longer conjugated chains. Further studies on the chalcones themselves reveal rotameric systems in both cis and trans-configurations (which may impact binding), and also studied was the effect of Topliss-based modification and its impact of binding to HSP90. Molecular dynamics confirmed good binding of identified chalcone hits.
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Structural bioinformatics studies and tool development related to drug discovery
- Authors: Hatherley, Rowan
- Date: 2016
- Subjects: Structural bioinformatics , Drug development , Natural products -- Databases , Natural products -- Biotechnology , Sequence alignment (Bioinformatics) , Malaria -- Chemotherapy , Heat shock proteins , Plasmodium falciparum
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: vital:4164 , http://hdl.handle.net/10962/d1020021
- Description: This thesis is divided into two distinct sections which can be combined under the broad umbrella of structural bioinformatics studies related to drug discovery. The first section involves the establishment of an online South African natural products database. Natural products (NPs) are chemical entities synthesised in nature and are unrivalled in their structural complexity, chemical diversity, and biological specificity, which has long made them crucial to the drug discovery process. South Africa is rich in both plant and marine biodiversity and a great deal of research has gone into isolating compounds from organisms found in this country. However, there is no official database containing this information, making it difficult to access for research purposes. This information was extracted manually from literature to create a database of South African natural products. In order to make the information accessible to the general research community, a website, named “SANCDB”, was built to enable compounds to be quickly and easily searched for and downloaded in a number of different chemical formats. The content of the database was assessed and compared to other established natural product databases. Currently, SANCDB is the only database of natural products in Africa with an online interface. The second section of the thesis was aimed at performing structural characterisation of proteins with the potential to be targeted for antimalarial drug therapy. This looked specifically at 1) The interactions between an exported heat shock protein (Hsp) from Plasmodium falciparum (P. falciparum), PfHsp70-x and various host and exported parasite J proteins, as well as 2) The interface between PfHsp90 and the heat shock organising protein (PfHop). The PfHsp70-x:J protein study provided additional insight into how these two proteins potentially interact. Analysis of the PfHsp90:PfHop also provided a structural insight into the interaction interface between these two proteins and identified residues that could be targeted due to their contribution to the stability of the Hsp90:Hop binding complex and differences between parasite and human proteins. These studies inspired the development of a homology modelling tool, which can be used to assist researchers with homology modelling, while providing them with step-by-step control over the entire process. This thesis presents the establishment of a South African NP database and the development of a homology modelling tool, inspired by protein structural studies. When combined, these two applications have the potential to contribute greatly towards in silico drug discovery research.
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