Project Manager:
Dr. Marijn van Jaarsveld

Expansion and optimal Exploitation of individual neoepitope Repertoire

Principal Investigators:
Prof. Ugur Sahin
Affiliation:
Johannes Gutenberg-Universität Mainz
HPC Platform used:
NHR Süd-West: Mogon/Mogon 2

Cancer mutanome vaccines targeting neoepitopes derived from somatic mutations have ideal properties to become an essential part of modern multimodal cancer therapy. Our goal is to fully realize this personalized cancer immunotherapy concept by addressing the key genomic and immunological challenges for successful application of this approach in patients with any type of cancer.

Project Manager:
Dr. Noelia Ferruz

A deep unsupervised Model for Protein Design

Principal Investigators:
Dr. Noelia Ferruz
Affiliation:
Universität Bayreuth
HPC Platform used:
NHR@FAU: ALEX - GPGPU cluster

The design of new functional proteins can tackle many of the problems humankind is facing today but so far has proven very challenging1. Analogies between protein sequences and human languages have been long noted and a summary of their most prominent similarities is described. Given the tremendous success of Natural Language Processing (NLP) methods in recent years, its application to protein research opens a fresh perspective, shifting from the current energy-function centered paradigm to an unsupervised learning approach based entirely on sequences. To explore this opportunity further we have pre-trained a generative language model on the entire protein sequence space. We find that our language model, ProtGPT2, effectively speaks the

Category:
Project Manager:
M.Sc. Andreas Bolke

Dedicated Monte Carlo Simulations and Image Reconstruction Algorithms for range Verification in Particle Therapy using Compton Cameras

Principal Investigators:
Prof. Dr. Magdalena Rafecas
Affiliation:
Universität zu Lübeck
HPC Platform used:
NHR@ZIB: Lise

We work on imaging for particle therapy. Particle beams (e.g. protons) can precisely destroy tumors while sparing healthy tissue. To verify the irradiation, Compton cameras (CC) can be used to detect gamma rays emerging from the patient. CC require complex algorithms to reconstruct images. We employ Monte Carlo simulations to recreate the irradiation and test reconstruction algorithms. The simulations and development of reconstruction approaches require much computing power. Thanks to HLRN, we simulate realistic therapeutic beams, the emerging rays and its detection with CC, and can test our reconstruction. Our approaches notably improve image quality. Further improvements are planed using a-prori information and refined data selection.

Category:
Project Manager:
Prof. Dr. Maria Andrea Mroginski

Antifungal Peptides: Elucidating their Mode of Action via molecular Dynamics Simulations

Principal Investigators:
Prof. Dr. Maria Andrea Mroginski
Affiliation:
Technische Universität Berlin
HPC Platform used:
NHR@ZIB: Lise

Increasing fungal resistance to fungicides prompt the urge for developing new antifungal peptides (AFP). This computational study aims the elucidation of mode of action of two parental AFPs as well as a large set of novel chimera peptides. Specifically, we will identify interaction hot spots with the fungal membrane by performing classical all-atom molecular dynamics simulations using enhanced sampling algorithms of large fungal membranes – AFP complexes.

Project Manager:
Prof. Dr. Christof Schütte

Machine Learning and Simulation for pH-Dependent Opioids

Principal Investigators:
Dr. Markus Weber
HPC Platform used:
NHR@ZIB: Lise

Strong painkillers (such as opioids) are essential to medicine. However, they are mostly addictive and have potentially deadly side effects. Simulation and machine learning techniques help in the search for tailor-made active substances that do not have these side effects. The interaction of the various algorithms raises questions about which computer architecture can support the calculations most effectively.

Project Manager:
Marius Trollmann

Resolving the Structure of mRNA-Vaccine Lipid Nanoparticles

Principal Investigators:
Prof. Dr. Rainer Böckmann
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen
HPC Platform used:
NHR@FAU: Alex GPU cluster

Lipid nanoparticles (LNPs) are very successfully employed as novel transport vehicles for mRNA vaccines. A major gap in our understanding and thus obstacle for future developments of nanoparticle-mRNA drugs, however, is the lack of a molecular picture and molecular insight into LNPs. In this project we aim to provide unique insight at the atomistic scale into the structure and mechanisms of these carriers.

Project Manager:
Daniel Bauer

Molecular Dynamics Study of the Sodium/Potassium Channels HCN

Principal Investigators:
Prof. Dr. Kay Hamacher
Affiliation:
Technische Universität Darmstadt
HPC Platform used:
NHR4CES@TUDa: Lichtenberg Cluster Darmstadt

Ion channels play a fundamental key role in all living organisms and are crucial for the signal transduction of neurons in higher animals. The hyperpolarization-activated cyclic nucleotide-gated (HCN) family of sodium/potassium channels are members of this protein family that are characterized by slow and weakly potassium selective inward current at hyperpolarizing voltages. HCN channels are expressed in a broad set of tissues in mammalia and are involved in an equally broad range of biological processes: in sinoatrial node cells of the heart, they are molecular facilitators of the pacemaker current (also known as ”funny current” If or Ih) which is required for subsequent generation of action potentials and ultimately leads to the

Life Sciences abonnieren