Prediction of aggregation rate and aggregation-prone segments in polypeptide sequences (original) (raw)
Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins
Nature Biotechnology, 2004
We have developed a statistical mechanics algorithm, TANGO, to predict protein aggregation. TANGO is based on the physico-chemical principles of b-sheet formation, extended by the assumption that the core regions of an aggregate are fully buried. Our algorithm accurately predicts the aggregation of a data set of 179 peptides compiled from the literature as well as of a new set of 71 peptides derived from human diseaserelated proteins, including prion protein, lysozyme and b2-microglobulin. TANGO also correctly predicts pathogenic as well as protective mutations of the Alzheimer b-peptide, human lysozyme and transthyretin, and discriminates between b-sheet propensity and aggregation. Our results confirm the model of intermolecular b-sheet formation as a widespread underlying mechanism of protein aggregation. Furthermore, the algorithm opens the door to a fully automated, sequence-based design strategy to improve the aggregation properties of proteins of scientific or industrial interest.
Prediction of Aggregation of Biologically-Active Peptides with the UNRES Coarse-Grained Model
Biomolecules
The UNited RESidue (UNRES) model of polypeptide chains was applied to study the association of 20 peptides with sizes ranging from 6 to 32 amino-acid residues. Twelve of those were potentially aggregating hexa- or heptapeptides excised from larger proteins, while the remaining eight contained potentially aggregating sequences, functionalized by attaching larger ends rich in charged residues. For 13 peptides, the experimental data of aggregation were used. The remaining seven were synthesized, and their properties were measured in this work. Multiplexed replica-exchange simulations of eight-chain systems were conducted at 12 temperatures from 260 to 370 K at concentrations from 0.421 to 5.78 mM, corresponding to the experimental conditions. The temperature profiles of the fractions of monomers and octamers showed a clear transition corresponding to aggregate dissociation. Low simulated transition temperatures were obtained for the peptides, which did not precipitate after incubation,...
Aggregation kinetics of short peptides: All-atom and coarse-grained molecular dynamics study
Biophysical Chemistry, 2019
Peptides can aggregate into ordered structures with different morphologies. The aggregation mechanism and evolving structures are the subject of intense research. In this paper we have used molecular dynamics to examine the sequence-dependence of aggregation kinetics for three short peptides: octaalanine (Ala8), octaasparagine (Asn8), and the heptapeptide GNNQQNY (abbreviated as GNN). First, we compared the aggregation of 20 randomly distributed peptides using the coarse-grained MARTINI force field and the atomistic OPLS-AA force field. We found that the MARTINI and OPLS-AA aggregation kinetics are similar for Ala8, Asn8, and GNN. Second, we used the MARTINI force field to study the early stages of aggregation kinetics for a larger system with 72 peptides. In the initial stage of aggregation small clusters grow by monomer addition. In the second stage, when the free monomers are depleted, the dominant cluster growth path is cluster-cluster coalescence. We quantified the aggregation kinetics in terms of rate equations. Our study shows that the initial aggregation kinetics are similar for Ala8, Asn8, and GNN but the molecular details can be different, especially for MARTINI Ala8. We hypothesize that peptide aggregation proceed in two steps. In the first step amorphous aggregates are formed, and then, in the second step, they reorganize into ordered structures. We conclude that sequence-specific differences show up in the second step of aggregation.
A Kinetic Approach to the Sequence–Aggregation Relationship in Disease-Related Protein Assembly
The Journal of Physical Chemistry B, 2014
It is generally accepted that oligomers of aggregating proteins play an important role in the onset of neurodegenerative diseases. While in silico aggregation studies of full length amyloidogenic proteins are computationally expensive, the assembly of short protein fragments derived from these proteins with similar aggregating properties has been extensively studied. In the present work molecular dynamics simulations are performed to follow peptide aggregation on the microsecond time scale. By defining aggregation states we identify transition networks, disconnectivity graphs and first passage time distributions to describe the kinetics of the assembly process. This approach unravels differences in the aggregation into hexamers of two peptides with different primary structures. The first is GNNQQNY, a hydrophilic fragment from the prion protein Sup35, and the second is KLVFFAE, a fragment from amyloid β-protein, with a hydrophobic core delimited by two charged amino acids. The assembly of GNNQQNY suggests a mechanism of monomer addition, with a bias towards parallel peptide pairs and a gradual increase in the amount of β-strand content. For KLVFFAE a mechanism involving dimers rather than monomers is revealed, involving a generally higher β-strand content and a transition towards a larger number of antiparallel peptide pairs during the rearrangement of the hexamer. The differences observed for the aggregation of the two peptides suggests the existence of a sequenceaggregation relationship.
Can Peptide Folding Simulations Provide Predictive Information for Aggregation Propensity?
The Journal of Physical Chemistry B, 2010
Nonnative peptide aggregation underlies many diseases and is a major problem in the development of peptidebased therapeutics. Efforts in the past decade have revealed remarkable correlations between aggregation rates or propensities and very simple sequence metrics like hydrophobicity and charge. Here, we investigate the extent to which a molecular picture of peptide folding bears out similar relationships. Using replica exchange molecular dynamics folding simulations, we compute equilibrium conformational ensembles of 142 hexaand decapeptide systems, of which about half readily form amyloid fibrils and half do not. The simulations are used to compute a variety of ensemble-based properties, and we investigate the extent to which these metrics provide molecular clues about fibril formation. To assess whether multiple metrics together are useful in understanding aggregation, we also develop a number of logistic regression models, some of which predict fibril formers with 70-80% accuracy and identify aggregation-prone regions in larger proteins. Importantly, these models quantify the importance of different molecular properties in aggregation driving forces; notably, they suggest that hydrophobic interactions play a dominant role.
Physical Chemistry Chemical Physics, 2012
The initiation and progression of Alzheimer's disease is coupled to the oligo-and polymerization of amyloid peptides in the brain. Amyloid like aggregates of protein domains were found practically independent of their primary sequences. Thus, the driving force of the transformation from the original to a disordered amyloid fold is expected to lie in the protein backbone common to all proteins. In order to investigate the thermodynamics of oligomerization, full geometry optimizations and frequency calculations were performed both on parallel and antiparallel b-pleated sheet model structures of [HCO-(Ala) 1-6-NH 2 ] 2 and (For-Ala 1-2-NH 2) 1-6 peptides, both at the B3LYP and M05-2X/6-311++G(d,p)//M05-2X/6-31G(d) levels of theory, both in vacuum and in water. Our results show that relative entropy and enthalpy both show a hyperbolic decrease with increasing residue number and with increasing number of strands as well. Thus, di-and oligomerization are always thermodynamically favored. Antiparallel arrangements were found to have greater stability than parallel arrangements of the polypeptide backbones. During our study the relative changes in thermodynamic functions are found to be constant for long enough peptides, indicating that stability and entropy terms are predictable. All thermodynamic functions of antiparallel di-and oligomers show a staggered nature along the increasing residue number. By identifying and analyzing the 6 newly emerging dimer vibrational modes of the 10-and 14-membered building units, the staggered nature of the entropy function can be rationalized. Thus, the vanishing rotational and translational modes with respect to single strands are converted into entropy terms ''holding tight'' the dimers and oligomers formed, rationalizing the intrinsic adherence of natural polypeptide backbones to aggregate.
AGGRESCAN: a server for the prediction and evaluation of "hot spots" of aggregation in polypeptides
BMC Bioinformatics, 2007
Background: Protein aggregation correlates with the development of several debilitating human disorders of growing incidence, such as Alzheimer's and Parkinson's diseases. On the biotechnological side, protein production is often hampered by the accumulation of recombinant proteins into aggregates. Thus, the development of methods to anticipate the aggregation properties of polypeptides is receiving increasing attention. AGGRESCAN is a web-based software for the prediction of aggregation-prone segments in protein sequences, the analysis of the effect of mutations on protein aggregation propensities and the comparison of the aggregation properties of different proteins or protein sets.
Sketching protein aggregation with a physics-based toy model
The Journal of Chemical Physics, 2013
We explore the applicability of a single-bead coarse-grained molecular model to describe the competition between protein folding and aggregation. We have designed very simple and regular sequences, based on our previous studies on peptide aggregation, that successfully fold into the three main protein structural families (all-α, all-β, and α + β). Thanks to equilibrium computer simulations, we evaluate how temperature and concentration promote aggregation. Aggregates have been obtained for all the amino acid sequences considered, showing that this process is common to all proteins, as previously stated. However, each structural family presents particular characteristics that can be related to its specific balance between hydrogen bond and hydrophobic interactions. The model is very simple and has limitations, yet it is able to reproduce both the cooperative folding of isolated polypeptide chains with regular sequences and the formation of different types of aggregates at high concentrations.
Peptide Aggregation in Finite Systems
Biophysical Journal, 2008
Universal features of the peptide aggregation process suggest a common mechanism, with a first-order phase transition in aqueous solutions of the peptides being the driving force. Small system sizes strongly affect the stability of the minor phase in the two-phase region. We show manifestations of this effect in aqueous solutions of fragments of the islet amyloid polypeptide, using computer simulation methods and invoking various approaches in characterizing clustering and aggregate formation. These systems with peptide concentrations deeply inside the immiscibility region show two distinct stable states, which interchange with time: one state contains a peptide aggregate; and the other state has an aggregate that is noticeably dissolved. The first state is relevant for macroscopic systems, whereas the second one is artificial. At a fixed concentration, the occurrence probability of the aggregate state vanishes upon decreasing the system size, thus indicating the necessity to apply a finite sizescaling for meaningful studies of peptide aggregation by simulations. The effect observed may be one of the factors responsible for the difference between intracellular and extracellular aggregation and fibrillization of polypeptides. The finite size of biological cells or their compartments may be playing a decisive role in hampering intracellular aggregation of highly insoluble amyloidogenic proteins, whereas aggregation is unavoidable in the extracellular space at the same peptide concentration.