D3CARP is a comprehensive target prediction and virtual screening platform composed of three representative drug design techniques, namely molecular docking, ligand similarity approach, and deep learning methods.
Overview of the target and ligand database:
• ~ 1 million molecules for 2D and 3D ligand similarity approaches.
• 9352 multi-conformational targets for molecular docking.
• 716 representative targets for rapid molecular docking.
• 5901 targets for deep learning-based classification model prediction.
• 2568 targets for deep learning-based regression model prediction.
• 1447 therapeutic targets.
• 2168 clinical diseases.
Target Prediction:
Virtual Screening
Citation
Shi, Y.; Zhang, X.; Yang, Y.; Cai, T.; Peng, C.; Wu, L.; Zhou, L.; Han, J.; Ma, M.; Zhu, W.; Xu, Z., D3CARP: a comprehensive platform with multiple-conformation based docking, ligand similarity search and deep learning approaches for target prediction and virtual screening. Comput. Biol. Med. 2023, 164, 107283. DOI:https://doi.org/10.1016/j.compbiomed.2023.107283
About D3Pharma
D3Pharma.com is a non-profit scientific research website.
It is developed by Prof Weiliang Zhu’s Laboratory, SIMM, CAS. It is composed of some drug discovery and design tools developed by the research group.
• D3Target-2019-nCov: a webserver provides multiple approaches to develop drugs against 2019-nCoV (SARS-COV-2), and to predict target proteins for the target-unknown active compounds or efficient drugs.
• D3Pockets: a webserver to detect and analyze the dynamic properties of ligand binding pockets on drug target protein.
• D3CARP: a comprehensive target prediction and virtual screening platform.
• D3DistalMutaion: a database describes the effect of distal mutation (mutations more than 10 Å away from the active site) on enzyme activity and classified enzymes into four classes, viz., no activity change, decrease activity, loss of activity and increase activity.
• D3PM: a database collects all kinds of protein motions, including overall structural changes upon ligand binding and the inherently flexibility of protein, as well as flap movements of residues within binding pocket.
• D3EGFR: a webserver for drug sensitivity retrieval and deep learning-guided drug sensitivity prediction of EGFR mutation-driven lung cancer.