Update README.md

README.md

@@ -2,21 +2,20 @@
 license: cc-by-nc-sa-2.0
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 <div align='center'>
-<h1> MolCRAFT Series for Drug Design </h1>
+<h1> MolCRAFT Series for Drug Design: MolJO </h1>
 
-[![Github](https://img.shields.io/badge/Github-4d8cd8?style=for-the-badge&logo=googledrive&logoColor=white)](https://github.com/AlgoMole/MolCRAFT/tree/master)
+[![Github](https://img.shields.io/badge/Github-4d8cd8?style=for-the-badge&logo=github&logoColor=white)](https://github.com/AlgoMole/MolCRAFT/tree/master)
 [![Blog](https://img.shields.io/badge/Blog-3858bf?style=for-the-badge&logo=homepage&logoColor=white)](https://MolCRAFT-GenSI.github.io/)
 [![Data](https://img.shields.io/badge/Data-4d8cd8?style=for-the-badge&logo=googledrive&logoColor=white)](https://drive.google.com/drive/folders/16KiwfMGUIk4a6mNU20GnUd0ah-mjNlhC?usp=share_link)
 
 </div>
 
-
 Welcome to the official repository for the MolCRAFT series of projects! This series focuses on developing and improving deep learning models for **structure-based drug design (SBDD)** and **molecule optimization (SBMO)**. Our goal is to create molecules with high binding affinity and plausible 3D conformations.
 
 This repository contains the source code for the following projects:
 
 * [**MolCRAFT**: Structure-Based Drug Design in Continuous Parameter Space](https://arxiv.org/abs/2404.12141) (ICML'24)
-* [**MolJO**: Empower Structure-Based Molecule Optimization with Gradient Guidance](https://arxiv.org/abs/2411.13280) (ICML'25)
+* [**MolJO**: Empower Structure-Based Molecule Optimization with Gradient Guided Bayesian Flow Networks](https://arxiv.org/abs/2411.13280) (ICML'25)
 * [**MolPilot**: Piloting Structure-Based Drug Design via Modality-Specific Optimal Schedule](https://arxiv.org/abs/2505.07286) (ICML'25)
 
 ## 📜 Overview
@@ -34,48 +33,10 @@ The MolCRAFT series addresses critical challenges in generative models for SBDD,
 
 ---
 
-## 🚀 Projects
-
-### MolCRAFT (Let's Craft the Molecules)
-
-<p align="center"><img src="asset/molcraft.gif" width="60%"></p>
-
-* **Description**: MolCRAFT is the first SBDD model that employs BFN and operates in a **continuous parameter space**. It introduces a novel noise-reduced sampling strategy to generate molecules with superior binding affinity and more stable 3D structures. MolCRAFT has demonstrated its ability to accurately model interatomic interactions, achieving reference-level Vina Scores.
-* **Key Contributions**:
-    * Operates in continuous parameter space for SBDD within BFN framework.
-    * Novel variance reduction sampling strategy that improves both sample quality and efficiency.
-    * Achieves state-of-the-art binding affinity and structural stability.
-
----
-
-### MolJO (Molecule Joint Optimization)
-
-![](asset/moljo_framework_all.png)
-
-* **Description**: MolJO is a gradient-based SBMO framework that leverages a continuous and differentiable space derived through Bayesian inference. It facilitates **joint guidance signals across different modalities** (continuous coordinates and discrete atom types) while preserving SE(3)-equivariance. MolJO introduces a novel backward correction strategy for an effective trade-off between exploration and exploitation.
-* **Key Contributions**:
-    * Gradient-based SBMO framework with joint guidance across different modalities.
-    * Backward correction strategy for optimized exploration-exploitation.
-    * State-of-the-art performance in practical optimization tasks, including multi-objective and constrained optimization for R-group redesign, scaffold hopping, etc.
-
----
-
-### MolPilot (How to Pilot the Aircraft)
-
-![](asset/molpilot_vos.png)
-
-* **Description**: MolPilot addresses challenges in geometric structure modeling by focusing on the **twisted probability path of multi-modalities** (continuous 3D positions and discrete 2D topologies). It proposes a VLB-Optimal Scheduling (VOS) strategy, optimizing the Variational Lower Bound as a path integral for SBDD. MolPilot significantly enhances molecular geometries and interaction modeling.
-* **Key Contributions**:
-    * Addresses multi-modality challenges in SBDD.
-    * Introduces VLB-Optimal Scheduling (VOS) strategy, generally applicable to a wide range of frameworks including diffusions.
-    * Achieves 95.9% PoseBusters passing rate on CrossDock with significantly improved molecular geometries.
-
----
-
-# MolJO
-Official implementation of ICML 2025 ["Empower Structure-Based Molecule Optimization with Gradient Guidance"](https://arxiv.org/abs/2411.13280).
+# 🚀 MolJO
+Official implementation of ICML 2025 ["Empower Structure-Based Molecule Optimization with Gradient Guided Bayesian Flow Networks"](https://arxiv.org/abs/2411.13280).
 
-![](../asset/moljo_framework.png)
+![](https://github.com/AlgoMole/MolCRAFT/tree/master/asset/moljo_framework.png)
 
 ## Environment
 It is highly recommended to install via docker if a Linux server with NVIDIA GPU is available.