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Centre for Misfolding Diseases

Royal Society University Research Fellow

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Dr Pietro Sormanni is a group leader supported by a Royal Society University Research Fellowship. His research focuses on the development of innovative data-driven technologies of rational antibody design, to obtain antibodies against targets that have been challenging to access using conventional approaches, and to improve or predict biophysical properties crucial for the successful development of antibody therapeutics. In his work he has established numerous collaborations and industrial partnerships, whose outcomes are beginning to demonstrate that computational approaches can be applied alongside established procedures to streamline antibody development, and to offer time- and cost-effective novel alternatives.  

Antibodies are key tools to address questions in biomedical research, are widely employed in diagnostics, and are increasingly used as therapeutics to treat many diseases, including cancer and neurodegeneration. Existing methods of antibody discovery and optimisation rely on the laboratory screening of large numbers of variants produced by library construction or by the immune system, which can be time consuming and costly, and sometimes result in antibodies exhibiting sub-optimal properties. Conversely, computational design could drastically reduce time and costs of antibody discovery, and in principle allow for a highly controlled parallel screening of multiple biophysical properties. Moreover, rational design inherently allows targeting specific regions on the target protein (epitopes), which can be particularly daunting using available techniques but is very important for many therapeutic applications.


Prior to taking up this post, Pietro held a postdoctoral Borysiewicz Biomedical Sciences  Fellowship from the University of Cambridge, obtained a PhD in Chemistry from the University of Cambridge, and an MSc in Theoretical Physics from the University of Milan.

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We are always looking for talented and enthusiastic individuals to join the team. If you are interested, please get in touch to discuss potential opportunities.

Selected publications



Dr Sormanni discusses his research

Tour of the Sormanni lab


Sequence-Based Prediction of Ph-Dependent Protein Solubility Using Camsol
M Oeller, R Kang, R Bell, H Ausserwoger, P Sormanni, M Vendruscolo
– SSRN Electronic Journal
Neuroserpin and transthyretin are extracellular chaperones that preferentially inhibit amyloid formation.
J West, S Satapathy, DR Whiten, M Kelly, NJ Geraghty, E-J Proctor, P Sormanni, M Vendruscolo, JN Buxbaum, M Ranson, MR Wilson
– Sci Adv
Discovery of Potent Inhibitors of α-Synuclein Aggregation Using Structure-Based Iterative Learning
R Horne, E Andrzejewska, P Alam, F Brotzakis, A Srivastava, A Aubert, M Nowinska, R Gregory, R Staats, A Possenti, S Chia, P Sormanni, B Ghetti, B Caughey, T Knowles, M Vendruscolo
An open-source automated PEG precipitation assay to measure the relative solubility of proteins with low material requirement.
M Vendruscolo, M Oeller, P Sormanni
– Scientific Reports
Computational maturation of a single-domain antibody against Aβ42 aggregation
J Lin, C Figazzolo, MA Metrick, P Sormanni, M Vendruscolo
– Chemical science
Assessment of Therapeutic AntibodyDevelopability by Combinations of In Vitro and In Silico Methods
A-M Wolf Pérez, N Lorenzen, M Vendruscolo, P Sormanni
– Methods in molecular biology (Clifton, N.J.)
Critical assessment of protein intrinsic disorder prediction
M Necci, D Piovesan, CAID Predictors, DisProt Curators, SCE Tosatto
– Nature methods
Comparative Studies in the A30P and A53T α-Synuclein C. elegans Strains to Investigate the Molecular Origins of Parkinson's Disease.
M Perni, A van der Goot, R Limbocker, TJ van Ham, FA Aprile, CK Xu, P Flagmeier, K Thijssen, P Sormanni, G Fusco, SW Chen, PK Challa, JB Kirkegaard, RF Laine, KY Ma, MBD Müller, T Sinnige, JR Kumita, SIA Cohen, R Seinstra, GS Kaminski Schierle, CF Kaminski, D Barbut, A De Simone, TPJ Knowles, M Zasloff, EAA Nollen, M Vendruscolo, CM Dobson
– Front Cell Dev Biol
Fragment-based computational design of antibodies targeting structured epitopes
MA Rangel, A Bedwell, E Costanzi, R Taylor, R Russo, G Bernardes, S Ricagno, J Frydman, M Vendruscolo, P Sormanni
Rationally Designed Bicyclic Peptides Prevent the Conversion of Aβ42 Assemblies Into Fibrillar Structures.
T Ikenoue, FA Aprile, P Sormanni, M Vendruscolo
– Frontiers in Neuroscience
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Group Leader

Research Interest Group

Email address


Clare Hall