Small Molecule Explorer

Chemistry Meets Computation

Cheminformatics applies computational methods to chemical data. At the heart of the field is a simple question: how do you represent a molecule in a form that a computer can reason about? The answer — molecular descriptors and fingerprints — enables virtual screening of millions of compounds, similarity searching in chemical databases, and quantitative predictions of drug-like properties.

This simulation lets you draw molecules, compute their descriptors, and compare them using fingerprint similarity.

What You’ll Explore

• Draw a molecule using a 2D sketcher or enter a SMILES string. SMILES (Simplified Molecular-Input Line-Entry System) is a compact text notation for molecular structure — for example, c1ccccc1 represents benzene and CC(=O)Oc1ccccc1C(=O)O represents aspirin.
• Compute molecular descriptors including molecular weight, LogP (a measure of lipophilicity), number of hydrogen bond donors and acceptors, polar surface area, and rotatable bond count. These properties determine whether a molecule can be absorbed orally — Lipinski’s Rule of Five provides a rough filter.
• Generate fingerprints. Morgan fingerprints (also called ECFP) encode the local chemical environment around each atom as a fixed-length bit vector. Two molecules with similar fingerprints tend to have similar biological activity — this is the “similar property principle.”
• Compare molecules using Tanimoto similarity, the standard metric for fingerprint comparison. A Tanimoto coefficient above 0.85 generally indicates high structural similarity; below 0.5 suggests the molecules are quite different.

Key Concepts

Molecular Representations

A molecule can be represented at many levels of abstraction:

• SMILES — a text string that encodes atoms, bonds, rings, and stereochemistry.
• Molecular graph — an undirected graph where nodes are atoms and edges are bonds.
• 3D coordinates — the spatial positions of all atoms, determined by experiment or computational prediction.
• Fingerprints — fixed-length binary or count vectors that summarise structural features.

Lipinski’s Rule of Five

Christopher Lipinski observed that most orally bioavailable drugs satisfy four criteria: molecular weight ≤ 500, LogP ≤ 5, hydrogen bond donors ≤ 5, and hydrogen bond acceptors ≤ 10. These rules are not absolute — many approved drugs violate them — but they are a useful first filter in early-stage drug discovery.

Tanimoto Similarity

For two binary fingerprints A and B, the Tanimoto coefficient is defined as |A ∩ B| / |A ∪ B| — the number of bits set in both, divided by the number set in either. It ranges from 0 (no bits in common) to 1 (identical fingerprints). Because it ignores bits that are off in both fingerprints, it is robust to the choice of fingerprint length.

Background Reading

1. Lipinski, C. A. et al. (2001). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 46(1–3), 3–26.
2. Rogers, D. & Hahn, M. (2010). Extended-connectivity fingerprints. Journal of Chemical Information and Modeling, 50(5), 742–754.
3. Weininger, D. (1988). SMILES, a chemical language and information system. Journal of Chemical Information and Computer Sciences, 28(1), 31–36.