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PhysChem Suite LogD

Distribution Coefficient Calculation

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LogD Overview

Predict the Distribution Coefficient from Structure

ACD/LogD predicts the octanol-water distribution coefficient (or apparent partition coefficient) from a structure.

Use ACD/LogD to:

  • Calculate distribution coefficient values (logD) for all compound species of organic molecules at various pH
  • View logD results at physiologically relevant pH values or discrete pH values of interest
  • Train the algorithm with experimental measurements of logP and pKa
Benefits

Everything You Need in a LogD Property Calculator

Fast, Accurate & Reliable

  • Industry-standard calculators for pKa and logP provide a foundation for accurate logD calculation
  • Evaluate the accuracy of results with the provided information—reliability index, five most similar structures in the database, and literature references for the original experimental data

Deeper Insights

  • Understand the behavior of your molecule with the automatically generated plot of logD versus pH
  • Create scatter plots, browse, filter, sort, rank, and prioritize compounds with ease

Several Calculators-in-One

  • Get several logD values by changing the combination of logP and pKa prediction algorithms to predict logD. Choose from three logP algorithms (Classic, GALAS, and Consensus), and two pKa algorithms (Classic and GALAS).

Customizable with In-House Data

  • Get the accuracy of an in-house model from a commercial product. Use experimentally measured logP and pKa values to expand the applicability domain to proprietary chemical space.
  • Build a training set per project for fine-tuned accuracy

Calculate logD from chemical structure. See values at physiologically relevant pH, or define pH values of interest

The software automatically identifies tautomers—choose to use the major or canonical form.

How it Works

Prediction in Seconds with LogD

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  • 1 Draw/import your structure
  • 2 Review results and make decisions
  • 3 Report to PDF or copy/paste
Product Features

Distribution Coefficient (LogD) Calculator Features

  • Predict logD from structure (draw in-app, or copy/paste from third-party drawing packages); SMILES string; InChI code; imported MOL, SK2, SKC, or CDX files; or search by name in the built-in dictionary
  • Select from a variety of logP and pKa algorithms (default: logP Consensus, pKa Classic)
  • View logD values at different pH
    • Physiologically relevant values (1.7, 4.6, 6.5, 7.4, 8.0)
    • Click and drag across the plot (logD vs pH) for logD at a pH value of interest
    • Add/remove predictions at a specific pH value
  • Calculate logD properties for groups or libraries of compounds and use built-in tools to sort, filter, plot, and rank results.
    • Set user-defined label colors
    • Filter results numerically
    • Sort results by ascending/descending values
  • See results for previously calculated values in the history
  • Report results to PDF
  • Train the model with experimental values of logP and pKa to improve predictions for proprietary chemical space
    • Create and select different training libraries for calculations, or switch to the built-in algorithm
Deployment/Integration Options

Choose the Deployment Option That Works for You

Desktop/Thick Client

Install ACD/LogD on individual computers to access the thick client, which provides a full graphical user interface and access to algorithm training tools.

Batch

Calculate logD for tens of thousands of compounds with minimal user intervention. Batch deployment is compatible with Microsoft Windows and Linux. Plug-in to corporate intranets or workflow tools such as Pipeline Pilot.

Percepta Portal/Thin Client

Use a browser-based application to predict logD. KNIME integration components are available. Host on your corporate intranet or the cloud. Available for Linux and Windows.

More Reasons to Use LogD

Technical Information about Distribution Coefficient Prediction

A Trainable LogD Calculator

Train the logD algorithm by training the underlying logP and pKa models. Improve prediction accuracy and expand the applicability of the model to novel chemical space.


How Are LogD Values Calculated?

The distribution coefficient (logD) is the ratio of the sum of the concentrations of all forms of the compound (both neutral and ionized) in each of the two phases (octanol and an aqueous buffer). Each form has a different tendency to partition between aqueous buffer and n-octanol. This is characterized by a pH independent partitioning coefficient—logPspecies (e.g., logP0, logP, logP2+, etc.).

The logD prediction algorithm calculates partitioning constants based on the fragmental algorithm of logP for the neutral form and a series of correction factors, while considering the type and position of ionization. LogD is calculated as a function of the distribution of all molecular species, governed by pH as predicted by the pKa.

ACD/LogD offers various algorithms for prediction of logP and pKa values and any combinations of these can be selected (and set as default) for prediction of logD.

General Information about LogD

What Is the Distribution Coefficient?

The distribution constant (D), also known as the apparent partition coefficient, is a measure of the hydrophilicity (‘aqueous-loving’) or hydrophobicity (‘aqueous-fearing’) an ionizable molecule is. It represents the tendency of a compound to differentially dissolve in two immiscible phases (typically octanol and aqueous buffer), while considering the distribution of ionized species based on pH. It is also referred to as the distribution coefficient. For example, see the partitioning of methylamine in octanol-water and how the distribution constant describes the partitioning:

LogD prediction models estimate the distribution constant as a logarithmic ratio (logD or ClogD). The distribution coefficient acts as a quantitative descriptor of the lipophilicity (or hydrophobicity) of ionizable compounds.


How Are LogD Values Used?

Drug Discovery—LogD values are used to understand and predict the in-vivo behavior of an active compound under physiological conditions. Since the pH environment is very different throughout the gastrointestinal tract (ranging from 1.4 in the stomach to 8 in the colon) understanding the lipophilicity/hydrophilicity of a drug lead under physiological conditions helps scientists understand behavior under substantially different chemical environs.

LogD values are also important in chromatographic method development (for selection of the appropriate pH and separation columns); in agrochemistry to develop herbicides and insecticides; in environmental chemistry to understand the behavior of pollutants, and in the development of many other consumer products.

What's New!

What's New in LogD Version 2021

  • Calculate the pH value at which a molecule has zero net charge (the isoelectric point)
  • Activate/deactivate extended tool tips from the Expert Panel
  • Add Similarity Index (SI) and the Data-Model Consistency Index (DMCI) values for predicted results, in the Spreadsheet Workspace, for a better understanding of their reliability