PhysChem, ADME & Toxicity Calculations with Percepta Software

Aqueous (Water) Solubility Module

• Calculates pH dependent aqueous solubility, intrinsic solubility, and solubility of the chemical dissolved in pure (unbuffered) water at 25°C and zero ionic strength; along with the equilibrium pH of the solution
• The model is trainable with experimental values to improve predictions for proprietary chemical space

Boiling Point/Vapor Pressure Module

• Estimates the boiling point of organic compounds at specified pressure
• Predicts the vapor pressure of organic compounds as a function of temperature

LogD Module

Calculate logD (lipophilicity based on pH for ionizable compounds) from structure.

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LogP Module

Calculate logP (lipophilicity) from structure.

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pK_a Module

Calulate pK_a values (acid dissociation) from structure.

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Sigma Module

• A model for calculation of substituent-specific parameters for selected fragments of the molecule:
• Eectronic constants (Hammett Sigmas)
• Steric constants (molar volume, molar refractivity)
• Hydrophobic constant (Hansch Pi)

Other PhysChem Descriptors

Molecular property calculators are also available for the following:

• Density
• Freely Rotatable Bonds
• H-Bond Donors and Acceptors
• Index of Refraction
• Molar Refractivity
• Molar Volume
• Molecular Weight
• Parachor
• Polar Surface Area
• Polarizability
• Rule-of-5
• Surface Tension

Absolv Module

The Absolv prediction module calculates Abraham solvation parameters from structure.

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Blood Brain Barrier Permeation Module

The blood-brain barrier (BBB) permeation model in ACD/Labs software provides a comprehensive evaluation of the permeation potential of candidate compounds. While prediction cannot replace experimentation, this module allows compounds to be ranked according to their passive transport across the BBB, based on the following information:

• Predictions of:
• Rate of passive diffusion/permeability (logPS)
• Extent of BBB permeation (logBB)—steady-state distribution ratio of a compound between brain tissue and plasma
• Brain/plasma equilibration rate (PS * f_{u, brain})
• Alerts for compounds likely to undergo transport across the BBB barrier by carrier mediated mechanisms

Cytochrome P450 Inhibitors Module

• Calculates the probability that your compound will be an inhibitor of one of the five major drug metabolizing enzymes—CYP3A4, CYP2D6, CYP2C9, CYP2C19, and CYP1A2—at two different IC₅₀ thresholds
• IC₅₀ < 50 µM (general inhibition);
• IC₅₀ < 10 µM (efficient inhibition)
• The model can be trained with experimental data for new compounds in order to expand its applicability domain

Cytochrome P450 Substrates Module

• Calculates the probability that your compound will be a substrate of one of the five major drug metabolizing enzymes—CYP3A4, CYP2D6, CYP2C9, CYP2C19, and CYP1A2
• The model can be trained with experimental data for new compounds in order to expand its applicability domain

Distribution Module

• Estimates the strength of drug binding to human plasma proteins as either the overall percentage bound in plasma or as an affinity constant to human serum albumin
• Both the %PPB and logK_a(HSA) models are trainable with user data
• Predict their apparent volume of distribution (V_d)

Maximum Recommended Daily Dose Module

• Approximate an estimation of the maximum oral dose of drug that can be used in the clinic

Oral Bioavailability Module

The oral bioavailability model uses a combination of probabilistic and mechanistic modeling techniques to predict oral bioavailability from structure, and relies on a number of other ACD/Labs prediction algorithms and experimental data sets. Results are provided as a quantitative prediction of bioavailability after oral administration (%F) of a dose defined by the user.

• Predict a number of endpoints that affect oral bioavailability:
• Solubility (dose/solubility ratio)
• Stability in acidic media
• Intestinal membrane permeability by passive or active transport (with a summary of transporters where relevant)
• P-gp efflux
• First pass metabolism in the liver
• View up to 5 of the most similar structures from the internal training set, with experimental results and literature references

Passive Absorption Module

Human Intestinal Absorption (HIA) and solubility are two key factors that affect oral bioavailability. The Passive Absorption model predicts the human intestinal permeability of drugs, taking into account trans-cellular and para-cellular routes, and ionization-specific differences in permeation rates. Predictions are based on mechanistic models that use a number of physicochemical parameters, including lipophilicity and ionization, as inputs. The model outputs the following calculated parameters:

• The extent of Human Intestinal Absorption (HIA) in terms of passive transport across the intestine(not affected by any side processes such as limited solubility/dissolution, variable oral dose, chemical stability, active transport, and first pass metabolism in gut or liver), indicating percentage contribution from transcellular and paracellular route.
• Passive permeability across jejunal epithelium, also indicating absorption rate.
• Passive permeability across Caco-2 cell monolayers, indicating percentage contribution from transcellular and paracellular route.

P-gp Specificity Module

P-glycoprotein (P-gp) is a clinically relevant efflux transporter that extrudes compounds from a large variety of cells. Its function has been associated with the drugs' absorption, distribution, excretion, CNS effects, multidrug resistance (MDR). P-gp transports a variety of natural compounds and drugs of different therapeutic areas.

Rapid identification of drug candidates that are P-gp substrates and/or inhibitors is possible using P-gp specificity model. Filtering and exclusion of P-gp substrates/inhibitors from huge 'in-house' libraries of synthesized compounds or virtual libraries is possible, followed by exclusion of such compounds from further development. P-gp specificity model may serve as an initial screen that could replace screening test based on P-gp ATPase activity measurements and partially replace expensive experiments with P-gp expressing cell monolayers and P-gp knock-out animals.

PK Explorer Module

• Estimates a number of parameters determining the pharmacokinetic profile of your compounds by using a set of differential equations from a multi-compartment model describing the organism of an average statistical human:
  • C_p(T)
  • T_max and C_p(max)
  • AUC after oral and intravenous administrations
  • Oral Bioavailability

Regioselectivity of Metabolism Module

The CYP Regioselectivity model is able to provide valuable insights into a compound's metabolic profile early in the drug discovery process when little or no experimental information is available, and labor intensive investigation of each compound in the screening process is prohibited by the large number of compounds involved.

• Predict metabolic soft spots for metabolism by:
• Human liver microsomes (HLM)
• Five major Cytochrome P450 enzymes (CYP3A4, CYP2D6, CYP2C9, CYP2C19, and CYP1A2)
• Identify metabolic sites on new chemical entities
• Guide synthesis of compounds with improved metabolic properties
• Help identify and elucidate likely metabolite structures

Acute Toxicity Module

• Predicts quantitative LD₅₀ values for two rodent species after different administration routes:
• LD₅₀ in mice after oral administration
• LD₅₀ in mice after intravenous administration
• LD₅₀ in mice after intraperitoneal administration
• LD₅₀ in mice after subcutaneous administration
• LD₅₀ in rats after oral administration
• LD₅₀ in rats after intraperitoneal administration
• Estimates qualitative OECD Hazard categories
• The expert system identifies hazardous substructures potentially responsible for the toxic effect

Aquatic Toxicity Module

• Predict LC₅₀ values of your compounds for two aquatic organisms—fathead minnows (P. promelas) and water fleas (D. magna)

Endocrine System Disruption Module

• Predicts the relative binding affinity of your compounds to the Estrogen Receptor which is associated with the possibility of reproductive toxicity and cancers

Mutagenicity Module

• Provides predictions for the probability of your producing a positive Ames test outcome

Health Effects Module

• Predicts the probable adverse effects of a compound on particular organs or organ systems based on long term organ specific toxicity studies encompassing various species and routes of administration
• The following organs and organ systems are considered:
• Blood
• Cardiovascular system
• Gastrointestinal system
• Kidney
• Liver
• Lungs

hERG Inhibition Module

• Evaluates your compounds for cardiotoxicity related to drug interactions with the human ether-a-go-go (hERG) channel

Irritation Module

• Calculates the potential of a compound to cause moderate or stronger eye and skin irritation as per the Draize test

Impurity Profiling Suite

Resulting from a collaboration with the FDA, this module offers insights into 21 toxic endpoints reflecting various mechanisms of hazardous activity including:

• Mutagenicity (Ames test, Mouse Lymphoma Assay, and other standard assays)
• Clastogenicity (Micronucleus test, Chromosomal Aberrations)
• DNA damage (Unscheduled DNA Synthesis)
• Carcinogenicity (FDA rodent carcinogenicity data)
• Endocrine disruption mechanisms (estrogen receptor binding)

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