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CLaSP Endpoints Documentation

Drug-like Integrated Features Documentation

🧬 CLaSP Prediction System

The CLaSP prediction system is a comprehensive drug property prediction platform that evaluates Absorption, Distribution, Metabolism, Excretion, and Toxicity characteristics of compounds.

📊 Prediction Accuracy High Precision
Machine learning models trained on extensive experimental data with prediction accuracy exceeding 85%
⚡ Fast Computation Millisecond
Optimized algorithm architecture enabling comprehensive ADMET prediction for single molecules in milliseconds
🎯 Multi-dimensional Assessment 20+ Parameters
Comprehensive evaluation covering physicochemical properties, ADME, and toxicity dimensions

🧪 Physicochemical Properties

Basic physical and chemical characteristics of molecules

MW Molecular Weight
Molecular weight is one of the fundamental characteristics of drug molecules, affecting membrane permeability, distribution, and clearance.
Result Interpretation:

Expressed in Daltons (Da), reflecting molecular size. Generally, drug molecules in the 150-500 Da range are ideal.

HBA H-Bond Acceptors
The number of hydrogen bond acceptors affects molecular solubility and membrane permeability, an important parameter in Lipinski's Rule of Five.
Result Interpretation:

Number of atoms in the molecule capable of accepting hydrogen bonds. Ideal range: ≤10

HBD H-Bond Donors
The number of hydrogen bond donors also affects molecular physicochemical properties and bioavailability.
Result Interpretation:

Number of atoms in the molecule capable of donating hydrogen bonds. Ideal range: ≤5

ROTBs Rotatable Bonds
The number of rotatable bonds reflects molecular flexibility, affecting target binding and membrane permeability.
Result Interpretation:

Number of freely rotatable single bonds in the molecule.

Excellent: 0-11
logP Lipophilicity
The lipophilicity coefficient is an important parameter for assessing molecular lipophilicity, significantly affecting ADMET properties.
Result Interpretation:

Logarithm of n-octanol/water partition coefficient, reflecting molecular lipophilicity. Ideal range: -0.4 to +5.6

💊 ADME Properties

Absorption, Distribution, Metabolism, Excretion related parameters

F50% Bioavailability
Oral bioavailability is the most important pharmacokinetic parameter for oral administration, reflecting drug efficiency in reaching systemic circulation.
Result Interpretation:

Probability value (0-1) of predicted bioavailability ≥50%.

Excellent: 0-0.3 Medium: 0.3-0.7 Poor: 0.7-1.0
Pgp inhibitor P-glycoprotein
P-glycoprotein is the most important efflux transporter; its inhibition may lead to drug-drug interactions.
Result Interpretation:

Probability value (0-1) of being predicted as a P-glycoprotein inhibitor.

Excellent: 0-0.3 Medium: 0.3-0.7 Poor: 0.7-1.0
PPB Plasma Protein Binding
Plasma protein binding rate regulates effective drug concentration at targets; only free drug can exert therapeutic effects.
Result Interpretation:

Predicted percentage of drug binding to plasma proteins. High binding may require higher doses to achieve therapeutic concentrations.

VDss Volume of Distribution
Steady-state volume of distribution reflects drug distribution between plasma and tissues, affecting drug half-life.
Result Interpretation:

Unit: -logL/kg. Values reflect drug tissue distribution characteristics and clearance half-life.

BSEP inhibitor Bile Salt Transport
Bile salt export pump inhibition often leads to drug-induced cholestasis, a common drug side effect.
Result Interpretation:

Probability value (0-1) of being predicted as a BSEP inhibitor.

Excellent: 0-0.3 Medium: 0.3-0.7 Poor: 0.7-1.0
CLp Plasma Clearance
Plasma clearance is a comprehensive indicator of drug clearance capacity by organs like liver and kidney.
Result Interpretation:

Unit: ml/(min*kg). Uses 5 ml/(min*kg) as threshold to distinguish high and low clearance compounds.

CYP Enzymes Metabolic Enzymes
Cytochrome P450 enzymes are involved in most drug metabolism; their inhibition and substrate characteristics affect drug interactions.
Result Interpretation:

Predicts compound inhibition and substrate characteristics for key metabolic enzymes like CYP3A4, CYP2D6, CYP2C9.

⚠️ Toxicity Assessment

Safety-related toxicity prediction parameters

DILI Hepatotoxicity
Drug-induced liver injury is liver damage caused by toxic effects of drugs or their metabolites during clinical use.
Result Interpretation:

Predicts whether compound has DILI-positive (hepatotoxic) or DILI-negative characteristics.

Neurotoxicity Nervous System
Drug-induced neurotoxicity can damage central and peripheral nervous systems, causing neurological and psychiatric symptoms.
Result Interpretation:

Probability value (0-1) of having neurotoxic potential.

Excellent: 0-0.3 Medium: 0.3-0.7 Poor: 0.7-1.0
Ames mutagenesis Mutagenicity
The Ames test is the most commonly used in vitro assay method for evaluating compound mutagenic potential.
Result Interpretation:

Predicts whether compound has Ames mutagenic potential, assessing genotoxicity risk.

Micronucleus Micronucleus Test
In vivo micronucleus test is a commonly used genotoxicity assay method for detecting chromosomal damage.
Result Interpretation:

Predicts whether compound has genotoxic potential, assessing chromosomal damage risk.

FDAMDD Maximum Recommended Dose
FDA maximum recommended daily dose is an important reference indicator for drug safety assessment.
Result Interpretation:

Uses 0.01 mmol/kg-bw/day as threshold; ≤0.01 is classified as FDAMDD positive, otherwise negative.

Reproductive Toxicity Reproductive System
Reproductive toxicity is one of the main reasons for drug withdrawal, significantly affecting fetal and reproductive function.
Result Interpretation:

Predicts whether compound has reproductive toxicity potential, assessing impact on reproductive health.

📋 Other Properties

Additional important drug property parameters

SA Score Synthetic Accessibility
Synthetic accessibility score evaluates the ease of compound synthesis, guiding medicinal chemistry optimization.
Result Interpretation:

Calculated based on molecular complexity and fragment contributions. Lower scores indicate easier synthesis.

Drug Score Druglikeness Score
Comprehensive assessment of compound potential to become a drug, integrating multiple pharmacokinetic and toxicity parameters.
Result Interpretation:

Score range 0-1, higher scores indicate better druglikeness. Generally >0.5 is considered to have good drug potential.

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