Supplementary Figure 6: MaSIF-search protocol for the generation of protein complexes.

a. A fingerprint is computed on a selected target site (left). A database of proteins with precomputed fingerprints is searched for the K-most similar fingerprints. Once these are matched, a set of correspondences between the matched patches is found with the RANSAC algorithm, which uses the fingerprints of other points in the patch to obtain a good alignment. RANSAC selects the alignment with the most points within 1.5 Å of each other. The transformation is then scored using: Euclidean distances; fingerprint distances; and the normal products between neighboring points (see Methods). b. Neural network architecture for the alignment scoring function. Correspondences are first assigned between the aligned binder and target patches based on the nearest point in 3D space. For every correspondence, the 3D distance between the points, the Euclidean distance between the fingerprint descriptors and the product of their normals is input into the neural network. The input is a matrix of size 200 by 3: the maximum number of points allowed in the patch times the three features. The output is a 2-dimensional logit with the predicted score.