Computational methods that use protein sequence and/ or protein structure to predict protein aggregation. The table below, shows the main features of software for prediction of protein aggregation
| Last Update | Access (Web server/downloadable) | Principle | Input | Output | |||
|---|---|---|---|---|---|---|---|
| Sequence / 3D Structure | Additional parameters | ||||||
| Amyloidogenic Patten[1] | 2004 | Web Server- AMYLPRED2 | Secondary structure-relatedAmyloidogenic pattern Submissions are scanned for the existence of this pattern --[VLSCWFNQE]-[ILTYWFNE]-[FIY]- at identity level, with the use of a simple custom script. | sequence | - | Amyloidogenic regions | |
| Tango [2] [3] [4] | 2004 | Web Server-TANGO | PhenomenologicalBased on physico-chemical principles of secondary structure formation extended by the assumption that the core regions of an aggregate are fully buried. | sequence | pH/ionic strength | Overall aggregation and amyloidoidogenic regions | |
| Average Packing Density[5] | 2006 | Web Server-AMYLPRED2 | Secondary structure-relatedRelates average packing density of residues to the formation of amyloid fibrils. | sequence | - | Amyloidogenic regions | |
| Beta-strand contiguity[6] | 2007 | Web Server- AMYLPRED2 | PhenomenologicalPrediction of B-strand propensity score to locate in the amyloid fibril. | sequence | - | beta-strand formation | |
| Hexapeptide Conformational Energy /Pre-amyl[7] | 2007 | Web Server- AMYLPRED2 | Secondary structure-relatedHexapeptides of a submitted protein are threaded onto over 2500 templates of microcrystallic structure of NNQQNY, energy values below -27.00 are considered as hits. | sequence | - | Amyloidogenic regions and energy | |
| AGGRESCAN[8] | 2007 | Web Servers -AMLYPRED2 & AGGRESCAN | PhenomenologicalPrediction of 'aggregation-prone' in protein sequences, based on an aggregation propensity scale for natural amino acids derived from in vivo experiments. | sequence | - | Overall aggregation and amyloidogenic regions | |
| Salsa[9] | 2007 | Web server - AMYPdb[10] | PhenomenologicalPrediction of the aggregation propensities single or multiple sequences based on physicochemical properties. | sequence | hot spot length | Amyloidogenic regions | |
| Pafig[11] | 2009 | Web server- AMYLPRED2Download | PhenomenologicalIdentification of Hexapeptides associated to amyloid fibrillar aggregates. | sequence | - | Amyloidogenic regions | |
| Net-CSSP[12] [13] [14] [15] | 2020 | Web Server - Net-CSSPAMYLPRED2 | Secondary structure-relatedQuantification of the influence of the tertiary interation on secondary structural preference. | sequence/pdb | single/dual network-threshold | Amyloidogenic propensity regions | |
| Betascan[16] | 2009 | Web Server - BetascanDownload - Betascan | Secondary structure-relatedPredict the probability that particular portions of a protein will form amyloid. | sequence | length | Amyloidogenic regions | |
| FoldAmyloid[17] | 2010 | Web Server - FoldAmyloid | Secondary structure-relatedPrediction of amyloid regions using expected probability of hydrogen bonds formation and packing densitites of residues. | sequence | scale, threshold, averaging frame | Amyloidogenic regions | |
| Waltz[18] [19] | 2010 | Web Server - Waltz & AMYLPRED2 | Secondary structure-relatedApplication of position-specific substitution matrices (PSSM) obtained from amyloidogenic peptides. | sequence | pH, specificity, sensitivity | Amyloidogenic regions | |
| Zipper DB [20] [21] [22] [23] | 2010 | Web Server- Zipper DB | Secondary structure-relatedStructure based prediction of fribrillation propoensities, using crystal strucutrue of the fibril forming peptide NNQQNY from the sup 35 prion protein of Saccharomyces cerevisiae. | sequence | - | Amyloidogenic regions and, energy and beta-sheet conformation | |
| STITCHER[24] | 2012 | Web Server - Stitcher (currently offline) | Secondary structure-related | sequence | - | Amyloidogenic regions | |
| MetAmyl[25] [26] [27] [28] | 2013 | Web Server - MetAmyl | Consensus methodAmyloidogenic patterns, average packing density, beta-strand contiguity, pafig, Net-CSSP, STITCHER | sequence | threshold | Overall generic and amyloidogenic regions based on the consensus | |
| AmylPred2[29] | 2013 | Web Server - AMYLPRED2 | Consensus methodAmyloidogenic patterns, average packing density, beta-strand contiguity, pafig, Net-CSSP, STITCHER | sequence | - | Overall generic and amyloidogenic regions based on the consensus | |
| PASTA 2.0[30] | 2014 | Web Server - PASTA 2.0 | Secondary structure-relatedPredicts the most aggregation-prone portions and the corresponding β-strand inter-molecular pairing for multiple input sequences. | sequence | top pairings and energies, mutations and protein-protein | Amyloidogenic regions, energy, and beta-sheet orientation in aggregates | |
| FISH Amyloid[31] | 2014 | Web Server - Comprec (currently offline) | Secondary structure-related | sequence | threshold | Amyloidogenic regions | |
| GAP[32] [33] [34] | 2014 | Web Server - GAP | Secondary structure-relatedIdentification of amyloid forming peptides and amorphous peptides using a dataset of 139 amyloids and 168 amorphous peptides. | sequence | - | Overall aggregation and amyloidogenic regions | |
| APPNN[35] | 2015 | Download - CRAN | PhenomenologicalAmyloidogenicity propensity predictor based on a machine learning approach through recursive feature selection and feed-forward neural networks, taking advantage of newly published sequences with experimental, in vitro, evidence of amyloid formation. | sequence | - | Amyloidogenic regions | |
| ArchCandy[36] | 2015 | Download- BiSMM | Secondary structure-relatedBased on an assumption that protein sequences that are able to form β-arcades are amyloidogenic. | sequence | - | Amyloidogenic regions | |
| Amyload[37] | 2015 | Web Server - Comprec (currently offline) | Consensus method | sequence | - | Overall generic and amyloidogenic regions | |
| SolubiS[38] [39] | 2016 | Web Server - SolubiS | 3D structure | pdb file | chain, threshold, gatekeeper | Aggregation propensity and stability vs mutations | |
| CamSol Structurally Corrected[40] [41] | 2017 | Web Server - Chemistry of Health | 3D structure | pdb file | pH, patch radius | Exposed aggregation-prone patches and mutated variants design | |
| CamSol intrinsic[42] [43] | 2017 | Web Server- Chemistry of Health | PhenomenologicalSequence-based method of predicting protein solubility and generic aggregation propensity. | sequence | pH | Calculation of the overall intrinsic solubility score and solubility profile | |
| AmyloGram[44] | 2017 | Web Server - AmyloGram | PhenomenologicalAmyloGram predicts amyloid proteins using n-gram encoding and random forests. | sequence | - | Overall aggregation and amyloidogenic regions | |
| BetaSerpentine[45] | 2017 | Web Server - BetaSerpentine-1.0 | Sequence-relatedReconstruction of amyloid structures containing adjacent β-arches. | sequence | - | Amyloidogenic regions | |
| AggScore[46] | 2018 | AggScore is available through Schrödinger's BioLuminate Suite as of software release 2018-1. | Secondary structure-relatedMethod that uses the distribution of hydrophobic and electrostatic patches on the surface of the protein, factoring in the intensity and relative orientation of the respective surface patches into an aggregation propensity function that has been trained on a benchmark set of 31 adnectin proteins. | sequence | - | Amyloidogenic regions | |
| AggreRATE-Pred[47] | 2018 | Web Server - AggreRAE-Pred | Secondary structure-relatedPredict changes in aggregation rate upon point mutations | sequence pdb | mutations | ||
| AGGRESCAN 3D 2.0[48] [49] [50] [51] [52] | 2019 | Web Server - Aggrescan3D | 3D structure | pdb file | dynamic mode, mutations, patch radius, stability, enhance solubility | Dynamic exposed aggregation-prone patches and mutated variants design | |
| Budapest amyloid predictor[53] | 2021 | Web Server - Budapest amyloid predictor | Hexapeptide | sequence | Amyloidgenecity of hexapeptide | ||
| ANuPP[54] | 2021 | Web Server - ANuPP | Hexapeptide and SequenceIdentification amyloid-fibril forming peptides and regions in protein sequences | sequence | Amyloidogenic hexapeptides and aggregation prone regions | ||