Deep geometric representations for modeling effects of mutations on protein-protein binding affinity
Fig 5
A case study on the antibodies (Abs) that neutralize SARS-CoV-2 by binding with the receptor-binding domain (RBD) of the spike protein.
(A) Structurally similar SARS-CoV-2 neutralizing Abs and their CDR3 sequences (S9 Table). (B) Pairwise prediction performance between structurally similar Abs. The structures of these Abs are not solved and approximated by homology modeling. (C and D) Prediction performance of GeoPPI and TopGBT on the single-point mutations of SARS-CoV-2 complexed with individual Abs. This newly collected single-point mutation dataset (S10 Table) contains 98 mutations and corresponding binding affinity changes, including the complexes of SARS-CoV-2 bound to CR3022 [40], C002, C104, C105, C110, C121, C119, C135, C144 [41]. Among them, GeoPPI obtains the highest correlation on the variants of C110. (E) The average predicted affinity changes of the mutations on each residue on the interface of C110 complexed with SARS-CoV-2. (F) The structure around site A107 on C110. (G) The structure around site W107 on C110 with the mutation A107W.