You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:

- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.
- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.
- Prevention: The content covers measures to prevent the spread of COVID-19.
- Mechanism: The paragraph explains the biological mechanisms of the virus.
- Case Report: The content is a report of a COVID-19 case.
- Transmission: The paragraph discusses how COVID-19 is transmitted.
- Diagnosis: The content is about diagnosing COVID-19 in individuals.

Your classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: ["Topic1", "Topic2", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.

Article:

We investigated compounds selected by molecular docking to identify a specific treatment for COVID-19 that decreases the interaction between angiotensin-converting enzyme 2 (ACE2) and the receptor-binding domain (RBD) of SARS-CoV-2. Five compounds that interact with ACE2 amino acids Gln24, Asp30, His34, Tyr41, Gln42, Met82, Lys353, and Arg357 were evaluated using specific binding assays for their effects on the interaction between ACE2 with RBD. The compound labeled ED demonstrated favorable ACE2-binding, with an IC50 of 31.95 muM. ED cytotoxicity, evaluated using PC3 cells in an MTT assay, was consistent with the low theoretical toxicity previously reported. We propose that ED mainly interacts with His34, Glu37, and Lys353 in ACE2 and that it has an inhibitory effect on the interaction of ACE2 with the RBD of the S-protein. We recommend further investigation to develop ED into a potential drug or adjuvant in COVID-19 treatment.
["Mechanism", "Treatment"]