Innoplexus Ag

Ansh Gupta

Om Sharma

Hari Kapa

Sudhanshu Kumar

Joel Joseph

Sandhya V

There is disclosed an Artificial Intelligence (AI) assisted drug discovery system and a method for generating active and inactive targets for a given drug. The generated targets comprise the complete target landscape for the given drug. The system comprises a processor which is configured to train a multi-label deep learning neural network and a predictive model to generate and validate a prediction score, and further execute the trained multi-label deep learning neural network and the trained predictive model to identify targets associated with the given drug, and generate the active and inactive targets for the given drug molecule in response to the generated prediction score for each target associated with the given drug.

System for prediction of the drug target landscape for therapeutic use and a method thereof

A system and a method for converting protein data bank (PDB) files into a grayscale image array is provided. The method includes extracting PDB files from a PDB, using a data extraction module. The method also includes converting, using a file conversion module, the PDB files into a data frame based on BioPandas. The method further includes selecting, using a column selection module, one or more columns from the data frame based on a pre-determined criteria. The method furthermore includes converting, using a column conversion module, the selected one or more columns into a NumPy array for rendering the data frame to resemble an image. The method furthermore includes resizing the NumPy array using an OpenCV for making size of the NumPy array uniform and for generating a grayscale image array.

Growing community of inventors

Menhdawal, India

Ansh Gupta