Defining 'Molecule' to a Broad Scientific Audience
The article discusses the complexities of defining and representing molecules across scientific disciplines, highlighting Bioregister's advancements in chemical structure visualization, uniqueness checking to identify chemically identical molecules despite differing monomer sequences, and new workflows for conjugating biologically active molecules such as antibody-drug conjugates using techniques like click chemistry.
Sometimes even this simple sounding question can generate an incredible amount of discussion. If we take the question a step further and ask how do you want to represent this molecule then even the best cross-functional team is likely to be divided.
The answers will of course differ depending on your scientific background and the size of the molecule. As you move towards the small molecule end of the spectrum the chemical structure of the molecule in question becomes more and more important and not just to the chemists in your team.
In Bioregister 3.2 we introduced the ability to generate full chemical representations of natural and non-natural entities. This enables scientists to visualise and share the chemical structures of their molecules and query them via sub-structure searches and share structures with collaborators.
With Bioregister 2020.1 we take a further step forward with the introduction of chemical structure uniqueness checking. Where one monomer ends and another begins is not always as obvious as it might sound and, even within an organisation, can be open to interpretation. We recommend that monomers are defined as the smallest chemically divisible unit, however we recognise that this does not always map easily to lab-based workflows. This means that if uniqueness is based on monomer sequence alone, chemically identical molecules can be registered as separate entities. It is vital that your registration system can recognise when two molecules represented by different monomers are actually chemically identical and Bioregister delivers just that.
Such talk of chemical structure leads us to another key development in Bioregister 2020.1: new workflows for the conjugation of biologically active molecules.
The conjugation of two or more biologically active molecules, be that antibody-drug conjugates or short peptides, often via a linker moiety, is a widely used technique. So called ‘click’ chemistry, the cycloaddition of azides and terminal alkynes, is commonly used due to selectivity and high yielding nature of the reaction. When building a molecule from a sequence definition, the monomers are joined together via their attachment points (R-groups) with the concomitant loss of the capping groups: i.e. water is lost in amide or phosphodiester bond forming reactions. In cycloaddition chemistry no capping groups are “lost” because all the atoms of the starting materials are also found in the product (the atoms of the alkyne and azide = the atoms of the triazole). As noted recently by the Pistoia Alliance, this type of chemistry poses challenges when using monomer-based representations of macromolecules such as HELM and that used in Bioregister. Bioregister 2020.1 removes the complexity of mapping this process by providing an automatic cross-linking workflow to enable the generation of click chemistry products which can be used for both single and bulk registration. The out-of-the-box monomers support the generation of 1,4-disubstitured triazoles and are provide a worked example showing how this functionality can be used to support other cycloaddition reactions.
Related
Cross-Functional Informatics Solutions for RNA Drug Discovery
The article discusses how RNA therapeutics, including ASOs, siRNA, and mRNA vaccines, leverage chemical modifications such as phosphorothioate backbone alterations and other structural changes to overcome challenges like poor cellular uptake and nuclease degradation, thereby enhancing efficacy, metabolism, and pharmacokinetics in RNA drug discovery.
Next Generation Biologics R&D
Christian Olsen of Dotmatics highlighted at the BioIT-World Expo how their flexible end-to-end R&D platform overcomes challenges in biologics discovery—such as fragmented, diverse, and siloed data from multiple complex analytical methods like sequencing, mass spectrometry, and flow cytometry—by unifying data and tools to enable multidimensional candidate profiling, streamline workflows, and accelerate preclinical biologics research.
From Fragmented Data to Unified Discovery: LifeArc's Approach to Multimodal R&D
LifeArc, a UK-based medical charity focused on transformative life science, has developed a collaborative, multidisciplinary R&D approach that integrates diverse data from over 100 internal scientists, external pharma, biotech, academic partners, and CROs across multiple therapeutic modalities—including small molecules and biologics like engineered antibodies—to streamline drug discovery and design for diseases such as cancer, Crohn’s disease, multiple sclerosis, rheumatoid arthritis, and COVID-19, enabling unified data flow and informed, data-driven decision-making that has already resulted in four licensed medications and several drugs in trials.
Why Cerevel Therapeutics Chose Dotmatics to Power Their Neuroscience Research
Cerevel Therapeutics, aiming to advance neuroscience research with support from Pfizer and Bain Capital, selected Dotmatics for its comprehensive, scalable cloud-based lab software platform that integrates electronic lab notebooks, assay automation, sample and inventory management, instrument integration, and advanced data analytics, enabling secure, collaborative, and efficient R&D workflows across biology and chemistry labs.
Dotmatics Lunch & Learn 2024 한국
The Dotmatics Lunch & Learn 2024 seminar for existing customers will be held on August 30 at 타운홀 코사이어티, featuring presentations on the new UI/UX of Dotmatics Platform 7.1, material and instrument management using Bioregister, and hands-on protocol creation with the Canvas feature, with parking, lunch provided, and attendees required to bring a laptop.
Maximize Efficiencies by Avoiding 9 Critical Lab Errors
The article outlines nine critical lab errors—such as redundant efforts due to siloed teams, nonrepeatable experiments from inconsistent recording, duplicate registrations from inadequate systems, data-entry errors, and unsearchable data—that hinder R&D efficiency, and recommends solutions like unified systems, standardized templates, automated data entry, and enhanced metadata use to streamline workflows, improve collaboration, and safeguard data integrity.