Webinar 13: May 12th, 12.00-13.00 (SAST); 12.00-13.00 (CET)

First talk:- Genomic variation driven 3-dimensional drug discovery – From drug targets to drug metabolism

Speaker: Prof. Dr. Özlem Tastan Bishop

Abstract: Determining the 3D structures of proteins through computational structural bioinformatics has been a long and challenging journey, leading to the AlphaFold team’s well-deserved recognition with the 2024 Nobel Prize in Chemistry. This breakthrough highlights the critical role of 3D structure in determining a protein’s function, interactions, and stability, factors with profound implications for health and disease. Yet, it also emphasizes how much we still must learn about proteins as dynamic macromolecules that encode complex, multilayered relational information, where even a single amino acid change in sequence can lead to significant structural and functional consequences, either beneficial or detrimental.

This talk will present a series of case studies from RUBi’s research projects to illustrate how genomic variations can influence various biological phenomena, including drug resistance and drug metabolism. It will also explore the challenges and possibilities of designing drugs for continually evolving proteins and argue for the critical importance of integrating variation information into drug discovery pipelines to better predict therapeutic outcomes and develop more effective treatments.

Second talk:- Rhodes adventure – molecular dynamic simulation of alpha-1-giardin

Speaker: Dawid Warmus

Abstract: During my Scientific Exchange at Rhodes University, I learned molecular dynamics (MD) simulations in Özlem Tastan Bishop's lab, using GROMACS to investigate biological molecules at the atomic level. My work progressed from studying monomer simulations to exploring complex lipid-protein interactions.

My project focuses on the unconventional protein secretion mechanism in the protozoan parasite Giardia lamblia. Based on our findings, alpha-giardins— parasitic annexins — are likely involved in this process, as they have been identified in the interactome of unconventionally secreted virulence factors of Giardia lamblia. Specifically, my simulations examine alpha-1-giardin, a member of this protein family.

Through systematic MD simulations, I analyzed the interactions of monomeric and trimeric forms of alpha-1-giardin with a lipid membrane, employing biologically relevant pH conditions that reflect the physiological state of Giardia lamblia.

The resulting in silico data will be validated through corresponding laboratory experiments, further advancing the integration of experimental and computational approaches in lipid-protein interaction research.

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