Tam's Blog

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 Data Modeller offers different types of data modelling:
Multiple Linear Regression models simple linear relations between data, and is fast and efficient.
Partial Least Squares reduces the dimensionality of the data set before creating a model. Suitable for data sets with many independent variables.
Neural Networks are able to model highly non-linear relations.
Support Vector Machines are also able to model complex relations and tend to be less prone to overfitting than Neural Networks.
K-Nearest-Neighbors for simple classification.

            
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