Loading
PDBj
メニューPDBj@FacebookPDBj@X(formerly Twitter)PDBj@BlueSkyPDBj@YouTubewwPDB FoundationwwPDBDonate
RCSB PDBPDBeBMRBAdv. SearchSearch help

6WN7

Homo sapiens S100A5

6WN7 の概要
エントリーDOI10.2210/pdb6wn7/pdb
分子名称Protein S100-A5, CALCIUM ION (3 entities in total)
機能のキーワードs100, calcium, ha5, ef-hand, metal binding protein
由来する生物種Homo sapiens (Human)
タンパク質・核酸の鎖数6
化学式量合計66718.69
構造登録者
Perkins, A.,Harms, M.J.,Wong, C.E.,Wheeler, L.C. (登録日: 2020-04-22, 公開日: 2020-09-30, 最終更新日: 2023-10-18)
主引用文献Wheeler, L.C.,Perkins, A.,Wong, C.E.,Harms, M.J.
Learning peptide recognition rules for a low-specificity protein.
Protein Sci., 29:2259-2273, 2020
Cited by
PubMed Abstract: Many proteins interact with short linear regions of target proteins. For some proteins, however, it is difficult to identify a well-defined sequence motif that defines its target peptides. To overcome this difficulty, we used supervised machine learning to train a model that treats each peptide as a collection of easily-calculated biochemical features rather than as an amino acid sequence. As a test case, we dissected the peptide-recognition rules for human S100A5 (hA5), a low-specificity calcium binding protein. We trained a Random Forest model against a recently released, high-throughput phage display dataset collected for hA5. The model identifies hydrophobicity and shape complementarity, rather than polar contacts, as the primary determinants of peptide binding specificity in hA5. We tested this hypothesis by solving a crystal structure of hA5 and through computational docking studies of diverse peptides onto hA5. These structural studies revealed that peptides exhibit multiple binding modes at the hA5 peptide interface-all of which have few polar contacts with hA5. Finally, we used our trained model to predict new, plausible binding targets in the human proteome. This revealed a fragment of the protein α-1-syntrophin that binds to hA5. Our work helps better understand the biochemistry and biology of hA5, as well as demonstrating how high-throughput experiments coupled with machine learning of biochemical features can reveal the determinants of binding specificity in low-specificity proteins.
PubMed: 32979254
DOI: 10.1002/pro.3958
主引用文献が同じPDBエントリー
実験手法
X-RAY DIFFRACTION (1.25 Å)
構造検証レポート
Validation report summary of 6wn7
検証レポート(詳細版)ダウンロードをダウンロード

252091

件を2026-04-15に公開中

PDB statisticsPDBj update infoContact PDBjnumon