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Laughton, C. A.

Publications and source records attributed to Laughton, C. A..

3 recordsLinked to original sources

Development of fluorescent peptide G Protein Coupled Receptor activation biosensors for NanoBRET characterisation of intracellular allosteric modulators

G protein coupled receptors (GPCRs) are widely therapeutically targeted, and recent advances in allosteric modulator development at this class of receptors offer further potential for exploitation. In particular GPCR intracellular allosteric modulators (IAM) represent a class of ligands that bind to the receptor-effector interface (e.g. G protein) and so inhibit agonist responses non-competitively. This potentially offers a tailored mode of action and greater selectivity between conserved receptor subtypes compared to classical orthosteric ligands. However, while specific examples of the IAM class of ligands are well described (particularly for chemokine receptors), a more general methodology for assessing compound interactions at the GPCR IAM site is lacking. Here fluorescent labelled peptides based on the G peptide C terminus are developed as novel binding and activation biosensors for the GPCR IAM binding site. In TR-FRET binding studies, unlabelled peptides derived from the GS subunit C-terminus were first characterised for their ability to positively modulate agonist affinity at the {beta}2-adrenoceptor. On this basis, a tetramethylrhodamine (TMR) labelled tracer was synthesized based on the 19 amino acid C terminal GS peptide (TMR-GS19cha18, where cha=cyclohexylalanine). Using NanoBRET technology to detect binding, TMR-GS19cha18 was recruited to Gs coupled {beta}2-adrenoceptor and EP2 receptors in an agonist dependent manner (correlated with ligand efficacy), but not to the Gi coupled CXCR2 receptor. Moreover, NanoBRET competition binding assays using TMR-GS19cha18 enabled direct assessment of the affinity of unlabelled ligands for {beta}2-adrenoceptor IAM site. Thus the NanoBRET platform using fluorescent-labelled G protein peptide mimetics offers novel potential for medium-throughput affinity screens to identify new IAMs, applicable across GPCRs coupled to a G protein class. Using the same platform, Gs peptide biosensors also represent useful tools to probe orthosteric agonist efficacy and the dynamics of receptor activation.

pharmacology and toxicology↗

Ligand-induced Conformational Selection Predicts the Selectivity of Cysteine Protease Inhibitors

Cruzain, a cysteine protease of Trypanosoma cruzi, is a validated target for the treatment of Chagas disease. Due to its high similarity in three-dimensional structure with human cathepsins and their sequence identity above 70% in the active site regions, identifying potent but selective cruzain inhibitors with low side effects on the host organism represents a significant challenge. Here a panel of nitrile ligands with varying potencies against cathepsin K, cathepsin L and cruzain, are studied by molecular dynamics simulations as both non-covalent and covalent complexes. Principal component analysis (PCA), identifies and quantifies patterns of ligand-induced conformational selection that enable the construction of a decision tree which can predict with high confidence a low-nanomolar inhibitor of each of three proteins, and determine the selectivity for one against others.

bioinformatics↗

MuGVRE. A virtual research environment for 3D/4D genomics

Multiscale Genomics (MuG) Virtual Research Environment (MuGVRE) is a cloud-based computational infrastructure created to support the deployment of software tools addressing the various levels of analysis in 3D/4D genomics. Integrated tools tackle needs ranging from high computationally demanding applications (e.g. molecular dynamics simulations) to high-throughput data analysis applications (like the processing of next generation sequencing). The MuG Infrastructure is based on openNebula cloud systems implemented at the Institute for research in Biomedicine, and the Barcelona Supercomputing Center, and has specific interfaces for users and developers. Interoperability of the tools included in MuGVRE is maintained through a rich set of metadata allowing the system to associate tools and data in a transparent manner. Execution scheduling is based in a traditional queueing system to handle demand peaks in applications of fixed needs, and an elastic and multi-scale programming model (pyCOMPSs, controlled by the PMES scheduler), for complex workflows requiring distributed or multi-scale executions schemes. MuGVRE is available at https://vre.multiscalegenomics.eu and documentation and general information at https://www.multiscalegenomics.eu. The infrastructure is open and freely accessible.

bioinformatics↗