Design of efficient computational workflows for in silico drug repurposing

Vanhaelen, Quentin; Mamoshina, Polina; Aliper, Alexander; Av, Artemov; Lezhnina, Ksenia; Ozerov, Ivan V.; Labat, Ivan; Zhavoronkov, Alex

doi:10.1016/j.drudis.2016.09.019

Cited by 131 publications

(86 citation statements)

References 92 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…One of the most impactful applications of DL in biomedicine was in the applications of generative models to de novo molecular design [32][33][34][35][36] . In the context of aging research, these new methods can be combined for geroprotector discovery [37][38][39][40][41] . Indeed, since 2013, many aging clocks have been developed in both humans and other model organisms.…”

Section: Introductionmentioning

confidence: 99%

Human microbiome aging clocks based on deep learning and tandem of permutation feature importance and accumulated local effects

Galkin

Aliper

Putin

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

The human gut microbiome is a complex ecosystem that both affects and is affected by its host status. Previous analyses of gut microflora revealed associations between specific microbes and host health and disease status, genotype and diet. Here, we developed a method of predicting biological age of the host based on the microbiological profiles of gut microbiota using a curated dataset of 1,165 healthy individuals (3,663 microbiome samples). Our predictive model, a human microbiome clock, has an architecture of a deep neural network and achieves the accuracy of 3.94 years mean absolute error in cross-validation. The performance of the deep microbiome clock was also evaluated on several additional populations. We further introduce a platform for biological interpretation of individual microbial features used in age models, which relies on permutation feature importance and accumulated local effects. This approach has allowed us to define two lists of 95 intestinal biomarkers of human aging. We further show that this list can be reduced to 39 taxa that convey the most information on their host's aging. Overall, we show that (a) microbiological profiles can be used to predict human age; and (b) microbial features selected by models are age-related.

show abstract

Section: Introductionmentioning

confidence: 99%

Human microbiome aging clocks based on deep learning and tandem of permutation feature importance and accumulated local effects

Galkin

Aliper

Putin

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…autoimmune inner ear disease, Meniere's disease). We acknowledge that there are many methods to identify drugs for repurposing or repositioning, including in silico methods, which have been reviewed elsewhere (Ferrero & Agarwal, 2018;Vanhaelen et al, 2017). However, our analyses highlight the potential use of the data for drug repurposing approaches.…”

Section: Implications For Pharmacologic Targeting Of Sv Cell Typesmentioning

confidence: 98%

Single cell and single nucleus RNA-Seq reveal cellular heterogeneity and homeostatic regulatory networks in adult mouse stria vascularis

Korrapati

Taukulis

Olszewski

et al. 2019

Preprint

View full text Add to dashboard Cite

The stria vascularis (SV) generates the endocochlear potential (EP) in the inner ear and is necessary for proper hair cell mechanotransduction and hearing. While channels belonging to SV cell types are known to play crucial roles in EP generation, relatively little is known about gene regulatory networks that underlie the ability of the SV to generate and maintain the EP. Using single cell and single nucleus RNA-sequencing, we identify and validate known and rare cell populations in the SV. Furthermore, we establish a basis for understanding molecular mechanisms underlying SV function by identifying potential gene regulatory networks as well as druggable gene targets. Finally, we associate known deafness genes with adult SV cell types. This work establishes a basis for dissecting the genetic mechanisms underlying the role of the SV in hearing and will serve as a basis for designing therapeutic approaches to hearing loss related to SV dysfunction.

show abstract

“…Moreover, information on the disease phenotype or gene expression profiles of drugs is necessary when a screen does not involve protein targets . In silico DR has been recently reviewed elsewhere in detail …”

Section: Approach For Drug Repositioningmentioning

confidence: 99%

Drug repositioning in cancer: The current situation in Japan

et al. 2020

View full text Add to dashboard Cite

Cancer is a leading cause of death worldwide, and the incidence continues to increase. Despite major research aimed at discovering and developing novel and effective anticancer drugs, oncology drug development is a lengthy and costly process, with high attrition rates. Drug repositioning (DR, also referred to as drug repurposing), the process of finding new uses for approved noncancer drugs, has been gaining popularity in the past decade. DR has become a powerful alternative strategy for discovering and developing novel anticancer drug candidates from the existing approved drug space. Indeed, the availability of several large established libraries of clinical drugs and rapid advances in disease biology, genomics/transcriptomics/ proteomics and bioinformatics has accelerated the pace of activity-based, literaturebased and in silico DR, thereby improving safety and reducing costs. However, DR still faces financial obstacles in clinical trials, which could limit its practical use in the clinic. Here, we provide a brief review of

show abstract

Design of efficient computational workflows for in silico drug repurposing

Cited by 131 publications

References 92 publications

Human microbiome aging clocks based on deep learning and tandem of permutation feature importance and accumulated local effects

Human microbiome aging clocks based on deep learning and tandem of permutation feature importance and accumulated local effects

Single cell and single nucleus RNA-Seq reveal cellular heterogeneity and homeostatic regulatory networks in adult mouse stria vascularis

Drug repositioning in cancer: The current situation in Japan

Contact Info

Product

Resources

About