Providing protonation insights for novel molecules

The protonation state of ionizable groups can play a critical role in understanding many of the biological processes involved in medicinal chemistry, such as membrane permeability, metabolism, and structure-activity relationships. While many programs attempt to predict pKas through parameterized models, large-scale access to primary measurements has previously been a difficult and tedious endeavor. pKa Prospector addresses this problem by providing rapid access to a comprehensive and relevant database of well-curated high-quality experimental pKa measurements. This database can be searched to identify the best data on the likely protonation state of novel molecules in biological systems.

The built-in experimental pKa database was compiled by Tony Slater of pKaData Limited from a collection of IUPAC sources. Each measurement has been individually verified, curated, and assigned a metric of quality. There are more than 30,000 experiments across 12,000 molecules represented. The database is particularly relevant for medicinal chemistry due to the strong preponderance of room temperature aqueous measurements, the many molecules with multiple experimental records, and the presence of over three hundred different heterocycles.

In addition to the provided database, pKa Prospector provides the necessary tools to process and incorporate additional pKa measurements into the application. These measurements, whether from an internal database or external publication, are completely integrated into the search process and results viewer.

pKa Prospector uses a sophisticated, electronically-aware search method that can rapidly identify the most appropriate model compounds from the pool of experimental measurements. These high-quality search results, as opposed to a single context-free prediction from a trained model, provides the user with model compounds upon which to make pKa estimates based on the abundance or paucity of relevant primary data.

Features

• A well-curated database of high-quality experimental pKa measurements
• Complete experimental data and reference for each measurement
• Search using rooted maximum common substructure (MCS) with "electronically-aware" scoring
• Sketch input structures
• Advanced filters and alternate search methods
• Search by fingerprint similarity
• Search by substructure
• Auto-identification of ionizable groups
• Automated interface for finding relevant model compounds
• Highlighting simplifies identification of model compounds with multiple ionizable groups
• Retains history of previous searches for easy access
• Output results in spreadsheet form 

For more information on pKa Prospector, check out the links below:

Documentation   >   Evaluate