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Heinz, M.

Publications and source records attributed to Heinz, M..

2 recordsLinked to original sources

AlphaFold modeling of polyubiquitin complexes and covalently linked proteins

AbstractCells use the covalent attachment of Ubiquitin (Ub) chains to mark proteins for degradation, alter their cellular localization or drive their association. Protein fate is encoded in the distinct poly-Ub linkages, exploiting the vast combinatorial space of linear and branched Ub modifications. AlphaFold has emerged as a powerful tool to predict the structure of protein-protein complexes. However, standard AlphaFold does not consider linkages between individual protein chains, limiting its applicability to Ub chains. The near complete conservation of the ubiquitin sequence and the large number of binding partners suppresses coevolutionary signals, further challenging the prediction of poly-Ub complex structures. We address this challenge, first, by introducing correlated cysteine mutations to induce linkage-specific proximity of Ubs in complex with interacting proteins. Second, we introduce short covalent linker groups in AlphaFold 3 calculations that mimic the isopeptide bonds between linked lysines and Ub C-terminal carboxylates. These two approaches enable the robust structural modeling of complexes involving poly-Ub chains with AlphaFold. The linker approach is general and can be used for other covalent inter-chain connections and to enforce distance restraints for integrative structural modeling.

bioinformatics↗

Structural Insights on Ionizable Dlin-MC3-DMA Lipids in DOPC Layers by Combining Accurate Atomistic Force Fields, Molecular Dynamics Simulations and Neutron Reflectivity

Ionizable lipids such as the promising Dlin-MC3-DMA (MC3) are essential for the successful design of lipid nanoparticles (LNPs) as drug delivery agents. Combining molecular dynamics simulations with experimental data such as neutron reflectivity experiments and other scattering techniques is essential to provide insights into the internal structure of LNPs, which is not fully understood to date. However, the accuracy of the simulations relies on the choice of force field parameters and high-quality experimental data is indispensable to verify the parametrization. For MC3, different parameterizations in combination with the CHARMM and the Slipids force field have recently emerged. Here, we complement the existing efforts by providing parameters for cationic and neutral MC3 compatible with the AMBER Lipid17 force field. Subsequently, we carefully assess the accuracy of the different force fields by providing a direct comparison to neutron reflectivity experiments of mixed lipid bilayers consisting of MC3 and DOPC at different pH. At low pH (cationic MC3) and at high pH (neutral MC3) the newly developed MC3 parameters in combination with AMBER Lipid17 for DOPC give good agreement with the experiments. Overall, the agreement is similar compared to the Park-Im parameters for MC3 in combination with the CHARMM36 force field for DOPC. The Ermilova-Swenson MC3 parameters in combination with the Slipids force field underestimate the bilayer thickness. While the distribution of cationic MC3 is very similar, the different force fields for neutral MC3 reveal distinct differences ranging from strong accumulation in the membrane center (current MC3/AMBER Lipid17 DOPC), over mild accumulation (Park-Im MC3/CHARMM36 DOPC) to surface accumulation (Ermilova-Swenson MC3/Slipids DOPC). These pronounced differences highlight the importance of accurate force field parameters and their experimental validation.

biophysics↗