Update README.md and add MIT License: simplified title/overview, added TDC hyperlink, updated dataset descriptions, removed Authors/Related Work sections, added MIT License file

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2025 ToxiMol
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE. 

README.md

@@ -1,19 +1,17 @@
-# ToxiMol: Breaking Bad Molecules - A Benchmark for Structure-Level Molecular Detoxification
+# ToxiMol: A Benchmark for Structure-Level Molecular Detoxification
 
 [![arXiv](https://img.shields.io/badge/arXiv-Coming%20Soon-red.svg)](https://arxiv.org)
 [![Dataset](https://img.shields.io/badge/🤗%20Hugging%20Face-ToxiMol-blue)](https://huggingface.co/datasets/DeepYoke/ToxiMol-benchmark)
 
 ## Overview
 
-**ToxiMol** is the first comprehensive benchmark for **molecular toxicity repair** tailored to general-purpose **Multimodal Large Language Models (MLLMs)**. This benchmark extends beyond conventional toxicity prediction and ADMET modeling, aiming to assess the ability of MLLMs to perform complex molecular structure refinement for detoxification purposes.
-
-Toxicity remains a leading cause of early-stage drug development failure, with approximately 90% of candidate compounds failing due to poor ADMET properties. Traditional toxicity mitigation strategies rely heavily on expert knowledge and extensive iterative experimentation. ToxiMol evaluates whether general-purpose MLLMs possess the capacity to recognize and repair toxic molecules, supporting the "detoxification" objectives of molecular design.
+**ToxiMol** is the first comprehensive benchmark for **molecular toxicity repair** tailored to general-purpose **Multimodal Large Language Models (MLLMs)**. This is the dataset repository for the paper "Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification?".
 
 ## Key Features
 
 ### 🧬 Comprehensive Dataset
 - **560 representative toxic molecules** spanning diverse toxicity mechanisms and varying granularities
-- **11 primary toxicity repair tasks** based on Therapeutics Data Commons (TDC) platform
+- **11 primary toxicity repair tasks** based on [Therapeutics Data Commons (TDC) platform](https://tdcommons.ai/single_pred_tasks/tox/)
 - **Multi-granular coverage**: Tox21 (12 sub-tasks), ToxCast (10 sub-tasks), and 9 additional datasets
 - **Multimodal inputs**: SMILES strings + 2D molecular structure images rendered using RDKit
 
@@ -39,12 +37,12 @@ The molecular toxicity repair task requires models to:
 | **ClinTox** | Binary Classification | 50 | Clinical toxicity data |
 | **DILI** | Binary Classification | 50 | Drug-induced liver injury |
 | **hERG** | Binary Classification | 50 | hERG channel inhibition |
-| **hERG_Central** | Binary Classification | 50 | Alternative hERG dataset |
+| **hERG_Central** | Binary Classification | 50 | Large-scale hERG database with integrated cardiac safety profiles |
 | **hERG_Karim** | Binary Classification | 50 | hERG data from Karim et al. |
 | **LD50_Zhu** | Regression (log(LD50) < 2) | 50 | Acute toxicity |
 | **Skin_Reaction** | Binary Classification | 50 | Adverse skin reactions |
-| **Tox21** | Binary Classification (12 sub-tasks) | 60 | Nuclear receptor & stress response pathways |
-| **ToxCast** | Binary Classification (10 sub-tasks) | 50 | Pathway-specific toxicity |
+| **Tox21** | Binary Classification (12 sub-tasks) | 60 | Nuclear receptors, stress response pathways, and cellular toxicity mechanisms (ARE, p53, ER, AR, etc.) |
+| **ToxCast** | Binary Classification (10 sub-tasks) | 50 | Diverse toxicity pathways including mitochondrial dysfunction, immunosuppression, and neurotoxicity |
 
 ### Data Structure
 Each entry contains:
@@ -112,24 +110,6 @@ If you use this dataset in your research, please cite:
 }
 ```
 
-## Authors
-
-**Fei Lin**¹†, **Ziyang Gong**²⁵†, **Cong Wang**³⁴†, **Yonglin Tian**³,  
-**Tengchao Zhang**¹, **Xue Yang**², **Gen Luo**⁵, **Fei-Yue Wang**¹³⁴*
-
-¹MUST, ²SJTU, ³CASIA, ⁴UCAS, ⁵Shanghai AI Lab
-
-† Equal Contribution  
-\* Corresponding author: [email protected]
-
 ## License
 
-[License information to be added]
-
-## Related Work
-
-This work contributes to the intersection of:
-- **Multimodal Large Language Models** in scientific domains
-- **Molecular toxicity prediction** and **ADMET modeling**
-- **Structure-based drug design** and **molecular optimization**
-- **Automated evaluation frameworks** for molecular generation tasks
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.