Structure-based inhibitor design and validation: Application to Plasmodium falciparum glutathione S-transferase Marli Botha MSc. Bioinformatics

Marli Botha © CSIR Background Structure-based inhibitor design and validation: Application to Plasmodium falciparum glutathione S-transferase Primary aim was to use a computational structure- based ligand design strategy to find novel ligands that can act as inhibitors to form the basis of future antimalarial drug development.

Marli Botha © CSIR A rational drug design strategy should be based on a validated target protein. With a proven relationship between its activity and the disease. The 3D structural information of the target protein should be available. X-ray or nuclear magnetic resonance (NMR) diffraction usually produces these structures. Preferably with a bound inhibitor. Structure-based inhibitor design

Marli Botha © CSIR Structure of the PfGST glutathione S- transferase active site with the bound inhibitor S-hexyl glutathione. The hydrogen interaction that is used by the substrate and substrate inhibitor (S-hexyl glutathione).

Marli Botha © CSIR Structure-based ligand design Newlead LUDI

Marli Botha © CSIR Structure of glutathione with fragments encircled that were used by NEWLEAD as building blocks to form new ligands. For NEWLEAD to function pharmacophore fragments have to be defined, the pharmacophore fragments defined for glutathione are the atoms encircled in various colors. LUDI uses potential interaction points on the receptor and then suggest modifications to the current ligand. Addition or replacement sites have to be supplied to the LUDI program. For GTX this was defined as indicated by the blue circles. Structure-based ligand design Newlead LUDI

Marli Botha © CSIR Structure-based inhibitor design and validation: Application to Plasmodium falciparum glutathione S-transferase In silico assessment and implementation of different ligand docking, scoring and design software to assemble a focused library of hypothetical inhibitory ligands of PfGST.

Marli Botha © CSIR Computer-based screening by docking and scoring Molecular docking: provided with the atomic coordinates of a receptor, the docking algorithm should be able to correctly predict the bound association between receptor and the ligand. Scoring functions: algorithm used to rank the docked poses or compare the affinity of different ligands for the same receptor (Perola et al., 2004).

Marli Botha © CSIR Docking program validation

Marli Botha © CSIR Protein binding affinity determination using consensus scoring Performance of scoring functions can be improved by using different scoring functions that estimate different properties. Although these scores have different scales, the average or summing of ranks should increase the discriminative ability of the scoring function (Clark et al., 2002). AutoDock provides an estimate of binding free energy in kcal/mol. LUDI provides a score that can be related to an inhibition constant (LUDI score 100 ≈ Ki of 100 mM). XScore provides an atomic binding score in pKd units that is related to the binding affinity.

Marli Botha © CSIR ● In order to gain trust in computer-based inhibitor design, as well as the method of affinity prediction, it is necessary to test some of these designed inhibitors experimentally. ● These results can be used as guidelines to optimize and improve this structure-based design protocol for further use. ● If this strategy proves to be successful, it can reduce the cost and time of future antimalarial drug development.

Marli Botha © CSIR Structure-based inhibitor design and validation: Application to Plasmodium falciparum glutathione S-transferase Exploring the relationship between the in silico and in vitro data for the inhibitors and their relevance to drug discovery and future prospects for antimalarial drugs.

Marli Botha © CSIR PfGST as a drug target P. falciparum contains only one isoform of the detoxification enzyme GST. PfGST detoxifies endogenous and other xenobiotic compounds (Liebau et al., 2002). The glutathione and thioredoxin system forms the basis of cellular antioxidant defense in Plasmodium species. The hypothesis is that PfGST inhibitors would have antimalarial effect independently. But also, work in synergy with other antimalarial drugs (Platel et al., 1999).

Marli Botha © CSIR In silico screening data for commercially available compounds In silico prediction: GTX > NDA > LAP > EDP

Marli Botha © CSIR Preliminary Inhibition Assays In vitro results: GTX > NDA > LAP > EDP

Marli Botha © CSIR Conclusion Proof of Principle: This approach can be used to design ligands that bind PfGST and predict a consensus score that can be used to rank these ligands according to their affinity for PfGST. In silico methodology could be developed to form a pipe- line that scientists can use to obtain a library of ranked scaffolds for future drug design. It provided chemical scaffolds for PfGST for future antimalarial drug development.

Marli Botha © CSIR Future Prospects WISDOM (Wide In-Silico Docking On Malaria) An initiative which is led by Professor Vincent Breton of the Laboratoire de Physique Corpusulaire, Universite Blaise Pascal, Clermont-Ferrand, France, it was decided to use the malaria protein glutathione-S-transferase (GST) as a model system for the virtual screening of a 4.6 million compound library using grid computing. The current FlexX screening programme is based on the curation of the target active site as a rigid body. It does, however, allow for ligand conformational flexibility. Professor Breton’s team is currently trying to implement the use of the AMBER forcefield in conjunction with the FlexX docking protocol. This will allow for molecular dynamics to be done in conjunction with the docking.

Marli Botha © CSIR Acknowledgements Supervisors Prof AI Louw (Bioschemistry,UP), Prof F Joubert (Bioinformatics,UP) and Prof CP Kenyon (CSIR). CSIR and University of Pretoria for bursaries. Prof E Liebau (Bernhard Nocht Institute for Tropical Medicine – Hamburg,Germany) for providing the pJC20-PfGST high copy expression plasmid. My fellow students and scientist for all their valued advice, insight and useful discussions.

“A mouse is an animal that, if killed in sufficiently many and creative ways, will generate a PhD.”