DeepAI AI Chat
Log In Sign Up

RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design

11/25/2020
by   Cheng-Hao Liu, et al.
0

De novo molecule generation often results in chemically unfeasible molecules. A natural idea to mitigate this problem is to bias the search process towards more easily synthesizable molecules using a proxy for synthetic accessibility. However, using currently available proxies still results in highly unrealistic compounds. We investigate the feasibility of training deep graph neural networks to approximate the outputs of a retrosynthesis planning software, and their use to bias the search process. We evaluate our method on a benchmark involving searching for drug-like molecules with antibiotic properties. Compared to enumerating over five million existing molecules from the ZINC database, our approach finds molecules predicted to be more likely to be antibiotics while maintaining good drug-like properties and being easily synthesizable. Importantly, our deep neural network can successfully filter out hard to synthesize molecules while achieving a 10^5 times speed-up over using the retrosynthesis planning software.

READ FULL TEXT

page 1

page 2

page 3

page 4

12/20/2017

In silico generation of novel, drug-like chemical matter using the LSTM neural network

The exploration of novel chemical spaces is one of the most important ta...
03/19/2014

Evolutionary Algorithm for Drug Discovery Interim Design Report

A software program which aims to provide an exploration capability over ...
04/08/2018

Accelerating Prototype-Based Drug Discovery using Conditional Diversity Networks

Designing a new drug is a lengthy and expensive process. As the space of...
08/14/2017

Learning to Plan Chemical Syntheses

From medicines to materials, small organic molecules are indispensable f...
01/28/2021

Automatic design of novel potential 3CL^pro and PL^pro inhibitors

With the goal of designing novel inhibitors for SARS-CoV-1 and SARS-CoV-...
10/05/2020

MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization

Molecule optimization is a fundamental task for accelerating drug discov...