Molegro Virtual Docker is an integrated platform for predicting protein-ligand interactions. Molegro Virtual Docker handles all aspects of the docking process from preparation of the molecules to determination of the potential binding sites of the target protein, and prediction of the binding modes of the ligands.

Molegro Virtual Docker offers high-quality docking based on a novel optimization technique combined with a user interface experience focusing on usability and productivity.

The Molegro Virtual Docker (MVD) has been shown to yield higher docking accuracy than other state-of-the-art docking products (MVD: 87%, Glide: 82%, Surflex: 75%, FlexX: 58%).

Molegro Virtual Docker provides

• High docking accuracy: the docking engine has been proven to correctly identify binding modes with high accuracy. Molegro Virtual Docker has been shown to outperform other docking programs with regard to identification of correct binding modes
• Easy-to-use interface: the built-in wizards enable the user to easily setup and perform docking runs. Advanced visualization and analysis tools are provided to examine ligand-receptor interactions and fine-tune found docking solutions
• Cross-platform: supported on Linux, Windows and Mac, allowing easy interoperability between platforms

A lot of powerful data modelling tools are also available directly from within Molegro Virtual Docker. Some of these features include:

• New and powerful regression features: Support Vector Machine regression and Partial Least Squares
• Classification using either K-Nearest Neighbors or Support Vector Machine classification
• Automated fine-tuning of regression and classification model parameters
• Spring-Mass Maps for visualization of high-dimensional data
• Clustering of data sets and subset selection
• Principal Component Analysis
• Outlier Detection

Software for drug discovery

• GPU-accelerated docking using CUDA.
• Protein-Ligand docking with cavity prediction.
• Similarity screening (template docking).
• Induced fit and displaceable water models.
• Molecular descriptors. Create regression models (neural nets and MLR).
• Repair and mutate residues.
• For Windows, Mac, and Linux.

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