Enzymes are proteins that act as catalysts in the chemical reactions of living organisms. The goal of this competition is to predict the thermostability of enzyme variants. The experimentally measured thermostability (melting temperature) data includes natural sequences, as well as engineered sequences with single or multiple mutations upon the natural sequences.
Understanding and accurately predict protein stability is a fundamental problem in biotechnology. Its applications include enzyme engineering for addressing the world’s challenges in sustainability, carbon neutrality and more. Improvements to enzyme stability could lower costs and increase the speed scientists can iterate on concepts. data extracted from :kaggle/input/novozymes-enzyme-stability-prediction/train.csv Objective :To develop a model to predict/rank the thermostability of enzyme variants based on experimental melting temperature data, which is obtained from Novozymes’s high throughput screening lab. Approch:Amino enzymes have been extracted from series of protein sequence and random forest approch is choosen for best performace along hyperparameter tuning.