EDUCATION

Degrees

2015. Med. Habil. University of Debrecen, Hungary

2013. D.Sc. biology Hungarian Academy of Sciences

1996. Ph.D. chemistry Eötvös Loránd University, Budapest, Hungary

1993. MSc. chemistry Eötvös Loránd University, Budapest, Hungary

Postdoctoral training

1998- 2000. Mount Sinai School of Medicine, New York, NY,USA

1997-1998. Rutgers University, New Brunswick, NJ, USA

1996-1997. University of Southern California, Los Angeles, CA, USA

POSITIONS

2020 - Professor
University of Padova, Italy

2016 - 2020 Professor
University of Debrecen, Hungary

2012 - 2020 Group leader (PI)
MTA-DE Laboratory of Protein Dynamics

2012 - 2016 Associate Professor
University of Debrecen, Hungary

2011 - 2011 EMBO fellow
University of Cambridge

Laboratory of Molecular Biology, MRC, Cambridge, UK

2010 - 2011 Visiting scientist
Weizmann Institute of Science, Rehovot, Israel

2000 - 2010 Senior scientist
Institute of Enzymology, Budapest, Hungary

I. Fuzzy Protein Interactions and Complexes

The classical model of biomolecular recognition is based on well-defined contacts between structured partners. In accord, intrinsically disordered proteins were considered to fold upon binding their specific partners. I pioneered in developing the fuzzy protein interactions paradigm (Fuxreiter, 2018a; Tompa and Fuxreiter, 2008), where the interaction elements either fold into alternative conformations or remain largely disordered, exhibiting a fast exchange of conformations in the complexed state (Sharma et al., 2015; Miskei et al., 2017a; Fuxreiter, 2018b). In fuzzy complexes, conformational and interaction heterogeneity is required to exert or regulate function (Fuxreiter et al., 2008; Fuxreiter et al., 2011). This concept has transformed our views how we think about biomolecular recognition and has opened new perspectives in structural biology.

I coined the term 'fuzziness' (Fuxreiter, 2012), indicating that dynamic conformational ensembles of proteins can be described by mathematical fuzzy sets (Fuxreiter, 2018c). I elaborated the molecular mechanisms of fuzzy interactions ( Fuxreiter et al., 2011; Fuxreiter, 2012), which can increase local concentration, exert transient interactions, facilitate allostery, or promote intramolecular autoinhibition to influence adjacent structured binding elements (Sharma et al., 2015; Miskei et al., 2017a; Fuxreiter, 2018b). With Peter Tompa, we proposed stochastic structure-function models for fuzzy complexes (Fuxreiter and Tompa, 2012a).

I demonstrated the importance of fuzzy interactions in a variety of biological problems ranging from specific gene-expression (Fuxreiter et al., 2011; Fuxreiter et al., 2008), tissue-specific alternative splicing (Buljan et al., 2013; Buljan et al., 2012), transcription-factor co-evolution (Nnamani et al., 2016), virus-host interactions (Duro et al., 2015; Troilo et al., 2018), context-dependence of protein functions (Miskei et al., 2017b), regulation of protein turnover (Sharma et al., 2019; van der Lee et al., 2014a), organisation of higher-order structures (Wu and Fuxreiter, 2016) and pathological conversion of biomolecular condensates (Tuu-Szabo et al., 2019; Tuu-Szabo et al., 2018). My lecture on Fuzzy Protein Theory links conformational heterogeneity to cellular function and has been accredited for higher medical education in the US (https://hstalks.com/t/3475/fuzzy-protein-theory-for-disordered-proteins/?biosci).

II. Binding Motifs and Partner Recognition Mechanisms by Intrinsically Disordered Proteins

Diverse biological functions of intrinsically disordered (ID) protein regions are realized via molecular recognition. How specific partner selection could be achieved in the absence of a well-folded structure? Pioneering in the field, I have elucidated two types of binding elements for biomolecular recognition of ID regions and elaborated the corresponding molecular mechanisms. Templated folding of ID regions can be driven by 'preformed' elements, which exhibit binding competent secondary structure conformations in the free form (Fuxreiter et al., 2004). The presence of these even transient binding motifs can reduce the entropic penalty, which is associated with the interaction. In contrast to the common belief that ID regions are random, I have demonstrated that their intrinsic conformational preferences overlap between unbound and complex states. Binding elements may sample different secondary structures, which drives their specific binding to different partners (Fuxreiter, 2018b; Sormanni et al., 2017). The preformed element concept has served as a basis to identify ID binding motifs from sequence (Pancsa and Fuxreiter, 2012), which are often termed as 'molecular recognition features' (MoRFs).

I have also demonstrated that ID protein regions can interact via linear peptide motifs (Fuxreiter et al., 2007). Linear motifs (LMs) are short, low-complexity sequences, which were observed specific protein-protein interactions. I have demonstrated that intrinsic disorder imparts plasticity on a few specificity-determining residues to drive their binding to versatile partners (Fuxreiter et al., 2007). I have also shown that linear motifs can serve as binding elements for ID regions, especially in the absence of distinct conformational preferences. This proposal was exploited in prediction of linear motifs and understanding their roles as cellular regulatory switches. We have also related the linear-motif and domain based interactions of ID proteins (Tompa et al., 2009).

III. Molecular and Sequence Determinants of Higher-Order Protein Structures and Dynamics, including Liquid-Liquid Phase Separation

Higher-order complexes include amyloids and prions, various kinds of signaling complexes generically denoted as signalosomes (Fuxreiter et al., 2008; Fuxreiter et al., 2014), and nuclear and cytoplasmic granules, which have recently emerged across the wide spectrum of the biological landscape (Boeynaems et al., 2018). These supramolecular assemblies have collectively transformed the classical concepts on cellular organization and signal transduction. Higher-order complexes differ from most traditional macromolecular complexes because their component proteins often polymerize or crosslink, leading to a variable stoichiometry and heterogeneous conformations. With Hao Wu (Harvard University) we aimed at integrated understanding of the structural and dynamic continuum of higher-order assemblies, and elucidate the underlying, common biophysical principles (Wu and Fuxreiter, 2016). We have provided a universal model to explain the dynamics of the different kinds of higher-order organisations related to their biological roles. We have further demonstrated that fuzzy protein interactions are critical for regulated formation and activity of higher-order structures (Wu and Fuxreiter, 2016). We have described how such regulatory mechanisms are influenced under pathological conditions. The proposed principles have been exploited to explain the protein interaction mechanisms of phase separation (Boeynaems et al., 2018) and generate abstract mathematical models for fibril formation (Boeynaems et al., 2018; Tuu-Szabo et al., 2019; Tuu-Szabo et al., 2018). In collaboration with Prof. Michele Vendruscolo (University of Cambridge) we have recently developed a sequence-based prediction method for liquid-liquid phase separation (Hardenberg et al., 2020)

References
Click here to download the file references.pdf

P. Tompa and M Fuxreiter (2008) Fuzzy complexes: polymorphism and structural disorder in protein–protein interactions. Trends in Biochem. Sci 33, 2-8

This is the first paper to demonstrate that conformational heterogeneity/disorder can be maintained in protein complexes and be required for function. Here we define the term 'fuzzy complexes''.

Boeynaems S, Alberti S, Fawzi NL, Mittag T, Polymenidou M, Rousseau F, Schymkowitz J, Shorter J, Wolozin B, Van Den Bosch L, Tompa P, Fuxreiter M. (2018) Protein phase separation: a new phase in cell biology. Trends Cell Biol. 28, 420-435. (cited: 286)

This paper provides insights into the key problems and questions of protein liquid-liquid phase separation. It shows how the interplay between intrinsically disordered regions, linear binding motifs and structured domains contributes to formation and regulated activity of biomolecular condensates.

Wu, H, Fuxreiter M (2016) The Structure and Dynamics of Higher-Order Assemblies: Amyloids, Signalosomes, and Granules. Cell 165, 1055-1066.

This is the first paper to provide a uniform biophysical model for all types of higher order assemblies, and demonstrates that fuzziness in protein interaction is a key element in higher-order organisation of proteins. We analyse the three factors, which determine the material state and show how decreasing conformational heterogeneity leads to fibrillisation.

M. Fuxreiter, I. Simon, P. Friedrich and P. Tompa (2004) Preformed structural elements feature in partner recognition by intrinsically unstructured proteins. J. Mol. Biol. 338, 1015-1026.

This is the first paper to propose a molecular mechanism for specific partner recognition of intrinsically disordered proteins. It emphasizes the role of transient secondary structures in binding.

M. Fuxreiter, P. Tompa, I. Simon (2007) Local structural disorder imparts plasticity on linear motifs. Bioinformatics 23, 950-956.

This is the first paper to propose that linear peptide motifs serve to mediate interactions of intrinsically disordered regions.

2017. Publication award of the Faculty of Medicine (University of Debrecen)

2014. Woman scientist award (University of Debrecen)

2014. Award for computational biology (regional)

2012. Momentum award (Hungarian Academy of Sciences)

2009. L’Oreal-Unesco ”Women for science” award

2009. Bolyai gold medal (Hungarian Academy of Sciences)

2007. Pro Scientia laurate (supervisor)

2004. New England Biolabs Award

2003. Young scientist award (Hungarian Academy of Sciences)

1998. Bio-Science award

1995. Young scientist award (Hungarian Biochemical Society)

1993. Pro Scientia lauretae

1993. Nívó award (Hungarian Chemical Society)

Biophysical Journal (Biophysical Society)

Journal of Molecular Biology

NIH, ERC, ANR, NSF, HFSP, EMBO, DFG, MRC, US-Israel BSF, VUB (Belgium), Ontario Research Awards (Canada), Singapore Ministry of Education, DFG (Germany), FWF (Austria)

Vrije Universiteit Brussel; Universitat Barcelona; Hebrew University; University of Toronto; University of Southern Florida; Institute for Research in Biomolecular Medicine, Barcelona

2017-2021. New perspectives in pharmaceutical research: peptide-protein interactions in regulating higher-order protein assemblies (FP7, PI)

2017-2022. Dynamic protein interactions: from higher-order organisations to phenotypes. (HAS, PI)

2015-2018. Non-globular proteins in molecular physiopathology. (COST, Consortium member)

2012-2017. Towards therapeutic applications of intrinsically disordered proteins. (HAS, PI)

2013-2016 The cellular, pathobiological and pathobiochemical roles of the multifunctional human transglutaminase 2. (NSF, participant)

2012-2015 Fuzziness in viral protein complexes. (NSF, PI)

2013-2014 Supercomputer system development (NRI, PI)

2011. Regulation of intrinsically disordered proteins via their complexes. (EMBO, PI)

2010-2011. The evolvability of protein disorder: an integrated computational-experimental approach. (FP7, PI)

2008-2011. Modelling and prediction of active states of proteins. (NSF, participant)

2005-2009. DNA enzymes. (FP6, Consortium member)

2004-2007. Molecular interpretation of specific DNA recognition. (NSF, PI)

2000-2003. Mechanism and specificity of restriction endonucleases. (NSF, PI)