Mechanical couplings of protein backbone and side chains exhibit scale-free network properties and specific hotspots for function
| Autor: | Timothy H. Click, Jhih-Wei Chu, Haw Yang, N. Nixon Raj |
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| Rok vydání: | 2021 |
| Předmět: |
Scale-free
Rigidity graph Biophysics Structure-mechanics statistical learning Rigidity (psychology) Protein dynamics Network theory Biochemistry Molecular dynamics Structural Biology Genetics Side chain ComputingMethodologies_COMPUTERGRAPHICS Physics Coupling PDZ3 Quantitative Biology::Biomolecules Scale-free network Function (mathematics) Computer Science Applications Serine protease All-atom molecular dynamics simulation Biological system TP248.13-248.65 Research Article Biotechnology |
| Zdroj: | Computational and Structural Biotechnology Journal Computational and Structural Biotechnology Journal, Vol 19, Iss, Pp 5309-5320 (2021) |
| ISSN: | 2001-0370 |
| Popis: | Graphical abstract Highlights • Statistical learning from protein dynamics unravels rigidities in interaction network. • Backbone and side-chain mechanical couplings exhibit scale-free network properties. • Graphical depiction of network rigidities captures sequence co-evolution patterns. • Functional sites at secondary structure peripheries are mechanical hotspots. • Our rigidity scores are compelling metrics for residue biological significance. A backbone-side-chain elastic network model (bsENM) is devised in this contribution to decipher the network of molecular interactions during protein dynamics. The chemical details in 5 μs all-atom molecular dynamics (MD) simulation are mapped onto the bsENM spring constants by self-consistent iterations. The elastic parameters obtained by this structure-mechanics statistical learning are then used to construct inter-residue rigidity graphs for the chemical components in protein amino acids. A key discovery is that the mechanical coupling strengths of both backbone and side chains exhibit heavy-tailed distributions and scale-free network properties. In both rat trypsin and PDZ3 proteins, the statistically prominent modes of rigidity graphs uncover the sequence-specific coupling patterns and mechanical hotspots. Based on the contributions to graphical modes, our residue rigidity scores in backbone and side chains are found to be very useful metrics for the biological significance. Most functional sites have high residue rigidity scores in side chains while the biologically important glycines are generally next to mechanical hotspots. Furthermore, prominent modes in the rigidity graphs involving side chains oftentimes coincide with the co-evolution patterns due to evolutionary restraints. The bsENM specifically devised to resolve the protein chemical character thus provides useful means for extracting functional information from all-atom MD. |
| Databáze: | OpenAIRE |
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