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Department of Chemistry

 

Dr Pietro Sormanni is a Borysiewicz Fellow at the University of Cambridge. 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. At the Centre for Misfolding Diseases, he is applying these technologies to generate novel opportunities for research, diagnostics, and eventually treatment of neurodegenerative disorders, such as Alzheimer's or Parkinson's disease. 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.  

Prior to pursuing his postdoctoral research, Pietro obtained a PhD in Chemistry from the University of Cambridge, and an MSc in Theoretical Physics from the University of Milan.

Publications

Different soluble aggregates of Aβ42 can give rise to cellular toxicity through different mechanisms.
S De, DC Wirthensohn, P Flagmeier, C Hughes, FA Aprile, FS Ruggeri, DR Whiten, D Emin, Z Xia, JA Varela, P Sormanni, F Kundel, TPJ Knowles, CM Dobson, C Bryant, M Vendruscolo, D Klenerman
– Nature Communications
(2019)
10,
1541
Biochemical and biophysical comparison of human and mouse beta‐2 microglobulin reveals the molecular determinants of low amyloid propensity
A Achour, L Broggini, X Han, R Sun, C Santambrogio, J Buratto, C Visentin, A Barbiroli, CMG De Luca, P Sormanni, F Moda, A De Simone, T Sandalova, R Grandori, C Camilloni, S Ricagno
– FEBS Journal
(2019)
febs.15046
A chemical kinetic basis for measuring translation initiation and elongation rates from ribosome profiling data
AK Sharma, P Sormanni, N Ahmed, P Ciryam, UA Friedrich, G Kramer, EP O'Brien
– PLOS Computational Biology
(2019)
15,
e1007070
Identifying A- and P-site locations on ribosome-protected mRNA fragments using Integer Programming.
N Ahmed, P Sormanni, P Ciryam, M Vendruscolo, CM Dobson, EP O'Brien
– Scientific reports
(2019)
9,
6256
A method of predicting the in vitro fibril formation propensity of A beta 40 mutants based on their inclusion body levels in E-coli
K Sanagavarapu, E Nüske, I Nasir, G Meisl, JN Immink, P Sormanni, M Vendruscolo, TPJ Knowles, A Malmendal, C Cabaleiro-Lago, S Linse
– Scientific reports
(2019)
9,
3680
Protein Solubility Predictions Using the CamSol Method in the Study of Protein Homeostasis.
P Sormanni, M Vendruscolo
– Cold Spring Harb Perspect Biol
(2019)
a033845
In vitro and in silico assessment of the developability of a designed monoclonal antibody library.
A-M Wolf Pérez, P Sormanni, JS Andersen, LI Sakhnini, I Rodriguez-Leon, JR Bjelke, AJ Gajhede, L De Maria, DE Otzen, M Vendruscolo, N Lorenzen
– mAbs
(2019)
11,
388
Attentive Cross-Modal Paratope Prediction
A Deac, P VeliČković, P Sormanni
– J Comput Biol
(2019)
26,
536
Developability Assessment of Engineered Monoclonal Antibody Variants with a Complex Self-Association Behavior Using Complementary Analytical and in Silico Tools.
L Shan, N Mody, P Sormani, KL Rosenthal, MM Damschroder, R Esfandiary
– Mol Pharm
(2018)
15,
5697
Third generation antibody discovery methods: in silico rational design.
P Sormanni, FA Aprile, M Vendruscolo
– Chem Soc Rev
(2018)
47,
9137
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Research Group

Telephone number

01223 763845 (shared)
01223 763842

Email address

ps589@cam.ac.uk

College

Clare Hall