This simulation offers insights into the behavior of proteins in an aqueous environment. Our pipeline is equipped with advanced force fields to recognize over 250 post-translational modifications (PTM), enabling in-depth analysis of protein stability, folding, and impact of mutation or PTM on protein conformation.
Use Cases
This simulation focuses on the interaction dynamics between proteins and ligands, crucial for drug discovery and target validation. Our pipeline allows researchers to assess the stability of ligand within the binding pocket, calculate binding free energy between ligand and protein, and gain a clear view of interaction behavior over time.
Use Cases
With ScientiFlow's pipeline, researchers can upload their protein structure and define the binding pocket for virtual drug screening. The process begins with screening compounds from ChemBL and FDA-approved drug databases using AutoDock Vina. Next, potential drugs are filtered by ADMET properties, followed by GNINA's AI-based CNN model for rigorous docking and enhanced scoring to identify potential leads. Finally, custom Python scripts analyze all possible bonded and non-bonded interactions between the top drug candidates and the protein target.
Use Cases
Cryo-EM data processing involves complex image reconstruction and refinement steps to produce high-resolution protein structures. Our automated pipeline utilizes RELION and other processing tools to refine raw Cryo-EM data, yielding high-quality 3D reconstructions that provide insights into macromolecular assemblies.
Use Cases