Each hormone binding site can be divided into an inner and outer binding cavity.
The five aromatic residues that form the core of each agonist binding site can be divided into two working groups, a triad (led by αY190) that behaves similarly at all sites and a coupled pair (led by γW55) that has a large influence on affinity only in fetal AChRs.
These mutations of the p53 DNA binding domain can be divided into two groups [ 24].
The methods for HLA peptide binding prediction can be divided into three categories: (1) position-specific scoring matrix (PSSM) based, (2) machine learning based, and (3) structure based.
The ATP-binding site can be divided into three subregions: the adenine region, the sugar region, and the phosphate-binding region [ 15].
In this context, figure 8 A (CRP) and B (FNR) shows that the proportions of genes with a TF-binding site can be divided roughly into three categories, depending on the degree of amino acid similarities within the TFs.
The cofactor-binding pocket can be divided into three regions: the adenine ribose moiety of NAD+, the nicotinamide ribose moiety and the catalytic center located deep inside the pocket.
On the basis of the constellation of amino acid residues at three positions essential for NAD-binding, ARTs can be divided into two major subclasses, ARTC (Cholera toxin-like) carrying the R-S-E triad motif and ARTD (Diphtheria toxin-like) carrying the H-Y-E triad motif (Hottiger et al. 2010).
In IP3R, the N-terminus forms the IP3-binding site, which can be divided into the ligand binding 'core' (residues 224 579) and the 'suppressor domain' (residues 1 223), with the latter inhibiting IP3 binding to the core [ 13, 14].
Computational approaches to TF binding site analysis can be divided into two categories, discovery and prediction.
