Unveiling Conserved Allosteric Hot Spots in Protein Domains from Sequences
Hacisuleyman, A.; Fasshauer, D.
Show abstract
The amino acid sequence determines the structure, function, and dynamics of a protein. In recent years, enormous progress has been made in translating sequence information into 3D structural information using artificial intelligence. However, because of the underlying methodology, it is an immense computational challenge to extract this information from the ever-increasing number of sequences. In the present study, we show that it is possible to create 2D contact maps from sequences, for which only a few exemplary structures are available on a laptop without the need for GPUs. This is achieved by using a pattern-matching approach. The resulting contact maps largely reflect the interactions in the 3D structures and contain information about its function and dynamics. This approach was used to explore the evolutionarily conserved allosteric mechanisms and identify the source- sink (driver-driven) relationships by using an established method that combines Schreibers concept of entropy transfer with a simple Gaussian network model. The validity of our method was tested on the DHFR, PDZ, SH3, and S100 domains, with our predictions consistently aligning with the experimental findings.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Design of novel Cyanovirin-N variants by modulation of binding dynamics through distal mutations 97%
- {Omega}-Loop mutations control dynamics of the active site by modulating the hydrogen-bonding network in PDC-3 β-lactamase 94%
- Myristoyl's dual role in allosterically regulating and localizing Abl kinase 94%
Similar papers in this journal
- Mutational scan inferred binding energetics and structure in intrinsically disordered protein CcdA 96%
- AlphaFold2 captures the conformational landscape of the HAMP signaling domain 95%
- Structural dynamics and functional cooperativity of human NQO1 by ambient temperature serial crystallography and simulations 94%
Similar papers in this journal
- Integrating multimeric threading with high-throughput experiments for structural interactome of Escherichia coli 96%
- Intrinsically disordered protein ensembles shape evolutionary rates revealing conformational patterns 94%
- Conformational variation in enzyme catalysis: A structural study on catalytic residues 93%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.