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- Bernardi, Anna, et al.
(författare)
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Multivalent glycoconjugates as anti-pathogenic agents
- 2013
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Ingår i: Chemical Society Reviews. - : Royal Society of Chemistry (RSC). - 0306-0012 .- 1460-4744. ; 42:11, s. 4709-4727
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Forskningsöversikt (refereegranskat)abstract
- Multivalency plays a major role in biological processes and particularly in the relationship between pathogenic microorganisms and their host that involves protein-glycan recognition. These interactions occur during the first steps of infection, for specific recognition between host and bacteria, but also at different stages of the immune response. The search for high-affinity ligands for studying such interactions involves the combination of carbohydrate head groups with different scaffolds and linkers generating multivalent glycocompounds with controlled spatial and topology parameters. By interfering with pathogen adhesion, such glycocompounds including glycopolymers, glycoclusters, glycodendrimers and glyconanoparticles have the potential to improve or replace antibiotic treatments that are now subverted by resistance. Multivalent glycoconjugates have also been used for stimulating the innate and adaptive immune systems, for example with carbohydrate-based vaccines. Bacteria present on their surfaces natural multivalent glycoconjugates such as lipopolysaccharides and S-layers that can also be exploited or targeted in anti-infectious strategies.
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2. |
- Thakkar, Amol, et al.
(författare)
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Artificial intelligence and automation in computer aided synthesis planning
- 2021
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Ingår i: Reaction Chemistry and Engineering. - : Royal Society of Chemistry (RSC). - 2058-9883. ; 6:1, s. 27-51
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Forskningsöversikt (refereegranskat)abstract
- In this perspective we deal with questions pertaining to the development of synthesis planning technologies over the course of recent years. We first answer the question: what is computer assisted synthesis planning (CASP) and why is it relevant to drug discovery and development? We draw a distinction between discovery and development, focusing on their differing requirements. We highlight the need for an automated synthesis platform which chemists can use to augment their workflows and what it entails. The interaction between experimental and computational scientists is emphasized as a key driver in the development of such technologies. Advances in the development and application of algorithms is then covered, drawing a distinction between physics based and statistical or data driven modelling paradigms, their use in, and how they contribute to augmented drug discovery and development. Finally, developments in the coupling of artificial intelligence and automation are discussed. Throughout, we emphasize the need for an inter-disciplinary approach, blurring the distinction between fields in the pursuit of artificial intelligence and automated platforms that can be integrated into chemical workflows.
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