Biology subjects

Rattray, Z.

Publications and source records attributed to Rattray, Z..

4 recordsLinked to original sources

bioRxiv2024

A first insight into the developability of an IgG3: A combined computational and experimental approach

Immunoglobulin G 3 (IgG3) monoclonal antibodies (mAbs) are high value scaffolds for developing novel therapies. Despite their wide-ranging therapeutic potential, IgG3 physicochemical properties and developability characteristics remain largely under-characterised. Protein-protein interactions elevate solution viscosity in high-concentration formulations impacting physico-chemical stability, manufacturability, and injectability of mAbs. Therefore, in this manuscript, the key molecular descriptors and biophysical properties of a model anti-IL-8 IgG1 and its IgG3 ortholog are characterised. A computational and experimental framework was applied to measure molecular descriptors impacting on their downstream developability. Findings from this approach underpin a detailed understanding of the molecular characteristics of IgG3 mAbs as potential therapeutic entities. This work is the first report examining the manufacturability of IgG3 for high concentration mAb formulations. While poorer conformational and colloidal stability, and elevated solution viscosity was observed for IgG3, future efforts controlling surface potential through sequence-engineering of solvent-accessible patches can be used to improve biophysical parameters that dictate mAb developability.

bioengineering↗

bioRxiv2024

Enhancing viscosity control in antibody formulations: A framework for the biophysical screening of mutations targeting solvent-accessible hydrophobic and electrostatic patches

The formulation of high-concentration monoclonal antibody (mAb) solutions in low dose volumes for autoinjector devices poses challenges in manufacturability and patient administration due to elevated solution viscosity. In the current study, we present a systematic experimental framework for the computational screening of molecular descriptors to guide the design of mutants with modified viscosity profiles accompanied by experimental evaluation. Our observations using a model anti-IL8 antibody reveal that the reduction in viscosity is influenced by the location of hydrophobic interactions, while targeting positively charged patches in mAb1 leads to the most significant viscosity increase compared to the wild-type mAb. We conclude that existing in silico predictions of physicochemical properties exhibit poor correlation with experimental parameters for antibodies with suboptimal developability characteristics, emphasizing the necessity for comprehensive case-by-case evaluations of mAbs. This approach aids in the rational design of mAbs with tailored solution viscosities, ensuring improved manufacturability and patient convenience in self-administration scenarios.

bioengineering↗

bioRxiv2022

Integration of mass-spectrometry-based metabolomics and proteomics to characterise different senescence induced molecular sub-phenotypes

Cellular senescence is a key driver of ageing and its related disease. Thus, targeting and eliminating senescent cells is a major focus in biogerontology to predict and ameliorate age-related malady. Many studies have focused on targeting senescence through the identification of its molecular biomarkers. However, these are not specific for senescence and have different expression patterns across various senescence phenotypes. Here we report a combination of molecular studies ({beta}-galactosidase expression, DNA damage and replication immunodetection) with a mass spectrometry analysis integrating intra and extracellular global metabolomics to reveal small molecules differentially expressed across multiple senescence phenotypes (replicative senescence, x-ray, and chemical-induced senescence). Altered key intracellular metabolic changes were identified, depending on the stress stimuli, which were consistent with the presence of pro-inflammatory metabolites in the cellular secretome. Our work shows the advantage of combining molecular and metabolomics studies for the detailed analysis of cellular senescence and that senescence phenotype changes upon induction method.

molecular biology↗

bioRxiv2022

The differential metabolic signature of breast cancer cellular response to olaparib treatment

Metabolic reprogramming and genomic instability are key hallmarks of cancer, the combined analysis of which has gained recent popularity. Given the emerging evidence indicating the role of oncometabolites in DNA damage repair and its routine use in breast cancer treatment, it is timely to fingerprint the impact of olaparib treatment in cellular metabolism. Here, we report the biomolecular response of breast cancer cell lines with DNA damage repair defects to olaparib exposure. Following evaluation of olaparib sensitivity in breast cancer cell lines, we immunoprobed DNA double strand break foci and evaluated changes in cellular metabolism at various olaparib treatment doses using untargeted mass spectrometry-based metabolomics analysis. Following identification of altered features, we performed pathway enrichment analysis to measure key metabolic changes occurring in response to olaparib treatment. We show a cell-line dependent response to olaparib exposure, and an increased susceptibility to DNA damage foci accumulation in triple-negative breast cancer cell lines. Metabolic changes in response to olaparib treatment were cell-line and dose-dependent, where we predominantly observed metabolic reprogramming of glutamine-derived amino acids and lipids metabolism. Our work demonstrates the effectiveness of combining molecular biology and metabolomics studies for the comprehensive characterisation of cell lines with different genetic profiles. Follow-on studies are needed to map the baseline metabolism of breast cancer cells and their unique response to drug treatment. Fused with genomic and transcriptomics data, such readout can be used to identify key oncometabolites and inform the rationale for the design of novel drugs or chemotherapy combinations.

cancer biology↗