Multiscale simulations of membrane processes

The requested computional time is for the following two main projects: (I) IFITM3 – a sensor of hemifusion IFITMs are currently one of the most broadly acting and clinically relevant anti-viral molecules. To allow the viral genome to enter and infect the host, viruses must fuse with either the endosomal membrane or plasma membrane. Our goal is to unravel how IFITM molecules alter the free energy landscape of viral fusion and which of IFITMs molecular characteristics determine viral restriction. The ultimate goal of the project is to exploit these insights to design artificial inhibitors and accelerators of fusion reactions for medicinal purposes and drug delivery. Our performed simulation have now pinpointed a potential mechanism on how IFITM3 is able to sense when a virus attacks the host cell. Namely, IFITM has an intra-molecular helix which is attracted to membrane defects (sensing) that are characteristic for viral fusion intermediates. The planned simulations will allow to explore its dependence on protein structure/sequence. (II) Artificial intelligence based molecular design (two project parts) Intensive parallel sampling and exploration of chemical space via high throughput molecular simulations enable unique and novel insights into the complex relationships between molecular structure and functionality, and has opened numerous perspectives for the design of novel materials. Our goal is to design evolutionary algorithms that are able to self-design molecules based on optimizing functionality via smart sampling of high dimensional chemical space. To this aim, we are developing a highly parallel software package coined Cellfish (built on the GROMACS engine for biomolecular simulations) which optimizes functionality (called fitness) via the sampling of chemical space driven by a molecular force-field based heuristic Hamiltonian (the fitness function). Not only does this method enable the design of novel materials, the resolved solution space of the fitness function enables unique insights into the physics that underpins sequence conservation in proteins (protein evolution). This project consists of two separate parts: (i) Evolution of a cholesterol sensing peptide motif (CRAC motif), (ii) evolution of a membrane defect sensing motif (ALPS motif).