Slogen: A Structure-based Lead Optimization Model Unifying Fragment Generation and Screening 1. Slogen is a groundbreaking model in the field of structure-based drug design, aiming to enhance the efficiency and effectiveness of lead optimization. It combines fragment generation and screening in a unified framework, addressing key challenges in synthetic feasibility and structural innovation. 2. The model integrates a transformer-based variational autoencoder (VAE) with an E(3)-equivariant graph neural network (GNN). The VAE is pretrained on a diverse set of fragments, enabling both generative decoding and similarity-based screening. The GNN captures 3D protein–fragment interactions, predicting optimal fragment elaborations. 3. Slogen demonstrates superior performance in fragment elaboration tasks, achieving higher hit rates and better binding affinities compared to state-of-the-art models like Delete and DeepFrag. It also explores a broader chemical space, generating more diverse and drug-like molecules. 4. In screening tasks, Slogen shows competitive performance, particularly on the Delete test set, significantly outperforming traditional methods such as AutoDock Vina. This highlights its potential for practical applications in fragment-based drug discovery. 5. Case studies on the Smoothened receptor (SMO) and D1 dopamine receptor (D1DR) further illustrate Slogen's ability to design high-affinity, drug-like molecules. These examples demonstrate its versatility and practical utility in real-world drug design scenarios. 6. Despite its strengths, Slogen has areas for improvement. It performs well in generating chemically plausible ring structures but struggles with capturing the distribution of BM scaffolds. Future work could focus on pretraining with a more diverse fragment set and incorporating advanced GNN architectures. 7. The study emphasizes the importance of a balanced fragmentation strategy that ensures both synthetic tractability and chemical diversity. Slogen's unified approach provides a scalable route toward structure-guided lead optimization, bridging the gap between fragment generation and screening. 📜Paper: biorxiv.org/content/10.1101/… #Slogen #LeadOptimization #StructureBasedDesign #DrugDiscovery #AIinPharma #FragmentGeneration #Screening #ComputationalBiology