Long COVID-19 Neuropeptide and Cytokine Expression Data with Computational Drug Screening

A 2026 study of 90 patients screened for long COVID-19 neuropsychological sequelae, with data on symptom prevalence, cytokine levels, and computational drug binding analyses. It contains experimental results for IL-6, IL-10, and Substance P (SP) expression and virtual screening of nine drug candidates against the NK1R receptor. The dataset includes patient demographics, symptom duration, and molecular dynamics stability metrics for identified drug hits.

Use Cases

• Correlate symptom prevalence percentages (fatigue, headache, anxiety, depression) with upregulated cytokine levels IL-6 and IL-10 from patient blood samples.
• Analyze the relationship between symptom persistence duration (19 ± 6 weeks, 44 ± 6 weeks) and neuropeptide Substance P (SP) expression across patient groups.
• Validate computational drug screening results by examining binding affinity scores (-9.3 kcal/mol, -8.7 kcal/mol) and molecular dynamics stability metrics (RMSD, RMSF, Rg) for aprepitant and N-acetyl-L-tryptophan.
• Model blood-brain barrier permeability and pharmacokinetic profiles for drug candidates identified as NK1R antagonists.

Strengths

• Includes experimental data from 90 patients (60% male, 40% female) with detailed age stratification and symptom duration metrics.
• Provides quantified cytokine and neuropeptide expression results (IL-6, IL-10, SP) with statistical significance (p < 0.001).
• Contains specific computational outputs, including binding affinities, RMSD (1.5–2.2 Å), RMSF (0.8–1.4 Å), and Rg (~21.6 Å) values from molecular dynamics simulations.

Limitations

• The dataset is extremely small (17.0 KB), contained within a DOCX file, suggesting it is a summary document rather than a raw, tabular dataset suitable for direct computational analysis.
• No column names or sample data are provided, limiting structured reuse for machine learning without significant manual extraction and curation.
• Patient sample is limited to 90 individuals from a single outpatient clinic, which may not be representative of broader long COVID-19 populations.

Provenance

Source

Muhammad Abdullah via figshare.

Collection Method

Patient screening and blood sample analysis via ELISA and RT-qPCR, followed by computational virtual screening of nine drugs.

Time Range

Study period not specified; data reflects a snapshot of long COVID-19 patients.

Freshness

Last updated in March 2026.

Geography

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