Synthetic Biology Speeds Up Drug Target Discovery

Xie, Yixuan; Yang, Yan-Fang; He, Yu; Wang, Xixi; Zhang, Peng

doi:10.3389/fphar.2020.00119

Cited by 13 publications

(7 citation statements)

References 80 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…When patient‐derived material is not available, RNA‐seq can be performed on artificial systems, such as cell lines with CRISPR‐introduced genetic variants (Adli, 2018; Meng et al, 2020; Sterneckert et al, 2014; Xie et al, 2020). Artificial systems with introduced variants directly probe the effect of defined variants on the RNA phenotype and are therefore applied to define the causative variant or combination of variants in complex haplotypes.…”

Section: Recommendations For Variant Interpretation With Rna‐seqmentioning

confidence: 99%

Guidelines for clinical interpretation of variant pathogenicity using RNA phenotypes

et al. 2022

View full text Add to dashboard Cite

Over the last 5 years, RNA sequencing (RNA‐seq) has been established and is increasingly applied as an effective approach complementary to DNA sequencing in molecular diagnostics. Currently, three RNA phenotypes, aberrant expression, aberrant splicing, and allelic imbalance, are considered to provide information about pathogenic variants. By providing a high‐throughput, transcriptome‐wide functional readout on variants causing aberrant RNA phenotypes, RNA‐seq has increased diagnostic rates by about 15% over whole‐exome sequencing. This breakthrough encouraged the development of computational tools and pipelines aiming to streamline RNA‐seq analysis for implementation in clinical diagnostics. Although a number of studies showed the added value of RNA‐seq for the molecular diagnosis of individuals with Mendelian disorders, there is no formal consensus on assessing variant pathogenicity strength based on RNA phenotypes. Taking RNA‐seq as a functional assay for genetic variants, we evaluated the value of statistical significance and effect size of RNA phenotypes as evidence for the strength of variant pathogenicity. This was determined by the analysis of 394 pathogenic variants, of which 198 were associated with aberrant RNA phenotypes and 723 benign variants. Overall, this study seeks to establish recommendations for integrating functional RNA‐seq data into the the American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines classification system.

show abstract

Section: Recommendations For Variant Interpretation With Rna‐seqmentioning

confidence: 99%

Guidelines for clinical interpretation of variant pathogenicity using RNA phenotypes

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Pathways are included in target validation. Drug discovery benefits from research targeted at identifying targets that govern and regulate activities in living organisms [37]. An examination of target validity, or if the molecule targets a biological component relevant to the disease, will be critical to moving any molecule forward.…”

Section: Target Validationmentioning

confidence: 99%

Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process

Hasan

Alsaiari

Fakhurji³

et al. 2022

Molecules

View full text Add to dashboard Cite

The conventional drug discovery approach is an expensive and time-consuming process, but its limitations have been overcome with the help of mathematical modeling and computational drug design approaches. Previously, finding a small molecular candidate as a drug against a disease was very costly and required a long time to screen a compound against a specific target. The development of novel targets and small molecular candidates against different diseases including emerging and reemerging diseases remains a major concern and necessitates the development of novel therapeutic targets as well as drug candidates as early as possible. In this regard, computational and mathematical modeling approaches for drug development are advantageous due to their fastest predictive ability and cost-effectiveness features. Computer-aided drug design (CADD) techniques utilize different computer programs as well as mathematics formulas to comprehend the interaction of a target and drugs. Traditional methods to determine small-molecule candidates as a drug have several limitations, but CADD utilizes novel methods that require little time and accurately predict a compound against a specific disease with minimal cost. Therefore, this review aims to provide a brief insight into the mathematical modeling and computational approaches for identifying a novel target and small molecular candidates for curing a specific disease. The comprehensive review mainly focuses on biological target prediction, structure-based and ligand-based drug design methods, molecular docking, virtual screening, pharmacophore modeling, quantitative structure–activity relationship (QSAR) models, molecular dynamics simulation, and MM-GBSA/MM-PBSA approaches along with valuable database resources and tools for identifying novel targets and therapeutics against a disease. This review will help researchers in a way that may open the road for the development of effective drugs and preventative measures against a disease in the future as early as possible.

show abstract

“…In fact, controlling or suppressing non-specific activation has been one of major battle fields in synthetic circuit design. A variety of genetic logic circuits have been developed to provide high specificity and versatility ( Xie et al, 2020 ). Similar approaches can be implemented to mechanosensitive synthetic circuits to address the background noise issue.…”

Section: Apply Mechanobiology To Engineer Immune Cellsmentioning

confidence: 99%

The application of mechanobiotechnology for immuno-engineering and cancer immunotherapy

Yoon

Pan

Wang

2022

Front. Cell Dev. Biol.

View full text Add to dashboard Cite

Immune-engineering is a rapidly emerging field in the past few years, as immunotherapy evolved from a paradigm-shifting therapeutic approach for cancer treatment to promising immuno-oncology models in clinical trials and commercial products. Linking the field of biomedical engineering with immunology, immuno-engineering applies engineering principles and utilizes synthetic biology tools to study and control the immune system for diseases treatments and interventions. Over the past decades, there has been a deeper understanding that mechanical forces play crucial roles in regulating immune cells at different stages from antigen recognition to actual killing, which suggests potential opportunities to design and tailor mechanobiology tools to novel immunotherapy. In this review, we first provide a brief introduction to recent technological and scientific advances in mechanobiology for immune cells. Different strategies for immuno-engineering are then discussed and evaluated. Furthermore, we describe the opportunities and challenges of applying mechanobiology and related technologies to study and engineer immune cells and ultimately modulate their function for immunotherapy. In summary, the synergetic integration of cutting-edge mechanical biology techniques into immune-engineering strategies can provide a powerful platform and allow new directions for the field of immunotherapy.

show abstract

Synthetic Biology Speeds Up Drug Target Discovery

Cited by 13 publications

References 80 publications

Guidelines for clinical interpretation of variant pathogenicity using RNA phenotypes

Guidelines for clinical interpretation of variant pathogenicity using RNA phenotypes

Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process

The application of mechanobiotechnology for immuno-engineering and cancer immunotherapy

Contact Info

Product

Resources

About