The PASTA server for protein aggregation prediction

Trovato, Antonio; Seno, Flavio; Tosatto, Silvio C. E.

doi:10.1093/protein/gzm042

Cited by 221 publications

(261 citation statements)

References 6 publications

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“…On the basis of our previous work on designing gammabodies specific for Aβ (4), we used multiple algorithms (20)(21)(22)(23)(24) to identify potential amyloidogenic peptide segments within α-Synuclein and IAPP to guide our design of gammabodies against each polypeptide. These algorithms predict amyloidogenic peptides based on properties such as hydrophobicity, charge, and propensity to form β-sheets and/or steric zippers.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, we selected the peptide hormone IAPP that forms amyloidogenic aggregates associated with type 2 diabetes (18), and the protein α-Synuclein that forms aggregates linked to Parkinson's disease (19). We identified 10-residue amyloidogenic peptide segments in IAPP (residues 22-NFGAILSSTN-31) and α-Synuclein (residues 69-AVVTGVTAVA-78) that are predicted to mediate amyloid formation of each polypeptide by multiple algorithms (20)(21)(22)(23)(24). Grafting these peptide segments into CDR3 (along with negatively charged residues at each edge of CDR3; SI Methods) yielded single-domain (V H ) gammabodies that are well-expressed (>20 mg/L) and fail to aggregate when heated.…”

Section: Iapp and α-Synuclein Gammabodies Potently Inhibit Amyloidmentioning

confidence: 99%

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Rational design of potent domain antibody inhibitors of amyloid fibril assembly

Ladiwala

Bhattacharya

Perchiacca

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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Fig. 7. IAPP and α-Synuclein gammabodies potently inhibit amyloid formation in a sequence-specific manner. IAPP (32 μM) and α-Synuclein (residues 1-115, 50 μM) were incubated in the absence (control) and presence of gammabodies (1:10 gammabody:monomer molar ratio), and fibrillization was monitored via (A) immunoblotting and (B) AFM. In B, IAPP and α-Synuclein fibrillization was also monitored in the presence of sequence-specific (R10/99, IAPP residues 7-17; 5C2, α-Synuclein residues 61-95) and conformation-specific (A11, prefibrillar oligomers; OC, fibrillar conformers) antibodies (1:10 antibody:monomer molar ratio). In B, the AFM images are 3 × 3 μm, and the blank images are samples with heights <1 nm. The heights of the IAPP and α-Synuclein aggregates are 21 ± 3 and 25 ± 4 nm, respectively.

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Section: Discussionmentioning

confidence: 99%

Section: Iapp and α-Synuclein Gammabodies Potently Inhibit Amyloidmentioning

confidence: 99%

Rational design of potent domain antibody inhibitors of amyloid fibril assembly

Ladiwala

Bhattacharya

Perchiacca

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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“…12,22 A number of different software packages have been developed to predict cross-beta-sheet aggregation-propensities based on the sequence. [23][24][25][26][27][28] There is no single computational method that is able to estimate antibody developability and shelf-life, but a number of established methods, developed for different purposes, can be utilized to assemble important aspects of rate-limiting steps of antibody degradation pathways and provide valuable estimations for antibody developability. Computational methods pinpoint potential liabilities to distinct sequence patterns, paving the way for rational engineering toward improved developability.…”

Section: Introductionmentioning

confidence: 99%

Boosting antibody developability through rational sequence optimization

Seeliger

Schulz

Litzenburger

et al. 2015

mAbs

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(2015) Boosting antibody developability through rational sequence optimization , mAbs, 7:3, 505-515, DOI: 10.1080DOI: 10. /19420862.2015 To link to this article: https://doi.org/10. 1080/19420862.2015 The application of monoclonal antibodies as commercial therapeutics poses substantial demands on stability and properties of an antibody. Therapeutic molecules that exhibit favorable properties increase the success rate in development. However, it is not yet fully understood how the protein sequences of an antibody translates into favorable in vitro molecule properties. In this work, computational design strategies based on heuristic sequence analysis were used to systematically modify an antibody that exhibited a tendency to precipitation in vitro. The resulting series of closely related antibodies showed improved stability as assessed by biophysical methods and longterm stability experiments. As a notable observation, expression levels also improved in comparison with the wild-type candidate. The methods employed to optimize the protein sequences, as well as the biophysical data used to determine the effect on stability under conditions commonly used in the formulation of therapeutic proteins, are described. Together, the experimental and computational data led to consistent conclusions regarding the effect of the introduced mutations. Our approach exemplifies how computational methods can be used to guide antibody optimization for increased stability.

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“…In addition, softwares exist to predict the propensity of protein stretches to form amyloid aggregates. The PASTA algorithm calculates the energy gained when parallel or antiparallel β-sheets are formed between the same stretch in a protein sequence [128]. The TANGO algorithm scans protein sequences for segments that are likely to simultaneously satisfy the following three properties: (i) to adopt a β-sheet secondary structure, (ii) to be buried (hydrophobic) and (iii) not to have any net charge (to avoid electrostatic repulsion or complementary electrostatic interaction) [129].…”

Section: Modeling Protein-materials Interactionsmentioning

confidence: 99%

Protein conformational changes induced by adsorption onto material surfaces: an important issue for biomedical applications of material science

Ballet¹,

Boulangé²,

Bréchet³

et al. 2010

Bulletin of the Polish Academy of Sciences: Technical Sciences

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Abstract. Protein adsorption on solid surfaces is a widespread phenomenon of large biological and biotechnological significance. Conformational changes are likely to accompany protein adsorption, but are difficult to evidence directly. Nevertheless they have important consequences, since the partial unfolding of protein domains can expose hitherto hidden amino acids. This remodeling of the protein surface can trigger the activation of molecular complexes such as the blood coagulation cascade or the innate immune complement system. In the case of extracellular matrix, it can also change the way cells interact with the material surfaces and result in modified cell behavior. In this review, we present direct and indirect evidences that support the view that some proteins change their conformation upon adsorption. We also show that both physical and chemical methods are needed to study the extent and kinetics of protein conformational changes. In particular, AFM techniques and cryo-electron microscopy provide useful and complementary information. We then review the chemical and topological features of both proteins and material surfaces in relation with protein adsorption. Mutating key amino acids in proteins changes their stability and this is related to material-induced conformational changes, as shown for instance with insulin. In addition, combinatorial methods should provide valuable information about peptide or antibody adsorption on well-defined material surfaces. These techniques could be combined with molecular modeling methods to decipher the rules governing conformational changes associated with protein adsorption.

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The PASTA server for protein aggregation prediction

Cited by 221 publications

References 6 publications

Rational design of potent domain antibody inhibitors of amyloid fibril assembly

Rational design of potent domain antibody inhibitors of amyloid fibril assembly

Boosting antibody developability through rational sequence optimization

Protein conformational changes induced by adsorption onto material surfaces: an important issue for biomedical applications of material science

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