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:

COVID-19 is one of the members of the coronavirus family that can easily assail humans. As of now, 10 million people are infected and above two million people have died from COVID-19 globally. Over the past year, several researchers have made essential advances in discovering potential drugs. Up to now, no efficient drugs are available on the market. The present study aims to identify the potent phytocompounds from different medicinal plants (Zingiber officinale, Cuminum cyminum, Piper nigrum, Curcuma longa, and Allium sativum). In total, 227 phytocompounds were identified and screened against the proteins S-ACE2 and M (pro) through structure-based virtual screening approaches. Based on the binding affinity score, 30 active phytocompounds were selected. Amongst, the binding affinity for beta-sitosterol and beta-elemene against S-ACE2 showed -12.0 and -10.9 kcal/mol, respectively. Meanwhile, the binding affinity for beta-sitosterol and beta-chlorogenin against M (pro) was found to be -9.7 and -8.4 kcal/mol, respectively. Further, the selected compounds proceeded with molecular dynamics simulation, prime MM-GBSA analysis, and ADME/T property checks to understand the stability, interaction, conformational changes, binding free energy, and pharmaceutical relevant parameters. Moreover, the hotspot residues such as Lys31 and Lys353 for S-ACE2 and catalytic dyad His41 and Cys145 for M (pro) were actively involved in the inhibition of viral entry. From the in silico analyses, we anticipate that this work could be valuable to ongoing novel drug discovery with potential treatment for COVID-19.
["Mechanism", "Treatment"]