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PhysChem Suite

Calculate Physicochemical Properties

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PhysChem Suite Overview

Calculators & Predictors for LogP, LogD, pKa, Aqueous Solubility, and more…

The physicochemical properties of a molecule can help you better understand its likely behavior, support QSPR high-throughput screening (HTS) of libraries, and data-driven lead optimization.

ACD/PhysChem Suite is made up of a number of prediction modules. It provides high-quality, structure-based calculations of physicochemical properties.

  • Predict aqueous solubility,* boiling point, logD,* logP,* pKa,* Sigma, and other molecular descriptors for organic compounds, from structure
  • Evaluate the calculated results with sorting, plotting tools
  • Assess the reliability of predicted physicochemical property values
  • Investigate quantitative structure-property relationships, structure modifications, and/or lead optimization for a target profile
  • Train predictors with experimental data to better reflect novel chemical space
  • Include custom models and in-house prediction algorithms

*Models are trainable with experimental data


Everything You Need in a Physicochemical Property Calculator

Easy to Use

  • Simply draw your structure for predictions. PhysChem Suite makes predicting physicochemical properties easy for everyone—medicinal, synthetic, and research chemists, and others
  • Train the models code-free. No need to be a software engineer, programmer, or computational chemist to improve prediction accuracy for novel chemical space.

Fast, Accurate, Reliable Results

  • Quickly calculate properties for single compounds or tens of thousands
  • Predictions are based on carefully curated databases of experimental data
  • Easily evaluate the reliability of results with a reliability index, a display of similar structures in the database, and literature references for the original experimental data

Convenient Visualization

  • Visualize the substructure/atomic contributions to a property value with color-mapping on the structure
  • Quickly identify favorable and unfavorable compounds in a library with user-defined color-coding of results in the spreadsheet

Deeper Insights

  • Identify trends and prioritize compounds easily with tools to create scatter plots, browse, filter, sort, and rank libraries
  • Make decisions confidently with a complete property profile of each molecule in one place

Customizable with In-House Data

  • Get the accuracy of in-house models from a commercial product. Use your own experimental data to expand the applicability domain of trainable modules.

Expandable to Third-Party Models

  • Create a single environment for predicted data by including third-party and in-house models
  • Use reliable results from PhysChem Suite to model more complex behaviors

Calculate properties for tens or hundreds of compounds. Create scatter plots to identify trends. Sort, filter, and rank results.

See all the properties calculated in PhysChem Suite, in one place.

Predict the boiling point of organic compounds. See the results as a plot or a table.

Calculate the acid dissociation constant (pKa) using two different algorithms. See all ionic forms by pH.

Predict logP. Color highlighting shows contributing structural features. See experimental values for similar structures.

How It Works

Predict in Seconds with PhysChem Suite

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  • 1 Draw/import your structure
  • 2 Select the property of interest
  • 3 Review results and make decisions
  • 4 Report to PDF or copy/paste
Customer Reviews
“Merck Germany has deployed Percepta Enterprise software at their Research facilities in Germany and North America. It provides in silico tools for the prediction of Physicochemical, ADME and Tox properties, helping support the medicinal chemists in their planning of syntheses and optimization of new chemical entities. Their main reasons for choosing ACD/Labs Percepta Enterprise were its ease of use and, in particular, its configurability and ability to use existing in-house built algorithms.”

“Clearly the industry standard PhysChem prediction models and [they] deserve the position. They are the most consistent predictions that are applicable and usable in more complex models of drug-likeness.”

Computational Chemist

“The big advantage of [the] software is the big 'Easy Button' for all predictions, where you just drop in a structure and hit go, then everything you want is right there.”

Brian Dean

Product Features

Physicochemical Property Calculator Features

  • Calculate physicochemical properties for organic molecules, metallo-organics, salts, hydrates, mixtures, proteins (MW ≤2000 Daltons), and polymeric units
  • Start with a 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
  • Several algorithms available for many predictions—see individual module for more details
  • Automatic detection of tautomeric forms (for applicable prediction modules)
    • Select the canonical or major form
  • Evaluate results
    • Structure highlighting for sub-structure/atomic contributions
    • Calculation protocols
  • Calculate physicochemical 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 via your activity history
  • Estimates of prediction accuracy to assess reliability of predicted values (information provided differs by module and calculation algorithm)
    • 95% confidence intervals
    • Interactive calculation protocols
    • Reliability Index and display of 5 most similar structures in the training library with experimental values and literature references
  • Report results to PDF or copy to your application of choice
  • Download QPRF and QMRF documents for ACD/LogP (GALAS model) and ACD/LogS0
  • Train algorithms with experimental data in select modules—logP, pKa, logD
  • Add custom models/algorithms and in-house prediction algorithms by connecting to an existing web service using an XML protocol, or in the form of a DLL (available in think client deployments only)
  • Gain insights into structure-property relationships
  • Understand and modify the pharmacokinetic profile of lead compounds
    • Good/bad indicators for Lipinksi’s rule of 5 and lead-likeness
  • Identify structural fragments responsible for toxicity
  • Modify sets of structures with the interactive optimization tool
    • Generate libraries of analogs with substituent modifications based on an optimal property profile
    • Sort, filter, and prioritize hundreds of structural analogs according to your desired property profile
    • Create and use custom fragment libraries
    • Target synthetically accessible fragments with the built-in retrosynthesis tool
  • Calculate quantitative solubility in pure (unbuffered) water at 25°C
  • Predict qualitative solubility at pH 7.4—compounds categorized from highly soluble to insoluble
    • GALAS (Global, Adjusted Locally According to Similarity) algorithm
    • Display of 5 most similar structures from the training set with experimental values
  • Estimate intrinsic solubility—logS0
    • Predictions based on a training set of >6800 compounds and a GALAS algorithm
    • Reliability value and up to 5 most similar structures from the training set provided with experimental data
  • Predict pH-dependent aqueous solubility—logS
    • Solubility at physiological pH values of interest (pH 1.7, 4.6, 6.5, 7.4, 8.0)
    • Plot of predicted pH versus solubility
  • Train the model with experimental values
  • Estimate the boiling point of organic compounds as a function of pressure
  • Predict the vapor pressure as a function of temperature
  • View results in a table or graphical plot
  • Predict logP—choose from three prediction algorithms:
    • Classic
    • GALAS (Global, Adjusted Locally According to Similarity)
    • Consensus logP based on the other two models.
  • Detailed calculation protocol lists all contributing functional groups, carbon atoms, and interactions through aliphatic, aromatic, and vinylic systems (Classic)
    • Click protocol entry to highlight the corresponding entity on the structure
  • Color highlighting of the molecule to highlight hydrophilic/lipophilic substructures (GALAS)
  • Train the model with experimental values to improve predictions for proprietary chemical space
    • Create and select different training libraries for calculations, or switch to the built-in algorithm

Learn more about ACD/LogP

LogD predictions are based on the logP and pKa models of PhysChem Suite

  • Select from a variety of logP and pKa algorithms (default: logP Consensus, pKa Classic)
  • View logD calculation results by 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
  • 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

Learn more about ACD/LogD

  • Calculate the acid dissociation constant (pKa) under standard conditions (25°C, zero ionic strength) in aqueous solution for every ionizable group
  • Choose from two different algorithms: ACD/pKa Classic (default calculator) and GALAS
  • Information about each ionization process (dissociation reaction) for all stages of ionization
  • Color-coding of ionizable groups: red = acidic, blue = basic, purple = amphoteric ionization centers; color intensity indicates acid/base strength.
  • Calculation of the strongest acid and base dissociation constants
  • Reliability range (in ±log units) for calculated pKa values
  • 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
  • Train the algorithm with experimental data

Learn more about ACD/pKa

  • Display of 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

Learn more about ACD/pKa

  • Calculate substituent-specific parameters for selected fragments of the molecule in aqueous solution, at zero ionic strength and 25°C
    • Electronic substituent constant (Hammett)
    • Steric constants (molar volume, molar refractivity)
    • Hydrophobic constant (Hansch Pi)
  • High accuracy—typical calculation accuracy of ±0.05
  • Internal database contains >850 substituents and >3000 carefully derived experimental electronic constants
  • 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
Deployment/Integration Options

Choose the Deployment Option That Works for You

Desktop/Thick Client

Install ACD/PhysChem Suite on individual computers to access the thick client which provides a full graphical user interface and access to algorithm training tools for trainable modules.


Perform high-throughput screening (HTS) of hundreds 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 physicochemical properties. KNIME integration components are available. Host on your corporate intranet or the cloud. Available for Linux and Windows OS.

More Reasons to Use PhysChem Suite

Trainable Calculators of Physicochemical Properties

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Use curated experimental data to expand the training database and the applicability domain of trainable models.

Both Classic and GALAS algorithms can be trained even if you aren’t a computational chemist or software engineer.

What's New!

What's New in PhysChem Suite v2021

  • 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