Researchers at the University of Amsterdam have pioneered a computational approach to designing peptides that target Bax, a key regulating protein of programmed neuronal cell death. Their study, recently published in Materials Advances, highlights how rational peptide design and molecular dynamics simulations could help develop new therapeutic strategies for neurodegenerative diseases such as Parkinson’s.
Peptide development strategy as reported in the paper. Image: HIMS / Mater. Adv. Peptide development strategy as reported in the paper. Image: HIMS / Mater. Adv.

The research was conducted in the Computational Chemistry group at the Van ‘t Hoff Institute for Molecular Sciences. Led by Dr Ioana M. Ilie in collaboration with Dr Lars P. van der Heide from the Swammerdam Institute for Life Sciences,MSc students Tom Vlaar and Bernadette M. Mayer pioneered a novel computational framework to design cyclic peptides for targets associated with neurodegenerative and cancerous diseases.

The joint research concerns an exploration of a method for modulating the process of apoptosis, the programmed cell death process that is essential for maintaining cellular balance. More specific, they focused on the so-called Bax protein that is a key regulator in apoptosis. It’s function depends, amongst others, on Mcl-1, a protein that acts as a natural inhibitor of Bax. In Parkinson’s disease, excessive neuronal cell death can be linked to the depletion of this Mcl-1 protein.

Cyclic peptides for Bax inhibition

The focus of the research now published in Materials Advances was to design cyclic peptides that mimic Mcl-1’s function. These might be used to restore proper Bax apoptosis regulation and potentially slow disease progression. Using rational design based on non-antibody scaffold crystal structures and molecular dynamics simulations, peptides were designed that bind with high affinity to Bax, targeting both its hydrophobiccanonical groove(a key protein region involved in apoptosis) and external regions. The researchers employed molecular dynamics simulations to determine the binding free energies of the peptides to Bax.

The results show strong peptide-Bax binding, suggesting potential for modulating apoptosis. Beyond their immediate application in apoptosis research, the findings provide a structural foundation for developing a machine-learning-powered peptide design engine, which could accelerate future therapeutic discoveries.

Abstract, as published with the paper

The proteins of the Bcl-2 family play crucial roles in regulating apoptosis. It is divided into pro-survival and pro-apoptotic proteins that determine cellular fate. In particular, Bax is a crucial executor of apoptosis as its activation initiates the apoptotic phenotype. Hence, targeting this protein represents an attractive therapeutic approach, which can aid in regulating apoptotic signalling and potentially contribute to the development of novel therapies against cancer and neurodegenerative diseases. Here, we introduce a digital paradigm, which relies on rational design and computer simulations to develop and validate peptide-based agents that bind to Bax. The peptides are rationally designed and optimized to bind to Bax starting from the crystal structures of affimers in complex with Bcl-2 proteins. Next, molecular dynamics simulations (MD) are employed to probe the stability of the Bax-peptide complexes and to estimate the binding free energies. The results show that the designed peptides bind with high affinity to Bax. Two of the designed peptides bind in the canonical hydrophobic groove (BH1 domain) of Bax and one peptide binds to the outside of the BH3 domain (α2-helix). Notably, the peptides restrict the flexibility of the {α1-α2} loop, modulating the bottom trigger site associated with toxicity. All in all, the results highlight the potential of these peptides as valuable tools for further exploration in modulating apoptotic pathways and set the structural foundation for a machine learning powered engine for peptide design.

Read the paper in Material Advances: Computational design of Bax-inhibiting peptides

Source: University of Amsterdam