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Centre for Misfolding Diseases

I am a Research Fellow at St. John's College, Senior Schmidt Science Fellow, and post-doctoral researcher at the Centre for Misfolding Diseases, Department of Chemistry. My research focusses on developing new experimental and predictive computational methods for examining the behaviour of biological molecules and systems, in particular proteins.

Proteins are the executive molecules of life that through diverse set of highly integrated and tightly regulated interactions set the molecular basis for our well-being. Yet the diverse and dynamic nature of proteins has made it challenging to devise methods that could be effectively used for understanding their roles in human health and disease. By bringing data science, machine learning, computational biology and chemistry approaches together with experimental sciences, I develop new in silico capabilities for probing the key molecular interactions that underpin biological function. I am particularly interested in modelling biomolecular phase separation and condensation processes and in understanding the biological rules and sequence grammar that govern the formation of such condensates. I further aim to understand how these systems can be modulated by small molecules as this development could open up the possibility for discovering therapeutics against biomolecular condensates and biological targets that have remained undruggable using conventional approaches.

I have co-authored over 40 peer-reviewed publications, book chapters and patents. Full list of my publications is available from: https://scholar.google.co.uk/citations?hl=en&user=7OQGF4oAAAAJ

Publications

Surface Electrostatics Govern the Emulsion Stability of Biomolecular Condensates
TJ Welsh, G Krainer, JR Espinosa, JA Joseph, A Sridhar, M Jahnel, WE Arter, KL Saar, S Alberti, R Collepardo-Guevara, TPJ Knowles
– Nano Letters: a journal dedicated to nanoscience and nanotechnology
(2022)
22,
612
Turning high-throughput structural biology into predictive inhibitor design
KL Saar, D Fearon, F von Delft, JD Chodera, AA Lee
(2021)
2021.10.15.464568
Deformable and robust core-shell protein microcapsules templated by liquid-liquid phase-separated microdroplets
Y Xu, Y Shen, TCT Michaels, KN Baumann, D Vigolo, Q Peter, Y Lu, KL Saar, D Vella, H Zhu, B Li, H Yang, APM Guttenplan, M Rodriguez-Garcia, D Klenerman, TPJ Knowles
– Advanced Materials Interfaces
(2021)
8,
2101071
Machine learning-aided protein identification from multidimensional signatures
Y Zhang, MA Wright, KL Saar, P Challa, AS Morgunov, QAE Peter, S Devenish, CM Dobson, TPJ Knowles
– Lab on a chip
(2021)
21,
2922
Rapid highly sensitive general protein quantification through on-chip chemiluminescence.
HK Chiu, T Kartanas, KL Saar, CM Luxhøj, S Devenish, TPJ Knowles
– Biomicrofluidics
(2021)
15,
024113
Learning the molecular grammar of protein condensates from sequence determinants and embeddings.
KL Saar, AS Morgunov, R Qi, WE Arter, G Krainer, AA Lee, TPJ Knowles
– Proceedings of the National Academy of Sciences
(2021)
118,
e2019053118
Learning the molecular grammar of protein condensates from sequence determinants and embeddings
K Saar
– Proceedings of the National Academy of Sciences of USA
(2021)
Direct Digital Sensing of Proteins in Solution through Single-Molecule Optofluidics
G Krainer, KL Saar, WE Arter, TPJ Knowles
– Biophysical Journal
(2021)
120,
114A
Machine learning aided top-down proteomics on a microfluidic platform
Y Zhang, M Wright, K Saar, P Challa, A Morgunov, Q Peter, S Devenish, C Dobson, TPJ Knowles
(2020)
2020.11.14.381376
Machine learning models for predicting protein condensate formation from sequence determinants and embeddings
K Saar, A Morgunov, R Qi, W Arter, G Krainer, A Lee, T Knowles
(2020)
2020.10.26.354753
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