N-terminal Prion Protein Peptides (PrP(120-144)) Form Parallel In-register β-Sheets via Multiple Nucleation-dependent Pathways

Design of parallel 𝛽-sheet nanofibrils using Monte Carlo search, coarse-grained simulations, and experimental testing

Peptide self-assembly into amyloid fibrils provides numerous applications in drug delivery and biomedical engineering applications. We augment our previously-established computational screening technique along with experimental biophysical characterization to discover 7-mer peptides that self-assemble into "parallel β-sheets", that is, β-sheets with N-terminus-to-C-terminus 𝛽-strand vectors oriented in parallel. To accomplish the desired β-strand organization, we applied the PepAD amino acid sequence design software to the Class-1 cross-β spine defined by Sawaya et al. This molecular configuration includes two layers of parallel β-sheets stacked such that N-terminus-to-C-terminus vectors are oriented antiparallel for molecules on adjacent β-sheets. The first cohort of PepAD identified peptides were examined for their fibrillation behavior in DMD/PRIME20 simulations, and the top performing sequence was selected as a prototype for a subsequent round of sequence refinement. The two rounds of design resulted in a library of eight 7-mer peptides. In DMD/PRIME20 simulations, five of these peptides spontaneously formed fibril-like structures with a predominantly parallel 𝛽-sheet arrangement, two formed fibril-like structure with <50% in parallel 𝛽-sheet arrangement and one remained a random coil. Among the eight candidate peptides produced by PepAD and DMD/PRIME20, five were synthesized and purified. All five assembled into amyloid fibrils composed of parallel β-sheets based on Fourier transform infrared spectroscopy, circular dichroism, electron microscopy, and thioflavin-T fluorescence spectroscopy measurements.

Sequence patterns and signatures: Computational and experimental discovery of amyloid-forming peptides

Screening amino acid sequence space via experiments to discover peptides that self-assemble into amyloid fibrils is challenging. We have developed a computational peptide assembly design (PepAD) algorithm that enables the discovery of amyloid-forming peptides. Discontinuous molecular dynamics (DMD) simulation with the PRIME20 force field combined with the FoldAmyloid tool is used to examine the fibrilization kinetics of PepAD-generated peptides. PepAD screening of ∼10,000 7-mer peptides resulted in twelve top-scoring peptides with two distinct hydration properties. Our studies revealed that eight of the twelve in silico discovered peptides spontaneously form amyloid fibrils in the DMD simulations and that all eight have at least five residues that the FoldAmyloid tool classifies as being aggregation-prone. Based on these observations, we re-examined the PepAD-generated peptides in the sequence pool returned by PepAD and extracted five sequence patterns as well as associated sequence signatures for the 7-mer amyloid-forming peptides. Experimental results from Fourier transform infrared spectroscopy (FTIR), thioflavin T (ThT) fluorescence, circular dichroism (CD), and transmission electron microscopy (TEM) indicate that all the peptides predicted to assemble in silico assemble into antiparallel β-sheet nanofibers in a concentration-dependent manner. This is the first attempt to use a computational approach to search for amyloid-forming peptides based on customized settings. Our efforts facilitate the identification of β-sheet-based self-assembling peptides, and contribute insights towards answering a fundamental scientific question: "What does it take, sequence-wise, for a peptide to self-assemble?".

Graph Clustering Analyses of Discontinuous Molecular Dynamics Simulations: Study of Lysozyme Adsorption on a Graphene Surface

Understanding the interfacial behaviors of biomolecules is crucial to applications in biomaterials and nanoparticle-based biosensing technologies. In this work, we utilized autoencoder-based graph clustering to analyze discontinuous molecular dynamics (DMD) simulations of lysozyme adsorption on a graphene surface. Our high-throughput DMD simulations integrated with a Go̅-like protein-surface interaction model makes it possible to explore protein adsorption at a large temporal scale with sufficient accuracy. The graph autoencoder extracts a low-dimensional feature vector from a contact map. The sequence of the extracted feature vectors is then clustered, and thus the evolution of the protein molecule structure in the absorption process is segmented into stages. Our study demonstrated that the residue-surface hydrophobic interactions and the π-π stacking interactions play key roles in the five-stage adsorption. Upon adsorption, the tertiary structure of lysozyme collapsed, and the secondary structure was also affected. The folding stages obtained by autoencoder-based graph clustering were consistent with detailed analyses of the protein structure. The combination of machine learning analysis and efficient DMD simulations developed in this work could be an important tool to study biomolecules' interfacial behaviors.

Engineering β-Sheet Peptide Coassemblies for Biomaterial Applications

Peptide coassembly, wherein at least two different peptides interact to form multicomponent nanostructures, is an attractive approach for generating functional biomaterials. Current efforts seek to design pairs of peptides, A and B, that form nanostructures (e.g., β-sheets with ABABA-type β-strand patterning) while resisting self-assembly (e.g., AAAAA-type or BBBBB-type β-sheets). To confer coassembly behavior, most existing designs have been based on highly charged variants of known self-assembling peptides; like-charge repulsion limits self-assembly while opposite-charge attraction promotes coassembly. Recent analyses using solid-state NMR and coarse-grained simulations reveal that preconceived notions of structure and molecular organization are not always correct. This perspective highlights recent advances and key challenges to understanding and controlling peptide coassembly.

CATCH Peptides Coassemble into Structurally Heterogeneous β-Sheet Nanofibers with Little Preference to β-Strand Alignment

Coassembling peptides offer an additional degree of freedom in the design of nanostructured biomaterials when compared to analogous self-assembling peptides. Yet, our understanding of how amino acid sequences encodes coassembled nanofiber structure is limited. Prior work on a charge-complementary pair, CATCH+ and CATCH- peptides, detected like-peptide nearest neighbors (CATCH+:CATCH+ and CATCH-:CATCH-) within coassembled β-sheet nanofibers; these self-associated peptide pairs marked a departure from an "ideal" coassembled structure. In this work, we employ solid-state NMR, isotope-edited FTIR, and coarse-grained molecular dynamics simulations to evaluate the alignment of β-strands within CATCH peptide nanofibers. Both experimental and computational results suggest that CATCH molecules coassemble into structurally heterogeneous nanofibers, which is consistent with our observations in another coassembling system, the King-Webb peptides. Within β-sheet nanofibers, β-strands were found to have nearest neighbors aligned in-register parallel, in-register antiparallel, and out-of-register. In comparison to the King-Webb peptides, CATCH nanofibers exhibit a greater degree of structural heterogeneity. By comparing the amino acid sequences of CATCH and King-Webb peptides, we can begin to unravel sequence-to-structure relationships, which may encode more precise coassembled β-sheet nanostructures.

Structural insights into peptide self-assembly using photo-induced crosslinking experiments and discontinuous molecular dynamics

Determining the structure of the (oligomeric) intermediates that form during the self-assembly of amyloidogenic peptides is challenging because of their heterogeneous and dynamic nature. Thus, there is need for methodology to analyze the underlying molecular structure of these transient species. In this work, a combination of fluorescence quenching, photo-induced crosslinking (PIC) and molecular dynamics simulation was used to study the assembly of a synthetic amyloid-forming peptide, Aβ16-22. A PIC amino acid containing a trifluormethyldiazirine (TFMD) group-Fmoc(TFMD)Phe-was incorporated into the sequence (Aβ*16-22). Electrospray ionization ion-mobility spectrometry mass-spectrometry (ESI-IMS-MS) analysis of the PIC products confirmed that Aβ*16-22 forms assemblies with the monomers arranged as anti-parallel, in-register β-strands at all time points during the aggregation assay. The assembly process was also monitored separately using fluorescence quenching to profile the fibril assembly reaction. The molecular picture resulting from discontinuous molecule dynamics simulations showed that Aβ16-22 assembles through a single-step nucleation into a β-sheet fibril in agreement with these experimental observations. This study provides detailed structural insights into the Aβ16-22 self-assembly processes, paving the way to explore the self-assembly mechanism of larger, more complex peptides, including those whose aggregation is responsible for human disease.

Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis

Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.

Discontinuous Molecular Dynamics Simulations of Biomolecule Interfacial Behavior: Study of Ovispirin-1 Adsorption on a Graphene Surface

Fundamental understanding of biomolecular interfacial behavior, such as protein adsorption at the microscopic scale, is critical to broad applications in biomaterials, nanomedicine, and nanoparticle-based biosensing techniques. The goal of achieving both computational efficiency and accuracy presents a major challenge for simulation studies at both atomistic and molecular scales. In this work, we developed a unique, accurate, high-throughput simulation method which, by integrating discontinuous molecular dynamics (DMD) simulations with the Go-like protein-surface interaction model, not only solves the dynamics efficiently, but also describes precisely the protein intramolecular and intermolecular interactions at the atomistic scale and the protein-surface interactions at the coarse-grained scale. Using our simulation method and in-house developed software, we performed a systematic study of α-helical ovispirin-1 peptide adsorption on a graphene surface, and our study focused on the effect of surface hydrophobic interactions and π-π stacking on protein adsorption. Our DMD simulations were consistent with full-atom molecular dynamics simulations and showed that a single ovispirin-1 peptide lay down on the flat graphene surface with randomized secondary structure due to strong protein-surface interactions. Peptide aggregates were formed with an internal hydrophobic core driven by strong interactions of hydrophobic residues in the bulk environment. However, upon adsorption, the hydrophobic graphene surface can break the hydrophobic core by denaturing individual peptide structures, leading to disassembling the aggregate structure and further randomizing the ovispirin-1 peptide's secondary structures.

Amyloid-Like Peptide Aggregates

Self-assembly of proteins and peptides into the amyloid fold is a widespread phenomenon in the natural world. The structural hallmark of self-assembly into amyloid fibrillar assemblies is the cross-beta motif, which conveys distinct morphological and mechanical properties. The amyloid fibril formation has contrasting results depending on the organism, in the sense that it can bestow an organism with the advantages of mechanical strength and improved functionality or, on the contrary, could give rise to pathological states. In this chapter we review the existing information on amyloid-like peptide aggregates, which could either be derived from protein sequences, but also could be rationally or de novo designed in order to self-assemble into amyloid fibrils under physiological conditions. Moreover, the development of self-assembled fibrillar biomaterials that are tailored for the desired properties towards applications in biomedical or environmental areas is extensively analyzed. We also review computational studies predicting the amyloid propensity of the natural amino acid sequences and the structure of amyloids, as well as designing novel functional amyloid materials.

Charge guides pathway selection in β-sheet fibrillizing peptide co-assembly

Peptide co-assembly is attractive for creating biomaterials with new forms and functions. Emergence of these properties depends on the peptide content of the final assembled structure, which is difficult to predict in multicomponent systems. Here using experiments and simulations we show that charge governs content by affecting propensity for self- and co-association in binary CATCH(+/-) peptide systems. Equimolar mixtures of CATCH(2+/2-), CATCH(4+/4-), and CATCH(6+/6-) formed two-component β-sheets. Solid-state NMR suggested the cationic peptide predominated in the final assemblies. The cationic-to-anionic peptide ratio decreased with increasing charge. CATCH(2+) formed β-sheets when alone, whereas the other peptides remained unassembled. Fibrillization rate increased with peptide charge. The zwitterionic CATCH parent peptide, "Q11", assembled slowly and only at decreased simulation temperature. These results demonstrate that increasing charge draws complementary peptides together faster, favoring co-assembly, while like-charged molecules repel. We foresee these insights enabling development of co-assembled peptide biomaterials with defined content and predictable properties.

Molecular complementarity and structural heterogeneity within co-assembled peptide β-sheet nanofibers

Self-assembling peptides have garnered an increasing amount of interest as a functional biomaterial for medical and biotechnological applications. Recently, β-sheet peptide designs utilizing complementary pairs of peptides composed of charged amino acids positioned to impart co-assembly behavior have expanded the portfolio of peptide aggregate structures. Structural characterization of these charge-complementary peptide co-assemblies has been limited. Thus, it is not known how the complementary peptides organize on the molecular level. Through a combination of solid-state NMR measurements and discontinuous molecular dynamics simulations, we investigate the molecular organization of King-Webb peptide nanofibers. KW+ and KW- peptides co-assemble into near stoichiometric two-component β-sheet structures as observed by computational simulations and ¹³C-¹³C dipolar couplings. A majority of β-strands are aligned with antiparallel nearest neighbors within the β-sheet as previously suggested by Fourier transform infrared spectroscopy measurements. Surprisingly, however, a significant proportion of β-strand neighbors are parallel. While charge-complementary peptides were previously assumed to organize in an ideal (AB)_n pattern, dipolar recoupling measurements on isotopically diluted nanofiber samples reveal a non-negligible amount of self-associated (AA and BB) pairs. Furthermore, computational simulations predict these different structures can coexist within the same nanofiber. Our results highlight structural disorder at the molecular level in a charge-complementary peptide system with implications on co-assembling peptide designs.

Anatomy of a selectively coassembled β-sheet peptide nanofiber

Peptide self-assembly, wherein molecule A associates with other A molecules to form fibrillar β-sheet structures, is common in nature and widely used to fabricate synthetic biomaterials. Selective coassembly of peptide pairs A and B with complementary partial charges is gaining interest due to its potential for expanding the form and function of biomaterials that can be realized. It has been hypothesized that charge-complementary peptides organize into alternating ABAB-type arrangements within assembled β-sheets, but no direct molecular-level evidence exists to support this interpretation. We report a computational and experimental approach to characterize molecular-level organization of the established peptide pair, CATCH. Discontinuous molecular dynamics simulations predict that CATCH(+) and CATCH(-) peptides coassemble but do not self-assemble. Two-layer β-sheet amyloid structures predominate, but off-pathway β-barrel oligomers are also predicted. At low concentration, transmission electron microscopy and dynamic light scattering identified nonfibrillar ∼20-nm oligomers, while at high concentrations elongated fibers predominated. Thioflavin T fluorimetry estimates rapid and near-stoichiometric coassembly of CATCH(+) and CATCH(-) at concentrations ≥100 μM. Natural abundance ¹³C NMR and isotope-edited Fourier transform infrared spectroscopy indicate that CATCH(+) and CATCH(-) coassemble into two-component nanofibers instead of self-sorting. However, ¹³C-¹³C dipolar recoupling solid-state NMR measurements also identify nonnegligible AA and BB interactions among a majority of AB pairs. Collectively, these results demonstrate that strictly alternating arrangements of β-strands predominate in coassembled CATCH structures, but deviations from perfect alternation occur. Off-pathway β-barrel oligomers are also suggested to occur in coassembled β-strand peptide systems.

Recent Advances in Coarse-Grained Models for Biomolecules and Their Applications

Molecular dynamics simulations have emerged as a powerful tool to study biological systems at varied length and timescales. The conventional all-atom molecular dynamics simulations are being used by the wider scientific community in routine to capture the conformational dynamics and local motions. In addition, recent developments in coarse-grained models have opened the way to study the macromolecular complexes for time scales up to milliseconds. In this review, we have discussed the principle, applicability and recent development in coarse-grained models for biological systems. The potential of coarse-grained simulation has been reviewed through state-of-the-art examples of protein folding and structure prediction, self-assembly of complexes, membrane systems and carbohydrates fiber models. The multiscale simulation approaches have also been discussed in the context of their emerging role in unravelling hierarchical level information of biosystems. We conclude this review with the future scope of coarse-grained simulations as a constantly evolving tool to capture the dynamics of biosystems.

Differential Misfolding Properties of Glaucoma-Associated Olfactomedin Domains from Humans and Mice

Mutations in myocilin, predominantly within its olfactomedin (OLF) domain, are causative for the heritable form of open angle glaucoma in humans. Surprisingly, mice expressing Tyr423His mutant myocilin, corresponding to a severe glaucoma-causing mutation (Tyr437His) in human subjects, exhibit a weak, if any, glaucoma phenotype. To address possible protein-level discrepancies between mouse and human OLFs, which might lead to this outcome, biophysical properties of mouse OLF were characterized for comparison with those of human OLF. The 1.55 Å resolution crystal structure of mouse OLF reveals an asymmetric 5-bladed β-propeller that is nearly indistinguishable from previous structures of human OLF. Wild-type and selected mutant mouse OLFs mirror thermal stabilities of their human OLF counterparts, including characteristic stabilization in the presence of calcium. Mouse OLF forms thioflavin T-positive aggregates with a similar end-point morphology as human OLF, but amyloid aggregation kinetic rates of mouse OLF are faster than human OLF. Simulations and experiments support the interpretation that kinetics of mouse OLF are faster because of a decreased charge repulsion arising from more neutral surface electrostatics. Taken together, phenotypic differences observed in mouse and human studies of mutant myocilin could be a function of aggregation kinetics rates, which would alter the lifetime of putatively toxic protofibrillar intermediates.

Thermodynamic phase diagram of amyloid-β (16-22) peptide

The aggregation of monomeric amyloid β protein (Aβ) peptide into oligomers and amyloid fibrils in the mammalian brain is associated with Alzheimer's disease. Insight into the thermodynamic stability of the Aβ peptide in different polymeric states is fundamental to defining and predicting the aggregation process. Experimental determination of Aβ thermodynamic behavior is challenging due to the transient nature of Aβ oligomers and the low peptide solubility. Furthermore, quantitative calculation of a thermodynamic phase diagram for a specific peptide requires extremely long computational times. Here, using a coarse-grained protein model, molecular dynamics (MD) simulations are performed to determine an equilibrium concentration and temperature phase diagram for the amyloidogenic peptide fragment Aβ_16-22 Our results reveal that the only thermodynamically stable phases are the solution phase and the macroscopic fibrillar phase, and that there also exists a hierarchy of metastable phases. The boundary line between the solution phase and fibril phase is found by calculating the temperature-dependent solubility of a macroscopic Aβ_16-22 fibril consisting of an infinite number of β-sheet layers. This in silico determination of an equilibrium (solubility) phase diagram for a real amyloid-forming peptide, Aβ_16-22, over the temperature range of 277-330 K agrees well with fibrillation experiments and transmission electron microscopy (TEM) measurements of the fibril morphologies formed. This in silico approach of predicting peptide solubility is also potentially useful for optimizing biopharmaceutical production and manufacturing nanofiber scaffolds for tissue engineering.

Structural mechanisms of oligomer and amyloid fibril formation by the prion protein

Misfolding and aggregation of the prion protein is responsible for multiple neurodegenerative diseases. Works from several laboratories on folding of both the WT and multiple pathogenic mutant variants of the prion protein have identified several structurally dissimilar intermediates, which might be potential precursors to misfolding and aggregation. The misfolded aggregates themselves are morphologically distinct, critically dependent on the solution conditions under which they are prepared, but always β-sheet rich. Despite the lack of an atomic resolution structure of the infectious pathogenic agent in prion diseases, several low resolution models have identified the β-sheet rich core of the aggregates formed in vitro, to lie in the α2-α3 subdomain of the prion protein, albeit with local stabilities that vary with the type of aggregate. This feature article describes recent advances in the investigation of in vitro prion protein aggregation using multiple spectroscopic probes, with particular focus on (1) identifying aggregation-prone conformations of the monomeric protein, (2) conditions which trigger misfolding and oligomerization, (3) the mechanism of misfolding and aggregation, and (4) the structure of the misfolded intermediates and final aggregates.

Structural basis for the complete resistance of the human prion protein mutant G127V to prion disease

Prion diseases are caused by the propagation of misfolded cellular prion proteins (PrPs). A completely prion disease-resistant genotype, V127M129, has been identified in Papua New Guinea and verified in transgenic mice. To disclose the structural basis of the disease-resistant effect of the G127V mutant, we determined and compared the structural and dynamic features of the G127V-mutated human PrP (residues 91-231) and the wild-type PrP in solution. HuPrP(G127V) contains α1, α2 and α3 helices and a stretch-strand (SS) pattern comprising residues Tyr128-Gly131 (SS1) and Val161-Arg164 (SS2), with extending atomic distances between the SS1 and SS2 strands, and a structural rearrangement of the Tyr128 side chain due to steric hindrance of the larger hydrophobic side chain of Val127. The extended α1 helix gets closer to the α2 and α3 helices. NMR dynamics analysis revealed that Tyr128, Gly131 and Tyr163 underwent significant conformational exchanges. Molecular dynamics simulations suggest that HuPrP(G127V) prevents the formation of stable β-sheets and dimers. Unique structural and dynamic features potentially inhibit the conformational conversion of the G127V mutant. This work is beneficial for understanding the molecular mechanisms underlying the complete resistance of the G127V mutant to prion disease and for developing new therapeutics for prion disease.

Seeding and cross-seeding fibrillation of N-terminal prion protein peptides PrP(120-144)

Prion diseases are infectious neurodegenerative diseases that are capable of cross-species transmission, thus arousing public health concerns. Seed-templating propagation of prion protein is believed to underlie prion cross-species transmission pathology. Understanding the molecular fundamentals of prion propagation is key to unravelling the pathology of prion diseases. In this study, we use coarse-grained molecular dynamics to investigate the seeding and cross-seeding aggregation of three prion protein fragments PrP(120-144) originating from human (Hu), bank vole (BV), and Syrian hamster (SHa). We find that the seed accelerates the aggregation of the monomer peptides by eliminating the lag phase. The monomer aggregation kinetics are mainly determined by the structure of the seed. The stronger the hydrophobic residues on the seed associate with each other, the higher the probability that the seed recruits monomer peptides to its surface/interface. For cross-seeding aggregation, we show that Hu has a strong tendency to adopt the conformation of the BV seed and vice versa; the Hu and BV monomers have a weak tendency to adopt the conformation of the SHa seed. These two findings are consistent with Apostol et al.'s experimental findings on PrP(138-143) and partially consistent with Jones et al.'s finding on PrP(23-144). We also identify several conformational mismatches when SHa cross-seeds BV and Hu peptides, indicating the existence of a cross-seeding barrier between SHa and the other two sequences. This study sheds light on the molecular mechanism of seed-templating aggregation of prion protein fragments underlying the sequence-dependent transmission barrier in prion diseases.

Simulations and Experiments Delineate Amyloid Fibrilization by Peptides Derived from Glaucoma-Associated Myocilin

Mutant myocilin aggregation is associated with inherited open angle glaucoma, a prevalent optic neuropathy leading to blindness. Comprehension of mutant myocilin aggregation is of fundamental importance to glaucoma pathogenesis and ties glaucoma to amyloid diseases such as Alzheimer's. Here, we probe the aggregation properties of peptides derived from the myocilin olfactomedin domain. Peptides P1 (residues 326-337) and P3 (residues 426-442) were identified previously to form amyloids. Coarse-grained discontinuous molecular dynamics simulations using the PRIME20 force field (DMD/PRIME20) predict that P1 and P3 are aggregation-prone; P1 consistently forms fibrillar aggregates with parallel in-register β-sheets, whereas P3 forms β-sheet-containing aggregates without distinct order. Natural abundance ¹³C solid-state NMR spectra validate that aggregated P1 exhibits amyloid signatures and is more homogeneous than aggregated P3. DMD/PRIME20 simulations provide a viable method to predict peptide aggregation propensities and aggregate structure/order which cannot be accessed by bioinformatics or readily attained experimentally.

Effects of pH and aggregation in the human prion conversion into scrapie form: a study using molecular dynamics with excited normal modes

There are two different prion conformations: (1) the cellular natural (PrP^C) and (2) the scrapie (PrP^Sc), an infectious form that tends to aggregate under specific conditions. PrP^C and PrP^Sc are widely different regarding secondary and tertiary structures. PrP^Sc contains more and longer β-strands compared to PrP^C. The lack of solved PrP^Sc structures precludes a proper understanding of the mechanisms related to the transition between cellular and scrapie forms, as well as the aggregation process. In order to investigate the conformational transition between PrP^C and PrP^Sc, we applied MDeNM (molecular dynamics with excited normal modes), an enhanced sampling simulation technique that has been recently developed to probe large structural changes. These simulations yielded new structural rearrangements of the cellular prion that would have been difficult to obtain with standard MD simulations. We observed an increase in β-sheet formation under low pH (≤ 4) and upon oligomerization, whose relevance was discussed on the basis of the energy landscape theory for protein folding. The characterization of intermediate structures corresponding to transition states allowed us to propose a conversion model from the cellular to the scrapie prion, which possibly ignites the fibril formation. This model can assist the design of new drugs to prevent neurological disorders related to the prion aggregation mechanism.