Receptor Protein Screening

1 Product Overview

This product offers significant technical advantages and service features. First, it is highly efficient and flexible. Utilizing an advanced high-throughput computational platform, it enables the rapid completion of tens of thousands of compound-protein docking screenings, significantly shortening research timelines. Second, the product supports personalized customization. Researchers can select specific compound libraries and protein target databases according to project requirements or dynamically adjust screening parameters to ensure results align closely with their research needs. In addition, the service employs state-of-the-art modeling technologies (e.g., AlphaFold) to generate high-accuracy protein structures, ensuring precision in docking analyses. Finally, binding energy analysis and visualized binding mode representations not only provide robust support for validating target proteins but also lay a solid foundation for subsequent compound optimization and efficacy research. In summary, this service provides biological researchers with an efficient, reliable, and data-rich tool for target prediction, aiding in drug discovery, mechanism exploration, and biotechnology innovation.

2 Product Screening Workflow

    2.1 Construction of Compound Models and Target Protein Libraries

Complete compound data, including molecular structures, physicochemical properties, and drug-likeness parameters, are collected to ensure the reliability of the screening process. The 3D structural models of compounds are created using ChemDraw. For all target proteins, amino acid sequences are obtained, and precise modeling is performed. Subsequently, ligand removal, ion removal, and hydrogenation are conducted, followed by file format conversion for further use.

    2.2 Molecular Docking Screening

Using AutoDock Vina, large-scale molecular docking is performed under the strictest parameters. The binding energies between compounds and all target proteins are calculated and ranked in descending order of binding affinity.

    2.3 Visualization of Binding Conformations (Optional)

Using DiffDock and NeuralPlexer, the binding conformations between target compounds and proteins are analyzed in detail. The best binding modes are identified based on confidence scores, while the interactions between compound functional groups and amino acid residues of the target protein are examined. This provides guidance for subsequent compound modifications to improve activity and stability while reducing drug toxicity.

3 Deliverables