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PhysChem Suite pKa™

Acid Dissociation Calculator

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pKa™ Overview

Predict pKa (Acid Dissociation and Ionization) for Organic Molecules

ACD/pKa accurately predicts acid dissociation constants directly from structure.

Use ACD/pKa to:

  • Calculate pKa for organic compounds, under standard conditions
  • Visualize all ionizable centers in your compound
  • Plot the distribution of all ionized microspecies as a function of pH
  • Assess the reliability of the predicted pKa value
  • Train the algorithm with your own experimental data
Benefits

Everything You Need in a pKa Calculator

Accurate, Reliable Results

  • Predictions are based on a database of >26,000 compounds
  • We are continually expanding the database to improve accuracy
  • Evaluate the accuracy of the calculated pKa with reliability index, five most similar structures in the database, and literature references for the original experimental data

Deeper Insights

  • Assess the distribution of ionized states and microspecies from a variety of plots
  • Understand the behavior of your molecule with automatically generated plots of pKa versus pH
  • Identify trends and prioritize compounds easily—create scatter plots, browse, filter, sort, and rank libraries

Convenient Visualization

  • Color-mapping on the structure helps you easily identify ionizable groups and the structure fragment related to each calculated pKa value
  • User-defined color-coding of results will help you quickly identify favorable and unfavorable entities in compound libraries

A 2-in-1 pKa Calculator

  • Results from two prediction algorithms in one software application

Customizable with In-House Data

  • Get the accuracy of an in-house model from a commercial product. Use your own experimental pKa data to expand the applicability domain to proprietary chemical space.
  • Build a training set for each project for fine-tuned accuracy

See the contribution of various ionization states to pKa and visualize all ionized microspecies as a function of pH

Click on each contributing microspecies to see the structure

Visualize a plot of protonation states vs pH

Visualize ionogenic group state vs pH as a plot

See tabulated results for net charge vs pH

View the full calculation protocol

How it Works

Predictions in Seconds with pKa

Request a Consultation or Demo

 

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

“The best software for routine pKa predictions!”

Susan Winks
H3D

Product Features

Acid Dissociation Constant (pKa) Calculator Features

  • Calculate pKa 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
  • Two algorithms: ACD/pKa Classic (default calculator) and GALAS (Global, Adjusted Locally According to Similarity)
    Learn about the algorithms
  • Prediction of the acid dissociation constant (pKa) under standard conditions (25°C, zero ionic strength) in aqueous solution for every ionizable group
  • Calculate pKa for organic molecules, metallo-organics, salts, hydrates, mixtures, proteins (MW ≤2000 Daltons), and polymeric units
  • Automatic detection of tautomeric forms
    • Select the canonical or major form (when applicable)
  • Information provided about each ionization process (dissociation reaction) for all stages of ionization
  • Color-coding of ionizable groups to identify acidic, basic, and amphoteric ionization centers
  • Calculation of the strongest acid and base dissociation constants
  • Estimation of the reliability of calculated pKa (in ±log units)
  • Detailed calculation protocol for each predicted ionization (referred to as dissociation stage)
    • Hover on a dissociation stage to see the related ionizable center highlighted on the structure
    • Click structure fragment to see it highlighted on the structure
  • Calculate pKa 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 or copy to your application of choice
  • Train the algorithm with experimental data
  • Display the percentage contribution of individual ionization microstages to the final pKa
  • View calculated pKa values as a function of pH in interactive plots (pH 0–14) and tables (select pH values including the physiologically relevant values 1.7, 4.6, 6.5, 7.4)
    • Net charge vs. pH
    • Click-and-drag slider on the plot to see the ionic forms present at the pH of interest
    • See the fraction of all ionic forms present at a pH of interest
    • Protonation state vs. pH
    • Click on the protonation state label to display/hide its curve on the plot
    • Ionogenic group state vs. pH
Deployment/Integration Options

Choose the Deployment
Option That Works for You

Desktop/Thick Client

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

Batch

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

Percepta Portal/Thin Client

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

More Reasons to Use pKa

Technical Information about pKa

A Trainable pKa Calculator

Experimentally determined pKa values can be used to train the GALAS algorithm even if you aren’t a computational chemist or software engineer. Improve prediction accuracy for proprietary chemistry with reliable pKa measurements.

Do You Have a Large Curated Set of Experimentally Measured pKa Values?

We are happy to help you expand the applicability domain of our algorithms to apply to your proprietary chemical space.
Contact Us to discuss your project

How Are pKa Values Calculated?

Classic Algorithm

The internal training database is made up of >26,000 compounds, representing >42,000 pKa values.

Hammet-type equations for popular ionizable functional groups and carefully derived electronic substituent constants (σ) are used to predict the most accurate pKa values.

Tautomeric equilibria, covalent hydration, resonance effects, and α, β-unsaturated systems are taken into consideration in the calculations.

GALAS Algorithm

The GALAS model is Global, Adjusted Locally According to Similarity. The internal training set contains >17,500 compounds representing >20,000 ionization centers.

A database of ionization centers, interaction constants, and interaction calculation methods are used to simulate a complete distribution plot and produce a full range of protonation states of the molecule at different pH conditions. pH dependency of net molecular charge, distribution of protonation states, and the average charge of each ionization center are provided.

General Information about pKa

How Are pKa and pH Related?

pKa (the acid dissociation constant) describes the inherent property of a compound or ionizable functional group to lose H+ and generate hydronium ions (H3O+).

pH measures the concentration of hydronium ions (H3O+) in aqueous solution

pH = -log [H3O+]

Download this document to Learn all about the acid dissociation constant (pKa)

How Are pKa Values Used in Research?

Synthetic chemists use the acid dissociation constant to understand what substances can be used to protonate or deprotonate a compound, to assist a reaction. In biochemistry, pKa helps scientists understand the activity of enzymes and the stability of proteins.

In pharmacology, the ionization of a compound changes its physical behavior and affects macro properties such as aqueous solubility and lipophilicity. pKa values are also used to understand more complex ADME characteristics.

pKa is used by chromatographers to select the appropriate pH of the mobile phase (buffer) for separations.

In environmental sciences, acid-base equilibria of humic acids help establish the potability and treatment of water and provide information about the health of waterways such as lakes and rivers.

What's New!

What's New in pKa v2024

  • Extensive improvements to the pKa algorithm with focus on complex heterocycles and novel therapeutic modalities (PROTACs), resulting from a significant expansion of the training set with more than 5000 experimental pKa values
  • Addition of exciting modern datasets, in collaboration with top pharmaceutical and government partners, bringing the full ACD/Labs pKa training data to >26,000 compounds and >42,000 experimental pKa values

Read the Full List of What’s New

Learn More about pKa
Application Note

Improving pKa Prediction Accuracy for PROTACs

Predicting the pKa of large molecules such as PROTACs is a major challenge in drug discovery. Our latest study shows how our ACD/pKa Classic algorithm delivers reliable predictions, outperforming some experimental data. Learn how new datasets help our latest model achieve even greater accuracy, showcasing our ongoing commitment in advancing drug development.
Press Releases

ACD/Labs Releases v2024 of Modeling Platform Percepta® to Support Pharmaceutical and Chemical R&D at the PhysChem Forum

Version 2024 of Percepta delivers substantial expansions to the training sets and algorithms, improving prediction accuracy for pKa and logP calculators, and a range of ADME and toxicity endpoints. This update also increases coverage of chemical space occupied by new therapeutic modalities such as proteolysis targeting chimeras (PROTACs).
Podcasts

Taking Charge of Drug Discovery: Understanding the Impact of Ionization in R&D

In this episode, ACD/Labs Senior Director of Technical and Scientific Services, Karim Kassam joins hosts Jesse and Bally to dive…
Presentations

Collaborations & Developments that Bring You Industry-Leading Predictive pKa

K. Lanevskij, ACD/Labs

Hear about collaborations with pharma and chemical companies that have helped enhance ACD/Labs industry-standard pKa algorithms, particularly the significant upgrades in speed, accuracy, and reduction of normalization errors in v2023.
Presentations

Accounting for Ionization in the Increasingly Digital R&D Paradigm

A. Anderson, ACD/Labs

The prevalence of ionizable compounds in pharmaceuticals makes pKa an important physicochemical property to consider in drug discovery and development….
Blog

The Importance of Ionization in Pharmaceutical R&D

Why pKa Values are Relevant to Scientists in Pharma/BioTech Many of the small molecules under investigation in pharmaceutical and biopharmaceutical…
Technical Document

>20 Years of Reliable pKa Predictions from ACD/Labs

This document provides an overview of the ACD/pKa Classic prediction model and a review of improvements in prediction accuracy including highlights…
Technical Document

An Introduction to the Acid Dissociation Constant (pKa)

pKa (the acid dissociation constant) describes the inherent property of a compound or ionizable functional group to lose H+ and…
Application Note

The Importance of Training Predictors

This application note discusses the importance of using the machine learning (model training) capabilities of predictive models to improve accuracy.
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