Deep generative models of 3D grids for structure-based drug discovery

Overview

What is liGAN?

liGAN is a research codebase for training and evaluating deep generative models for de novo drug design based on 3D atomic density grids. It is based on libmolgrid and the gnina fork of caffe.

VAE paper - 2 minute talk

CVAE paper - 15 minute talk

Dependencies

  • numpy
  • pandas
  • scikit-image
  • openbabel
  • rdkit
  • molgrid
  • torch
  • protobuf
  • gnina version of caffe

Usage

You can use the scripts download_data.sh and download_weights.sh to download the test data and weights that were evaluated in the above papers.

The script generate.py is used to generate atomic density grids and molecular structures from a trained generative model.

Its basic usage can be seen in the scripts generate_vae.sh:

LIG_FILE=$1 # e.g. data/molport/0/102906000_8.sdf

python3 generate.py \
  --data_model_file models/data_48_0.5_molport.model \
  --gen_model_file models/vae.model \
  --gen_weights_file weights/gen_e_0.1_1_disc_x_10_0.molportFULL_rand_.0.0_gen_iter_100000.caffemodel \
  --rec_file data/molport/10gs_rec.pdb \
  --lig_file $LIG_FILE \
  --out_prefix VAE \
  --n_samples 10 \
  --fit_atoms \
  --dkoes_make_mol \
  --output_sdf \
  --output_dx \
  --gpu

And generate_cvae.sh:

REC_FILE=$1 # e.g. data/crossdock2020/PARP1_HUMAN_775_1012_0/2rd6_A_rec.pdb
LIG_FILE=$2 # e.g. data/crossdock2020/PARP1_HUMAN_775_1012_0/2rd6_A_rec_2rd6_78p_lig_tt_min.sdf

python3 generate.py \
  --data_model_file models/data_48_0.5_crossdock.model \
  --gen_model_file models/cvae.model \
  --gen_weights_file weights/lessskip_crossdocked_increased_1.lowrmsd.0_gen_iter_1500000.caffemodel \
  --rec_file $REC_FILE \
  --lig_file $LIG_FILE \
  --out_prefix CVAE \
  --n_samples 10 \
  --fit_atoms \
  --dkoes_make_mol \
  --output_sdf \
  --output_dx \
  --gpu

Both scripts can be run from the root directory of the repository.

Owner
Matt Ragoza
PhD student, Intelligent Systems Program, Pitt SCI
Matt Ragoza
Rethinking the Importance of Implementation Tricks in Multi-Agent Reinforcement Learning

RIIT Our open-source code for RIIT: Rethinking the Importance of Implementation Tricks in Multi-AgentReinforcement Learning. We implement and standard

405 Jan 06, 2023
This repository attempts to replicate the SqueezeNet architecture and implement the same on an image classification task.

SqueezeNet-Implementation This repository attempts to replicate the SqueezeNet architecture using TensorFlow discussed in the research paper: "Squeeze

Rohan Mathur 3 Dec 13, 2022
Controlling the MicriSpotAI robot from scratch

Project-MicroSpot-AI Controlling the MicriSpotAI robot from scratch Colaborators Alexander Dennis Components from MicroSpot The MicriSpotAI has the fo

Dennis Núñez-Fernández 5 Oct 20, 2022
PyTorch implementation for View-Guided Point Cloud Completion

PyTorch implementation for View-Guided Point Cloud Completion

22 Jan 04, 2023
Implementation of our recent paper, WOOD: Wasserstein-based Out-of-Distribution Detection.

WOOD Implementation of our recent paper, WOOD: Wasserstein-based Out-of-Distribution Detection. Abstract The training and test data for deep-neural-ne

8 Dec 24, 2022
Official repository of the paper Privacy-friendly Synthetic Data for the Development of Face Morphing Attack Detectors

SMDD-Synthetic-Face-Morphing-Attack-Detection-Development-dataset Official repository of the paper Privacy-friendly Synthetic Data for the Development

10 Dec 12, 2022
A tool for making map images from OpenTTD save games

OpenTTD Surveyor A tool for making map images from OpenTTD save games. This is not part of the main OpenTTD codebase, nor is it ever intended to be pa

Aidan Randle-Conde 9 Feb 15, 2022
Predicting Tweet Sentiment Maching Learning and streamlit

Predicting-Tweet-Sentiment-Maching-Learning-and-streamlit (I prefere using Visual Studio Code ) Open the folder in VS Code Run the first cell in requi

1 Nov 20, 2021
Official implementation for paper Render In-between: Motion Guided Video Synthesis for Action Interpolation

Render In-between: Motion Guided Video Synthesis for Action Interpolation [Paper] [Supp] [arXiv] [4min Video] This is the official Pytorch implementat

8 Oct 27, 2022
A deep learning library that makes face recognition efficient and effective

Distributed Arcface Training in Pytorch This is a deep learning library that makes face recognition efficient, and effective, which can train tens of

Sajjad Aemmi 10 Nov 23, 2021
An energy estimator for eyeriss-like DNN hardware accelerator

Energy-Estimator-for-Eyeriss-like-Architecture- An energy estimator for eyeriss-like DNN hardware accelerator This is an energy estimator for eyeriss-

HEXIN BAO 2 Mar 26, 2022
PyTorch implementation of the ideas presented in the paper Interaction Grounded Learning (IGL)

Interaction Grounded Learning This repository contains a simple PyTorch implementation of the ideas presented in the paper Interaction Grounded Learni

Arthur Juliani 4 Aug 31, 2022
TensorFlow ROCm port

Documentation TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, a

ROCm Software Platform 622 Jan 09, 2023
Computational inteligence project on faces in the wild dataset

Table of Contents The general idea How these scripts work? Loading data Needed modules and global variables Parsing the arrays in dataset Extracting a

tooraj taraz 4 Oct 21, 2022
graph-theoretic framework for robust pairwise data association

CLIPPER: A Graph-Theoretic Framework for Robust Data Association Data association is a fundamental problem in robotics and autonomy. CLIPPER provides

MIT Aerospace Controls Laboratory 118 Dec 28, 2022
Official implementation of Unfolded Deep Kernel Estimation for Blind Image Super-resolution.

Unfolded Deep Kernel Estimation for Blind Image Super-resolution Hongyi Zheng, Hongwei Yong, Lei Zhang, "Unfolded Deep Kernel Estimation for Blind Ima

Z80 15 Dec 26, 2022
Gradient-free global optimization algorithm for multidimensional functions based on the low rank tensor train format

ttopt Description Gradient-free global optimization algorithm for multidimensional functions based on the low rank tensor train (TT) format and maximu

5 May 23, 2022
[TIP 2021] SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction

SADRNet Paper link: SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction Requirements python

Multimedia Computing Group, Nanjing University 99 Dec 30, 2022
This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their coordinates and detected labels.

This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their

Liron Bdolah 8 May 22, 2022
A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation

Paper Khoi Nguyen, Sinisa Todorovic "A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation", accepted to ICCV 2021 Our code is mai

Khoi Nguyen 5 Aug 14, 2022