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Updated: Dec 31, 2025
Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
Published on: December 9, 2016
In silico analysis of alternative splicing on drug-target gene interactions
Yanrong Ji1, Rama K Mishra2,3,4, Ramana V Davuluri5
1Division of Health and Biomedical Informatics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Abstract:
Identifying and evaluating the right target are the most important factors in early drug discovery phase. Most studies focus on one protein ignoring the multiple splice-variant or protein-isoforms, which might contribute to unexpected therapeutic activity or adverse side effects. Here, we present computational analysis of cancer drug-target interactions affected by alternative splicing. By integrating information from publicly available databases, we curated 883 FDA approved or investigational stage small molecule cancer drugs that target 1,434 different genes, with an average of 5.22 protein isoforms per gene. Of these, 618 genes have ≥5 annotated protein-isoforms. By analyzing the interactions with binding pocket information, we found that 76% of drugs either miss a potential target isoform or target other isoforms with varied expression in multiple normal tissues. We present sequence and structure level alignments at isoform-level and make this information publicly available for all the curated drugs. Structure-level analysis showed ligand binding pocket architectures differences in size, shape and electrostatic parameters between isoforms. Our results emphasize how potentially important isoform-level interactions could be missed by solely focusing on the canonical isoform, and suggest that on- and off-target effects at isoform-level should be investigated to enhance the productivity of drug-discovery research.
Insights
Drug discovery must consider protein isoforms, as most cancer drugs miss or target unintended variants. Analyzing alternative splicing reveals crucial isoform-level interactions missed by focusing only on the main protein, improving drug development.
Area of Science:
- Pharmacology
- Genomics
- Computational Biology
Background:
- Identifying effective drug targets is critical in early drug discovery.
- Focusing on a single protein ignores splice variants (isoforms) that can cause side effects or alter efficacy.
Purpose of the Study:
- To computationally analyze cancer drug-target interactions considering alternative splicing and protein isoforms.
- To highlight the impact of isoform-level differences on drug efficacy and safety.
Main Methods:
- Integrated data from public databases to curate cancer drugs and their targeted genes.
- Analyzed drug interactions with protein isoforms, including binding pocket information and expression levels.
- Performed sequence and structure-level alignments for drug-target interactions at the isoform level.
Main Results:
- Curated 883 cancer drugs targeting 1,434 genes, with an average of 5.22 protein isoforms per gene.
- Found that 76% of drugs either miss a target isoform or interact with isoforms having varied expression in normal tissues.
- Identified significant differences in ligand binding pocket architecture between protein isoforms.
Conclusions:
- Solely focusing on canonical protein isoforms can lead to missed therapeutic opportunities and potential off-target effects.
- Investigating isoform-level interactions is essential for enhancing the productivity and safety of cancer drug discovery.
- The study provides publicly available isoform-level interaction data for curated cancer drugs.
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