Metal‐Templated Design of Chemically Switchable Protein Assemblies with High‐Affinity Coordination Sites

Kakkis, A.; Gagnon, Derek M.; Esselborn, Julian; Britt, R. David; Tezcan, F.A.

doi:10.1002/ange.202009226

Cited by 7 publications

(6 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After this, the system will undergo the same minimization, heating, and equilibration as the MD simulation for PMF does. Then, a 12-window TI was applied to the system with up to six imidazole ligands and the metalloprotein 49 to slowly mutate the "timask1" ion to "timask2" and compare the relative energy change. The process-related files can also be found at https://github.com/lizhen62017/MIRIAM/TI.…”

Section: Molecular Dynamics Simulations Using Thermodynamic Integrati...mentioning

confidence: 99%

Simulating Metal-Imidazole Complexes

Li,

Bhowmik,

Sagresti

et al. 2024

Preprint

View full text Add to dashboard Cite

One commonly observed binding motif in metalloproteins involves the interaction between a metal ion and histidine's imidazole sidechains. Although previous imidazole-M(II) parameters established the flexibility and reliability of the 12-6-4 Lennard-Jones (LJ)-type nonbonded model by simply tuning the ligating atom’s polarizability, they have not been applied to multiple-imidazole complexes. To fill this gap, we systematically simulate multiple-imidazole complexes (ranging from one to six) for five metal ions (Co(II), Cu(II), Mn(II), Ni(II), and Zn(II)) which commonly appear in metalloproteins. Using extensive (40ns per PMF window) sampling to assemble free energy association profiles (using OPC water and standard HID imidazole charge models from AMBER) and comparing them to DFT calculations, a new set of parameters was developed to focus on energetic and geometric features of multiple-imidazole complexes. The obtained free energy profiles agree with the experimental binding free energy and DFT calculated distances. Further investigation of the simulations revealed the existence of ligand-ligand hydrogen bonds and partial π-stacking while one ligand dissociates from the complex. To validate our model, we show that we can close the thermodynamic cycle for metal-imidazole complexes with up to six imidazole molecules in the first solvation shell. Given the success in closing the thermodynamic cycles, we then used the same extended sampling method for six other metal ions (Ag(I), Ca(II), Cd(II), Cu(I), Fe(II), and Mg(II)) to obtain new parameters. Since these new parameters can reproduce the one-imidazole geometry and energy accurately, we hypothesize that they will reasonably predict the binding free energy of higher-level coordination numbers. Hence, we did not extend the analysis of these ions up to six imidazole complexes. Overall, the results shed light on metal-protein interactions by emphasizing the importance of ligand-ligand interaction and metal-π-stacking within metalloproteins.

show abstract

Section: Molecular Dynamics Simulations Using Thermodynamic Integrati...mentioning

confidence: 99%

Simulating Metal-Imidazole Complexes

Li,

Bhowmik,

Sagresti

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Metal ion binding sites can be used to engineer protein-protein interactions (PPI) [10][11][12] and the hypothesis has been put forward that one origin of macromolecular complexity is the superficial binding of metal ions in early single domain proteins. 12 While simple metal ion binding sites can be rapidly engineered because initial coordination on a protein surface can for example be achieved by creating an i, i+4 di-histidine site on an alpha-helix 13 or by placing cysteines in spatial proximity, 14 the engineering of complex metal ion binding sites e.g. in the protein interior is considerably more difficult 2,11 as such sites are often supported by a network of hydrogen bonds.…”

Section: Introductionmentioning

confidence: 99%

Accurate prediction of transition metal ion location via deep learning

Dürr

Levy

Rothlisberger

2022

Preprint

View full text Add to dashboard Cite

Metal ions are essential cofactors for many proteins. In fact, currently, about half of the structurally characterized proteins contain a metal ion. Metal ions play a crucial role for many applications such as enzyme design or design of protein-protein interactions because they are biologically abundant, tether to the protein using strong interactions, and have favorable catalytic properties e.g. as Lewis acid. Computational design of metalloproteins is however hampered by the complex electronic structure of many biologically relevant metals such as zinc that can often not be accurately described using a classical force field. In this work, we develop two tools - Metal3D (based on 3D convolutional neural networks) and Metal1D (solely based on geometric criteria) to improve the identification and localization of zinc and other metal ions in experimental and computationally predicted protein structures. Comparison with other currently available tools shows that Metal3D is the most accurate metal ion location predictor to date outperforming geometric predictors including Metal1D by a wide margin using a single structure as input. Metal3D outputs a confidence metric for each predicted site and works on proteins with few homologes in the protein data bank. The predicted metal ion locations for Metal3D are within 0.70 +- 0.64 Å of the experimental locations with half of the sites below 0.5 Å. Metal3D predicts a global metal density that can be used for annotation of structures predicted using e.g. AlphaFold2 and a per residue metal density that can be used in protein design workflows for the location of suitable metal binding sites and rotamer sampling to create novel metalloproteins. Metal3D is available as easy to use webapp, notebook or commandline interface.

show abstract

“…Many strategies employing weak interactions have been reported to design protein self-assemblies, such as electrostatic interaction, 3 ligand−receptor interaction, 4 host−guest interaction, 5 and metal coordination. 6 However, these methods require either sophisticated engineering of the protein building blocks or abiotic conditions (e.g., synthetic molecules, electrolyte combination, and specific pH). Although in-cell protein assembly techniques have been developed for the construction of protein crystals, 7 it is still challenging to mimic natural protein assembly processes in vitro and illustrate the detailed mechanisms.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Therefore, exploring the self-assembly mechanism and fabricating novel materials of proteins have aroused noteworthy interests. Many strategies employing weak interactions have been reported to design protein self-assemblies, such as electrostatic interaction, ligand–receptor interaction, host–guest interaction, and metal coordination . However, these methods require either sophisticated engineering of the protein building blocks or abiotic conditions (e.g., synthetic molecules, electrolyte combination, and specific pH).…”

Section: Introductionmentioning

confidence: 99%

Formation of β-Lactoglobulin Self-Assemblies via Liquid–Liquid Phase Separation for Applications beyond the Biological Functions

Zhang

Deng

Wang³

et al. 2021

ACS Appl. Mater. Interfaces

View full text Add to dashboard Cite

Proteins are like miracle machines, playing important roles in living organisms. They perform vital biofunctions by further combining together and/or with other biomacromolecules to form assemblies or condensates such as membraneless organelles. Therefore, studying the self-assembly of biomacromolecules is of fundamental importance. In addition to their biological activities, protein assemblies also exhibit extra properties that enable them to achieve applications beyond their original functions. Herein, this study showed that in the presence of monosaccharides, ethylene glycols, and amino acids, β-lactoglobulin (β-LG) can form assemblies with specific structures, which were highly reproducible. The mechanism of the assembly process was studied through multi-scale observations and theoretical analysis, and it was found that the assembling all started from the formation of solute-rich liquid droplets via liquid–liquid phase separation (LLPS). These droplets then combined together to form condensates with elaborate structures, and the condensates finally evolved to form assemblies with various morphologies. Such a mechanism of the assembly is valuable for studying the assembly processes that frequently occur in living organisms. Detailed studies concerning the properties and applications of the obtained β-LG assemblies showed that the assemblies exhibited significantly better performances than the protein itself in terms of autofluorescence, antioxidant activity, and metal ion absorption, which indicates broad applications of these assemblies in bioimaging, biodetection, biodiagnosis, health maintenance, and pollution treatment. This study revealed that biomacromolecules, especially proteins, can be assembled via LLPS, and some unexpected application potentials could be found beyond their original biological functions.

show abstract

Metal‐Templated Design of Chemically Switchable Protein Assemblies with High‐Affinity Coordination Sites

Cited by 7 publications

References 63 publications

Simulating Metal-Imidazole Complexes

Simulating Metal-Imidazole Complexes

Accurate prediction of transition metal ion location via deep learning

Formation of β-Lactoglobulin Self-Assemblies via Liquid–Liquid Phase Separation for Applications beyond the Biological Functions

Contact Info

Product

Resources

About