PASS: Computational Properties of NSAIDs Ketoprofen and Ibuprofen Degradants

An in-silico investigation of spectral, physicochemical, biological, and toxicological properties for two Nonsteroidal Anti-inflammatory drugs (NSAIDs) and their major degradants. The dataset, created by Protyoi Chakraborty and last updated in May 2026, includes results from density functional theory calculations, molecular docking, MD simulation, and ADMET/PASS predictions. The study highlights toxicological impacts such as carcinogenic, nephrotoxic, and hematotoxic properties for several degradants.

Use Cases

• Predicting drug and degradant toxicity based on ADMET and PASS parameters mentioned in the description
• Analyzing molecular binding affinity and interaction modes based on docking results against the Cyclooxygenase-2 receptor
• Comparing physicochemical properties like HOMO-LUMO gaps calculated via density functional theory
• Assessing environmental and human health risks from NSAID degradants based on the described toxicological properties

Strengths

• Includes results from a 100-ns molecular dynamics simulation demonstrating complex stability
• Provides specific computational results, such as a HOMO-LUMO gap of 3.806 eV for one degradant and 6.063 eV for another
• Released under a permissive CC-BY-4.0 license for reuse

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• The dataset is very small at 5.5 KB, indicating limited scope

Provenance

Source

figshare

Collection Method

Computational methods including density functional theory (B3LYP/6-31g+(d,p) basis set), molecular docking, MD simulation, and ADMET/PASS prediction.

Time Range

The study period is not specified.

Freshness

Last updated 2026-05-06 17:34:01; freshness should be verified

Geography

The geographic scope of the study is not specified.