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This study applies Taft linear free-energy relationships to study kinetic trends in the enzymatic hydrolysis of sterically hindered substrates.

Although the 5-year survival rate for colorectal cancer is below 10%, it increases to greater than 90% if it is diagnosed early. We hypothesized from our research that analyzing non-synonymous single nucleotide variants (SNVs) in a patient's exome sequence would be an indicator for high genetic risk of developing colorectal cancer.

The authors investigate the ability of machine learning models to developing new drug-like molecules by learning desired chemical properties versus simply generating molecules that similar to those in the training set.

The authors use the Lanczos algorithm to computationally solve the Schrodinger equation for 2D potentials with a Python program