Drug Discovery

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• AI 'scientist' finds that toothpaste ingredient may help fight drug-resistant malaria
• FDA to Test New Trial Designs, Assess A.I. Models

Applications of machine learning in drug discovery and development | J. Vamathevan, D. Clark, P. Czodrowski, I. Dunham, E. Ferran, G. Lee, B. Li, A. Madabhushi, P. Shah, M. Spitzer, and S. Zhao

Drug Discovery using Python

• ESOL:  Estimating Aqueous Solubility Directly from Molecular Structure | John S. Delaney
• Maximizing computational tools for successful drug discovery | Chanin Nantasenamat and Virapong Prachayasittikul
• Machine Learning for Making Sense of Big Data in Drug Discovery Presentation | Chanin Nantasenamat
• Cheminformatics in Python: Predicting Solubility of Molecules | End-to-End Data Science Project Code | Chanin Nantasenamat - GitHub ...Libraries: PyCaret, scikit-learn, Pandas, and RDKit; a toolkit for cheminformatics. Environment: Colaboratory
• Using Computer Code to Decipher Genetic Code
• ROSALIND Platform

In this Jupyter notebook, we will dive into the world of Cheminformatics which lies at the interface of Informatics and Chemistry. We will be reproducing a research article (by John S. Delaney) by applying Linear Regression to predict the solubility of molecules (i.e. solubility of drugs is an important physicochemical property in Drug discovery, design and development). This idea for this notebook was inspired by the excellent blog post by Pat Walters where he reproduced the Linear Regression model with similar degree of performance as that of Delaney. This example is also briefly described in the book Deep Learning for the Life Sciences: Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More.Cheminformatics in Python: Predicting Solubility of Molecules | End-to-End Data Science Project | Chanin Nantasenamat