Abstract: The present disclosure relates to novel compounds, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of cancer and related diseases and conditions.

Abstract: The present disclosure relates to novel compounds, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of estrogen-related diseases and conditions.

Abstract: The present disclosure relates to novel compounds, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of cancer and related diseases and conditions. In some embodiments, the compounds disclosed herein exhibit androgen receptor degradation activity.

Abstract: The present disclosure relates to novel compounds, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of cancer and related diseases and conditions. In some embodiments, the compounds disclosed herein exhibit androgen receptor degradation activity.

Abstract: The present disclosure relates to novel compounds, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of cancer and related diseases and conditions. In some embodiments, the compounds disclosed herein exhibit androgen receptor degradation activity.

Abstract: A computer-implemented method for predicting molecule properties is disclosed. According to some embodiments, the method may include receiving an input file of a compound. The method may also include implementing a neural network to determine molecular configurations of the compound based on the input file and a plurality of molecular descriptors associated with the compound. The method may also generating, using the neural network, one or more three-dimensional (3D) models of the compound based on the determined molecular configurations of the compound. The method may also include determining, using the neural network, energy scores of the one or more 3D models when the compound is docked into a protein. The method may further include determining a property of the docked compound based on the energy scores.

Abstract: The present disclosure relates to novel compounds, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of cancer and related diseases and conditions. In some embodiments, the compounds disclosed herein exhibit androgen receptor degradation activity.

Abstract: The present disclosure relates to novel compounds, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of cancer and related diseases and conditions.

Abstract: The present disclosure relates to novel compounds having estrogen receptor alpha degradation activity, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of cancer and related diseases and conditions.

Abstract: The present disclosure relates to novel compounds having estrogen receptor alpha degradation activity, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of cancer and related diseases and conditions.

Abstract: The present disclosure relates to novel compounds having estrogen receptor alpha degradation activity, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of cancer and related diseases and conditions.

Abstract: The present disclosure relates to novel compounds, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of estrogen-related diseases and conditions.

Abstract: A computer-implemented method for predicting molecule properties is disclosed. According to some embodiments, the method may include receiving an input file of a compound. The method may also include implementing a neural network to determine molecular configurations of the compound based on the input file and a plurality of molecular descriptors associated with the compound. The method may also generating, using the neural network, one or more three-dimensional (3D) models of the compound based on the determined molecular configurations of the compound. The method may also include determining, using the neural network, energy scores of the one or more 3D models when the compound is docked into a protein. The method may further include determining a property of the docked compound based on the energy scores.

Abstract: A computer-implemented method for predicting a conformation of a ligand docked into a protein is disclosed. According to some embodiments, the method may include determining one or more poses of the ligand in the protein, the poses being representative conformations of the ligand. The method may also include determining, using a neural network, energy scores of the poses. The method may further include determining a proper conformation for the docked ligand based on the energy scores.

Abstract: The present disclosure relates to novel compounds, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of estrogen-related diseases and conditions.

Abstract: The present disclosure relates to novel compounds, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of estrogen-related diseases and conditions.

Abstract: The present disclosure relates to novel compounds, pharmaceutical compositions containing such compounds, and their use in prevention and treatment of estrogen-related diseases and conditions.

Abstract: Computational methods for classifying and predicting protein side chain conformations utilizing a data driven scoring function are disclosed. According to some embodiments, the methods may include obtaining structure data representing a plurality of conformations of a compound. The methods may also include determining structural differences among the conformations. The methods may also include classifying, based on the structural differences, the conformations into one or more clusters. The methods may also include determining representative conformations of the dusters, wherein an average structural difference between a representative conformation of a duster and conformations in the duster is below a predetermined threshold. The method may further include determining the representative conformations as poses of the compound.