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Kristina Hetherington

Researcher at University of Leeds

Publications -  5
Citations -  86

Kristina Hetherington is an academic researcher from University of Leeds. The author has contributed to research in topics: Peptidomimetic & Saturation (chemistry). The author has an hindex of 3, co-authored 5 publications receiving 52 citations.

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Predicting and Experimentally Validating Hot-Spot Residues at Protein-Protein Interfaces.

TL;DR: A comparative analysis of multiple CAS methods is described, which highlights effective approaches to improve the accuracy of predicting hot-spot residues and introduces a new method, BUDE Alanine Scanning, which can be applied to single structures from crystallography and to structural ensembles from NMR or molecular dynamics data.
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Supramolecular Self-Sorting Networks using Hydrogen-Bonding Motifs.

TL;DR: Examination of the interactions between individual components, experimentally and computationally, provided a rationale for the product distribution during each phase of a cascade, resulting in the construction of a biomimetic network in which the presence or absence of different components provides multiple unique pathways to distinct self‐sorted configurations.
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Stapled Peptides as HIF-1α/p300 Inhibitors: Helicity Enhancement in the Bound State Increases Inhibitory Potency.

TL;DR: This work identifies constrained peptide inhibitors of the HIF‐1α/p300 interaction that are more potent than their unconstrained sequences and demonstrates the ability of the peptide to adopt a bioactive α‐helical conformation in the p300 bound state is better supported in the constrained variant.
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Query-guided protein–protein interaction inhibitor discovery

TL;DR: A general approach to the discovery of orthosteric PPI inhibitors that mimic specific secondary protein structures that will enable discovery of inhibitors of a wide range of unrelated secondary structure-mediated PPIs.
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Towards optimizing peptide-based inhibitors of protein-protein interactions: predictive saturation variation scanning (PreSaVS).

TL;DR: A simple-to-implement and experimentally validated computational workflow for sequence modification of peptide inhibitors of protein–protein interactions (PPIs) is described.