Allosteric modulation of fluorescence revealed by hydrogen bond dynamics in a genetically encoded maltose biosensor

Berksoz, Melike; Atilgan, Canan

doi:10.1002/prot.26688

Cited by 3 publications

(1 citation statement)

References 59 publications

(112 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Increased RMSF values in the bound state for the residues distal to the binding interface reflects a general property of proteins. [37][38][39] While this increased flexibility is usually accompanied by the rigidification of the binding site residues, in GB1 we find the latter effect to be minimal, because the interface is made up of secondary structural elements (Figure 1b).…”

Section: Analyses Of Structuresmentioning

confidence: 74%

Deciphering GB1’s Single Mutational Landscape: Insights from MuMi Analysis

Guclu,

Atilgan,

Atilgan

2024

Preprint

Self Cite

View full text Add to dashboard Cite

Mutational changes that affect the binding of the C2 fragment of Streptococcal protein G (GB1) to the Fc domain of human IgG (IgG-Fc) have been extensively studied using deep mutational scanning (DMS), and the binding affinity of all single mutations has been measured experimentally in the literature. To investigate the underlying molecular basis, we performin-silicomutational scanning for all possible single mutations, along with 2-µs-long molecular dynamics (WT-MD) of the wild-type (WT) GB1 in both unbound and IgG-Fc bound forms. We compute the hydrogen bonds between GB1 and IgG-Fc in WT-MD to identify the dominant hydrogen bonds for binding, which we then assess in conformations produced by Mutation and Minimization (MuMi) to explain the fitness landscape of GB1 and IgG-Fc binding. Furthermore, we analyze MuMi and WT-MD to investigate the dynamics of binding, focusing on the relative solvent accessibility (RSA) of residues and the probability of residues being located at the binding interface. With these analyses, we explain the interactions between GB1 and IgG-Fc and display the structural features of binding. Our findings pave the way for improved predictive accuracy in protein stability and interaction studies, which are crucial for advancements in drug design and synthetic biology.

show abstract

Section: Analyses Of Structuresmentioning

confidence: 74%

Deciphering GB1’s Single Mutational Landscape: Insights from MuMi Analysis

Guclu,

Atilgan,

Atilgan

2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Deciphering GB1’s Single Mutational Landscape: Insights from MuMi Analysis

Guclu,

Atilgan,

Atilgan

2024

J. Phys. Chem. B

View full text Add to dashboard Cite

Mutational changes that affect the binding of the C2 fragment of Streptococcal protein G (GB1) to the Fc domain of human IgG (IgG-Fc) have been extensively studied using deep mutational scanning (DMS), and the binding affinity of all single mutations has been measured experimentally in the literature. To investigate the underlying molecular basis, we perform in silico mutational scanning for all possible single mutations, along with 2 μs-long molecular dynamics (WT-MD) of the wild-type (WT) GB1 in both unbound and IgG-Fc bound forms. We compute the hydrogen bonds between GB1 and IgG-Fc in WT-MD to identify the dominant hydrogen bonds for binding, which we then assess in conformations produced by Mutation and Minimization (MuMi) to explain the fitness landscape of GB1 and IgG-Fc binding. Furthermore, we analyze MuMi and WT-MD to investigate the dynamics of binding, focusing on the relative solvent accessibility of residues and the probability of residues being located at the binding interface. With these analyses, we explain the interactions between GB1 and IgG-Fc and display the structural features of binding. In sum, our findings highlight the potential of MuMi as a reliable and computationally efficient tool for predicting protein fitness landscapes, offering significant advantages over traditional methods. The methodologies and results presented in this study pave the way for improved predictive accuracy in protein stability and interaction studies, which are crucial for advancements in drug design and synthetic biology.

show abstract

Ranking Single Fluorescent Protein Based Calcium Biosensor Performance by Molecular Dynamics Simulations

Berksoz,

Atilgan

2024

Preprint

Self Cite

View full text Add to dashboard Cite

Genetically Encoded Fluorescent Biosensors (GEFBs) have become indispensable tools for visualizing biological processes in vivo. A typical GEFB is composed of a sensory domain (SD) which undergoes a conformational change upon ligand binding and a genetically fused fluorescent protein (FP). Ligand binding in the SD allosterically modulates the chromophore environment and changes its spectral properties. Single fluorescent (FP)-based biosensors, a subclass of GEFBs, offer a simple experimental setup; they are easy to produce in living cells, structurally stable and simple due to their single-wavelength operation. However, they pose a significant challenge for structure optimization, especially concerning the length and residue content of linkers between the FP and SD which affect how well the chromophore responds to conformational change in the SD. In this work, we use classical all-atom molecular dynamics simulations to analyze the dynamic properties of a series of calmodulin-based calcium biosensors, all with different FP-SD interaction interfaces and varying degrees of calcium binding dependent fluorescence change. Our results indicate that biosensor performance can be predicted based on distribution of water molecules around the chromophore and shifts in hydrogen bond occupancies between the ligand-bound and ligand-free sensor structures.

show abstract

Allosteric modulation of fluorescence revealed by hydrogen bond dynamics in a genetically encoded maltose biosensor

Cited by 3 publications

References 59 publications

Deciphering GB1’s Single Mutational Landscape: Insights from MuMi Analysis

Deciphering GB1’s Single Mutational Landscape: Insights from MuMi Analysis

Deciphering GB1’s Single Mutational Landscape: Insights from MuMi Analysis

Ranking Single Fluorescent Protein Based Calcium Biosensor Performance by Molecular Dynamics Simulations

Contact Info

Product

Resources

About