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Emerging Computational Framework for Synthetic Transcriptional Reporters: LSD

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Zara Nwosu
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Emerging Computational Framework for Synthetic Transcriptional Reporters: LSD

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Understanding the LSD Framework

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The field of computational biology has seen tremendous advancements over the years. Among these, the development of a pioneering computational framework known as LSD (Logical Design of Synthetic cis-regulatory DNA) offers a new approach to study cell states and transitions. The LSD framework designs and generates synthetic transcriptional reporters, offering a comprehensive and robust method for studying cell identities and state changes.

How Does LSD Work?

The LSD framework predicts putative cis-regulatory elements using signature genes and transcription factors. It designs candidate synthetic locus control regions (sLCRs) for genetic tracing. This method is validated through the design and synthesis of sLCRs for a variety of biological settings and cell states, including glioblastoma heterogeneity and transition.

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Proving Functionality and Specificity of LSD

The sLCRs designed by LSD demonstrate functionality and specificity, outperforming first-generation reporters. The framework enables the discovery of cell-state regulators through CRISPR activation screens. The LSD framework also supports the design of AAV-compatible short, potent, and low-variable sLCRs for gene therapy. Single-cell RNA sequencing (scRNA-seq) data can be used as signature gene inputs for LSD, and chromatin accessibility and 3D genome organization can guide the design of sLCRs.

Computational Tools for Peptide-Based Therapeutics

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Computational tools are not only used for studying cell states and transitions, they are also applied in the search for peptide-based therapeutics. Virtual screening of peptide libraries is used to identify novel peptides for therapeutic implementations. Despite the potential challenges linked to the employment of peptides as therapeutics, computational approaches, mainly structure-based virtual screening (SBVS), provide significant support in the identification and application of bioactive peptides, such as anticancer, antimicrobial/antiviral peptides, and peptides blocking amyloid fiber formation.

Perturbation MPRA: An Effective Tool for Sequence Design Strategies

In addition to LSD and SBVS, Perturbation Massively Parallel Reporter Assays (MPRAs) offer another optimized sequence design strategy. Three different perturbation approaches have been benchmarked and the study recommends designing sequences by randomly shuffling the nucleotides of the perturbed site in perturbation MPRAs. This is followed by a coherence check to prevent the introduction of other variations of the target motifs. The potential of Perturbation MPRA in predicting non-coding regulatory activities is also highlighted, providing guidance for establishing a gold standard of perturbation MPRA techniques.

Conclusion

Computational biology is revolutionizing our understanding of cell states and transitions, and the design of peptide-based therapeutics. The LSD framework, structure-based virtual screening, and perturbation MPRA techniques offer robust and efficient approaches for the design, synthesis, and functional validation of synthetic transcriptional reporters. These tools and techniques hold significant potential for future research and applications in gene therapy and personalized medicine.

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