Ultra-Large Libraries

• Working with Large Virtual Chemical Libraries: Part 3 - Thompson Sampling for Classification

  Exhaustively screening billion-compound virtual libraries would take decades, so we need smarter ways to hunt for molecules. I look at how we can adapt Thompson Sampling, a classic reinforcement learning technique, using the Beta distribution to efficiently find active compounds without breaking our computers.

  Read article

• Working with Large Virtual Chemical Libraries: Part 2 - Genetic Algorithms

  When a virtual library is way too massive to screen one molecule at a time, genetic algorithms offer an elegant way out. In part two of this series, I explore how biologically inspired selection can navigate massive combinatorial spaces using just building block data.

  Read article

• Working with Large Virtual Chemical Libraries: Part 1 - Active Learning

  If a computational scoring function takes just one second per molecule, screening a billion-compound library would take nearly 32 years. In part one of this series, I look at how we can use active learning loops to train a machine learning model, allowing us to intelligently hunt down the highest-performing molecules without exhaustively testing the whole library.

  Read article