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Trained caffe models
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Question about only train CNN_affinity for crossdock_default2018. #29

Open RJ-Li opened 1 year ago

RJ-Li commented 1 year ago

Hello developers!

I saw the format of types for training both CNN_score and CNN_affinity needs rmsd and affinity label, but I don't wanna train or use CNN_score in my work, so I am searching for how to make it only for CNN_affinity.

But different papers have different types file format, such as in data/PDBBind2016/Refined_types:

dkoes commented 1 year ago

You can adjust the model file (https://github.com/gnina/models/blob/master/acs2018/default2018.model) to only use the labels you want in the loss function.

RJ-Li commented 1 year ago

Hi, just ask you to make sure the built-in crossdock_default2018.caffemodel is trained on crossdock2020 dataset or PDBbind_v2019_refined-set? I only know its redocking power is tested on PDBbind_v2019_refined-set, and crossdock2020 is generated based on Pocketome.

dkoes commented 1 year ago

The crossdock prefix means it was trained on the crossdocked set.

Dadiao-shuai commented 1 year ago

Have you trained the default2018.model on PDBbind_v2020/v2019? I read the article Three-Dimensional Convolutional Neural Networks and a CrossDocked Data Set for Structure-Based Drug Design , which says you trained them on PDBbind_v2016