fix app link; add gif (#241)

* fix app link; add gif

* add gif

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Co-authored-by: zhougm <[email protected]>

Author: ZhouGengmo

README.md

@@ -57,11 +57,11 @@ Documentation of Uni-Mol tools is available at https://unimol.readthedocs.io/en/
 
 Uni-Mol Docking V2: Towards realistic and accurate binding pose prediction
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-[![arXiv](https://img.shields.io/badge/arXiv-2405.11769-00ff00.svg)](https://arxiv.org/abs/2405.11769) ![Static Badge](https://img.shields.io/badge/Bohrium_Apps-Uni--Mol_Docking_V2-blue?link=https%3A%2F%2Fbohrium.dp.tech%2Fapps%2Funimoldockingv2)
+[![arXiv](https://img.shields.io/badge/arXiv-2405.11769-00ff00.svg)](https://arxiv.org/abs/2405.11769) [![Static Badge](https://img.shields.io/badge/Bohrium_Apps-Uni--Mol_Docking_V2-blue)](https://bohrium.dp.tech/apps/unimoldockingv2)
 
 
-<p align="center"><img src="unimol_docking_v2/figure/bohrium_app.png" width=60%></p>
-<p align="center"><b>Uni-Mol Docking V2 Bohrium App Interface</b></p>
+<p align="center"><img src="unimol_docking_v2/figure/bohrium_app.gif" width=60%></p>
+<p align="center"><b>Uni-Mol Docking V2 Bohrium App</b></p>
 
 We update Uni-Mol Docking to Uni-Mol Docking V2, which demonstrates a remarkable improvement in performance, accurately predicting the binding poses of 77+% of ligands in the PoseBusters benchmark with an RMSD value of less than 2.0 Å, and 75+\% passing all quality checks. This represents a significant increase from the 62% achieved by the previous Uni-Mol Docking model. Notably, our Uni-Mol Docking approach generates chemically accurate predictions, circumventing issues such as chirality inversions and steric
 clashes that have plagued previous ML models.