A Review of Current In Silico Methods for Repositioning Drugs and Chemical Compounds

Abstract

Drug repositioning is a new way of applying the existing therapeutics to new disease indications. Due to the exorbitant cost and high failure rate in developing new drugs, the continued use of existing drugs for treatment, especially anti-tumor drugs, has become a widespread practice. With the assistance of high-throughput sequencing techniques, many efficient methods have been proposed and applied in drug repositioning and individualized tumor treatment. Current computational methods for repositioning drugs and chemical compounds can be divided into four categories: (i) feature-based methods, (ii) matrix decomposition-based methods, (iii) network-based methods, and (iv) reverse transcriptome-based methods. In this article, we comprehensively review the widely used methods in the above four categories. Finally, we summarize the advantages and disadvantages of these methods and indicate future directions for more sensitive computational drug repositioning methods and individualized tumor treatment, which are critical for further experimental validation.

RAID: Regression Analysis based Inductive DNA microarray for Precise Read-Across

“…The present approach integrates QSAR and IVIVE and will contribute to other areas of research, such as drug repositioning, which recently attracted attentions towards pharmaceuticals that are available on the market and might be repurposed for new diseases (Jourdan et al, 2020). However, the previously proposed methodologies (Iwata et al, 2018; Lippmann et al, 2018; Zhu et al, 2020; He et al, 2021) have a room for improving the IVIVE aspect of in vivo prediction. Thus, our system provides an alternative to screen candidate drugs and explore new biologically similar drugs at a low cost.…”

“…However, the previously proposed methodologies (Iwata et al, 2018;Lippmann et al, 2018;Zhu et al, 2020;He et al, 2021) have a room for improving the IVIVE aspect of in vivo prediction. Thus, our system provides an alternative to screen candidate drugs and explore new biologically similar drugs at a low cost.…”

RAID: Regression Analysis–Based Inductive DNA Microarray for Precise Read-Across

“…The present approach integrates QSAR and IVIVE and will contribute to other areas of research, such as drug repositioning, which has recently attracted attention toward pharmaceuticals that are available on the market and might be repurposed for new diseases (Jourdan et al, 2020). However, the previously proposed methodologies (Iwata et al, 2018;Lippmann et al, 2018;Zhu et al, 2020;He et al, 2021) have room for improving the IVIVE aspect of in vivo predictions. Thus, our system provides an Pros.…”

Exploration of Potential Ewing Sarcoma Drugs from FDA-Approved Pharmaceuticals through Computational Drug Repositioning, Pharmacogenomics, Molecular Docking, and MD Simulation Studies

“…Drug repositioning approaches assist in minimizing the cost and time of the drug development process due to their known efficacy and therapeutic potential against other diseases . There are various computational methods such as feature-based methods, matrix decomposition-based methods, network-based methods, and reverse transcriptome-based methods for drug repositioning. , However, it has been observed that drug development efforts for the treatment of Ewing sarcoma (ES) have been largely unsuccessful in the last decade …”

“…2 There are various computational methods such as feature-based methods, matrix decomposition-based methods, network-based methods, and reverse transcriptome-based methods for drug repositioning. 3,4 However, it has been observed that drug development efforts for the treatment of Ewing sarcoma (ES) have been largely unsuccessful in the last decade. 5 ES is a cancerous tumor usually observed in bones and other soft tissues like cartilages and nerve tissues, respectively.…”