AUTHOR=Shayakhmetov Rim , Kuznetsov Maksim , Zhebrak Alexander , Kadurin Artur , Nikolenko Sergey , Aliper Alexander , Polykovskiy Daniil 

TITLE=Molecular Generation for Desired Transcriptome Changes With Adversarial Autoencoders

JOURNAL=Frontiers in Pharmacology

VOLUME=11

YEAR=2020

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2020.00269

DOI=10.3389/fphar.2020.00269

ISSN=1663-9812

ABSTRACT=<p>Gene expression profiles are useful for assessing the efficacy and side effects of drugs. In this paper, we propose a new generative model that infers drug molecules that could induce a desired change in gene expression. Our model—the Bidirectional Adversarial Autoencoder—explicitly separates cellular processes captured in gene expression changes into two feature sets: those <italic>related</italic> and <italic>unrelated</italic> to the drug incubation. The model uses <italic>related</italic> features to produce a drug hypothesis. We have validated our model on the LINCS L1000 dataset by generating molecular structures in the SMILES format for the desired transcriptional response. In the experiments, we have shown that the proposed model can generate novel molecular structures that could induce a given gene expression change or predict a gene expression difference after incubation of a given molecular structure. The code of the model is available at <uri xlink:href="https://github.com/insilicomedicine/BiAAE" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/insilicomedicine/BiAAE</uri>.</p>