Skip to main content

Research Repository

Advanced Search

Outputs (24)

Optimizing Excipient Properties to Prevent Aggregation in Biopharmaceutical Formulations (2023)
Journal Article
King, T. E., Humphrey, J. R., Laughton, C. A., Thomas, N. R., & Hirst, J. D. (2024). Optimizing Excipient Properties to Prevent Aggregation in Biopharmaceutical Formulations. Journal of Chemical Information and Modeling, 64(1), 265–275. https://doi.org/10.1021/acs.jcim.3c01898

Excipients are included within protein biotherapeutic solution formulations to improve colloidal and conformational stability but are generally not designed for the specific purpose of preventing aggregation and improving cryoprotection in solution.... Read More about Optimizing Excipient Properties to Prevent Aggregation in Biopharmaceutical Formulations.

Design, Synthesis, and Application of Fluorescent Ligands Targeting the Intracellular Allosteric Binding Site of the CXC Chemokine Receptor 2 (2023)
Journal Article
Casella, B. M., Farmer, J. P., Nesheva, D. N., Williams, H. E., Charlton, S. J., Holliday, N. D., …Mistry, S. N. (2023). Design, Synthesis, and Application of Fluorescent Ligands Targeting the Intracellular Allosteric Binding Site of the CXC Chemokine Receptor 2. Journal of Medicinal Chemistry, https://doi.org/10.1021/acs.jmedchem.3c00849

The inhibition of CXC chemokine receptor 2 (CXCR2), a key inflammatory mediator, is a potential strategy in the treatment of several pulmonary diseases and cancers. The complexity of endogenous chemokine interaction with the orthosteric binding site... Read More about Design, Synthesis, and Application of Fluorescent Ligands Targeting the Intracellular Allosteric Binding Site of the CXC Chemokine Receptor 2.

Linear Binary Classifier to Predict Bacterial Biofilm Formation on Polyacrylates (2023)
Journal Article
Contreas, L., Hook, A. L., Winkler, D. A., Figueredo, G., Williams, P., Laughton, C. A., …Williams, P. M. (2023). Linear Binary Classifier to Predict Bacterial Biofilm Formation on Polyacrylates. ACS Applied Materials and Interfaces, 15(11), 14155-14163. https://doi.org/10.1021/acsami.2c23182

Bacterial infections are increasingly problematic due to the rise of antimicrobial resistance. Consequently, the rational design of materials naturally resistant to biofilm formation is an important strategy for preventing medical device-associated i... Read More about Linear Binary Classifier to Predict Bacterial Biofilm Formation on Polyacrylates.

In Vitro Anticancer Properties of Novel Bis-Triazoles (2022)
Journal Article
Saleh, M. M., Abuarqoub, D. A., Hammad, A. M., Hossan, M. S., Ahmed, N., Aslam, N., …Bradshaw, T. D. (2023). In Vitro Anticancer Properties of Novel Bis-Triazoles. Current Issues in Molecular Biology, 45(1), 175-196. https://doi.org/10.3390/cimb45010014

Here, we describe the anticancer activity of our novel bis-triazoles MS47 and MS49, developed previously as G-quadruplex stabilizers, focusing specifically upon the human melanoma MDA-MB-435 cell line. At the National Cancer Institute (NCI), USA, bis... Read More about In Vitro Anticancer Properties of Novel Bis-Triazoles.

Development of fluorescent peptide G protein-coupled receptor activation biosensors for NanoBRET characterization of intracellular allosteric modulators (2022)
Journal Article
Farmer, J. P., Mistry, S. N., Laughton, C. A., & Holliday, N. D. (2022). Development of fluorescent peptide G protein-coupled receptor activation biosensors for NanoBRET characterization of intracellular allosteric modulators. FASEB Journal, 36(11), Article e22576. https://doi.org/10.1096/fj.202201024R

G protein-coupled receptors (GPCRs) are widely therapeutically targeted, and recent advances in allosteric modulator development at these receptors offer further potential for exploitation. Intracellular allosteric modulators (IAM) represent a class... Read More about Development of fluorescent peptide G protein-coupled receptor activation biosensors for NanoBRET characterization of intracellular allosteric modulators.

GLIMPS: A Machine Learning Approach to Resolution Transformation for Multiscale Modeling (2021)
Journal Article
Louison, K. A., Louison, K. A., Dryden, I. L., & Laughton, C. A. (2021). GLIMPS: A Machine Learning Approach to Resolution Transformation for Multiscale Modeling. Journal of Chemical Theory and Computation, 17(12), 7930-7937. https://doi.org/10.1021/acs.jctc.1c00735

We describe a general approach to transforming molecular models between different levels of resolution, based on machine learning methods. The approach uses a matched set of models at both levels of resolution for training, but requires only the coor... Read More about GLIMPS: A Machine Learning Approach to Resolution Transformation for Multiscale Modeling.

Ligand-induced conformational selection predicts the selectivity of cysteine protease inhibitors (2019)
Journal Article
Sartori, G. R., Leitão, A., Montanari, C. A., & Laughton, C. A. (2019). Ligand-induced conformational selection predicts the selectivity of cysteine protease inhibitors. PLoS ONE, 14(12), Article e0222055. https://doi.org/10.1371/journal.pone.0222055

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 reg... Read More about Ligand-induced conformational selection predicts the selectivity of cysteine protease inhibitors.

Principal nested shape space analysis of molecular dynamics data (2019)
Journal Article
Dryden, I. L., Kim, K., Laughton, C. A., & Le, H. (2019). Principal nested shape space analysis of molecular dynamics data. Annals of Applied Statistics, 13(4), 2213-2234. https://doi.org/10.1214/19-AOAS1277

Molecular dynamics simulations produce huge datasets of temporal sequences of molecules. It is of interest to summarize the shape evolution of the molecules in a succinct, low-dimensional representation. However, Euclidean techniques such as principa... Read More about Principal nested shape space analysis of molecular dynamics data.

Tios: The Internet of Simulations. Turning Molecular Dynamics into a Data Streaming Web Application (2019)
Journal Article
Meletiou, A., Gebbie-Rayet, J., & Laughton, C. (2019). Tios: The Internet of Simulations. Turning Molecular Dynamics into a Data Streaming Web Application. Journal of Chemical Information and Modeling, 59(8), 3359-3364. https://doi.org/10.1021/acs.jcim.9b00351

The configuration of most current academic high-performance computing (HPC) resources tends to enforce ways of working with, and thinking about, molecular dynamics (MD) simulations that are not always optimal. For example, when the aim of the simulat... Read More about Tios: The Internet of Simulations. Turning Molecular Dynamics into a Data Streaming Web Application.