Computational methods that use protein sequence and/ or protein structure to predict

protein aggregation In molecular biology, protein aggregation is a phenomenon in which intrinsically-disordered or mis-folded proteins aggregate (i.e., accumulate and clump together) either intra- or extracellularly. Protein aggregates have been implicated in a wi ...

. The table below, shows the main features of software for prediction of protein aggregation

Table

{, class="wikitable" , +Table 1 ! rowspan="2" , Method ! rowspan="2" , Last Update ! rowspan="2" , Access (Web server/downloadable) ! rowspan="2" , Principle ! colspan="2" , Input ! rowspan="2" , Output , - !Sequence / 3D Structure !Additional parameters , - , Amyloidogenic Patten , 2004 , Web Server
AMYLPRED2
, Secondary structure-related

Amyloid Amyloids are aggregates of proteins characterised by a fibrillar morphology of 7–13 nm in diameter, a beta sheet (β-sheet) secondary structure (known as cross-β) and ability to be stained by particular dyes, such as Congo red. In the hu ...

ogenic pattern Submissions are scanned for the existence of this pattern {P}-{PKRHW}- LSCWFNQE LTYWFNE IY{PKRH} at identity level, with the use of a simple custom script. , sequence , - , Amyloidogenic regions , - , Tango , 2004 , Web Serve
TANGO
, Phenomenological Based 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 , 2006 , Web Serve
AMYLPRED2
, Secondary structure-related Relates average packing density of residues to the formation of amyloid fibrils. , sequence , - , Amyloidogenic regions , - , Beta-strand contiguity , 2007 , Web Server
AMYLPRED2
, Phenomenological Prediction of B-strand propensity score to locate in the amyloid fibril. , sequence , - , beta-strand formation , - , Hexapeptide Conformational Energy /Pre-amyl , 2007 , Web Server
AMYLPRED2
, Secondary structure-related Hexapeptides 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 , 2007 , Web Servers
AMLYPRED2

AGGRESCAN
, Phenomenological Prediction 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
'' , 2007
Web server
- AMYPdb , Phenomenological Prediction of the aggregation propensities single or multiple sequences based on physicochemical properties. , sequence , hot spot length , Amyloidogenic regions , - , '
Pafig
'' , 2009 , Web server
AMYLPRED2
, Phenomenological Identification of Hexapeptides associated to amyloid fibrillar aggregates. , sequence , - , Amyloidogenic regions , - , Net-CSSP , 2020 , Web Server
Net-CSSPAMYLPRED2
, Secondary structure-related Quantification of the influence of the tertiary interation on secondary structural preference. , sequence/pdb , single/dual network-threshold , Amyloidogenic propensity regions , - , Betascan , 2009 , Web Server

Download
Betascan
, Secondary structure-related Predict the probability that particular portions of a protein will form amyloid. , sequence , length , Amyloidogenic regions , - , FoldAmyloid , 2010 , Web Server
FoldAmyloid
, Secondary structure-related Prediction of amyloid regions using expected probability of hydrogen bonds formation and packing densitites of residues. , sequence , scale, threshold, averaging frame , Amyloidogenic regions , - , Waltz , 2010 , Web Server -
Waltz
&
AMYLPRED2
, Secondary structure-related Application of position-specific substitution matrices (PSSM) obtained from amyloidogenic peptides. , sequence , pH, specificity, sensitivity , Amyloidogenic regions , - , Zipper DB , 2010 , Web Server
Zipper DB
, Secondary structure-related Structure 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 , 2012 , Web Server
Stitcher
(currently offline) , Secondary structure-related , sequence , - , Amyloidogenic regions , - , MetAmyl , 2013 , Web Server
MetAmyl
, Consensus method Amyloidogenic patterns, average packing density, beta-strand contiguity, pafig, Net-CSSP, STITCHER , sequence , threshold , Overall generic and amyloidogenic regions based on the consensus , - , AmylPred2 , 2013 , Web Server
AMYLPRED2
, Consensus method Amyloidogenic patterns, average packing density, beta-strand contiguity, pafig, Net-CSSP, STITCHER , sequence , - , Overall generic and amyloidogenic regions based on the consensus , - , PASTA 2.0 , 2014 , Web Server

, Secondary structure-related Predicts 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 , 2014 , Web Server
Comprec
(currently offline) , Secondary structure-related , sequence , threshold , Amyloidogenic regions , - , GAP , 2014 , Web Server
GAP
, Secondary structure-related Identification of amyloid forming peptides and amorphous peptides using a dataset of 139 amyloids and 168 amorphous peptides. , sequence , - , Overall aggregation and amyloidogenic regions , - , APPNN , 2015 , Download
CRAN
, Phenomenological Amyloidogenicity 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 , 2015 , Download
BiSMM
, Secondary structure-related Based on an assumption that protein sequences that are able to form β-arcades are amyloidogenic. , sequence , - , Amyloidogenic regions , - , Amyload , 2015 , Web Server
Comprec
(currently offline) , Consensus method , sequence , - , Overall generic and amyloidogenic regions , - , SolubiS , 2016 , Web Server
SolubiS
, 3D structure , pdb file , chain, threshold, gatekeeper , Aggregation propensity and stability vs mutations , - , CamSol Structurally Corrected , 2017 , Web Server
Chemistry of Health
, 3D structure , pdb file , pH, patch radius , Exposed aggregation-prone patches and mutated variants design , - , CamSol intrinsic , 2017 , Web Server
Chemistry of Health
, Phenomenological Sequence-based method of predicting protein solubility and generic aggregation propensity. , sequence , pH , Calculation of the overall intrinsic solubility score and solubility profile , - , AmyloGram , 2017 , Web Server -
AmyloGram
, Phenomenological AmyloGram predicts amyloid proteins using n-gram encoding and random forests. , sequence , - , Overall aggregation and amyloidogenic regions , - , BetaSerpentine , 2017 , Web Server
BetaSerpentine-1.0
, Sequence-related Reconstruction of amyloid structures containing adjacent β-arches. , sequence , - , Amyloidogenic regions , - , AggScore , 2018 , AggScore is available throug
Schrödinger's BioLuminate Suite as of software release 2018-1.
, Secondary structure-related Method 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 , 2018 , Web Server
AggreRAE-Pred
, Secondary structure-related Predict changes in aggregation rate upon point mutations , sequence pdb , mutations , , - , AGGRESCAN 3D 2.0 , 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 , 2021 , Web Server
Budapest amyloid predictor
, Hexapeptide , sequence , , Amyloidgenecity of hexapeptide , - , ANuPP{{Cite journal, last1=Prabakaran, first1=R., last2=Rawat, first2=Puneet, last3=Kumar, first3=Sandeep, last4=Michael Gromiha, first4=M., date=May 2021, title=ANuPP: A Versatile Tool to Predict Aggregation Nucleating Regions in Peptides and Proteins, url=https://linkinghub.elsevier.com/retrieve/pii/S0022283620306252, journal=Journal of Molecular Biology, language=en, volume=433, issue=11, pages=166707, doi=10.1016/j.jmb.2020.11.006, pmid=33972019, s2cid=228867153 , 2021 , Web Server
ANuPP
, Hexapeptide and Sequence Identification amyloid-fibril forming peptides and regions in protein sequences , sequence , , Amyloidogenic hexapeptides and aggregation prone regions

References

Protein structure Structural bioinformatics software Proteomics Neurodegenerative disorders

Table

See also

References