Lipinski's rule of 5

What is Lipinski's Rule of Five?

Lipinski's Rule of Five (Ro5) predicts whether a compound is likely to be orally bioavailable based on four physicochemical properties. Compounds that violate more than one criterion are less likely to be absorbed through the gastrointestinal tract.

The rule is named for the observation that three of the four numerical thresholds are multiples of five. It remains one of the most widely used filters in early-stage drug discovery for identifying drug-like molecules.

For comprehensive property analysis, our Molecular Descriptors tool calculates these and many additional chemical properties. For ADMET predictions using machine learning, see ADMET-AI.

The four criteria

Poor oral absorption is more likely when a compound violates more than one of:

• Molecular weight: $\text{MW} \leq 500$ Da. Larger molecules have difficulty crossing biological membranes via passive diffusion.

• Lipophilicity: $\log P \leq 5$. The octanol-water partition coefficient measures hydrophobicity. Values above 5 indicate poor aqueous solubility.

• Hydrogen bond donors: $\text{HBD} \leq 5$. Counted as N-H and O-H bonds. Excessive donors impair membrane permeability.

• Hydrogen bond acceptors: $\text{HBA} \leq 10$. Includes all nitrogen and oxygen atoms. The limit reflects desolvation energy costs during membrane transit.

A compound can violate one criterion and still be considered drug-like. Two or more violations indicate likely absorption problems.

Veber's Rule

This tool also evaluates Veber's rule, which focuses on molecular flexibility:

• Rotatable bonds: $\leq 10$
• Topological polar surface area: $\text{TPSA} \leq 140$ Ų

Veber's rule complements Ro5 by addressing conformational flexibility, which affects how well a molecule can adopt the conformation needed for membrane permeation. A compound passes Veber's rule only if it satisfies both criteria.

Input formats

Enter SMILES strings in any of these formats:

Plain SMILES (one per line):

CCO
CC(=O)Oc1ccccc1C(=O)O

Tab-separated (name followed by SMILES):

ethanol	CCO
aspirin	CC(=O)Oc1ccccc1C(=O)O

You can also fetch compounds directly from PubChem using the batch fetcher.

Understanding the results

The output table includes calculated properties and three pass/fail assessments:

We recommend prioritizing compounds marked as Drug-like: Yes for oral drug development. Compounds with 1 Lipinski violation may still be viable candidates, especially if they pass Veber's rule.

Why these thresholds matter

Oral drugs must balance competing requirements:

Solubility vs. permeability: A drug needs enough aqueous solubility to dissolve in the GI tract, but sufficient lipophilicity to cross cell membranes. The MW and LogP criteria balance these demands.

Hydrogen bonding: Every hydrogen bond a molecule forms with water must be broken during membrane transit. Too many donors or acceptors creates an energetic barrier to absorption.

Molecular size: The 500 Da threshold approximates the upper limit for efficient passive diffusion. Larger molecules can still be absorbed via active transport, but passive diffusion becomes unreliable.

Limitations

Several classes of successful drugs violate Ro5:

• Natural products: Cyclosporine, erythromycin, and other natural product-derived drugs often exceed Ro5 limits but achieve bioavailability through active transport or specialized pathways.

• Transporter substrates: The rule assumes passive diffusion. Compounds transported by active mechanisms can be larger and more polar.

• Protein-protein interaction (PPI) inhibitors: Disrupting protein interfaces often requires larger molecules, leading to "beyond Rule of Five" (bRo5) drug development. For PPI-specific assessment, see QEPPi.

• Modern formulations: Prodrugs, nanoformulations, and permeation enhancers can overcome traditional Ro5 limitations.

Related tools

• Molecular Descriptors - Calculate 200+ chemical descriptors including all Ro5 properties
• ADMET-AI - Machine learning predictions for absorption, distribution, metabolism, excretion, and toxicity
• Toxicity Prediction - Predict potential toxicity endpoints
• QEPPi - Assess suitability for protein-protein interaction inhibition

Based on: Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev. 1997;23(1-3):3-25. DOI: 10.1016/S0169-409X(96)00423-1