Fig. 1
From: PS3N: leveraging protein sequence-structure similarity for novel drug-drug interaction discovery
Proposed protein sequence-structure similarity network (PS3N) model for predicting adverse drug events. Using the method of Similarity Network Fusion (SNF) we create a single \(N \times N\) fusion matrix for N drugs. From the fusion matrix, we compute the feature vectors for each pair of drugs. PT denotes protein targets. In this way, we will have possible \(\left( {\begin{array}{c}N\\ 2\end{array}}\right)\) rows and each row will have N columns as features. These feature vectors are then fed into a multi-layer perception model. For the protein sequence similarity network, the number of hidden layers would reduce to 3 since we have less number of drugs.
