Construction of SHERLOCK-based sgRNA for SARS-CoV-2 Diagnostics from Indonesia

Abstract

Handling a pandemic requires high sensitivity, high specificity, simple, fast, and flexible tests. However, conventional test methods (RT-PCR and Rapid Antigen) have weaknesses in test efficiency. Specific High sensitivity Enzymatic Reporter un-LOCKing (SHERLOCK), is a new technology that can detect nucleic acids even with limited sample preparation, but with high sensitivity, high specificity, rapidly, and flexibly. The key to the specificity of the SHERLOCK diagnostic method is the single guide RNA (sgRNA). The purpose of this study was to analyze the design of the SHERLOCK sgRNA, which has optimum potential to be used as a Cas13a marker to recognize the spike protein gene of the Receptor Binding Domain of the SARS-CoV-2 strain from Indonesia. The method used was an in-silico approach using genomic and proteomic data and molecular docking. This study used a sample of 37 genomic data representing 86 types of SARS-CoV-2 spike protein mutations in Indonesia. Based on the docking candidate results, sgRNA8 has the lowest energy to bind to the viral protospacer target SARS-CoV-2 and a high melting point value at 70.3°C, indicating that the sgRNA8 chain is the optimal candidate for sgRNA.