Project LeaderDr David Ascher
Location: Bio21 Institute, 30 Flemington Rd
The ability to identify the effects of mutations is allowing us to optimise proteins for therapeutic and biotechnological purposes.
Antibodies are becoming increasingly important in therapeutic capacity, due to their ability to bind with high specificity and affinity to an enormous variety of substances. Although many programs have been developed to predict the affinity of a protein-protein interaction, none had been specifically designed for antibodies. Antibodies rely on a unique binding mode, interactions through 6 highly variable loops, which is significantly different from general protein-protein interfaces. We hope to harness these features for modelling an antibody's affinity toward its antigen. Using graph-based signatures we have been able to identify mutations altering an antibodies binding affinity. Furthermore, we have been able to identify antibody escape mutations, which lead to reduced effectiveness of these therapies. We are now further developing this into a validated platform that can be used to guide tomorrow's antibody engineering solutions. Other specific efforts include mapping and optimisation of antigenic epitopes, and optimisation of therapeutic antibodies to minimise aggregation and poor pharmacokinetics.
Many potential biotherapeutics are restricted in their therapeutic potential due to inherent significant limitations- including thermal and in vivo instability, immunogenicity and rapid plasma clearance. We have been overcoming these limitations through directed protein engineering, using the predictions from the mutational analysis platform to identify optimal stabilising and immune masking mutations, with minimal effect on protein activity. In particular we have been applying this to the optimisation of proteins that could be used as enzyme replacement therapies in rare genetic diseases such as Alkaptonuria and OTC deficiency. We are also trying to modify the binding properties of toxins to improve their therapeutic potential.
Optimising biotechnological processes
Using our mutational analysis pipeline we have been analysing the active sites of important industrial enzymes, such as cellulases in bioethanol production, in order to improve their efficiency, activity, stability and reduce feedback inhibition, major limitations in most biotechnological processes.
Designing peptides and nucleic acids that bind to specific proteins
We are developing novel computational methods for assessing peptide and nucleic acid binding affinity to a protein. This will be used as a basis for the development of a de novo design platform of peptides and nucleic acids to target specific proteins with high affinity and specificity. This has practical applications in the in silico identification of optimal binding motifs and the design of novel therapeutics.
We are also using graph-based signatures to evaluate protein structure, chemistry, interactions and geometry. This will help aid in the identification of problems in structures, but are also being used to build tools to identify active sites, and to identify protein, nucleic acid and small molecule interaction sites, including cryptic pockets.
Dr David Ascher, Group Leader
Dr Douglas Pires
Carlos Rodrigues, PhD Student
YooChan Myung, PhD Student
Liviu Copoiu, PhD Student
Willy Cornelissen, Masters Student
Vasishth Sidarala, Masters Student
Professor Sir Tom Blundell, University of Cambridge
Dr Lisa Kaminskas, University of Queensland
Professor Chris Smith, University of Cambridge
Jack Brockhoff Foundation Grant: “Understanding the Molecular Mechanisms of Complex Mutations”.
This research project is available to PhD students to join as part of their thesis.
Please contact the Research Group Leader to discuss your options.
- Jubb HC, Higuerueloa AP, Ochoa-Montañoa B, Pittb, WR, Ascher DB, Blundell TL. Arpeggio: a web server for calculating and visualising interatomic interactions in protein structures. Journal of Molecular Biology 2016; In Press.
- Pires DEV, Ascher DB. mCSM-AB: a web server for predicting antibody-antigen affinity changes upon mutation with graph-based signatures. Nucleic Acids Research 2016; 44: W469-473.
- Pires DEV, Blundell TL, Ascher DB. mCSM-lig: quantifying the effects of mutations on protein-ligand affinity in genetic disease and the emergence of drug resistance. Scientific Reports 2016; 6: 29575.
- Pires DEV, Chen J, Blundell TL, Ascher DB. In silico functional dissection of saturation mutagenesis: Interpreting the relationship between phenotypes and changes in protein stability, interactions and activity. Scientific Reports 2016; 6: 19848.
- Chan LJ, Ascher DB, Yadav R, Bulitta JB, Landersdorfer CB, Porter CJ, Williams CC, Kaminskas LM. Conjugation of 10 kDa linear PEG onto trastuzumab Fab is sufficient to significantly enhance lymphatic exposure while preserving in vitro biological activity. Molecular Pharmaceutics 2016; 13(4): 1229-1241.
Faculty Research Themes
School Research Themes
For further information about this research, please contact the research group leader.