Deep Learning in Drug Design

<p>PART 1: Deep learning theories and methods for drug design</p><p>1. CHAPTER 1 Molecular representations in deep learning</p><p>2. CHAPTER 2 CNNs in drug design</p><p>3. CHAPTER 3 GNNs in drug design</p><p>4. CHAPTER 4 RNNs and LSTM in drug design</p><p>5. CHAPTER 5 Deep reinforcement learning in drug design</p><p>6. CHAPTER 6 Transformer and drug design</p><p>7. CHAPTER 7 Generative models for drug design</p><p>8. CHAPTER 8 Geometric graph learning for drug design</p><p>9. CHAPTER 9 Self-supervised learning for drug discovery</p><p>10. CHAPTER 10 Transfer learning and meta-learning for drug discovery</p><p>11. CHAPTER 11 Explainable artificial intelligence for drug design models</p><p>12. CHAPTER 12 Large models in drug design</p> <p>PART 2: Deep learning applications in drug design</p><p>13. CHAPTER 13 Deep learning for protein secondary structure prediction</p><p>14. CHAPTER 14 Deep learning in protein structure prediction</p><p>15. CHAPTER 15 Deep learning for affinity prediction and interface prediction in molecular interactions</p><p>16. CHAPTER 16 Deep learning for complex structure prediction in molecular interactions</p><p>17. CHAPTER 17 Deep learning in chemical synthesis and retrosynthesis</p><p>18. CHAPTER 18 Deep learning for ADME prediction</p><p>19. CHAPTER 19 Deep learning for toxicity prediction</p><p>20. CHAPTER 20 Deep learning for TCR-pMHC binding prediction</p><p>21. CHAPTER 21 Deep learning for B-cell epitope prediction and receptor-antigen binding</p><p>prediction</p><p>22. CHAPTER 22 Deep learning for antigen-specific antibody design</p><p>23. CHAPTER 23 Ethical and regulatory of artificial intelligence in drug design</p>