Fig. 8
From: 3D deep convolutional neural networks for amino acid environment similarity analysis
Importance visualization of local amino acid microenvironments. Visualizations of importance scores of each input atom are displayed as heat maps. The color demonstrates how each atom within the local box contribute to the decision. The importance scores range from 0 to 100. Atoms with the lowest important scores (<20) are shown in white, and the red to blue heat map spectrum highlights the most important to the least important atoms. Transparent light pink spheres are drawn to show the space previously occupied by the removed residue. a Microenvironment surrounding a key ASP residue at the EF_HAND calcium binding site (PDB: 1A2X, ASP 63.) Our importance score map indicates that the correct prediction relies on the two nitrogen atoms, which are in close proximity to the electronegative oxygen atoms of the removed aspartic acid residue. b Microenvironment surrounding a PROSITE INSULIN motif, with the key CYS residue removed (PDB:1IZA, CYS 7.) The 3DCNN network made the correct prediction of CYS primarily based on the SG atom from a nearby cysteine residue. This SG atom originally forms disulfide bond with the SG atom of the removed cysteine residue. The unique disulfide bond pattern was implicitly captured by our network to facilitate the classification. c Microenvironment surrounding a phenylalanine residue (PDB: 1ZPL, PHE_52). The three highlighted regions in the heat map are the side-chain atoms of VAL 54, ILE 48, VAL 2, all of which comprise of non-polar carbon atoms. d Microenvironment surrounding a valine residue (PDB: 1VJ9 [64], VAL 200). The highlighted atom groups are the side-chains of MET 207, TRP 29 and ILE 121, which are similarly non-polar