binding-kinetics — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited binding-kinetics (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Analyze, predict, and optimize drug-target binding kinetics: on-rates (kon), off-rates (koff), residence time (RT = 1/koff), thermodynamic signatures (ΔH/ΔS), and structure-kinetics relationships (SKR).
| File | Content |
|---|---|
references/kinetics-theory.md | kon/koff/KD/RT definitions, kinetic selectivity, two-state binding, conformational selection vs induced fit, thermodynamic signatures |
references/spr-analysis.md | SPR sensorgrams, 1:1 Langmuir fitting, two-state model, Rmax/Rtheor, bulk correction, Biacore data parsing, Python fitting |
references/itc-analysis.md | ITC thermogram integration, n/KD/ΔH/ΔS/ΔG fitting, SEDPHAT equivalents in Python, van't Hoff, enthalpy-entropy compensation |
references/residence-time-md.md | τRAMD (random acceleration MD), funnel metadynamics, WTmetaD koff estimation, HTMD τRAMD Python, unbinding pathway analysis |
references/kinetic-qsar.md | Structure-kinetics relationships (SKR), features for koff/kon models, kinetic maps (LE vs kinetic efficiency), koff cliff detection |
"Fit my SPR data" → spr-analysis.md
"Fit my ITC experiment" → itc-analysis.md
"Compute residence time from MD" → residence-time-md.md
"Build a model to predict koff" → kinetic-qsar.md
"Why does my drug work despite poor KD?" → kinetics-theory.md
# Core kinetic relationships
KD = koff / kon # M (equilibrium dissociation constant)
pKD = -log10(KD) # analogous to pIC50
RT = 1 / koff # seconds (residence time)
t_half = ln(2) / koff # seconds (half-life of complex)
# Thermodynamics
ΔG = RT_gas * ln(KD) # kcal/mol (RT_gas = 0.592 at 298K)
ΔG = ΔH - T*ΔS # enthalpy-entropy decomposition
# Typical drug ranges
# kon: 10^4 – 10^7 M^-1 s^-1
# koff: 10^-5 – 10^-1 s^-1
# KD: nM – µM
# RT: 10 s – 10^5 s (hours)docking skillforce-fields skill + MDAnalysischem_props.py, chem_analyze.pymmpa skilluncertainty-qsar skill~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.