ASEdb: a database of alanine mutations and their effects on the free energy of binding in protein interactions

By Kurt S. Thorn, Andrew A. Bogan. Bioinform., 2001

401 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/d2e33950c2f94b6ee9ad646a8af901a4b6d631ba

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

In Molecular Biology

Citations in the corpus

Dissecting protein–protein recognition sites (2002, background): “Trp, Tyr, and Arg are highly preferred at hot spots, Ser and Thr are disfavored, and Leu, Val (but not Ile) are essentially absent.(38,39) In our data, Trp and Tyr have the highest propensity for the core of recognition sites, and Ser and Thr have a negative propensity.”
Protein–Protein Interaction Hotspots Carved into Sequences (2007, methodology): “We used the ASEdb database of experimental alanine scans [12], which lists residues that were mutated to alanine and the effect (in terms of DDG) this mutation had on the interaction between two proteins.”
Protein-Protein Interactions: Coupling of Structurally Conserved Residues and of Hot Spots across Interfaces. Implications for Docking (2004, methodology): “Intriguingly, the local packing Thorn (Thorn and Bogan, 2001; Bogan and Thorn, 1998) density around both hot spots and conserved residues correlate remarkably well with residue conservation.”
3D deep convolutional neural networks for amino acid environment similarity analysis (2017, methodology): “This technique is often used in protein-protein interaction hot spot detection for identifying potential interacting residues [3].”
BeAtMuSiC: prediction of changes in protein–protein binding affinity on mutations (2013, methodology): “Alanine scanning mutagenesis has been widely used to experimentally characterize protein–protein interfaces and identify these hotspots, which constitute prime targets for the modulation of protein–protein interactions (14,15).”
Recent advances in the development of protein–protein interactions modulators: mechanisms and clinical trials (2020, background): “0 kcal/mol.(32) Tryptophan, arginine, and tyrosine are more likely to appear in hot-spots than other amino acids.”
SKEMPI 2.0: an updated benchmark of changes in protein–protein binding energy, kinetics and thermodynamics upon mutation (2018, methodology): “1 were found by checking the references in the ASEdb [71] and PINT [36] databases,”
Protein–protein interaction and quaternary structure (2008, positive): “These data, collected in the ASEdb database (Thorn & Bogan, 2001), suggest that the ‘hotspot ’ residues, those that have a large effect on the stability of a complex when mutated, tend to be surrounded by energetically less important residues that occlude bulk solvent from them.”