Advances in Malaria Pharmacology and the online Guide to MALARIA PHARMACOLOGY: IUPHAR Review X

Antimalarial drug discovery has until recently been driven by high-throughput phenotypic cellular screening, allowing millions of compounds to be assayed and delivering clinical drug candidates. In this review, we will focus on target-based approaches, describing recent advances in our understanding of druggable targets in the malaria parasite. Targeting multiple stages of the Plasmodium lifecycle, rather than just the clinically symptomatic asexual blood stage, has become a requirement for new antimalarial medicines, and we link pharmacological data clearly to the parasite stages to which it applies. Finally, we highlight the IUPHAR/MMV Guide to MALARIA PHARMACOLOGY, a web resource developed for the malaria research community that provides open and optimized access to published data on malaria pharmacology

A consensus-based and readable extension of Linear Code for Reaction Rules (LiCoRR).

Systems glycobiology aims to provide models and analysis tools that account for the biosynthesis, regulation, and interactions with glycoconjugates. To facilitate these methods, there is a need for a clear glycan representation accessible to both computers and humans. Linear Code, a linearized and readily parsable glycan structure representation, is such a language. For this reason, Linear Code was adapted to represent reaction rules, but the syntax has drifted from its original description to accommodate new and originally unforeseen challenges. Here, we delineate the consensuses and inconsistencies that have arisen through this adaptation. We recommend options for a consensus-based extension of Linear Code that can be used for reaction rule specification going forward. Through this extension and specification of Linear Code to reaction rules, we aim to minimize inconsistent symbology thereby making glycan database queries easier. With a clear guide for generating reaction rule descriptions, glycan synthesis models will be more interoperable and reproducible thereby moving glycoinformatics closer to compliance with FAIR standards. Here, we present Linear Code for Reaction Rules (LiCoRR), version 1.0, an unambiguous representation for describing glycosylation reactions in both literature and code

A consensus-based and readable extension of Linear Code for Reaction Rules (LiCoRR).

Systems glycobiology aims to provide models and analysis tools that account for the biosynthesis, regulation, and interactions with glycoconjugates. To facilitate these methods, there is a need for a clear glycan representation accessible to both computers and humans. Linear Code, a linearized and readily parsable glycan structure representation, is such a language. For this reason, Linear Code was adapted to represent reaction rules, but the syntax has drifted from its original description to accommodate new and originally unforeseen challenges. Here, we delineate the consensuses and inconsistencies that have arisen through this adaptation. We recommend options for a consensus-based extension of Linear Code that can be used for reaction rule specification going forward. Through this extension and specification of Linear Code to reaction rules, we aim to minimize inconsistent symbology thereby making glycan database queries easier. With a clear guide for generating reaction rule descriptions, glycan synthesis models will be more interoperable and reproducible thereby moving glycoinformatics closer to compliance with FAIR standards. Here, we present Linear Code for Reaction Rules (LiCoRR), version 1.0, an unambiguous representation for describing glycosylation reactions in both literature and code

Advances in Malaria Pharmacology and the online Guide to MALARIA PHARMACOLOGY: IUPHAR Review X.

Antimalarial drug discovery has until recently been driven by high-throughput phenotypic cellular screening, allowing millions of compounds to be assayed and delivering clinical drug candidates. In this review, we will focus on target-based approaches, describing recent advances in our understanding of druggable targets in the malaria parasite. Targeting multiple stages of the Plasmodium lifecycle, rather than just the clinically symptomatic asexual blood stage, has become a requirement for new antimalarial medicines, and we link pharmacological data clearly to the parasite stages to which it applies. Finally, we highlight the IUPHAR/MMV Guide to MALARIA PHARMACOLOGY, a web resource developed for the malaria research community that provides open and optimized access to published data on malaria pharmacology.Wellcom

Advances in malaria pharmacology and the online guide to MALARIA PHARMACOLOGY: IUPHAR review 38.

Antimalarial drug discovery has until recently been driven by high-throughput phenotypic cellular screening, allowing millions of compounds to be assayed and delivering clinical drug candidates. In this review, we will focus on target-based approaches, describing recent advances in our understanding of druggable targets in the malaria parasite. Targeting multiple stages of the Plasmodium lifecycle, rather than just the clinically symptomatic asexual blood stage, has become a requirement for new antimalarial medicines, and we link pharmacological data clearly to the parasite stages to which it applies. Finally, we highlight the IUPHAR/MMV Guide to MALARIA PHARMACOLOGY, a web resource developed for the malaria research community that provides open and optimized access to published data on malaria pharmacology.Wellcom

Adaptive laboratory evolution in S. cerevisiae highlights role of transcription factors in fungal xenobiotic resistance

In vitro evolution and whole genome analysis were used to comprehensively identify the genetic determinants of chemical resistance in Saccharomyces cerevisiae. Sequence analysis identified many genes contributing to the resistance phenotype as well as numerous amino acids in potential targets that may play a role in compound binding. Our work shows that compound-target pairs can be conserved across multiple species. The set of 25 most frequently mutated genes was enriched for transcription factors, and for almost 25 percent of the compounds, resistance was mediated by one of 100 independently derived, gain-of-function SNVs found in a 170 amino acid domain in the two Zn2C6 transcription factors YRR1 and YRM1 (p < 1 × 10-100). This remarkable enrichment for transcription factors as drug resistance genes highlights their important role in the evolution of antifungal xenobiotic resistance and underscores the challenge to develop antifungal treatments that maintain potency