Prediction of the absolute aggregation rates of amyloidogenic polypeptide chains

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

Factors influencing amyloid fibril formation

Protein aggregation is a complex process with several stages that lead to the formation of complex structures and shapes with a broad variability in stability and toxicity. The aggregation process is affected by various factors and environmental conditions that disrupt the protein's original state, including internal factors like mutations, expression levels, and polypeptide chain truncation, as well as external factors, such as dense molecular surroundings, post-translation modifications, and interactions with other proteins, nucleic acids, small molecules, metal ions, chaperones, and lipid membranes. During the aggregation process, the biological activity of an aggregating protein may be reduced or eliminated, whereas the resulting aggregates may have the potential to be immunogenic, or they may have other undesirable properties. Finding the cause(s) of protein aggregation and controlling it to an acceptable level is among the most crucial topics of research in academia and biopharmaceutical companies. This chapter aims to review intrinsic pathways of protein aggregation and potential extrinsic variables that influence this process.

Methotrexate for Drug Repurposing as an Anti-Aggregatory Agent to Mercuric Treated α-Chymotrypsinogen-A

Protein aggregation is related to numerous pathological conditions like Alzheimer's and Parkinson's disease. In our study, we have shown that an already existing FDA-approved drug; methotrexate (MTX) can be reprofiled on preformed α-chymotrypsinogen A (α-Cgn A) aggregates. The zymogen showed formation of aggregates upon interaction with mercuric ions, with increasing concentration of Hg2Cl2 (0-150 µM). The hike in ThT and ANS fluorescence concomitant with blue shift, bathochromic shift and the hyperchromic effect in the CR absorbance, RLS and turbidity measurements, substantiate the zymogen β-rich aggregate formation. The secondary structural alterations of α- Cgn A as analyzed by CD measurements, FTIR and Raman spectra showed the transformation of native β-barrel conformation to β-inter-molecular rich aggregates. The native α- Cgn A have about 30% α-helical content which was found to be about 3% in presence of mercuric ions suggesting the formation of aggregates. The amorphous aggregates were visualized by SEM. On incubation of Hg2Cl2 treated α- Cgn A with increasing concentration of the MTX resulted in reversing aggregates to the native-like structure. These results were supported by remarkable decrease in ThT and ANS fluorescence intensities and CR absorbance and also consistent with CD, FTIR, and Raman spectroscopy data. MTX was found to increase the α-helical content of the zymogen from 3 to 15% proposing that drug is efficient in disrupting the β-inter-molecular rich aggregates and reverting it to native like structure. The SEM images are in accordance with CD data showing the disintegration of aggregates. The most effective concentration of the drug was found to be 120 µM. Molecular docking analysis showed that MTX molecule was surrounded by the hydrophobic residues including Phe39, His40, Arg145, Tyr146, Thr151, Gly193, Ser195, and Gly216 and conventional hydrogen bonds, including Gln73 (bond length: 2.67Å), Gly142 (2.59Å), Thr144 (2.81Å), Asn150 (2.73Å), Asp153 (2.71Å), and Cys191 (2.53Å). This investigation will help to find the use of already existing drugs to cure protein misfolding-related abnormalities.

Amyloid aggregates induced by the p53-R280T mutation lead to loss of p53 function in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a malignant tumor that is highly prevalent in Southeast Asia, especially in South China. The pathogenesis of NPC is complex, and genetic alterations of tumor suppressors and proto-oncogenes play important roles in NPC carcinogenesis. p53 is unexpectedly highly expressed in NPC and possesses an uncommon mutation of R280T, which is different from a high frequency of hotspot mutations or low expression in other tumors. However, the mechanism of p53 loss of function and its correlation with R280T in NPC are still unclear. In this study, p53 amyloid aggregates were found to be widespread in NPC and can be mainly induced by the R280T mutation. Aggregated p53-R280T impeded its entry into the nucleus and was unable to initiate the transcription of downstream target genes, resulting in decreased NPC cell cycle arrest and apoptosis. In addition, NPC cells with p53-R280T amyloid aggregates also contributed aggressively to tumor growth in vivo. Transcriptome analysis suggested that p53 amyloid aggregation dysregulated major signaling pathways associated with the cell cycle, proliferation, apoptosis, and unfolded protein response (UPR). Further studies revealed that Hsp90, as a key molecular chaperone in p53 folding, was upregulated in NPC cells with p53-R280T aggregation, and the upregulated Hsp90 facilitated p53 aggregation in turn, forming positive feedback. Therefore, Hsp90 inhibitors could dissociate p53-R280T aggregation and restore the suppressor function of p53 in vitro and in vivo. In conclusion, our study demonstrated that p53-R280T may misfold to form aggregates with the help of Hsp90, resulting in the inability of sequestered p53 to initiate the transcription of downstream target genes. These results revealed a new mechanism for the loss of p53 function in NPC and provided novel mechanistic insight into NPC pathogenesis.

Amyloid Aggregation Is Potently Slowed Down by Osmolytes Due to Compaction of Partially Folded State

Amyloid aggregation is a key process in amyloidoses and neurodegenerative diseases. Hydrophobicity is one of the major driving forces for this type of aggregation, as an increase in hydrophobicity generally correlates with aggregation susceptibility and rate. However, most experimental systems in vitro and prediction tools in silico neglect the contribution of protective osmolytes present in the cellular environment. Here, we assessed the role of hydrophobic mutations in amyloid aggregation in the presence of osmolytes. To achieve this goal, we used the model protein human muscle acylphosphatase (mAcP) and mutations to leucine that increased its hydrophobicity without affecting its thermodynamic stability. Osmolytes significantly slowed down the aggregation kinetics of the hydrophobic mutants, with an effect larger than that observed on the wild-type protein. The effect increased as the mutation site was closer to the middle of the protein sequence. We propose that the preferential exclusion of osmolytes from mutation-introduced hydrophobic side-chains quenches the aggregation potential of the ensemble of partially unfolded states of the protein by inducing its compaction and inhibiting its self-assembly with other proteins. Our results suggest that including the effect of the cellular environment in experimental setups and predictive softwares, for both mechanistic studies and drug design, is essential in order to obtain a more complete combination of the driving forces of amyloid aggregation.

Energy Landscapes and Heat Capacity Signatures for Monomers and Dimers of Amyloid-Forming Hexapeptides

Amyloid formation is a hallmark of various neurodegenerative disorders. In this contribution, energy landscapes are explored for various hexapeptides that are known to form amyloids. Heat capacity (CV) analysis at low temperature for these hexapeptides reveals that the low energy structures contributing to the first heat capacity feature above a threshold temperature exhibit a variety of backbone conformations for amyloid-forming monomers. The corresponding control sequences do not exhibit such structural polymorphism, as diagnosed via end-to-end distance and a dihedral angle defined for the monomer. A similar heat capacity analysis for dimer conformations obtained using basin-hopping global optimisation shows clear features in end-to-end distance versus dihedral correlation plots, where amyloid-forming sequences exhibit a preference for larger end-to-end distances and larger positive dihedrals. These results hold true for sequences taken from tau, amylin, insulin A chain, a de novo designed peptide, and various control sequences. While there is a little overall correlation between the aggregation propensity and the temperature at which the low-temperature CV feature occurs, further analysis suggests that the amyloid-forming sequences exhibit the key CV feature at a lower temperature compared to control sequences derived from the same protein.

Differential effects of DTT on HEWL amyloid fibrillation and fibril morphology at different pH

Proteins can transform from their native state to a state having fibrillar aggregates characterized by cross β sheet structure. The fibrillar aggregates are known as amyloid and have been linked to several disorders. Disulfide bonds in proteins are one of the important factors that determine the propensity of aggregation. Hen Egg White Lysozyme (HEWL) was used by us as a model protein to decipher the role disulfide bonds play in the amyloid fibril formation and fibril morphology by using Dithiothreitol (DTT) as reducing agent at pH 2.7 and pH 7.4. We found that DTT can have different effects on HEWL amyloid depending on pH and the buffer used for preparing the amyloid fibrils. Our studies highlight the critical role of non-native disulfide bonds in amyloidogenesis and how disruption of these bonds can greatly affect the fibrillation process. Overall, these studies throw light on the fibrillation mechanism and can be explored further in designing effective inhibitors against amyloidosis.

Potential of tetradecyltrimethylammonium bromide in preventing fibrillation/aggregation of lysozyme: biophysical studies

A key step in the prevention of neurodegenerative disorders is to inhibit protein aggregation or fibrillation process. Functionality recognition is an essential strategy in developing effective therapeutics in addressing the treatment of amyloidosis. Here, we have focused on an approach based on structure-property energetics correlation associated with tetradecyltrimethylammonium bromide (TTAB), a cationic surfactant that acts as an inhibitor targeting different stages of hen egg-white lysozyme fibrillation. Characterization of amyloid fibrils and the inhibitory capability of 16 mM TTAB surfactant on fibrillation were investigated with the calorimetric, spectroscopic and microscopic techniques. ThT binding fluorescence studies inferred that micellar TTAB exerts its maximum inhibitory effect against amyloid fibrillation than monomer TTAB. The TEM measurements also confirmed complete absence of amyloid fibrils at micellar TTAB. At the same time, the transformation of β-sheet to α-helix under the action of TTAB was confirmed by the Far-UV CD spectroscopy. Although there have been some reports suggesting that cationic surfactants can induce aggregation in proteins, this work suggests that polar interactions between head groups of TTAB and amyloid fibrils are the predominant factors that cause retardation in fibrillation by interrupting/disturbing the intermolecular hydrogen bond of β-sheets. The present finding has explored the knowledge-based details in developing efficient potent inhibitors and provides a platform to treat diseases associated with protein misfolding.Communicated by Ramaswamy H. Sarma.

The role of heat shock proteins in preventing amyloid toxicity

The oligomerization of monomeric proteins into large, elongated, β-sheet-rich fibril structures (amyloid), which results in toxicity to impacted cells, is highly correlated to increased age. The concomitant decrease of the quality control system, composed of chaperones, ubiquitin-proteasome system and autophagy-lysosomal pathway, has been shown to play an important role in disease development. In the last years an increasing number of studies has been published which focus on chaperones, modulators of protein conformational states, and their effects on preventing amyloid toxicity. Here, we give a comprehensive overview of the current understanding of chaperones and amyloidogenic proteins and summarize the advances made in elucidating the impact of these two classes of proteins on each other, whilst also highlighting challenges and remaining open questions. The focus of this review is on structural and mechanistic studies and its aim is to bring novices of this field "up to speed" by providing insight into all the relevant processes and presenting seminal structural and functional investigations.

p53 amyloid aggregation in cancer: function, mechanism, and therapy

Similar to neurodegenerative diseases, the concept that tumors are prion like diseases has been proposed in recent years. p53, the most well-known tumor suppressor, has been extensively studied for its expression, mutation, and function in various tumors. Currently, an interesting phenomenon of p53 prion-like aggregation has been found in several tumors, and studies have found that its pathological aggregation may lead to functional alterations and ultimately affect tumor progression. It has been demonstrated that the mechanism of p53 aggregation involves its mutation, domains, isoform, etc. In addition to p53 itself, some other factors, including Zn²⁺ concentration, pH, temperature and chaperone abnormalities, can also contribute to p53 aggregation. Although there are some studies about the mechanism and role of p53 aggregation and amyloidosis in tumors, there still exist some controversies. In this paper, we review the mechanism of p53 amyloid fibril structure and discuss the characteristics and effects of p53 amyloid aggregation, as well as the pathogenic mechanism leading to the occurrence of aggregation in tumors. Finally, we summarize the various inhibitors targeting p53 aggregation and prion-like behavior. In conclusion, a comprehensive understanding of p53 aggregation can expand our understanding of the causes leading its loss of physiological function and that targeting p53 aggregation might be a promising therapeutic strategy for tumor therapy.

Evolution of homo-oligomerization of methionine S-adenosyltransferases is replete with structure-function constrains

Homomers are prevalent in bacterial proteomes, particularly among core metabolic enzymes. Homomerization is often key to function and regulation, and interfaces that facilitate the formation of homomeric enzymes are subject to intense evolutionary change. However, our understanding of the molecular mechanisms that drive evolutionary variation in homomeric complexes is still lacking. How is the diversification of protein interfaces linked to variation in functional regulation and structural integrity of homomeric complexes? To address this question, we studied quaternary structure evolution of bacterial methionine S‐adenosyltransferases (MATs)—dihedral homotetramers formed along a large and conserved dimeric interface harboring two active sites, and a small, recently evolved, interdimeric interface. Here, we show that diversity in the physicochemical properties of small interfaces is directly linked to variability in the kinetic stability of MAT quaternary complexes and in modes of their functional regulation. Specifically, hydrophobic interactions within the small interface of Escherichia coli MAT render the functional homotetramer kinetically stable yet impose severe aggregation constraints on complex assembly. These constraints are alleviated by electrostatic interactions that accelerate dimer‐dimer assembly. In contrast, Neisseria gonorrhoeae MAT adopts a nonfunctional dimeric state due to the low hydrophobicity of its small interface and the high flexibility of its active site loops, which perturbs small interface integrity. Remarkably, in the presence of methionine and ATP, N. gonorrhoeae MAT undergoes substrate‐induced assembly into a functional tetrameric state. We suggest that evolution acts on the interdimeric interfaces of MATs to tailor the regulation of their activity and stability to unique organismal needs.

PDB Code(s): 7R2W;7R3B;

Peptide Model of the Mutant Proinsulin Syndrome. II. Nascent Structure and Biological Implications

Toxic misfolding of proinsulin variants in β-cells defines a monogenic diabetes syndrome, designated mutant INS-gene induced diabetes of the young (MIDY). In our first study (previous article in this issue), we described a one-disulfide peptide model of a proinsulin folding intermediate and its use to study such variants. The mutations (LeuB15→Pro, LeuA16→Pro, and PheB24→Ser) probe residues conserved among vertebrate insulins. In this companion study, we describe 1H and 1H-13C NMR studies of the peptides; key NMR resonance assignments were verified by synthetic 13C-labeling. Parent spectra retain nativelike features in the neighborhood of the single disulfide bridge (cystine B19-A20), including secondary NMR chemical shifts and nonlocal nuclear Overhauser effects. This partial fold engages wild-type side chains LeuB15, LeuA16 and PheB24 at the nexus of nativelike α-helices α1 and α3 (as defined in native proinsulin) and flanking β-strand (residues B24-B26). The variant peptides exhibit successive structural perturbations in order: parent (most organized) > SerB24 >> ProA16 > ProB15 (least organized). The same order pertains to (a) overall α-helix content as probed by circular dichroism, (b) synthetic yields of corresponding three-disulfide insulin analogs, and (c) ER stress induced in cell culture by corresponding mutant proinsulins. These findings suggest that this and related peptide models will provide a general platform for classification of MIDY mutations based on molecular mechanisms by which nascent disulfide pairing is impaired. We propose that the syndrome's variable phenotypic spectrum-onsets ranging from the neonatal period to later in childhood or adolescence-reflects structural features of respective folding intermediates.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

The role of intra and inter-molecular disulfide bonds in modulating amyloidogenesis: A review

All proteins have the inherent ability to undergo transformation from their native structure to a β sheet rich fibrillar structure, called amyloid when subjected to specific conditions. Proteins with a high propensity to form amyloid fibrils have been implicated in a variety of disorders like Alzheimer's disease, Parkinson's disease, Type II diabetes, Amyotrophic Lateral Sclerosis (ALS) and prion diseases. Among the various critical factors that modulate the process of amyloid formation, disulfide bonds have been identified as one of the key determinants of amyloid propensity in proteins. Studies have shown that intra-molecular disulfide bonds impart stability to the native structure of a protein and decrease the tendency for amyloid aggregation, whereas intermolecular disulfide bonds aid in the process of aggregation. In this review, we will analyze the varying effects of both intra as well as inter-molecular disulfide bonds on the amyloid aggregation propensities of a few proteins associated with amyloid disorders.

De novo design of peptides that coassemble into β sheet-based nanofibrils

Peptides’ hierarchical coassembly into nanostructures enables controllable fabrication of multicomponent biomaterials. In this work, we describe a computational and experimental approach to design pairs of charge-complementary peptides that selectively coassemble into β-sheet nanofibers when mixed together but remain unassembled when isolated separately. The key advance is a peptide coassembly design (PepCAD) algorithm that searches for pairs of coassembling peptides. Six peptide pairs are identified from a pool of ~10⁶ candidates via the PepCAD algorithm and then subjected to DMD/PRIME20 simulations to examine their co-/self-association kinetics. The five pairs that spontaneously aggregate in kinetic simulations selectively coassemble in biophysical experiments, with four forming β-sheet nanofibers and one forming a stable nonfibrillar aggregate. Solid-state NMR, which is applied to characterize the coassembling pairs, suggests that the in silico peptides exhibit a higher degree of structural order than the previously reported CATCH(+/−) peptides.

Determination of amyloid core regions of insulin analogues fibrils

A rapid-acting insulin lispro and long-acting insulin glargine are commonly used for the treatment of diabetes. Clinical cases have described the formation of injectable amyloidosis with these insulin analogues, but their amyloid core regions of fibrils were unknown. To reveal these regions, we have analysed the hydrolyzates of insulin fibrils and its analogues using high-performance liquid chromatography and mass spectrometry methods and found that insulin and its analogues have almost identical amyloid core regions that intersect with the predicted amyloidogenic regions. The obtained results can be used to create new insulin analogues with a low ability to form fibrils.

Abbreviations

a.a., amino acid residues; HPLC-MS, high-performance liquid chromatography/mass spectrometry; m/z, mass-to-charge ratio; TEM, transmission electron microscopy.

Nicking and fragmentation are responsible for α-lactalbumin amyloid fibril formation at acidic pH and elevated temperature

Amyloid fibrils are ordered aggregates that may be formed from disordered, partially unfolded, and fragments of proteins and peptides. There are several diseases, which are due to the formation and deposition of insoluble β-sheet protein aggregates in various tissue, collectively known as amyloidosis. Here, we have used bovine α-lactalbumin as a model protein to understand the mechanism of amyloid fibril formation at pH 1.6 and 65°C under non-reducing conditions. Amyloid fibril formation is confirmed by Thioflavin T fluorescence and atomic force microscopy (AFM). Our finding demonstrates that hydrolysis of peptide bonds occurs under these conditions, which results in nicking and fragmentation. The nicking and fragmentation have been confirmed on non-reducing and reducing gel. We have identified the fragments by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry. The fragmentation may initiate nucleation as it coincides with AFM images. Conformational changes associated with monomer resulting in fibrillation are shown by circular dichroism and Raman spectroscopy. The current study highlights the importance of nicking and fragmentation in amyloid fibril formation, which may help understand the role of acidic pH and proteolysis under in vivo conditions in the initiation of amyloid fibril formation.

AbsoluRATE: An in-silico method to predict the aggregation kinetics of native proteins

Protein aggregation has two aspects, namely, mechanistic and kinetics. Understanding protein aggregation kinetics is critical for prediction of progression of diseases caused by amyloidosis, accumulation of aggregates in biotherapeutics during storage and engineering commercial nano-biomaterials. In this work, we have collected experimentally determined absolute protein aggregation rates and developed an SVM based regression model to predict absolute rates of protein and peptide aggregation near-physiological conditions. The regression model achieved a correlation coefficient of 0.72 with MAE of 0.91 (natural log of k_app, where k_app is in hour^-1) using leave-one-out cross-validation on a dataset of 82 non-redundant proteins/peptides. The model accounts for the experimental conditions (such as temperature, pH, ionic and protein concentration) and sequence-based properties. The amino acid sequence features revealed by this model as being important for aggregation kinetics, are also associated with the aggregation mechanism. In particular, inherent aggregation propensity of the protein/peptide sequence and number of aggregation prone regions (APRs) unpunctuated by the gatekeeping residues, were found to play important roles in the prediction of the absolute aggregation rates. This analysis shows that mechanism and kinetics of protein aggregation are coupled via common sequence attributes. The aggregation kinetic prediction method developed in this work is available at https://web.iitm.ac.in/bioinfo2/absolurate-pred/index.html.

Protein nanofibril design via manipulation of hydrogen bonds

The process of amyloid nanofibril formation has broad implications including the generation of the strongest natural materials, namely silk fibers, and their major contribution to the progression of many degenerative diseases. The key question that remains unanswered is whether the amyloidogenic nature, which includes the characteristic H-bonded β-sheet structure and physical characteristics of protein assemblies, can be modified via controlled intervention of the molecular interactions. Here we show that tailored changes in molecular interactions, specifically in the H-bonded network, do not affect the nature of amyloidogenic fibrillation, and even have minimal effect on the initial nucleation events of self-assembly. However, they do trigger changes in networks at a higher hierarchical level, namely enhanced 2D packaging which is rationalized by the 3D hierarchy of β-sheet assembly, leading to variations in fibril morphology, structural composition and, remarkably, nanomechanical properties. These results pave the way to a better understanding of the role of molecular interactions in sculpting the structural and physical properties of protein supramolecular constructs.

The concept of protein folding/unfolding and its impacts on human health

Proteins have evolved in specific 3D structures and play different functions in cells and determine various reactions and pathways. The newly synthesized amino acid chains once depart ribosome must crumple into three-dimensional structures so can be biologically active. This process of protein that makes a functional molecule is called protein folding. The protein folding is both a biological and a physicochemical process that depends on the sequence of it. In fact, this process occurs more complicated and in some cases and in exposure to some molecules like glucose (glycation), mistaken folding leads to amyloid structures and fatal disorders called conformational diseases. Such conditions are detected by the quality control system of the cell and these abnormal proteins undergo renovation or degradation. This scenario takes place by the chaperones, chaperonins, and Ubiquitin-proteasome complex. Understanding of protein folding mechanisms from different views including experimental and computational approaches has revealed some intermediate ensembles such as molten globule and has been subjected to biophysical and molecular biology attempts to know more about prevalent conformational diseases.

A theoretical study of polymorphism in VQIVYK fibrils

The VQIVYK fragment from the Tau protein, also known as PHF6, is essential for aggregation of Tau into neurofibrillary lesions associated with neurodegenerative diseases. VQIVYK itself forms amyloid fibrils composed of paired β-sheets. Therefore, the full Tau protein and VQIVYK fibrils have been intensively investigated. A central issue in these studies is polymorphism, the ability of a protein to fold into more than one structure. Using all-atom molecular simulations, we generate five stable polymorphs of VQIVYK fibrils, establish their relative free energy with umbrella sampling methods, and identify the side chain interactions that provide stability. The two most stable polymorphs, which have nearly equal free energy, are formed by interdigitation of the mostly hydrophobic VIY "face" sides of the β-sheets. Another stable polymorph is formed by interdigitation of the QVK "back" sides. When we turn to examine structures from cryo-electron microscopy experiments on Tau filaments taken from diseased patients or generated in vitro, we find that the pattern of side chain interactions found in the two most stable face-to-face as well as the back-to-back polymorphs are recapitulated in amyloid structures of the full protein. Thus, our studies suggest that the interactions stabilizing PHF6 fibrils explain the amyloidogenicity of the VQIVYK motif within the full Tau protein and provide justification for the use of VQIVYK fibrils as a test bed for the design of molecules that identify or inhibit amyloid structures.

Protein aggregation: in silico algorithms and applications

Protein aggregation is a topic of immense interest to the scientific community due to its role in several neurodegenerative diseases/disorders and industrial importance. Several in silico techniques, tools, and algorithms have been developed to predict aggregation in proteins and understand the aggregation mechanisms. This review attempts to provide an essence of the vast developments in in silico approaches, resources available, and future perspectives. It reviews aggregation-related databases, mechanistic models (aggregation-prone region and aggregation propensity prediction), kinetic models (aggregation rate prediction), and molecular dynamics studies related to aggregation. With a multitude of prediction models related to aggregation already available to the scientific community, the field of protein aggregation is rapidly maturing to tackle new applications.

Proteostasis of Islet Amyloid Polypeptide: A Molecular Perspective of Risk Factors and Protective Strategies for Type II Diabetes

The possible link between hIAPP accumulation and β-cell death in diabetic patients has inspired numerous studies focusing on amyloid structures and aggregation pathways of this hormone. Recent studies have reported on the importance of early oligomeric intermediates, the many roles of their interactions with lipid membrane, pH, insulin, and zinc on the mechanism of aggregation of hIAPP. The challenges posed by the transient nature of amyloid oligomers, their structural heterogeneity, and the complex nature of their interaction with lipid membranes have resulted in the development of a wide range of biophysical and chemical approaches to characterize the aggregation process. While the cellular processes and factors activating hIAPP-mediated cytotoxicity are still not clear, it has recently been suggested that its impaired turnover and cellular processing by proteasome and autophagy may contribute significantly toward toxic hIAPP accumulation and, eventually, β-cell death. Therefore, studies focusing on the restoration of hIAPP proteostasis may represent a promising arena for the design of effective therapies. In this review we discuss the current knowledge of the structures and pathology associated with hIAPP self-assembly and point out the opportunities for therapy that a detailed biochemical, biophysical, and cellular understanding of its aggregation may unveil.

AggreRATE-Pred: a mathematical model for the prediction of change in aggregation rate upon point mutation

MOTIVATION

Protein aggregation is a major unsolved problem in biochemistry with implications for several human diseases, biotechnology and biomaterial sciences. A majority of sequence-structural properties known for their mechanistic roles in protein aggregation do not correlate well with the aggregation kinetics. This limits the practical utility of predictive algorithms.

RESULTS

We analyzed experimental data on 183 unique single point mutations that lead to change in aggregation rates for 23 polypeptides and proteins. Our initial mathematical model obtained a correlation coefficient of 0.43 between predicted and experimental change in aggregation rate upon mutation (P-value <0.0001). However, when the dataset was classified based on protein length and conformation at the mutation sites, the average correlation coefficient almost doubled to 0.82 (range: 0.74-0.87; P-value <0.0001). We observed that distinct sequence and structure-based properties determine protein aggregation kinetics in each class. In conclusion, the protein aggregation kinetics are impacted by local factors and not by global ones, such as overall three-dimensional protein fold, or mechanistic factors such as the presence of aggregation-prone regions.

AVAILABILITY AND IMPLEMENTATION

The web server is available at http://www.iitm.ac.in/bioinfo/aggrerate-pred/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Macromolecular crowding stabilises native structure of α-chymotrypsinogen-A against hexafluoropropanol-induced aggregates

Cell interior is extremely congested with tightly packed biological macromolecules that exerts macromolecular crowding effect, influencing biophysical properties of proteins. To have a deeper insight into it we studied consequences of crowding on aggregation susceptibility and structural stability of α-chymotrypsinogen-A, pro-enzyme of serine protease family, upon addition of co-solvent reported to exert stress on polypeptides crafting favourable conditions for aggregation. Hexafluoropropan-2-ol (HFIP), a fluorinated alcohol caused structural disruption at 5% v/v unveiled by reduced intrinsic intensity and blue shifted ANS spectra. Significantly enhanced, red-shifted ThT and Congo red spectra sustained conformational changes concomitant with aggregation. FTIR and CD results confirmed transition of native structure to non-native extended, cross-linked beta-sheets. Transmission electron micrographs visibly exhibited incidence of amorphous aggregates. Macromolecular crowding, typically mimicked by concentrated solutions of dextran 70, was noticeably witnessed to defend conformational stability under denaturing condition. The native structure was retained maximally in presence of 100 mg/ml followed by 200 and 300 mg/ml dextran indicating concentration dependent deceleration of aggregate formation. It can be established that explicit consideration of crowding effects using relevant range of inert crowding agents must be a requisite for presumptions on intracellular conformational behaviour of proteins deduced from in vitro experiments.

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.

CPAD 2.0: a repository of curated experimental data on aggregating proteins and peptides

The Curated Protein Aggregation Database (CPAD) is a manually curated and open-access database dedicated to providing comprehensive information related to mechanistic, kinetic and structural aspects of protein and peptide aggregation. The database has been updated to CPAD 2.0 by significantly expanding datasets and improving the user-interface. Key features of CPAD 2.0 are (i) 83,098 data points on aggregation kinetics experiments, (ii) 565 structures related to aggregation, which are classified into proteins, fibrils, and protein-ligand complexes, (iii) 2031 aggregating/non-aggregating peptides with pre-calculated aggregation properties, and (iv) 912 aggregation-prone regions in amyloidogenic proteins. This database will help the scientific community (a) by facilitating research leading to improved understanding of protein aggregation, (b) by helping develop, validate and benchmark mechanistic and kinetic models of protein aggregation, and (c) by assisting experimentalists with design of their investigations and dissemination of data generated by their studies. CPAD 2.0 can be accessed at https://web.iitm.ac.in/bioinfo2/cpad2/index.html.

Protein Solubility Predictions Using the CamSol Method in the Study of Protein Homeostasis

One of the major functions of the protein homeostasis system is to maintain proteins in their soluble states, and indeed several human disorders are associated with the aberrant aggregation of proteins. An active involvement of the protein homeostasis system is necessary to avoid aggregation because proteins are expressed at levels close to their solubility limits, hence being poorly soluble. The mechanisms by which the protein homeostasis system acts to control protein aggregation are, however, still not known in much detail. To facilitate systematic investigations of these mechanisms, we describe here the CamSol method of predicting protein solubility, and illustrate its initial applications. We anticipate that with the advent of powerful proteomics and transcriptomic methods, in combination with the use of the CamSol method and related approaches to predict the solubility and other biophysical properties of proteins, it will become possible to increase our understanding of the principles of protein homeostasis related to the maintenance of the proteome in its soluble form.

Considerations on the Rational Design of Covalently Conjugated Cell-Penetrating Peptides (CPPs) for Intracellular Delivery of Proteins: A Guide to CPP Selection Using Glucarpidase as the Model Cargo Molecule

Access of proteins to their intracellular targets is limited by a hydrophobic barrier called the cellular membrane. Conjugation with cell-penetrating peptides (CPPs) has been shown to improve protein transduction into the cells. This conjugation can be either covalent or non-covalent, each with its unique pros and cons. The CPP-protein covalent conjugation may result in undesirable structural and functional alterations in the target protein. Therefore, we propose a systematic approach to evaluate different CPPs for covalent conjugations. This guide is presented using the carboxypeptidase G2 (CPG2) enzyme as the target protein. Seventy CPPs —out of 1155— with the highest probability of uptake efficiency were selected. These peptides were then conjugated to the N- or C-terminus of CPG2. Translational efficacy of the conjugates, robustness and thermodynamic properties of the chimera, aggregation possibility, folding rate, backbone flexibility, and aspects of in vivo administration such as protease susceptibility were predicted. The effect of the position of conjugation was evaluated using unpaired t-test (p < 0.05). It was concluded that N-terminal conjugation resulted in higher quality constructs. Seventeen CPP-CPG2/CPG2-CPP constructs were identified as the most promising. Based on this study, the bioinformatics workflow that is presented may be universally applied to any CPP-protein conjugate design.

Protein Microgels from Amyloid Fibril Networks

Nanofibrillar forms of amyloidogenic proteins were initially discovered in the context of protein misfolding and disease but have more recently been found at the origin of key biological functionality in many naturally occurring functional materials, such as adhesives and biofilm coatings. Their physiological roles in nature reflect their great strength and stability, which has led to the exploration of their use as the basis of artificial protein-based functional materials. Particularly for biomedical applications, they represent attractive building blocks for the development of, for instance, drug carrier agents due to their inherent biocompatibility and biodegradability. Furthermore, the propensity of proteins to self-assemble into amyloid fibrils can be exploited under microconfinement, afforded by droplet microfluidic techniques. This approach allows the generation of multi-scale functional microgels that can host biological additives and can be designed to incorporate additional functionality, such as to aid targeted drug delivery.

Prediction of amyloid aggregation rates by machine learning and feature selection

A novel data-based machine learning algorithm for predicting amyloid aggregation rates is reported in this paper. Based on a highly nonlinear projection from 16 intrinsic features of a protein and 4 extrinsic features of the environment to the protein aggregation rate, a feedforward fully connected neural network (FCN) with one hidden layer is trained on a dataset composed of 21 different kinds of amyloid proteins and tested on 4 rest proteins. FCN shows a much better performance than traditional algorithms, such as multivariable linear regression and support vector regression, with an average accuracy higher than 90%. Furthermore, by the correlation analysis and the principal component analysis, seven key features, folding energy, HP patterns for helix, sheet and helices cross membrane, pH, ionic strength, and protein concentration, are shown to constitute a minimum feature set for characterizing the amyloid aggregation kinetics.

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.

Unified theoretical description of the kinetics of protein aggregation

Solution conditions chosen for the production of amyloid can also promote formation of significant extents of amorphous protein aggregate. In one interpretation, the amyloid and amorphous aggregation pathways are considered to be in competition with each other. An alternative conceptualization involves considering amorphous aggregation as an obligatory intermediate process of the amyloid formation pathway. Here, we review recently developed macroscopic-level theories of protein aggregation that unify these two competing models into a single paradigm. Key features of the unified model included (1) a description of the amorphous aggregate as a second liquid phase with the degree of liquid-like character determined by the mobility of the monomer within it, and (2) heterogeneous growth pathways based on nucleation, growth, and fragmentation of amyloid occurring within different phases and at their interfacial boundary. Limiting-case behaviors of the protein aggregation reaction, either singly involving amyloid or amorphous aggregate production, and mixed-case behaviors, involving competitive and/or facilitated growth of amorphous and amyloid species, are presented and reviewed in context. This review principally describes an approach developed by Hirota and Hall 2019 (Hirota, N. and Hall, D. 2019. Protein Aggregation Kinetics: A Unified Theoretical Description. Chapter 7 of 'Protein Solubility and Amorphous Aggregation: From Academic Research to Applications in Drug Discovery and Bioindustry' edited by Y. Kuroda and F. Arisaka. CMC Publishers). Sections of that work are translated from the original Japanese and republished here with the full permission of CMC Publishing Corporation.

Protein engineering approaches for antibody fragments: directed evolution and rational design approaches

The number of therapeutic antibodies in preclinical, clinical, or approved phases has been increasing exponentially, mostly due to their known successes. Development of antibody engineering methods has substantially hastened the development of therapeutic antibodies. A variety of protein engineering techniques can be applied to antibodies to improve their afinity and/or biophysical properties such as solubility and stability. Antibody fragments (where all or some parts of constant regions are eliminated while the essential antigen binding region is preserved) are more suitable for protein engineering techniques because there are many in vitro screening technologies available for antibody fragments but not full-length antibodies. Improvement of biophysical characteristics is important in the early development phase because most antibodies fail at the later stage of development and this leads to loss of resources and time. Here, we review directed evolution and rational design methods to improve antibody properties. Recent developments in rational design approaches and antibody display technologies, and especially phage display, which was recently awarded the 2018 Nobel Prize, are discussed to be used in antibody research and development.

Increased sequence hydrophobicity reduces conformational specificity: A mutational case study of the Arc repressor protein

The amino-acid sequences of soluble, globular proteins must have hydrophobic residues to form a stable core, but excess sequence hydrophobicity can lead to loss of native state conformational specificity and aggregation. Previous studies of polar-to-hydrophobic mutations in the β-sheet of the Arc repressor dimer showed that a single substitution at position 11 (N11L) leads to population of an alternate dimeric fold in which the β-sheet is replaced by helix. Two additional hydrophobic mutations at positions 9 and 13 (Q9V and R13V) lead to population of a differently folded octamer along with both dimeric folds. Here we conduct a comprehensive study of the sequence determinants of this progressive loss of fold specificity. We find that the alternate dimer-fold specifically results from the N11L substitution and is not promoted by other hydrophobic substitutions in the β-sheet. We also find that three highly hydrophobic substitutions at positions 9, 11, and 13 are necessary and sufficient for oligomer formation, but the oligomer size depends on the identity of the hydrophobic residue in question. The hydrophobic substitutions increase thermal stability, illustrating how increased hydrophobicity can increase folding stability even as it degrades conformational specificity. The oligomeric variants are predicted to be aggregation-prone but may be hindered from doing so by proline residues that flank the β-sheet region. Loss of conformational specificity due to increased hydrophobicity can manifest itself at any level of structure, depending upon the specific mutations and the context in which they occur.

Cause and consequence of Aβ - Lipid interactions in Alzheimer disease pathogenesis

Self-templating propagation of protein aggregate conformations is increasingly becoming a significant factor in many neurological diseases. In Alzheimer disease (AD), intrinsically disordered amyloid-β (Aβ) peptides undergo aggregation that is sensitive to environmental conditions. High-molecular weight aggregates of Aβ that form insoluble fibrils are deposited as senile plaques in AD brains. However, low-molecular weight aggregates called soluble oligomers are known to be the primary toxic agents responsible for neuronal dysfunction. The aggregation process is highly stochastic involving both homotypic (Aβ-Aβ) and heterotypic (Aβ with interacting partners) interactions. Two of the important members of interacting partners are membrane lipids and surfactants, to which Aβ shows a perpetual association. Aβ-membrane interactions have been widely investigated for more than two decades, and this research has provided a wealth of information. Although this has greatly enriched our understanding, the objective of this review is to consolidate the information from the literature that collectively showcases the unique phenomenon of lipid-mediated Aβ oligomer generation, which has largely remained inconspicuous. This is especially important because Aβ aggregate "strains" are increasingly becoming relevant in light of the correlations between the structure of aggregates and AD phenotypes. Here, we will focus on aspects of Aβ-lipid interactions specifically from the context of how lipid modulation generates a wide variety of biophysically and biochemically distinct oligomer sub-types. This, we believe, will refocus our thinking on the influence of lipids and open new approaches in delineating the mechanisms of AD pathogenesis. This article is part of a Special Issue entitled: Protein Aggregation and Misfolding at the Cell Membrane Interface edited by Ayyalusamy Ramamoorthy.

In Silico Methods in Antibody Design

Antibody therapies with high efficiency and low toxicity are becoming one of the major approaches in antibody therapeutics. Based on high-throughput sequencing and increasing experimental structures of antibodies/antibody-antigen complexes, computational approaches can predict antibody/antigen structures, engineering the function of antibodies and design antibody-antigen complexes with improved properties. This review summarizes recent progress in the field of in silico design of antibodies, including antibody structure modeling, antibody-antigen complex prediction, antibody stability evaluation, and allosteric effects in antibodies and functions. We listed the cases in which these methods have helped experimental studies to improve the affinities and physicochemical properties of antibodies. We emphasized how the molecular dynamics unveiled the allosteric effects during antibody-antigen recognition and antibody-effector recognition.

A sticky situation: Aberrant protein-protein interactions in Parkinson's disease

The aberrant aggregation of normally soluble proteins into amyloid fibrils is the pathological hallmark of several neurodegenerative disorders, including Alzheimer's and Parkinson's diseases. Understanding this process will be key to developing both diagnostic and therapeutic approaches for neurodegenerative diseases. Recent advances in biophysical techniques, coupled with kinetic analyses have enabled a thorough description of the key molecular steps involved in protein aggregation. In this review, we discuss these advances and how they have been applied to study the ability of one such protein, α-Synuclein, to form neurotoxic oligomers.

Strikingly different effects of cholesterol and 7-ketocholesterol on lipid bilayer-mediated aggregation of amyloid beta (1-42)

Oxidized cholesterol has been widely reported to contribute to the pathogenesis of Alzheimer's disease (AD). However, the mechanism by which they affect the disease is not fully understood. Herein, we aimed to investigate the effect of 7-ketocholesterol (7keto) on membrane-mediated aggregation of amyloid beta (Aβ-42), one of the critical pathogenic events in AD. We have shown that when cholesterol is present in lipid vesicles, kinetics of Aβ nuclei formation is moderately hindered while that of fibril growth was considerably accelerated. The partial substitution of cholesterol with 7keto slightly enhanced the formation of Aβ-42 nuclei and remarkably decreased fibril elongation, thus maintaining the peptide in protofibrillar aggregates, which are reportedly the most toxic species. These findings add in understanding of how cholesterol and its oxidation can affect Aβ-induced cytotoxicity.

•

Cholesterol and 7-ketocholesterol membranes had different effects on Aβ aggregation.

•

Cholesterol-containing membranes considerably accelerated fibril elongation of Aβ-42.

•

7-ketocholesterol membranes remarkably decreased Aβ-42 fibril elongation.