Methods in molecular biology
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Drug sensitivity testing utilizing preclinical disease models such as cancer cell lines is an important and widely used tool for drug development. Importantly, when combined with molecular data such as gene copy number variation or somatic coding mutations, associations between drug sensitivity and molecular data can be used to develop markers to guide patient therapies. ⋯ Importantly, the systematic sensitivity testing of organoid cultures to anticancer drugs identified clinical gene-drug interactions, suggestive of their potential as preclinical models for testing anticancer drug sensitivity. In this chapter, we describe how to perform medium/high-throughput drug sensitivity screens using 3D organoid cell cultures.
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Gene editing has great therapeutic impact, being of interest for many scientists worldwide. Clustered regularly interspaced short palindromic repeats (CRISPR) technology has been adapted for gene editing to serve as an efficient, rapid, and cost-effective tool. ⋯ The gRNA targets the genome site to be edited, giving great importance to its design to obtain increased efficiency and decreased off-target events. In this chapter, we describe different tools to design suitable gRNAs for a variety of experimental purposes.
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The increase in the number of Web-based resources on posttranslational modification sites (PTMSs) in proteins is accelerating. This chapter presents a set of computational protocols describing how to work with the Internet resources when dealing with PTMSs. The protocols are intended for querying in PTMS-related databases, search of the PTMSs in the protein sequences and structures, and calculating the pI and molecular mass of the PTM isoforms. Thus, the modern bioinformatics prediction tools make it feasible to express protein modification in broader quantitative terms.
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Network-aided in silico approaches have been widely used for prediction of drug-target interactions and evaluation of drug safety to increase the clinical efficiency and productivity during drug discovery and development. Here we review the advances and new progress in this field and summarize the translational applications of several new network-aided in silico approaches we developed recently. ⋯ These state-of-the-art network-aided in silico approaches have been used for the discovery and development of broad-acting and targeted clinical therapies for various complex diseases, in particular for oncology drug repositioning. In this chapter, the described network-aided in silico protocols are appropriate for target-centric drug repositioning to various complex diseases, but expertise is still necessary to perform the specific oncology projects based on the cancer targets of interest.
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Rapid evaluation of the CRISPR gRNA activity is an essential step of employing the technology in editing genes. Through machine learning strategy, the rule sets for in silico designing gRNAs with high activity has greatly improved. However, there are still discrepancies between different prediction rule sets, and between the predicted and actual gRNA activities. ⋯ We had previously developed a dual-fluorescent surrogate system, called C-Check, which based on single-strand annealing repair of the DNA double-strand breaks introduced by CRISPR-Cas9 to generate a functional EGFP. The system offers a tool for rapid functional evaluation of CRISPR gRNA activity, as well as for enrichment of gene edited cells. In this chapter, we will give a step-by-step instruction on the design, generation, and application of the C-Check system for quantifying gRNA activities.