PepPCBench enables a robust evaluation of PFNN-based methods and supports their continued development for peptide-protein structure prediction, and highlights the influence of peptide length, conformational flexibility, and training set similarity on prediction accuracy.
Si-Long Zhai, Huifeng Zhao, Ji-Ke Wang et al.· Journal of Chemical Informat...· 13 citations· ⚡1
CarsiDock-Cov is presented, a new paradigm distinguishing itself as the first deep learning (DL)-guided approach for covalent docking, offering an automated and efficient solution that shows considerable promise for accelerating covalent drug discovery and design.
Chao Shen, Hongyan Du, Xujun Zhang et al.· Acta Pharmaceutica Sinica B· 12 citations
The results indicate that this fully automated, open-source system holds potential value for improving the efficiency and sustainability of molecular synthesis, and the integration of organic and enzymatic synthesis enhances molecule construction efficiency.
ERAM aligns pre-trained molecular representations from Protein Language Model with the knowledge of enzyme catalysis by modeling enzymatic reactions as multi-relational data, and demonstrates its potential as a versatile and effective tool for enzyme catalysis research.
An integrated virtual screening strategy based on molecular fingerprint similarity, pharmacophore models, molecular docking, and molecular dynamics simulation is proposed and three promising lead compounds targeting RIPK3 for AD treatment are offered.
Chenggong Fu, Qin Li, Yuwei Yang et al.· Molecular diversity· 0 citations
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