Blog Archives

Hot Topics: Resting-State Structure and Gating Mechanism of a Voltage-Gated Sodium Channel

In this report the Catterall laboratory succeeded in solving the high resolution structure of a voltage-gated Na+-channel (Nav) in its resting state (1). Why is this difficult and why is this important? It is difficult because Navs exist in the

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Hot Topics: The atlas of aminergic GPCR mutagenesis

G protein-coupled receptors (GPCRs) are an important family of signal-transducing membrane proteins capable of binding various types of ligands from the extracellular space and activating various signalling pathways inside the cell, rendering them one of the largest protein target families

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Database Release 2019.3

We have now made the third IUPHAR/BPS Guide to Pharmacology database release of 2019 (2019.3). It includes updates focussed on preparation for the next edition of The Concise Guide to PHARMACOLOGY (2019/20), due out later this year. Content Updates GtoPdb

Posted in Database updates, Guide to Malaria Pharmacology, Hot Topics

Hot Topics: Time to FRET about GPCR activation dynamics?

G protein coupled receptors (GPCRs) are crucial for the transduction of extracellular stimuli to the intracellular space. Upon activation, GPCRs undergo large conformational changes to engage transducers and stimulate intracellular responses. However, the kinetics of agonist induced GPCR conformational changes

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Hot Topics: Rise up against statistical significance, probably.

A recent commentary in Nature has the provocative title “Retire Statistical Significance” (1, with a list of more than 800 signatories) and has been widely interpreted as a call for the entire concept of statistical significance to be abandoned. Closer

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Hot Topics: Exciting Times for Ion Channel Pharmacology

Whilst life is always exciting as an ion channel pharmacologist, the last few months have been particularly so, with a large number of publications showing structures of ion channels with regulatory molecules bound to them. In just the last month,

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Hot Topics: Ligand biological activity predicted by cleaning positive and negative chemical correlations

New machine learning algorithm for drug discovery that is twice as efficient as the industry standard and identified potential ligands for the M1 receptor, a potential target for the treatment of Alzheimer’s disease. A paper from Lee et al. [1]

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