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Ligand intelligence

Once you’ve identified a protein target, the next question is: what molecules are already known to bind to it? OpenDDE pulls bioactivity data from ChEMBL, the world’s largest open database of drug-like molecules with experimental binding data.

What is bioactivity data?

Bioactivity data tells you how strongly a molecule binds to a protein target. This is measured experimentally in a lab. The most common measurements are:

MetricFull nameWhat it measures
IC50Half-maximal inhibitory concentrationThe concentration needed to inhibit 50% of the target’s activity. Lower = more potent.
KiInhibition constantThe binding affinity of an inhibitor. Lower = tighter binding.
KdDissociation constantHow tightly a molecule binds overall. Lower = stronger binding.
EC50Half-maximal effective concentrationThe concentration needed for 50% of the maximum biological effect.

Values are typically reported in nanomolar (nM). A compound with an IC50 of 10 nM is very potent; one with 10,000 nM (10 μM) is weak.

Rule of thumb: A “hit” in drug discovery typically has activity below 10,000 nM. A “lead” is below 1,000 nM. A clinical candidate is usually below 100 nM.

Understanding clinical phases

Some compounds in ChEMBL have reached clinical trials. OpenDDE shows the clinical phase where applicable:

PhaseWhat happensTypical size
Phase ISafety testing in healthy volunteers20–100 people
Phase IIEfficacy and dose-finding in patients100–300 people
Phase IIILarge-scale efficacy confirmation1,000–3,000 people
Phase IVPost-market surveillanceOngoing monitoring
ApprovedFDA/EMA approved drugAvailable to patients

How to read the ligand table

The ligand table in OpenDDE shows all known compounds for your target. Key columns:

  • Name / ChEMBL ID — The compound identifier. Click to see its 2D structure.
  • Activity type — IC50, Ki, Kd, or EC50.
  • Activity (nM) — The measured value. Sortable: lower is more potent.
  • Phase — Clinical development stage (if applicable).
  • SMILES — The molecular structure in text format.

You can sort by any column by clicking the header. The table supports searching and filtering.

What “drug-like” means

Not every molecule that binds a target can become a drug. It also needs to be absorbed, distributed, metabolized, and excreted safely. Lipinski’s Rule of Five is a quick filter:

  • Molecular weight ≤ 500 Da
  • LogP (lipophilicity) ≤ 5
  • Hydrogen bond donors ≤ 5
  • Hydrogen bond acceptors ≤ 10

Compounds violating more than one rule are less likely to be orally bioavailable. OpenDDE computes these properties via RDKit and flags violations in the druglikeness scoring panel.

How activity cliffs help drug design

An activity cliff is a pair of molecules that are structurally very similar (Tanimoto similarity > 0.7) but have drastically different binding activity (ratio > 10×). These cliffs are goldmines for medicinal chemists because they reveal which small structural changes have the biggest impact on potency.

OpenDDE automatically detects activity cliffs for your target and highlights the most significant pairs. See SAR analysis for more.

Next: Complex prediction →