Contact information
Philip Biggin
We are developing and applying computational methods to examine conformational changes and properties of ligand-binding that occur within receptor proteins. We are particularly interested in two distinct families of receptors: 1. The ionotropic glutamate receptors and 2. The nicotinic acetylcholine receptor. Although there has been a recent increase in the amount of structural information available, many questions still remain concerning the dynamics associated with these processes (see Figure 1). For example, how does the binding of agonist cause the transmembrane domain to open? What determines whether an agonist will act as a full or partial agonist? How can channel opening be modulated? How do certain compounds interfere with the process of desensitization? We use molecular dynamics to examine the molecular motion of these receptors at the atomic level (see Figures 2 and 3 for recent examples).
Furthermore, via free energy calculations, we are able to make quantitative predictions that can be tested experimentally. A better understanding of the manner in which ligand-gated ion channels work should be useful in the design of new drug treatments for a range of diseases including Alzheimer's, Parkinsons's, and epilepsy.
We are also interested in conformational change in a broader sense. Two areas that we are currently focussing on are 1. How molecular motion has evolved. 2. How best to describe transitions between discrete states. The conservation of structure (ie. fold) has been discussed for a long time. We are interested in trying to understand how well molecular motion is conserved amongst protein folds. Our results so far have demonstrated that large conformational changes are dictated by fold, but smaller higher-frequency motions are dictated by sequence.
Recent publications
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Conformational transitions and allosteric modulation in a heteromeric glycine receptor.
Journal article
Gibbs E. et al, (2023), Nat Commun, 14
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Evaluating the use of absolute binding free energy in the fragment optimisation process
Journal article
Alibay I. et al, (2022), Communications Chemistry, 5
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When is a hydrophobic gate not a hydrophobic gate?
Journal article
Seiferth D. et al, (2022), J Gen Physiol, 154
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Scoring Functions for Protein-Ligand Binding Affinity Prediction using Structure-Based Deep Learning: A Review.
Journal article
Meli R. et al, (2022), Front Bioinform, 2
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Structural insights into binding of therapeutic channel blockers in NMDA receptors.
Journal article
Chou T-H. et al, (2022), Nat Struct Mol Biol, 29, 507 - 518