LABORATORY INFORMATICS
The EMBL-EBI South Building on the Wellcome Genome Campus g
tools that are designed to help streamline the entire Quantitative structure-activity relationship (QSAR)/Quantitative structure- property relationships (QSPR) process, from data curation to the deployment of prediction models. Cheminformatics and in silico
techniques have been growing in focus for the past two decades, suggests Matteo Bertola, Alvascience co-founder and head of software development. ‘Cheminformatics has traditionally been viewed as something of a niche field within the pharma/biotech sector but, in fact, it’s critical for many sectors of discovery and R&D,’ he explained. ‘Just about every agrochemical, food, oil and gas, pharma or materials science organisation has a cheminformatics department because these organisations all need to work with molecules, and try to understand the chemistry of foodstuffs and crop products, drugs, petro- and speciality chemicals, and new materials.’ Organisations today expect to work
with software that allows them to screen huge numbers of molecules and create reliable models to test specific properties or evaluate a prediction, Bertola noted. ‘They may commonly have some endpoint that was acquired experimentally, on which they want to build a mathematical model that allows them to test new molecules against that endpoint, and rule out or rule in molecules they may want to take to the next level.’
One of the main challenges, Bertola suggests, is ‘how to create models that are reliable, and explain how the molecule will behave in the real world, so you can
18 Scientific Computing World Autumn 2021
test structures with some degree of confidence.’ Another challenge is how to explore the sheer size of chemical space that is available and find the best molecules that fit the required properties and, ultimately, functionality. With these goals and challenges
as starting points, Alvascience has built a suite of desktop QSAR and cheminformatics tools to aid the
“Just about every agrochemical, food, oil and gas, pharma or materials science organisation has a cheminformatics department because these organisations all need to work with molecules”
complete workflow. Data curation is often the first step of a QSAR pipeline, and the firm’s alvaMolecule platform has been developed to allow users to analyse, visualise, curate and standardise a molecular dataset. ‘In the next step, alvaDesc calculates molecular fingerprints and thousands of molecular descriptors in an efficient way,’ Bertola continued. ‘Molecular descriptors are also key components for the development of models to predict given endpoints, so we’ve developed
alvaModel to enable users to generate QSAR/QSPR regression or classification models to predict the endpoint you need. ‘The software, making use of genetic algorithms, can search for high- performing models by selecting the descriptors from those previously calculated in alvaDesc. Once your models have been created, you can share them with your colleagues, who can use alvaRunner to apply the models to new molecular datasets. In this way, you do not need to use other software for applying models as alvaRunner provides a single solution.’ alvaModel and alvaRunner can thus effectively be applied together to build and deploy QSAR/QSPR regression and classification models, with alvaRunner offered as a software tool that allows users to apply models, created using alvaModel, on a new set of molecules. Alvascience also offers a tool for
de novo molecular design, called alvaBuilder, which has been developed as a user-friendly software that lets users generate new molecules with a set of desired properties, starting from a defined training set. ‘The suite of tools effectively addresses this concept of a cheminformatics pipeline, starting with data curation, and then getting to deployment of a model,’ added Bertola. All Alvascience’s tools are offered
solely as desktop solutions, available for Windows, Linux and macOS. ‘We’ve stayed away from the cloud as many customers don’t want to share any of their data with third parties,’ Bertola pointed out, ‘but we are not ruling out possible expansion into cloud offerings in the future.’
@scwmagazine |
www.scientific-computing.com
Jeff Dowling
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