The three-dimensional structure prediction tool of protein-small molecule complexes based on deep learning algorithm can obtain the interaction information between compounds and specific residues according to the three-dimensional structure, and provide clues for the structure optimization of small molecules.

A virtual screening tool based on deep learning algorithms to rapidly screen chemically diverse small molecule libraries to obtain a list of potentially active molecules.

A tool for predicting the three-dimensional structure of protein-protein complexes, providing clues for the study of protein structure and function.

Predict the three-dimensional structure of the target protein (POI), E3 ligase, and PROTAC ternary complex, and evaluate the rationality of linker fragments of different lengths to form PROTAC molecules.

2D chemical structure cluster analysis

Given a target molecule, a built-in library of target structures is screened to obtain potential targets that the molecule may bind to.

Protein-DNA Complex Structure Prediction Tool

Protein-RNA Complex Structure Prediction Tool

A 3D structure prediction tool for antigen-antibody complexes based on deep learning algorithms. Based on the predicted structures, energy contributions of the interfacial contact residues are calculated, which may provide clues for CDR optimization.

According to the signaling pathway, the built-in target related to the pathway can be selected, and molecular docking can be carried out for some or all of the targets related to the pathway.

According to the signaling pathway, the built-in target related to the pathway can be selected, and molecular docking can be carried out for some or all of the targets related to the pathway.

Users can create custom target sets for molecular docking against some or all of the custom target sets.

Predicting potential interacting target proteins based on target protein sequences

Compound synthesis route design based on deep learning algorithm, given target compound to generate synthesis route.

HNMR prediction based on experimental data

Prediction of boiling point at different pressures (0.5-760mmHg)