The ACtilA Comformer algorithm begins by generating an initial set of molecular conformations. These initial structures are then evaluated using physics-based models to determine their energy values. The algorithm proceeds to narrow down the possibilities by selectively pruning or filtering out conformations with unfavorable energy profiles. Additionally, artificial intelligence (AI) based on machine learning is incorporated to generate deeper understanding of molecular characteristics that might contribute to mature structures.
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