Prediction of "hot spots" of aggregation in disease-linked polypeptides

Extraction, isolation, synthesis, and biological evaluation of novel piperic acid derivatives for the treatment of Alzheimer's disease

In this paper, we developed a series of piperic acid (PA) analogs with the aim of overcoming the limitations associated with the natural products for the management of Alzheimer's disease (AD). A comprehensive SAR study was performed to enhance cholinesterase inhibition of PA. The acetylcholinesterase inhibition and its kinetic data suggested 6j as the lead molecule (AChE IC50 = 2.13 ± 0.015 µM, BChE = 28.19 ± 0.20%), in comparison to PA (AChE = 7.14 ± 0.98%) which was further selected for various biological studies in AD models. 6j, exhibited interaction with the peripheral anionic site of AChE, BBB permeability (Pe = 7.98), and antioxidant property (% radical scavenging activity = 35.41 ± 1.09, 2.43 ± 1.65, for 6j and PA at 20 M μ , respectively). The result from the metal chelation study suggests that 6j did not effectively chelate iron. The molecular modeling studies suggested that 6j could effectively interact with Ser293, Phe295, Arg296, and Tyr34 of AChE. In the cell-based cytotoxicity studies, 6j exhibited cytocompatibility at the different tested concentrations. The acute toxicity data on mice suggested that compound 6j had no renal and hepatotoxicity at 500 mg/kg. Moreover, 6j could effectively reverse scopolamine-induced amnesia by improving spatial and cognitive memory in mice. The above results strongly suggest that compound 6j may act as a novel multi-targeted lead for AD therapy.

Furosemide Derails Human Lysozyme Fibrillation by Interacting with Aggregation Hot Spots: A Biophysical Comprehension

Kidney-associated human lysozyme amyloidosis leads to renal impairments;thus, patients are often prescribed furosemide. Based on this fact, the effect of furosemide on induced human lysozyme fibrillation, in vitro, is evaluated by spectroscopic, calorimetric, computational, and cellular-based assays/methods. Results show that furosemide increases the lag phase and decreases the apparent rate of aggregation of human lysozyme, thereby decelerating the nucleation phase and amyloid fibril formation, as confirmed by the decrease in the level of Thioflavin-T fluorescence. Fewer entities of hydrodynamic radii of ∼171 nm instead of amyloid fibrils (∼412 nm) are detected in human lysozyme in the presence of furosemide by dynamic light scattering. Moreover, furosemide decreases the extent of conversion of the α/β structure of human lysozyme into a predominant β-sheet. The isothermal titration calorimetry established that furosemide forms a complex with human lysozyme, which was also confirmed through fluorescence quenching and computational studies. Also, human lysozyme lytic activity is inhibited competitively by furosemide due to the involvement of amino acid residues of the active site in catalysis, as well as complex formation. Conclusively, furosemide interacts with Gln58, Ile59, Asn60, Ala108, and Trp109 of aggregation-prone regions 2 and 4 of human lysozyme, thereby masking its sites of aggregation and generating only lower-order entities that are less toxic to red blood cells than the fibrils. Thus, furosemide slows the progression of amyloid fibrillation in human lysozyme.

Biophysical insight into anti-amyloidogenic nature of novel ionic Co(II)(phen)(H2O)4]+[glycinate]- chemotherapeutic drug candidate against human lysozyme aggregation

In the recent past, there has been an ever-increasing interest in the search for metal-based therapeutic drug candidates for protein misfolding disorders (PMDs) particularly neurodegenerative disorders such as Alzheimer's, Parkinson's, Prion's diseases, and amyotrophic lateral sclerosis. Also, different amyloidogenic variants of human lysozyme (HL) are involved in hereditary systemic amyloidosis. Metallo-therapeutic agents are extensively studied as antitumor agents, however, they are relatively unexplored for the treatment of non-neuropathic amyloidoses. In this work, inhibition potential of a novel ionic cobalt(II) therapeutic agent (CoTA) of the formulation [Co(phen)(H2O)4]+[glycinate]- is evaluated against HL fibrillation. Various biophysical techniques viz., dye-binding assays, dynamic light scattering (DLS), differential scanning calorimetry (DSC), electron microscopy, and molecular docking experiments validate the proposed mechanism of inhibition of HL fibrillation by CoTA. The experimental corroborative results of these studies reveal that CoTA can suppress and slow down HL fibrillation at physiological temperature and pH. DLS and 1-anilino-8-naphthalenesulfonate (ANS) assay show that reduced fibrillation in the presence of CoTA is marked by a significant decrease in the size and hydrophobicity of the aggregates. Fluorescence quenching and molecular docking results demonstrate that CoTA binds moderately to the aggregation-prone region of HL (Kb = 6.6 × 104 M-1), thereby, inhibiting HL fibrillation. In addition, far-UV CD and DSC show that binding of CoTA to HL does not cause any change in the stability of HL. More importantly, CoTA attenuates membrane damaging effects of HL aggregates against RBCs. This study identifies inorganic metal complexes as a therapeutic intervention for systemic amyloidosis.

Unraveling the underlying mechanisms of reduced amyloidogenic properties in human calcitonin via double mutations

The therapeutic efficacy of peptide-based drugs is commonly hampered by the intrinsic propensity to aggregation. A notable example is human calcitonin (hCT), a peptide hormone comprising 32 amino acids, which is synthesized and secreted by thyroid gland parafollicular cells (C cells). This hormone plays a vital role in regulating blood calcium levels and upholding bone integrity. Despite its physiological importance, utilizing hCT as a drug is hampered by its inclination to form amyloid. To address this limitation, an alternative is provided by salmon calcitonin (sCT), which possesses a lower aggregation propensity. Although sharing the same disulfide bond at the N terminus as hCT, sCT differs from hCT at a total of 16 amino acid positions. However, due to the dissimilarity in sequences, using sCT as a clinical replacement occasionally results in adverse side effects in patients. Earlier investigations have highlighted the significant roles of Tyr-12 and Asn-17 in inducing the formation of amyloid fibrils. By introducing double mutations at these sites, the ability to hinder aggregation can be significantly augmented. This study delves into the oligomerization and helical structure formation of the hCT double mutant (Y12LN17H hCT, noted as DM hCT), as well as two single mutants (Y12L and N17H), aiming to elucidate the mechanism behind hCT fibrillization. In addition, computational prediction tools were employed again to identify potential substitutes. Although the results yielded were not entirely satisfactory, a comparison between the newly examined and previously found hCT double mutants provides insights into the reduced aggregation propensity of the latter. This research endeavor holds the promise of informing the design of more effective therapeutic peptide drugs in the future.

A3D Model Organism Database (A3D-MODB): a database for proteome aggregation predictions in model organisms

Protein aggregation has been associated with aging and different pathologies and represents a bottleneck in the industrial production of biotherapeutics. Numerous past studies performed in Escherichia coli and other model organisms have allowed to dissect the biophysical principles underlying this process. This knowledge fuelled the development of computational tools, such as Aggrescan 3D (A3D) to forecast and re-design protein aggregation. Here, we present the A3D Model Organism Database (A3D-MODB) http://biocomp.chem.uw.edu.pl/A3D2/MODB, a comprehensive resource for the study of structural protein aggregation in the proteomes of 12 key model species spanning distant biological clades. In addition to A3D predictions, this resource incorporates information useful for contextualizing protein aggregation, including membrane protein topology and structural model confidence, as an indirect reporter of protein disorder. The database is openly accessible without any need for registration. We foresee A3D-MOBD evolving into a central hub for conducting comprehensive, multi-species analyses of protein aggregation, fostering the development of protein-based solutions for medical, biotechnological, agricultural and industrial applications.

Proteome encoded determinants of protein sorting into extracellular vesicles

Extracellular vesicles (EVs) are membranous structures released by cells into the extracellular space and are thought to be involved in cell-to-cell communication. While EVs and their cargo are promising biomarker candidates, sorting mechanisms of proteins to EVs remain unclear. In this study, we ask if it is possible to determine EV association based on the protein sequence. Additionally, we ask what the most important determinants are for EV association. We answer these questions with explainable AI models, using human proteome data from EV databases to train and validate the model. It is essential to correct the datasets for contaminants introduced by coarse EV isolation workflows and for experimental bias caused by mass spectrometry. In this study, we show that it is indeed possible to predict EV association from the protein sequence: a simple sequence-based model for predicting EV proteins achieved an area under the curve of 0.77 ± 0.01, which increased further to 0.84 ± 0.00 when incorporating curated post-translational modification (PTM) annotations. Feature analysis shows that EV-associated proteins are stable, polar, and structured with low isoelectric point compared to non-EV proteins. PTM annotations emerged as the most important features for correct classification; specifically, palmitoylation is one of the most prevalent EV sorting mechanisms for unique proteins. Palmitoylation and nitrosylation sites are especially prevalent in EV proteins that are determined by very strict isolation protocols, indicating they could potentially serve as quality control criteria for future studies. This computational study offers an effective sequence-based predictor of EV associated proteins with extensive characterisation of the human EV proteome that can explain for individual proteins which factors contribute to their EV association.

Structural insights and aggregation propensity of a super-stable monellin mutant: A new potential building block for protein-based nanostructured materials

Protein fibrillation is commonly associated with pathologic amyloidosis. However, under appropriate conditions several proteins form fibrillar structures in vitro that can be used for biotechnological applications. MNEI and its variants, firstly designed as single chain derivatives of the sweet protein monellin, are also useful models for protein fibrillary aggregation studies. In this work, we have drawn attention to a protein dubbed Mut9, already characterized as a "super stable" MNEI variant. Comparative analysis of the respective X-ray structures revealed how the substitutions present in Mut9 eliminate several unfavorable interactions and stabilize the global structure. Molecular dynamic predictions confirmed the presence of a hydrogen-bonds network in Mut9 which increases its stability, especially at neutral pH. Thioflavin-T (ThT) binding assays and Fourier transform infrared (FTIR) spectroscopy indicated that the aggregation process occurs both at acidic and neutral pH, with and without addition of NaCl, even if with a different kinetics. Accordingly, Transmission Electron Microscopy (TEM) showed a fibrillar organization of the aggregates in all the tested conditions, albeit with some differences in the quantity and in the morphology of the fibrils. Our data underline the great potential of Mut9, which combines great stability in solution with the versatile conversion into nanostructured biomaterials.

Saturation mutagenesis of α-synuclein reveals monomer fold that modulates aggregation

α-Synuclein (aSyn) aggregation underlies neurodegenerative synucleinopathies. aSyn seeds are proposed to replicate and propagate neuronal pathology like prions. Seeding of aSyn can be recapitulated in cellular systems of aSyn aggregation; however, the mechanism of aSyn seeding and its regulation are not well understood. We developed an mEos-based aSyn seeding assay and performed saturation mutagenesis to identify with single-residue resolution positive and negative regulators of aSyn aggregation. We not only found the core regions that govern aSyn aggregation but also identified mutants outside of the core that enhance aggregation. We identified local structure within the N terminus of aSyn that hinders the fibrillization propensity of its aggregation-prone core. Based on the screen, we designed a minimal aSyn fragment that shows a ~4-fold enhancement in seeding activity and enabled discrimination of synucleinopathies. Our study expands the basic knowledge of aSyn aggregation and advances the design of cellular systems of aSyn aggregation to diagnose synucleinopathies based on protein conformation.

Chaotic aging: intrinsically disordered proteins in aging-related processes

The development of aging is associated with the disruption of key cellular processes manifested as well-established hallmarks of aging. Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) have no stable tertiary structure that provide them a power to be configurable hubs in signaling cascades and regulate many processes, potentially including those related to aging. There is a need to clarify the roles of IDPs/IDRs in aging. The dataset of 1702 aging-related proteins was collected from established aging databases and experimental studies. There is a noticeable presence of IDPs/IDRs, accounting for about 36% of the aging-related dataset, which is however less than the disorder content of the whole human proteome (about 40%). A Gene Ontology analysis of the used here aging proteome reveals an abundance of IDPs/IDRs in one-third of aging-associated processes, especially in genome regulation. Signaling pathways associated with aging also contain IDPs/IDRs on different hierarchical levels, revealing the importance of "structure-function continuum" in aging. Protein-protein interaction network analysis showed that IDPs present in different clusters associated with different aging hallmarks. Protein cluster with IDPs enrichment has simultaneously high liquid-liquid phase separation (LLPS) probability, "nuclear" localization and DNA-associated functions, related to aging hallmarks: genomic instability, telomere attrition, epigenetic alterations, and stem cells exhaustion. Intrinsic disorder, LLPS, and aggregation propensity should be considered as features that could be markers of pathogenic proteins. Overall, our analyses indicate that IDPs/IDRs play significant roles in aging-associated processes, particularly in the regulation of DNA functioning. IDP aggregation, which can lead to loss of function and toxicity, could be critically harmful to the cell. A structure-based analysis of aging and the identification of proteins that are particularly susceptible to disturbances can enhance our understanding of the molecular mechanisms of aging and open up new avenues for slowing it down.

Amyloid-like aggregation of recombinant β-lactoglobulin at pH 3.5 and 7.0: Is disulfide bond removal the key to fibrillation?

Functional nanofibrils from globular proteins are usually formed by heating for several hours at pH 2.0, which induces acidic hydrolysis and consecutive self-association. The functional properties of these micro-metre-long anisotropic structures are promising for biodegradable biomaterials and food applications, but their stability at pH > 2.0 is low. The results presented here show that modified β-lactoglobulin can also form nanofibrils by heating at neutral pH without prior acidic hydrolysis; the key is removing covalent disulfide bonds. The aggregation behaviour of various recombinant β-lactoglobulin variants was systemically studied at pH 3.5 and 7.0. The suppression of intra- and intermolecular disulfide bonds by eliminating one to three out of the five cysteines makes the non-covalent interactions more prevalent and allow for structural rearrangement. This stimulated the linear growth of worm-like aggregates. Full elimination of all five cysteines led to the transformation of worm-like aggregates into actual fibril structures (several hundreds of nanometres long) at pH 7.0. This understanding of the role of cysteine in protein-protein interactions will help to identify proteins and protein modifications to form functional aggregates at neutral pH.

Histidine tautomerism-mediated transthyretin amyloidogenesis: A molecular insight

Characterization of the conformational alterations involved in monomer misfolding is essential for elucidating the molecular basis of the initial stage of protein accumulation. Here, we report the first structural analyses of transthyretin (TTR) (26-57) fragments with two histidine tautomeric states (δ; N_δ1H and ε; N_ε2H) using replica-exchange molecular dynamics (REMD) simulations. Explaining the organizational properties and misfolding procedure is challenging because the δ and ε configurations can occur in the free neutral state. REMD revealed that β-sheet generation is favored for the δδ (16.8%) and εδ (6.7%) tautomeric isomers, showing frequent main-chain contacts between the stable regions near the head (N-terminus) and central (middle) part compared to the εε (4.8%) and δε (2.8%) isomers. The presence of smaller and wider local energy minima may be related to the structural stability and toxicity of δδ/εδ and εε/δε. Histidines31 and 56 were the parts of regular (such as β-strand) and nonregular (such as coil) secondary structures within the highly toxic TTR isomer. For TTR amyloidosis, focusing on hazardous isomeric forms with high sheet contents may be a potent treatment strategy. Overall, our findings support the tautomerism concept and aid in our comprehension of the basic tautomeric actions of neutral histidine throughout the misfolding process.

A machine learning strategy for the identification of key in silico descriptors and prediction models for IgG monoclonal antibody developability properties

Identification of favorable biophysical properties for protein therapeutics as part of developability assessment is a crucial part of the preclinical development process. Successful prediction of such properties and bioassay results from calculated in silico features has potential to reduce the time and cost of delivering clinical-grade material to patients, but nevertheless has remained an ongoing challenge to the field. Here, we demonstrate an automated and flexible machine learning workflow designed to compare and identify the most powerful features from computationally derived physiochemical feature sets, generated from popular commercial software packages. We implement this workflow with medium-sized datasets of human and humanized IgG molecules to generate predictive regression models for two key developability endpoints, hydrophobicity and poly-specificity. The most important features discovered through the automated workflow corroborate several previous literature reports, and newly discovered features suggest directions for further research and potential model improvement.

Beta-rich intermediates in denaturation of lysozyme: accelerated molecular dynamics simulations

Amyloid fibrillar aggregates play a critical role in many neurodegenerative disorders. Conversion of globular proteins into fibrils is associated with global conformational rearrangement and involves the transformation of α-helices to β-sheets. In the present work, the accelerated molecular dynamics technique was applied to study the unfolding of hen egg-white lysozyme at elevated temperatures, and the transformation of the native structure to a disordered one was analyzed. The influence of the disulfide bonds on the conformational dynamics and the energy landscape of denaturation process was considered. Our results show that formation of the metastable β-enriched conformers of individual protein molecules may precede the aggregation process. These β-rich intermediates can play a role of bricks making up fibrils.Communicated by Ramaswamy H. Sarma.

DES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases

More than 30 types of amyloids are linked to close to 50 diseases in humans, the most prominent being Alzheimer’s disease (AD). AD is brain-related local amyloidosis, while another amyloidosis, such as AA amyloidosis, tends to be more systemic. Therefore, we need to know more about the biological entities’ influencing these amyloidosis processes. However, there is currently no support system developed specifically to handle this extraordinarily complex and demanding task. To acquire a systematic view of amyloidosis and how this may be relevant to the brain and other organs, we needed a means to explore "amyloid network systems" that may underly processes that leads to an amyloid-related disease. In this regard, we developed the DES-Amyloidoses knowledgebase (KB) to obtain fast and relevant information regarding the biological network related to amyloid proteins/peptides and amyloid-related diseases. This KB contains information obtained through text and data mining of available scientific literature and other public repositories. The information compiled into the DES-Amyloidoses system based on 19 topic-specific dictionaries resulted in 796,409 associations between terms from these dictionaries. Users can explore this information through various options, including enriched concepts, enriched pairs, and semantic similarity. We show the usefulness of the KB using an example focused on inflammasome-amyloid associations. To our knowledge, this is the only KB dedicated to human amyloid-related diseases derived primarily through literature text mining and complemented by data mining that provides a novel way of exploring information relevant to amyloidoses.

Scan-Find-Scan-Model: Discrete Site-Targeted Suppressor Design Strategy for Amyloid-β

Alzheimer's disease is undoubtedly the most well-studied neurodegenerative disease. Consequently, the amyloid-β (Aβ) protein ranks at the top in terms of getting attention from the scientific community for structural property-based characterization. Even after decades of extensive research, there is existing volatility in terms of understanding and hence the effective tackling procedures against the disease that arises due to the lack of knowledge of both specific target- and site-specific drugs. Here, we develop a multidimensional approach based on the characterization of the common static-dynamic-thermodynamic trait of the monomeric protein, which efficiently identifies a small target sequence that contains an inherent tendency to misfold and consequently aggregate. The robustness of the identification of the target sequence comes with an abundance of a priori knowledge about the length and sequence of the target and hence guides toward effective designing of the target-specific drug with a very low probability of bottleneck and failure. Based on the target sequence information, we further identified a specific mutant that showed the maximum potential to act as a destabilizer of the monomeric protein as well as enormous success as an aggregation suppressor. We eventually tested the drug efficacy by estimating the extent of modulation of binding affinity existing within the fibrillar form of the Aβ protein due to a single-point mutation and hence provided a proof of concept of the entire protocol.

Improved Stability of Human CGI-58 Induced by Phosphomimetic S237E Mutation

In lipolysis, the activating function of CGI-58 is regulated by its interaction with perilipin 1 (PLIN1) localized on the lipid droplet (LD), and its release is controlled by phosphorylation. Once lipolysis is stimulated by catecholamines, protein kinase A (PKA)-mediated phosphorylation enables the dissociation of the CGI-58/PLIN1 complex, thereby recruiting adipose triglyceride lipase (ATGL) and hormone-sensitive lipase (HSL) to initiate fatty acid release. It has been shown that mouse CGI-58 mutant S239E, which mimics the phosphorylation of this residue, is able to dissociate from the CGI-58/PLIN1 complex and activate ATGL. Here, we analyze the stabilizing effect on human CGI-58 of a triple tryptophan to alanine mutant (3WA) on the LD-binding motif, as well as a quadruple mutant in which the phosphomimetic S237E substitution was introduced to the 3WA construct (3WA/S237E). We found that tryptophan residues promote wild-type (WT) protein aggregation in solution since their substitution for alanine residues favors the presence of the monomer. Our experimental data showed increased thermal stability and solubility of 3WA/S237E protein compared to the 3WA mutant. Moreover, the 3WA/S237E protein showed proper folding and a functional binding site for oleoyl-CoA. The analysis of a bioinformatic three-dimensional (3D) model suggests an intramolecular interaction between the phosphomimetic glutamic acid and a residue of the α/β hydrolase core. This could explain the increased solubility and stability observed in the 3WA/S237E mutant and evidences the possible role of serine 237 phosphorylation.

Peptides derived from gp43, the most antigenic protein from Paracoccidioides brasiliensis, form amyloid fibrils in vitro: implications for vaccine development

Fungal infection is an important health problem in Latin America, and in Brazil in particular. Paracoccidioides (mainly P. brasiliensis and P. lutzii) is responsible for paracoccidioidomycosis, a disease that affects mainly the lungs. The glycoprotein gp43 is involved in fungi adhesion to epithelial cells, which makes this protein an interesting target of study. A specific stretch of 15 amino acids that spans the region 181–195 (named P10) of gp43 is an important epitope of gp43 that is being envisioned as a vaccine candidate. Here we show that synthetic P10 forms typical amyloid aggregates in solution in very short times, a property that could hamper vaccine development. Seeds obtained by fragmentation of P10 fibrils were able to induce the aggregation of P4, but not P23, two other peptides derived from gp43. In silico analysis revealed several regions within the P10 sequence that can form amyloid with steric zipper architecture. Besides, in-silico proteolysis studies with gp43 revealed that aggregation-prone, P10-like peptides could be generated by several proteases, which suggests that P10 could be formed under physiological conditions. Considering our data in the context of a potential vaccine development, we redesigned the sequence of P10, maintaining the antigenic region (HTLAIR), but drastically reducing its aggregation propensity.

Protein structure and aggregation: a marriage of necessity ruled by aggregation gatekeepers

Protein aggregation propensity is a pervasive and seemingly inescapable property of proteomes. Strikingly, a significant fraction of the proteome is supersaturated, meaning that, for these proteins, their native conformation is less stable than the aggregated state. Maintaining the integrity of a proteome under such conditions is precarious and requires energy-consuming proteostatic regulation. Why then is aggregation propensity maintained at such high levels over long evolutionary timescales? Here, we argue that the conformational stability of the native and aggregated states are correlated thermodynamically and that codon usage strengthens this correlation. As a result, the folding of stable proteins requires kinetic control to avoid aggregation, provided by aggregation gatekeepers. These unique residues are evolutionarily selected to kinetically favor native folding, either on their own or by coopting chaperones.

Cryptic amyloidogenic regions in intrinsically disordered proteins: Function and disease association

The amyloid conformation is considered a fundamental state of proteins and the propensity to populate it a generic property of polypeptides. Multiple proteome-wide analyses addressed the presence of amyloidogenic regions in proteins, nurturing our understanding of their nature and biological implications. However, these analyses focused on highly aggregation-prone and hydrophobic stretches that are only marginally found in intrinsically disordered regions (IDRs). Here, we explore the prevalence of cryptic amyloidogenic regions (CARs) of polar nature in IDRs. CARs are widespread in IDRs and associated with IDPs function, with particular involvement in protein–protein interactions, but their presence is also connected to a risk of malfunction. By exploring this function/malfunction dichotomy, we speculate that ancestral CARs might have evolved into functional interacting regions playing a significant role in protein evolution at the origins of life.

Rational optimization of a monoclonal antibody improves the aggregation propensity and enhances the CMC properties along the entire pharmaceutical process chain

The discovery of therapeutic monoclonal antibodies (mAbs) primarily focuses on their biological activity favoring the selection of highly potent drug candidates. These candidates, however, may have physical or chemical attributes that lead to unfavorable chemistry, manufacturing, and control (CMC) properties, such as low product titers, conformational and colloidal instabilities, or poor solubility, which can hamper or even prevent development and manufacturing. Hence, there is an urgent need to consider the developability of mAb candidates during lead identification and optimization. This work provides a comprehensive proof of concept study for the significantly improved developability of a mAb variant that was optimized with the help of sophisticated in silico tools relative to its difficult-to-develop parental counterpart. Interestingly, a single amino acid substitution in the variable domain of the light chain resulted in a three-fold increased product titer after stable expression in Chinese hamster ovary cells. Microscopic investigations revealed that wild type mAb-producing cells displayed potential antibody inclusions, while the in silico optimized variant-producing cells showed a rescued phenotype. Notably, the drug substance of the in silico optimized variant contained substantially reduced levels of aggregates and fragments after downstream process purification. Finally, formulation studies unraveled a significantly enhanced colloidal stability of the in silico optimized variant while its folding stability and potency were maintained. This study emphasizes that implementation of bioinformatics early in lead generation and optimization of biotherapeutics reduces failures during subsequent development activities and supports the reduction of project timelines and resources.

Effect of formulation and peptide folding on the fibrillar aggregation, gelation, and oxidation of a therapeutic peptide

The physical and chemical stability of therapeutic peptides presents challenges in developing robust formulations. The stability of the formulation affects product safety, efficacy and quality. Therefore, an understanding of the effects of formulation variables on the peptide's conformational structure and on its possible physical and chemical degradation is vital. To this end, computational and experimental analysis were employed to investigate the impact of formulation, peptide folding and product handling on oxidation, fibrillar aggregation and gelation of teriparatide. Teriparatide was used as a model drug due to the correlation of its conformation in solution with its pharmacological activity. Fibrillar aggregation and gelation were monitored using four orthogonal techniques. An innovative, automated platform coupled with ion mobility mass spectrometry was used for profiling chemical degradants. Increases in teriparatide concentration, pH, and ionic strength were found to increase the rate of fibrillar aggregation and gelation. Conversely, an increase in peptide folding and stabilization of the folded structures was found to decrease the rate of fibrillar aggregation and gelation. Moreover, the rate of oxidation was found to be inversely related to its solution concentration and extent of peptide folding. The present study provides an insight into formulation strategies designed to reduce the potential risk of physical and chemical degradation of peptides with a defined conformation.

The chaperone-binding activity of the mitochondrial surface receptor Tom70 protects the cytosol against mitoprotein-induced stress

Most mitochondrial proteins are synthesized as precursors in the cytosol and post-translationally transported into mitochondria. The mitochondrial surface protein Tom70 acts at the interface of the cytosol and mitochondria. In vitro import experiments identified Tom70 as targeting receptor, particularly for hydrophobic carriers. Using in vivo methods and high-content screens, we revisit the question of Tom70 function and considerably expand the set of Tom70-dependent mitochondrial proteins. We demonstrate that the crucial activity of Tom70 is its ability to recruit cytosolic chaperones to the outer membrane. Indeed, tethering an unrelated chaperone-binding domain onto the mitochondrial surface complements most of the defects caused by Tom70 deletion. Tom70-mediated chaperone recruitment reduces the proteotoxicity of mitochondrial precursor proteins, particularly of hydrophobic inner membrane proteins. Thus, our work suggests that the predominant function of Tom70 is to tether cytosolic chaperones to the outer mitochondrial membrane, rather than to serve as a mitochondrion-specifying targeting receptor.

Membrane-dependent amyloid aggregation of human BAX α9 (173-192)

Mitochondrial outer membrane permeabilization, which is a critical step in apoptosis, is initiated upon transmembrane insertion of the C-terminal α-helix (α9) of the proapoptotic Bcl-2 family protein BAX. The isolated α9 fragment (residues 173-192) is also competent to disrupt model membranes, and the structures of its membrane-associated oligomers are of interest in understanding the potential roles of this sequence in apoptosis. Here, we used ultrafast two-dimensional infrared (2D IR) spectroscopy, thioflavin T binding, and transmission electron microscopy to show that the synthetic BAX α9 peptide (α9p) forms amyloid aggregates in aqueous environments and on the surfaces of anionic small unilamellar vesicles. Its inherent amyloidogenicity was predicted by sequence analysis, and 2D IR spectra reveal that vesicles modulate the β-sheet structures of insoluble aggregates, motivating further examination of the formation or suppression of BAX amyloids in apoptosis.

Residue Interaction Network Analysis Predicts a Val24-Ile31 Interaction May be Involved in Preventing Amyloid-Beta (1-42) Primary Nucleation

Alzheimer's disease (AD) patients could benefit from a more effective treatment than the current FDA-approved options. Because amyloid-beta (Aβ) is thought to play a central role in AD pathogenesis, many experimental drugs attempt to reduce Aβ-induced pathology. Preventing amyloid accumulation may be a more effective strategy than clearing Aβ plaques after they form. If preventing Aβ accumulation can treat or prevent AD, then understanding Aβ primary nucleation may aid rational drug design. This study examines Aβ residue interaction networks and reports network and structural observations that may provide insight into primary nucleation. While many studies identify structural features of Aβ that promote aggregation, this study reports features that may resist primary nucleation by examining Aβ42 studies in more and less polar solvents. In Aβ42 in a less polar solvent (PDB ID: 1IYT), Val24 and Ile31 have higher betweenness and residue centrality values. This may be due to a predicted interaction between Val24 and Ile31. Residues in the central hydrophobic cluster (CHC) of Aβ40 and Aβ42 had significantly higher betweenness values compared to the average betweenness of the structures, highlighting the CHC's reported role in oligomerization. The predicted interaction between Val24 and Ile31 may reduce the likelihood of primary nucleation of Aβ.

PredAmyl-MLP: Prediction of Amyloid Proteins Using Multilayer Perceptron

Amyloid is generally an aggregate of insoluble fibrin; its abnormal deposition is the pathogenic mechanism of various diseases, such as Alzheimer's disease and type II diabetes. Therefore, accurately identifying amyloid is necessary to understand its role in pathology. We proposed a machine learning-based prediction model called PredAmyl-MLP, which consists of the following three steps: feature extraction, feature selection, and classification. In the step of feature extraction, seven feature extraction algorithms and different combinations of them are investigated, and the combination of SVMProt-188D and tripeptide composition (TPC) is selected according to the experimental results. In the step of feature selection, maximum relevant maximum distance (MRMD) and binomial distribution (BD) are, respectively, used to remove the redundant or noise features, and the appropriate features are selected according to the experimental results. In the step of classification, we employed multilayer perceptron (MLP) to train the prediction model. The 10-fold cross-validation results show that the overall accuracy of PredAmyl-MLP reached 91.59%, and the performance was better than the existing methods.

Protein-Based Nano-Vessels Facilitates the Victoria Blue B Mediated Inhibition of Amyloid Fibrillation

Amyloid fibrils are associated with a number of serious and incurable diseases. The understanding of the pathogenic formation of amyloid proteins is progressing. Nonetheless, no treatment is available to deal with amyloid diseases. It is reported here that victoria blue B (VBB) contains an intrinsic marginal inhibitory activity toward protein fibrillation. Moreover, when VBB is co-assembled with scaffold proteins to form fluorescent protein nano-vessels (VBB-FPNs), these complexes show much improved fibrillation inhibitory effects. VBB-FPNs can effectively inhibit lysozyme fibrils formation likely through delaying the nucleation and elongation in a concentration-dependent manner as shown by fluorescent assay, circular dichroism, transmission electron microscopy, and atomic force microscopy. This work describes a new inhibitor of protein fibrillation and provides a new means to enhance the inhibition efficiency of given inhibitors, thus affording a fresh angle to modulate protein fibrillation.

iAMY-SCM: Improved prediction and analysis of amyloid proteins using a scoring card method with propensity scores of dipeptides

Fast, accurate identification and characterization of amyloid proteins at a large-scale is essential for understating their role in therapeutic intervention strategies. As a matter of fact, there exist only one in silico model for amyloid protein identification using the random forest (RF) model in conjunction with various feature types namely the RFAmy. However, it suffers from low interpretability for biologists. Thus, it is highly desirable to develop a simple and easily interpretable prediction method with robust accuracy as compared to the existing complicated model. In this study, we propose iAMY-SCM, the first scoring card method-based predictor for predicting and analyzing amyloid proteins. Herein, the iAMY-SCM made use of a simple weighted-sum function in conjunction with the propensity scores of dipeptides for the amyloid protein identification. Cross-validation results indicated that iAMY-SCM provided an accuracy of 0.895 that corresponded to 10-22% higher performance than that of widely used machine learning models. Furthermore, iAMY-SCM achieving an accuracy of 0.827 as evaluated by an independent test, which was found to be comparable to that of RFAmy and was approximately 9-13% higher than widely used machine learning models. Furthermore, the analysis of estimated propensity scores of amino acids and dipeptides were performed to provide insights into the biophysical and biochemical properties of amyloid proteins. As such, this demonstrates that the proposed iAMY-SCM is efficient and reliable in terms of simplicity, interpretability and implementation. To facilitate ease of use of the proposed iAMY-SCM, a user-friendly and publicly accessible web server at http://camt.pythonanywhere.com/iAMY-SCM has been established. We anticipate that that iAMY-SCM will be an important tool for facilitating the large-scale prediction and characterization of amyloid protein.

The status of the terminal regions of α-synuclein in different forms of aggregates during fibrillization

The α-synuclein (αSN) amyloid fibrillization process is known to be a crucial phenomenon associated with neuronal loss in various neurodegenerative diseases, most famously Parkinson's disease. The process involves different aggregated species and ultimately leads to formation of β-sheet rich fibrillar structures. Despite the essential role of αSN aggregation in the pathoetiology of various neurological disorders, the characteristics of various assemblies are not fully understood. Here, we established a fluorescence-based model for studying the end-parts of αSN to decipher the structural aspects of aggregates during the fibrillization. Our model proved highly sensitive to the events at the early stage of the fibrillization process, which are hardly detectable with routine techniques. Combining fluorescent and PAGE analysis, we found different oligomeric aggregates in the nucleation phase of fibrillization with different sensitivity to SDS and different structures based on αSN termini. Moreover, we found that these oligomers are highly dynamic: after reaching peak levels during fibrillization, they decline and eventually disappear, suggesting their transformation into other αSN aggregated species. These findings shed light on the structural features of various αSN aggregates and their dynamics in synucleinopathies.

Nucleic acids in inclusion bodies obtained from E. coli cells expressing human interferon-gamma

BACKGROUND

Inclusion bodies (IBs) are protein aggregates in recombinant bacterial cells containing mainly the target recombinant protein. Although it has been shown that IBs contain functional proteins along with protein aggregates, their direct application as pharmaceuticals is hindered by their heterogeneity and hazardous contaminants with bacterial origin. Therefore, together with the production of soluble species, IBs remain the main source for manufacture of recombinant proteins with medical application. The quality and composition of the IBs affect the refolding yield and further purification of the recombinant protein. The knowledge whether nucleic acids are genuine components or concomitant impurities of the IBs is a prerequisite for the understanding of the IBs formation and for development of optimized protocols for recombinant protein refolding and purification. IBs isolated from Escherichia coli overexpressing human interferon-gamma (hIFNγ), a protein with therapeutic application, were used as a model.

RESULTS

IBs were isolated from E. coli LE392 cells transformed with a hIFNγ expressing plasmid under standard conditions and further purified by centrifugation on a sucrose cushion, followed by several steps of sonication and washings with non-denaturing concentrations of urea. The efficiency of the purification was estimated by SDS-PAGE gel electrophoresis and parallel microbiological testing for the presence of residual intact bacteria. Phenol/chloroform extraction showed that the highly purified IBs contain both DNA and RNA. The latter were studied by UV spectroscopy and agarose gel electrophoresis combined with enzymatic treatment and hybridization. DNA was observed as a diffuse fraction mainly in the range of 250 to 1000 bp. RNA isolated by TRIzol^® also demonstrated a substantial molecular heterogeneity. Hybridization with ³²P-labelled oligonucleotides showed that the IBs contain rRNA and are enriched of hIFNγ mRNA.

CONCLUSIONS

The results presented in this study indicate that the nucleic acids might be intrinsic components rather than co-precipitated impurities in the IBs. We assume that the nucleic acids are active participants in the aggregation of recombinant proteins and formation of the IBs that originate from the transcription and translation machinery of the microbial cell factory. Further studies are needed to ascertain this notion.

Computational prediction of protein aggregation: Advances in proteomics, conformation-specific algorithms and biotechnological applications

Protein aggregation is a widespread phenomenon that stems from the establishment of non-native intermolecular contacts resulting in protein precipitation. Despite its deleterious impact on fitness, protein aggregation is a generic property of polypeptide chains, indissociable from protein structure and function. Protein aggregation is behind the onset of neurodegenerative disorders and one of the serious obstacles in the production of protein-based therapeutics. The development of computational tools opened a new avenue to rationalize this phenomenon, enabling prediction of the aggregation propensity of individual proteins as well as proteome-wide analysis. These studies spotted aggregation as a major force driving protein evolution. Actual algorithms work on both protein sequences and structures, some of them accounting also for conformational fluctuations around the native state and the protein microenvironment. This toolbox allows to delineate conformation-specific routines to assist in the identification of aggregation-prone regions and to guide the optimization of more soluble and stable biotherapeutics. Here we review how the advent of predictive tools has change the way we think and address protein aggregation.

Design, synthesis and biological evaluation of novel naturally-inspired multifunctional molecules for the management of Alzheimer's disease

In our overall goal to overcome the limitations associated with natural products for the management of Alzheimer's disease and to develop in-vivo active multifunctional cholinergic inhibitors, we embarked on the development of ferulic acid analogs. A systematic SAR study to improve upon the cholinesterase inhibition of ferulic acid with analogs that also had lower logP was carried out. Enzyme inhibition and kinetic studies identified compound 7a as a lead molecule with preferential acetylcholinesterase inhibition (AChE IC₅₀ = 5.74 ± 0.13 μM; BChE IC₅₀ = 14.05 ± 0.10 μM) compared to the parent molecule ferulic acid (% inhibition of AChE and BChE at 20 μM, 15.19 ± 0.59 and 19.73 ± 0.91, respectively). Molecular docking and dynamics studies revealed that 7a fits well into the active sites of AChE and BChE, forming stable and strong interactions with key residues Asp74, Trp286, and Tyr337 in AChE and with Tyr128, Trp231, Leu286, Ala328, Phe329, and Tyr341 in BChE. Compound 7a was found to be an efficacious antioxidant in a DPPH assay (IC₅₀ = 57.35 ± 0.27 μM), and it also was able to chelate iron. Data from atomic force microscopy images demonstrated that 7a was able to modulate aggregation of amyloid β_1-42. Upon oral administration, 7a exhibited promising in-vivo activity in the scopolamine-induced AD animal model and was able to improve spatial memory in cognitive deficit mice in the Y-maze model. Analog 7a could effectively reverse the increased levels of AChE and BChE in scopolamine-treated animals and exhibited potent ex-vivo antioxidant properties. These findings suggest that 7a can act as a lead molecule for the development of naturally-inspired multifunctional molecules for the management of Alzheimer's and other neurodegenerative disorders.

pH-Dependent Aggregation in Intrinsically Disordered Proteins Is Determined by Charge and Lipophilicity

Protein aggregation is associated with an increasing number of human disorders and premature aging. Moreover, it is a central concern in the manufacturing of recombinant proteins for biotechnological and therapeutic applications. Nevertheless, the unique architecture of protein aggregates is also exploited by nature for functional purposes, from bacteria to humans. The relevance of this process in health and disease has boosted the interest in understanding and controlling aggregation, with the concomitant development of a myriad of algorithms aimed to predict aggregation propensities. However, most of these programs are blind to the protein environment and, in particular, to the influence of the pH. Here, we developed an empirical equation to model the pH-dependent aggregation of intrinsically disordered proteins (IDPs) based on the assumption that both the global protein charge and lipophilicity depend on the solution pH. Upon its parametrization with a model IDP, this simple phenomenological approach showed unprecedented accuracy in predicting the dependence of the aggregation of both pathogenic and functional amyloidogenic IDPs on the pH. The algorithm might be useful for diverse applications, from large-scale analysis of IDPs aggregation properties to the design of novel reversible nanofibrillar materials.

Supreme activity of gramicidin S against resistant, persistent and biofilm cells of staphylococci and enterococci

Three promising antibacterial peptides were studied with regard to their ability to inhibit the growth and kill the cells of clinical strains of Staphylococcus aureus, Enterococcus faecalis and Enterococcus faecium. The multifunctional gramicidin S (GS) was the most potent, compared to the membranotropic temporin L (TL), being more effective than the innate-defence regulator IDR-1018 (IDR). These activities, compared across 16 strains as minimal bactericidal and minimal inhibitory concentrations (MIC), are independent of bacterial resistance pattern, phenotype variations and/or biofilm-forming potency. For S. aureus strains, complete killing is accomplished by all peptides at 5 × MIC. For E. faecalis strains, only GS exhibits a rapid bactericidal effect at 5 × MIC, while TL and IDR require higher concentrations. The biofilm-preventing activities of all peptides against the six strains with the largest biofilm biomass were compared. GS demonstrates the lowest minimal biofilm inhibiting concentrations, whereas TL and IDR are consistently less effective. In mature biofilms, only GS completely kills the cells of all studied strains. We compare the physicochemical properties, membranolytic activities, model pharmacokinetics and eukaryotic toxicities of the peptides and explain the bactericidal, antipersister and antibiofilm activities of GS by its elevated stability, pronounced cell-penetration ability and effective utilization of multiple modes of antibacterial action.

Advances in the Prediction of Protein Aggregation Propensity

Background:

Protein aggregation into β-sheet-enriched insoluble assemblies is being found to be associated with an increasing number of debilitating human pathologies, such as Alzheimer’s disease or type 2 diabetes, but also with premature aging. Furthermore, protein aggregation represents a major bottleneck in the production and marketing of proteinbased therapeutics. Thus, the development of methods to accurately forecast the aggregation propensity of a certain protein is of much value.

Methods/Results:

A myriad of in vitro and in vivo aggregation studies have shown that the aggregation propensity of a certain polypeptide sequence is highly dependent on its intrinsic properties and, in most cases, driven by specific short regions of high aggregation propensity. These observations have fostered the development of a first generation of algorithms aimed to predict protein aggregation propensities from the protein sequence. A second generation of programs able to map protein aggregation on protein structures is emerging. Herein, we review the most representative online accessible predictive tools, emphasizing their main distinctive features and the range of applications.

Conclusion:

In this review, we describe representative biocomputational approaches to evaluate the aggregation properties of protein sequences and structures, while illustrating how they can become very useful tools to target protein aggregation in biomedicine and biotechnology.

Delving into the amyloidogenic core of human leukocyte chemotactic factor 2

ALECT2 (leukocyte chemotactic factor 2) amyloidosis is one of the most recently identified amyloid-related diseases, with LECT2 amyloids commonly found in different types of tissues. Under physiological conditions, LECT2 is a 16 kDa multifunctional protein produced by the hepatocytes and secreted into circulation. The pathological mechanisms causing LECT2 transition into the amyloid state are still largely unknown. In the case of ALECT2 patients, there is no disease-causing mutation, yet almost all patients carry a common polymorphism that appears to be necessary but not sufficient to directly trigger amyloidogenesis. In this work, we followed a reductionist methodology in order to detect critical amyloidogenic "hot-spots" during the fibrillation of LECT2. By associating experimental and computational assays, this approach reveals the explicit amyloidogenic core of human LECT2 and pinpoints regions with distinct amyloidogenic properties. The fibrillar architecture of LECT2 polymers, based on our results, provides a wealth of detailed information about the amyloidogenic "hot-spot" interactions and represents a starting point for future peptide-driven intervention in ALECT2 amyloidosis.

Computational Assessment of Bacterial Protein Structures Indicates a Selection Against Aggregation

The aggregation of proteins compromises cell fitness, either because it titrates functional proteins into non-productive inclusions or because it results in the formation of toxic assemblies. Accordingly, computational proteome-wide analyses suggest that prevention of aggregation upon misfolding plays a key role in sequence evolution. Most proteins spend their lifetimes in a folded state; therefore, it is conceivable that, in addition to sequences, protein structures would have also evolved to minimize the risk of aggregation in their natural environments. By exploiting the AGGRESCAN3D structure-based approach to predict the aggregation propensity of >600 Escherichia coli proteins, we show that the structural aggregation propensity of globular proteins is connected with their abundance, length, essentiality, subcellular location and quaternary structure. These data suggest that the avoidance of protein aggregation has contributed to shape the structural properties of proteins in bacterial cells.

Amyloid Aggregation of Bacillus circulans Xylanase under Native Conditions and its Modulation by β-Amyloid-Derived Peptide Fragments

The aggregation of intrinsically disordered proteins into fibrils is implicated in many neurodegenerative diseases. Amyloid aggregation is a generic property of proteins as evidenced by globular proteins that often form amyloid aggregates under partially denaturing conditions. Recently, multiple lines of evidence have suggested that the amyloid aggregation of globular proteins can also occur under native conditions. Unfortunately, amyloid aggregation under native conditions has been demonstrated in only a handful of cases. Engineering a globular protein's amyloid aggregation might benefit from its fusion to an amyloid-derived fragment with reduced aggregation propensity. Unfortunately, the impacts of such fragments on the amyloid aggregation under native conditions have yet to be examined. In this study, we show that a globular protein, Bacillus circulans xylanase (BCX), can aggregate to form amyloid fibrils under native conditions. When BCX was mixed with or fused to the non-self-aggregating fragments, KLVFWAK and ELVFWAE-which were derived from β-amyloid (Aβ)-they modulated the BCX amyloid aggregation to differing extents. This study also provides insight into a correlation between the kinetic stability and amyloid aggregation of BCX, and supports a view that Aβ-derived fragments can be useful for the modulating amyloid aggregation of some, though not all, proteins.

Modulation of the aggregation of an amyloidogenic sequence by flanking-disordered region in the intrinsically disordered antigen merozoite surface protein 2

The abundant Plasmodium falciparum merozoite surface protein MSP2, a potential malaria vaccine candidate, is an intrinsically disordered protein with some nascent secondary structure present in its conserved N-terminal region. This relatively ordered region has been implicated in both membrane interactions and amyloid-like aggregation of the protein, while the significance of the flanking-disordered region is unclear. In this study, we show that aggregation of the N-terminal conserved region of MSP2 is influenced in a length- and sequence-dependent fashion by the disordered central variable sequences. Intriguingly, MSP2 peptides containing the conserved region and the first five residues of the variable disordered regions aggregated more rapidly than a peptide corresponding to the conserved region alone. In contrast, MSP2 peptides extending 8 or 12 residues into the disordered region aggregated more slowly, consistent with the expected inhibitory effect of flanking-disordered sequences on the aggregation of amyloidogenic ordered sequences. Computational analyses indicated that the helical propensity of the ordered region of MSP2 was modulated by the adjacent disordered five residues in a sequence-dependent manner. Nuclear magnetic resonance and circular dichroism spectroscopic studies with synthetic peptides confirmed the computational predictions, emphasizing the correlation between aggregation propensity and conformation of the ordered region and the effects thereon of the adjacent disordered region. These results show that the effects of flanking-disordered sequences on a more ordered sequence may include enhancement of aggregation through modulation of the conformational properties of the more ordered sequence.

Biomolecular Corona Dictates Aβ Fibrillation Process

Amyloid beta (Aβ), which forms toxic oligomers and fibrils in brain tissues of patients with Alzheimer's disease, is broadly used as a model protein to probe the effect of nanoparticles (NPs) on oligomerization and fibrillation processes. However, the majority of the reports in the field have ignored the effect of the biomolecular corona on the fibrillogenesis of the Aβ proteins. The biomolecular corona, which is a layer composed of various types of biomolecules that covers the surface of NPs upon their interaction with biological fluids, determines the biological fates of NPs. Therefore, during in vivo interaction of NPs with Aβ protein, what the Aβ actually "sees" is the human plasma and/or cerebrospinal fluid (CSF) biomolecular-coated NPs rather than the pristine surface of NPs. Here, to mimic the in vivo effects of therapeutic NPs as antifibrillation agents, we probed the effects of a biomolecular corona derived from human CSF and/or plasma on Aβ fibrillation. The results demonstrated that the type of biomolecular corona can dictate the inhibitory or acceleratory effect of NPs on Aβ_1-42 and Aβ_25-35 fibrillation processes. More specifically, we found that the plasma biomolecular-corona-coated gold NPs, with sphere and rod shapes, has less inhibitory effect on Aβ_1-42 fibrillation kinetics compared with CSF biomolecular-corona-coated and pristine NPs. Opposite results were obtained for Aβ_25-35 peptide, where the pristine NPs accelerated the Aβ_25-35 fibrillation process, whereas corona-coated ones demonstrated an inhibitory effect. In addition, the CSF biomolecular corona had less inhibitory effect than those obtained from plasma.

RFAmyloid: A Web Server for Predicting Amyloid Proteins

Amyloid is an insoluble fibrous protein and its mis-aggregation can lead to some diseases, such as Alzheimer’s disease and Creutzfeldt–Jakob’s disease. Therefore, the identification of amyloid is essential for the discovery and understanding of disease. We established a novel predictor called RFAmy based on random forest to identify amyloid, and it employed SVMProt 188-D feature extraction method based on protein composition and physicochemical properties and pse-in-one feature extraction method based on amino acid composition, autocorrelation pseudo acid composition, profile-based features and predicted structures features. In the ten-fold cross-validation test, RFAmy’s overall accuracy was 89.19% and F-measure was 0.891. Results were obtained by comparison experiments with other feature, classifiers, and existing methods. This shows the effectiveness of RFAmy in predicting amyloid protein. The RFAmy proposed in this paper can be accessed through the URL http://server.malab.cn/RFAmyloid/.