respectively. Then, these extracted atom and residue features are processed by a pairwise interaction prediction module to derive the predicted pairwise interaction matrix
In a first pair having a first interaction and a second pair having a second interaction, more specifically speaking, at least one factor selected from four factors (i.e., the peak position in mass spectral data obtained for each compound, the peak position and intensity, the interval between...
26 Moreover, there is another hot task, drug–target interaction (DTI) prediction,27, 28, 29, 30, 31 which is similar to CPI prediction. Although both are essentially interactions between chemical compounds and proteins, their predictions are significantly different as follows. First, in terms ...
We herein evaluate the performance of DRIFT in terms of similar compound searching (Böhm et al., 2004), compound-protein interaction prediction, and drug target identification using three independent datasets. We provide a user-friendly webserver, DRIFT (http://Drift.Dokhlab.org), to ...
Improving compound- protein interaction prediction by building up highly credible negative samples. Bioinformatics. 2015;31(12):i221-9.Liu H, Sun J, Guan J, et al. Improving compound-protein interaction prediction by building up highly ... Zhou,Shuigeng,Zheng,... - 《Bioinformatics》 被引量:...
Categorization of compound-protein interaction (CPI) prediction models. FASTA, FAST-All; SMILES, Simplified molecular input line entry system. Protein structure-based CPI prediction Compound-protein interactions occur in three-dimensional space. The 3D structural data of protein-compound interactions can ...
ii“0_main” — 2022/12/23 — 2:04 — page 1 — #1iiiiiiSystem BiologyCSI: Contrastive Data Stratif i cation for InteractionPrediction and its Application toCompound-Protein Interaction PredictionApurva Kalia 1 , Dilip Krishnan 2 and Soha Hassoun 1,3,∗1 Department of Computer Science, ...
Combining effective feature embedding with powerful deep learning techniques, our method provides a general computational pipeline for accurate compound-protein interaction prediction, even when the interaction knowledge of compounds and proteins is entirely unknown. Evaluations on current large-scale databases...
However, compound-protein interaction is not a simple binary on-off relationship, but a continuous value reflects how tightly the compound binds to a particular target protein, also called binding affinity. RESULTS. In this study, we propose an end-to-end neural network model, called BACPI, ...
interaction (1 for existence, and 0 otherwise) between thei-th atom of the compound and thej-th residue of the protein when forming a complex structure. The interaction sites of the compound or protein can be then derived from this pairwise interaction matrix by maximizing over rows or ...