QPowered Compound2DeNovoDrugPropMax –A Novel Programmatic Tool Incorporating Deep Learning and In Silico Methods for Automated In Silico Bio- Activity Discovery for any Compound of Interest

Network data is composed of nodes and edges. Successful application of machine learning/deeplearning algorithms on network data to make node classification and link prediction have been shownin the area of social networks through which highly customized suggestions are offered to socialnetwork users. Similarly one can attempt the use of machine learning/deep learning algorithms onbiological network data to generate predictions of scientific usefulness. In the presented work,compound-drug target interaction network data set from bindingDB has been used to train deeplearning neural network and a multi class classification has been implemented to classify PubChemcompound queried by the user into class labels of PBD IDs. This way target interaction prediction forPubChem compounds is carried out using deep learning. The user is required to input the PubChemCompound ID (CID) of the compound the user wishes to gain information about its predictedbiological activity and the tool outputs the RCSB PDB IDs of the predicted drug target interaction forthe input CID. Further the tool also optimizes the compound of interest of the user toward druglikeness properties through a deep learning based structure optimization with a deep learning baseddrug likeness optimization protocol. The tool also incorporates a feature to perform automated InSilico modelling for the compounds and the predicted drug targets to uncover their protein-ligandinteraction profiles. The program is hosted, supported and maintained at the following GitHubrepositoryhttps://github.com/bengeof/Compound2DeNovoDrugPropMaxAnticipating the rise in the use of quantum computing and quantum machine learning in drug discovery we usethe Penny-lane interface to quantum hardware to turn classical Keras layers used in our machine/deeplearning models into a quantum layer and introduce quantum layers into classical models to produce aquantum-classical machine/deep learning hybrid model of our tool and the code corresponding to thesame is provided belowhttps://github.com/bengeof/QPoweredCompound2DeNovoDrugPropMax