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1 Overview

序号 名称 来源/下载地址 相关文献 安装步骤 测试
01 ShapeProtrudeDist rdkit - -
02 ShapeTanimotoDist rdkit - -
03 ShapeTverskyIndex rdkit - -
04 SC score rdkit @Yang2020 -
05 Gobbi_Pharm2D rdkit - -
06 USR oddt @Ballester2007 -
07 USRCAT oddt @Schreyer2012 -
08 Electroshape oddt @Armstrong2010 -
09 ACPC riken @Berenger2014 Installation
10 ESP-Sim pip @Bolcalto2021 -
11 PAPER SimTK @Haque2010 software
12 MolShaCS code.google @VazdeLima2013 -
13 🌟SHAFTS lilab @Liu2011 software
14 ShaEP mivainio @Vainio2009 -
15 SimG lilab @Cai2013 software
16 EGNN git @Satorras2022 usage
-
  • 相关综述:
    • [@Bero2017] Similarity Measure for Molecular Structure: A Brief Review
    • [@Kumar2018] Advances in the Development of Shape Similarity Methods and Their Application in Drug Discovery
    • [@Jiang2021a] A comprehensive comparative assessment of 3D molecular similarity tools in ligand-based virtual screening

2 Installation

2.1 ACPC


  1. Install Opam
    sudo apt install software-properties-common
    sudo add-apt-repository ppa:avsm/ppa # may get message that `ERROR: '~avsm' user or team does not exist`, please try again
    sudo apt update
    sudo apt install gnuplot-x11 autoconf opam make gcc patch
  2. Initialization Opam
    rm -rf ~/.opam
    opam init --disable-sandboxin # for LXC container
  3. Install ACPC
    opam install ACPC # try until prompt change from `Processing  1/1: [default: http]` to `Processing  1/1`:

2.2 PAPER


已下载在molecule-3d-similarity/softwares/目录下

2.3 SHAFTS


已下载在molecule-3d-similarity/softwares/目录下, 如果出现./Cynthia: No such file or directory错误,可以尝试安装sudo apt-get install lib32stdc++6参考)。

2.4 SimG


已下载在molecule-3d-similarity/softwares/目录下

2.5 EGNN


2.5.1 文件树

.
├── ae_datasets
│   ├── dataloader.py
│   ├── d_creator.py
│   ├── d_selector.py
│   └── __init__.py
├── dude # need to notice
│   ├── data # dude preprocess data
│   │   ├── aa2ar.csv
│   │   ├── abl1.csv
│   │   ├── ace.csv
│   │   ├── aces.csv
...
│   │   └── xiap.csv
│   ├── data.py # load data utils
│   ├── __init__.py
│   ├── models.py # construct models
│   └── utils.py
├── eval.py
├── graph.py
├── LICENSE
├── losess.py
├── main_ae.py
├── main_dude.py # dude main
├── main_nbody.py
├── main_qm9.py
├── models
│   ├── ae.py
│   ├── egnn_clean
│   │   ├── egnn_clean.py
│   │   └── __init__.py
│   ├── egnn.png
│   ├── gcl.py
│   └──  __init__.py
├── n_body_system
├── qm9
├── README.md
└── utils.py

2.5.2 模型结构

bs -> batch size
nn -> node number
nt -> node type
cp -> charge power
pm -> postion number (len(x, y, z) = 3)
  1. 模型构建参数

    名称 含义 类型 取值 备注
    1 in_node_nf 输入节点类型数 int 11*(2+1) nf=number of feature;
    in_node_nf=nt*(cp+1);
    2 in_edge_nf 输入边类型数 int 4 (single, double, triple, aromatic)
    3 hidden_nf embedding维度 int 128
    4 device 模型载入设备 torch.device -
    5 n_layers E_GCL数量 int 7
    6 attention 注意力机制 bool -
  2. 模型输入参数

    名称 含义 形状 关联中间变量 备注
    1 h Nodes输入向量 (2, bs*nn, nt*(cp+1)) one_hot, chargs, charge_power,
    charge_scale, device
    输入均为包含两个元素的列表,
    第一元素代表ref,第二个元素代表prb
    2 x Nodes的三维坐标 (2, bs*nn, pm) -
    3 edges Edges输入向量 (2, 2, bs*(n^2-3n+1)) - 列表中每一个元素
    形如[tensor1, tensor2]这样的方式构建;
    代表[rows, cols];
    只记录邻接矩阵中的上三角矩阵中的边
    4 edge_attr 边属性向量 (2, bs*(n^2-3n+1), 5) -
    5 node_mask 掩模padding节点 (2, bs, nn) charges 动态padding;
    未使用;
    6 edge_mask 掩模不存在边 (2, bs*(n^2-3n+1), 1)
    7 n_nodes 节点数量 (2, 1)
    8 label 标签 (1) actives还是decoys

2.5.3 数据输入

  1. 数据预处理 使用molecule-3d-similarity/test.ipynb文件中的代码,对DUD-E的数据进行预处理,对每一个靶点得到具有(name, smiles, label, charges, position, edges)列的CSV文件。
  2. DataUp waiting...
  3. Dataset waiting...
  4. DataLoader waiting...

Question

  1. sudo: add-apt-repository: command not found https://linuxconfig.org/sudo-apt-add-repository-command-not-found

    sudo apt install software-properties-common

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