HIGHLIGHTS
- What: To assay the efficacy of the model the authors conducted validation on the membrane-permeability of cyclic peptides which achieved an accu racy of 0.87 and R-squared of 0.503 on CycPeptMPDB using semi-supervised training and obtained an accuracy of 0.84 and R-squared of 0.384 using a model with frozen parameters on an external dataset. In this regard, the authors propose MuCoCP, a multimodal contrastive learn ing pre-trained neural_network based on priori chemical knowl edge for analyzing cyclic peptide properties. Given this, the authors propose a multimodal framework aimed . . .

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