Sequence-Based Prediction of Fuzzy Protein Interactions

It is becoming increasingly recognised that disordered proteins may be fuzzy, in that they can exhibit a wide variety of binding modes. In addition to the well-known process of folding upon binding (disorder-to-order transition), many examples are emerging of interacting proteins that remain disordered in their bound states (disorder-to-disorder transitions). Furthermore, disordered proteins may populate ordered and disordered states to different extents depending on their partners (context-dependent binding). Here we assemble three datasets comprising disorder-to-order, context-dependent, and disorder-to-disorder transitions of 828 protein regions represented in 2157 complexes and elucidate the sequence-determinants of the different interaction modes. We found that fuzzy interactions originate from local sequence compositions that promote the sampling of a wide range of different structures. Based on this observation, we developed the FuzPred method (http://protdyn-fuzpred.org) of predicting the binding modes of disordered proteins based on their amino acid sequences, without specifying their partners. We thus illustrate how the amino acid sequences of proteins can encode a wide range of conformational changes upon binding, including transitions from disordered to ordered and from disordered to disordered states

Sequence-based prediction of protein binding mode landscapes.

Interactions between disordered proteins involve a wide range of changes in the structure and dynamics of the partners involved. These changes can be classified in terms of binding modes, which include disorder-to-order (DO) transitions, when proteins fold upon binding, as well as disorder-to-disorder (DD) transitions, when the conformational heterogeneity is maintained in the bound states. Furthermore, systematic studies of these interactions are revealing that proteins may exhibit different binding modes with different partners. Proteins that exhibit this context-dependent binding can be referred to as fuzzy proteins. Here we investigate amino acid code for fuzzy binding in terms of the entropy of the probability distribution of transitions towards decreasing order. We implement these entropy calculations into the FuzPred (http://protdyn-fuzpred.org) algorithm to predict the range of context-dependent binding modes of proteins from their amino acid sequences. As we illustrate through a variety of examples, this method identifies those binding sites that are sensitive to the cellular context or post-translational modifications, and may serve as regulatory points of cellular pathways

Interfacial water as a “hydration fingerprint” in the noncognate complex of BamHI. Biophys

ABSTRACT The molecular code of specific DNA recognition by proteins as a paradigm in molecular biology remains an unsolved puzzle primarily because of the subtle interplay between direct protein-DNA interaction and the indirect contribution from water and ions. Transformation of the nonspecific, low affinity complex to a specific, high affinity complex is accompanied by the release of interfacial water molecules. To provide insight into the conversion from the loose to the tight form, we characterized the structure and energetics of water at the protein-DNA interface of the BamHI complex with a noncognate sequence and in the specific complex. The fully hydrated models were produced with Grand Canonical Monte Carlo simulations. Proximity analysis shows that water distributions exhibit sequence dependent variations in both complexes and, in particular, in the noncognate complex they discriminate between the correct and the star site. Variations in water distributions control the number of water molecules released from a given sequence upon transformation from the loose to the tight complex as well as the local entropy contribution to the binding free energy. We propose that interfacial waters can serve as a ''hydration fingerprint'' of a given DNA sequence

Proteome-wide landscape of solubility limits in a bacterial cell

Proteins are prone to aggregate when expressed above their solubility limits. Aggregation may occur rapidly, potentially as early as proteins emerge from the ribosome, or slowly, following synthesis. However, in vivo data on aggregation rates are scarce. Here, we classified the Escherichia coli proteome into rapidly and slowly aggregating proteins using an in vivo image-based screen coupled with machine learning. We find that the majority (70%) of cytosolic proteins that become insoluble upon overexpression have relatively low rates of aggregation and are unlikely to aggregate co-translationally. Remarkably, such proteins exhibit higher folding rates compared to rapidly aggregating proteins, potentially implying that they aggregate after reaching their folded states. Furthermore, we find that a substantial fraction (similar to 35%) of the proteome remain soluble at concentrations much higher than those found naturally, indicating a large margin of safety to tolerate gene expression changes. We show that high disorder content and low surface stickiness are major determinants of high solubility and are favored in abundant bacterial proteins. Overall, our study provides a global view of aggregation rates and hence solubility limits of proteins in a bacterial cell.Peer reviewe

Observation of an α-synuclein liquid droplet state and its maturation into Lewy body-like assemblies.

Misfolded α-synuclein is a major component of Lewy bodies, which are a hallmark of Parkinson's disease (PD). A large body of evidence shows that α-synuclein can aggregate into amyloid fibrils, but the relationship between α-synuclein self-assembly and Lewy body formation remains unclear. Here, we show, both in vitro and in a Caenorhabditis elegans model of PD, that α-synuclein undergoes liquid‒liquid phase separation by forming a liquid droplet state, which converts into an amyloid-rich hydrogel with Lewy-body-like properties. This maturation process towards the amyloid state is delayed in the presence of model synaptic vesicles in vitro. Taken together, these results suggest that the formation of Lewy bodies may be linked to the arrested maturation of α-synuclein condensates in the presence of lipids and other cellular components.Wellcome Trust (065807/Z/01/Z) (203249/Z/16/Z). Also, the UK Medical Research Council (MRC) (MR/K02292X/1), Alzheimer Research UK (ARUK) (ARUK-PG013-14), Michael J Fox Foundation (16238) and from Infinitus China Ltd

Observation of an α-synuclein liquid droplet state and its maturation into Lewy body-like assemblies.

Misfolded α-synuclein is a major component of Lewy bodies, which are a hallmark of Parkinson's disease (PD). A large body of evidence shows that α-synuclein can aggregate into amyloid fibrils, but the relationship between α-synuclein self-assembly and Lewy body formation remains unclear. Here, we show, both in vitro and in a Caenorhabditis elegans model of PD, that α-synuclein undergoes liquid‒liquid phase separation by forming a liquid droplet state, which converts into an amyloid-rich hydrogel with Lewy-body-like properties. This maturation process towards the amyloid state is delayed in the presence of model synaptic vesicles in vitro. Taken together, these results suggest that the formation of Lewy bodies may be linked to the arrested maturation of α-synuclein condensates in the presence of lipids and other cellular components.Wellcome Trust (065807/Z/01/Z) (203249/Z/16/Z). Also, the UK Medical Research Council (MRC) (MR/K02292X/1), Alzheimer Research UK (ARUK) (ARUK-PG013-14), Michael J Fox Foundation (16238) and from Infinitus China Ltd

Alternatively spliced exon regulates context-dependent MEF2D higher-order assembly during myogenesis

: During muscle cell differentiation, the alternatively spliced, acidic β-domain potentiates transcription of Myocyte-specific Enhancer Factor 2 (Mef2D). Sequence analysis by the FuzDrop method indicates that the β-domain can serve as an interaction element for Mef2D higher-order assembly. In accord, we observed Mef2D mobile nuclear condensates in C2C12 cells, similar to those formed through liquid-liquid phase separation. In addition, we found Mef2D solid-like aggregates in the cytosol, the presence of which correlated with higher transcriptional activity. In parallel, we observed a progress in the early phase of myotube development, and higher MyoD and desmin expression. In accord with our predictions, the formation of aggregates was promoted by rigid β-domain variants, as well as by a disordered β-domain variant, capable of switching between liquid-like and solid-like higher-order states. Along these lines, NMR and molecular dynamics simulations corroborated that the β-domain can sample both ordered and disordered interactions leading to compact and extended conformations. These results suggest that β-domain fine-tunes Mef2D higher-order assembly to the cellular context, which provides a platform for myogenic regulatory factors and the transcriptional apparatus during the developmental process

MobiDB: Intrinsically disordered proteins in 2021

The MobiDB database (URL: https://mobidb.org/) provides predictions and annotations for intrinsically disordered proteins. Here, we report recent developments implemented in MobiDB version 4, regarding the database format, with novel types of annotations and an improved update process. The new website includes a re-designed user interface, a more effective search engine and advanced API for programmatic access. The new database schema gives more flexibility for the users, as well as simplifying the maintenance and updates. In addition, the new entry page provides more visualisation tools including customizable feature viewer and graphs of the residue contact maps. MobiDB v4 annotates the binding modes of disordered proteins, whether they undergo disorder-to-order transitions or remain disordered in the bound state. In addition, disordered regions undergoing liquid-liquid phase separation or post-translational modifications are defined. The integrated information is presented in a simplified interface, which enables faster searches and allows large customized datasets to be downloaded in TSV, Fasta or JSON formats. An alternative advanced interface allows users to drill deeper into features of interest. A new statistics page provides information at database and proteome levels. The new MobiDB version presents state-of-the-art knowledge on disordered proteins and improves data accessibility for both computational and experimental users.Fil: Piovesan, Damiano. Università di Padova; ItaliaFil: Necci, Marco. Università di Padova; ItaliaFil: Escobedo, Nahuel Abel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Monzon, Alexander Miguel. Università di Padova; ItaliaFil: Viczián, András. Università di Padova; ItaliaFil: Mičetić, Ivan. Università di Padova; ItaliaFil: Quaglia, Federica. Università di Padova; ItaliaFil: Paladin, Lisanna. Università di Padova; ItaliaFil: Ramasamy, Pathmanaban. Vrije Unviversiteit Brussel; Bélgica. University of Ghent; Bélgica. Interuniversity Institute of Bioinformatics in Brussels; BélgicaFil: Dosztányi, Zsuzsanna. Eötvös Loránd University; HungríaFil: Vranken, Wim F.. Vrije Unviversiteit Brussel; Bélgica. Interuniversity Institute of Bioinformatics in Brussels; BélgicaFil: Davey, Norman E.. The Institute Of Cancer Research; Reino UnidoFil: Parisi, Gustavo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Fuxreiter, Monika. Università di Padova; ItaliaFil: Tosatto, Silvio C. E.. Università di Padova; Itali