Prediction of "aggregation-prone" and "aggregation-susceptible" regions in proteins associated with neurodegenerative diseases

Red emissive fluorescent carbon dots based on ternary carbon source for imaging α-synuclein fibrils

The misfolding and aggregation of α-synuclein monomers usually cause the occurrence and development of Parkinson's disease (PD). It is important to develop effective methods for detection of α-synuclein aggregates. Carbon dots (CDs) could be the potential fluorescence probe for this purpose owing to their appreciated optical properties. However, undefined structure of CDs and complicated three-dimensional structure of protein severely hindered the design of fluorescence probe towards protein aggregates. Herein, a red emissive fluorescent amphiphilic CD, named as CL-9, was designed with a high sensitivity to α-synuclein fibrils by a one-step heating process, using the ternary carbon source, including Congo red, l-tryptophan and urea. The CL-9 exhibited turn-on red emissive fluorescence towards α-synuclein fibril, but remained no change towards its monomer. Compared with the original Congo red dye, CL-9 exhibited stronger turn-on red fluorescence towards α-synuclein fibrils with better anti-photobleaching resistance, biocompatibility and signal-to-noise ratio. The CL-9 was successful as a fluorescent probe to image α-synuclein fibrils in NL-5901 C. elegans. The present study provided a feasible approach using the multiple carbon sources to construct the CDs based fluorescence probe targeting amyloid proteins.

Structures prediction and replica exchange molecular dynamics simulations of α-synuclein: A case study for intrinsically disordered proteins

In recent years, a variety of three-dimensional structure prediction tools, including AlphaFold2, AlphaFold3, I-TASSER, C-I-TASSER, Phyre2, ESMFold, and RoseTTAFold, have been employed in the investigation of intrinsically disordered proteins. However, a comprehensive validation of these tools specifically for intrinsically disordered proteins has yet to be conducted. In this study, we utilize AlphaFold2, AlphaFold3, I-TASSER, C-I-TASSER, Phyre2, ESMFold, and RoseTTAFold to predict the structure of a model intrinsically disordered α-synuclein protein. Additionally, extensive replica exchange molecular dynamics simulations of the intrinsically disordered protein are conducted. The resulting structures from both structure prediction tools and replica exchange molecular dynamics simulations are analyzed for radius of gyration, secondary and tertiary structure properties, as well as Cα and Hα chemical shift values. A comparison of the obtained results with experimental data reveals that replica exchange molecular dynamics simulations provide results in excellent agreement with experimental observations. However, none of the structure prediction tools utilized in this study can fully capture the structural characteristics of the model intrinsically disordered protein. This study shows that a cluster of ensembles are required for intrinsically disordered proteins. Artificial-intelligence based structure prediction tools such as AlphaFold3 and C-I-TASSER could benefit from stochastic sampling or Monte Carlo simulations for generating an ensemble of structures for intrinsically disordered proteins.

Amyloid Beta Leads to Decreased Acetylcholine Levels and Non-Small Cell Lung Cancer Cell Survival via a Mechanism That Involves p38 Mitogen-Activated Protein Kinase and Protein Kinase C in a p53-Dependent and -Independent Manner

Several studies have shown an inverse correlation between the likelihood of developing a neurodegenerative disorder and cancer. We previously reported that the levels of amyloid beta (Aβ), at the center of Alzheimer's disease pathophysiology, are regulated by acetylcholinesterase (AChE) in non-small cell lung cancer (NSCLC). Here, we examined the effect of Aβ or its fragments on the levels of ACh in A549 (p53 wild-type) and H1299 (p53-null) NSCLC cell media. ACh levels were reduced by cell treatment with Aβ 1-42, Aβ 1-40, Aβ 1-28, and Aβ 25-35. AChE and p53 activities increased upon A549 cell treatment with Aβ, while knockdown of p53 in A549 cells increased ACh levels, decreased AChE activity, and diminished the Aβ effects. Aβ increased the ratio of phospho/total p38 MAPK and decreased the activity of PKC. Inhibiting p38 MAPK reduced the activity of p53 in A549 cells and increased ACh levels in the media of both cell lines, while opposite effects were found upon inhibiting PKC. ACh decreased the activity of p53 in A549 cells, decreased p38 MAPK activity, increased PKC activity, and diminished the effect of Aβ on those activities. Moreover, the negative effect of Aβ on cell viability was diminished by cell co-treatment with ACh.

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.

Computational investigation on the conformational dynamics of C-terminal truncated α-synuclein bound to membrane

Accelerated progression rates in Parkinson's disease (PD) have been linked to C-terminal domain (CTD) truncations of monomeric α-Synuclein (α-Syn), which have been suggested to increase amyloid aggregation in vivo and in vitro. In the brain of PD patients, CTD truncated α-Syn was found to have lower cell viability and tends to increase in the formation of fibrils. The CTD of α-Syn acts as a guard for regulating the normal functioning of α-Syn. The absence of the CTD may allow the N-terminal of α-Syn to interact with the membrane thereby affecting the normal functioning of α-Syn, and all of which will affect the etiology of PD. In this study, the conformational dynamics of CTD truncated α-Syn (1-99 and 1-108) monomers and their effect on the protein-membrane interactions were demonstrated using the all-atom molecular dynamics (MD) simulation method. From the MD analyses, it was noticed that among the two truncated monomers, α-Syn (1-108) was found to be more stable, shows rigidness at the N-terminal region and contains a significant number of intermolecular hydrogen bonds between the non-amyloid β-component (NAC) region and membrane, and lesser number of extended strands. Further, the bending angle in the N-terminal domain was found to be lesser in the α-Syn (1-108) in comparison with the α-Syn (1-99). Our findings suggest that the truncation on the CTD of α-Syn affects its interaction with the membrane and subsequently has an impact on the aggregation.Communicated by Ramaswamy H. Sarma.

Substitution of Met-38 to Ile in γ-synuclein found in two patients with amyotrophic lateral sclerosis induces aggregation into amyloid

α-, β-, and γ-Synuclein are intrinsically disordered proteins implicated in physiological processes in the nervous system of vertebrates. α-synuclein (αSyn) is the amyloidogenic protein associated with Parkinson's disease and certain other neurodegenerative disorders. Intensive research has focused on the mechanisms that cause αSyn to form amyloid structures, identifying its NAC region as being necessary and sufficient for amyloid assembly. Recent work has shown that a 7-residue sequence (P1) is necessary for αSyn amyloid formation. Although γ-synuclein (γSyn) is 55% identical in sequence to αSyn and its pathological deposits are also observed in association with neurodegenerative conditions, γSyn is resilient to amyloid formation in vitro. Here, we report a rare single nucleotide polymorphism (SNP) in the SNCG gene encoding γSyn, found in two patients with amyotrophic lateral sclerosis (ALS). The SNP results in the substitution of Met38 with Ile in the P1 region of the protein. These individuals also had a second, common and nonpathological, SNP in SNCG resulting in the substitution of Glu110 with Val. In vitro studies demonstrate that the Ile38 variant accelerates amyloid fibril assembly. Contrastingly, Val110 retards fibril assembly and mitigates the effect of Ile38. Substitution of residue 38 with Leu had little effect, while Val retards, and Ala increases the rate of amyloid formation. Ile38 γSyn also results in the formation of γSyn-containing inclusions in cells. The results show how a single point substitution can enhance amyloid formation of γSyn and highlight the P1 region in driving amyloid formation in another synuclein family member.

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.

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.

AggBERT: Best in Class Prediction of Hexapeptide Amyloidogenesis with a Semi-Supervised ProtBERT Model

The prediction of peptide amyloidogenesis is a challenging problem in the field of protein folding. Large language models, such as the ProtBERT model, have recently emerged as powerful tools in analyzing protein sequences for applications, such as predicting protein structure and function. In this article, we describe the use of a semisupervised and fine-tuned ProtBERT model to predict peptide amyloidogenesis from sequences alone. Our approach, which we call AggBERT, achieved state-of-the-art performance, demonstrating the potential for large language models to improve the accuracy and speed of amyloid fibril prediction over simple heuristics or structure-based approaches. This work highlights the transformative potential of machine learning and large language models in the fields of chemical biology and biomedicine.

Census of exposed aggregation-prone regions in proteomes

Loss of solubility usually leads to the detrimental elimination of protein function. In some cases, the protein aggregation is also required for beneficial functions. Given the duality of this phenomenon, it remains a fundamental question how natural selection controls the aggregation. The exponential growth of genomic sequence data and recent progress with in silico predictors of the aggregation allows approaching this problem by a large-scale bioinformatics analysis. Most of the aggregation-prone regions are hidden within the 3D structure, rendering them inaccessible for the intermolecular interactions responsible for aggregation. Thus, the most realistic census of the aggregation-prone regions requires crossing aggregation prediction with information about the location of the natively unfolded regions. This allows us to detect so-called 'exposed aggregation-prone regions' (EARs). Here, we analyzed the occurrence and distribution of the EARs in 76 reference proteomes from the three kingdoms of life. For this purpose, we used a bioinformatics pipeline, which provides a consensual result based on several predictors of aggregation. Our analysis revealed a number of new statistically significant correlations about the presence of EARs in different organisms, their dependence on protein length, cellular localizations, co-occurrence with short linear motifs and the level of protein expression. We also obtained a list of proteins with the conserved aggregation-prone sequences for further experimental tests. Insights gained from this work led to a deeper understanding of the relationship between protein evolution and 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.

The Role of Proteolysis in Amyloidosis

Amyloidoses are a group of diseases associated with deposits of amyloid fibrils in different tissues. So far, 36 different types of amyloidosis are known, each due to the misfolding and accumulation of a specific protein. Amyloid deposits can be found in several organs, including the heart, brain, kidneys, and spleen, and can affect single or multiple organs. Generally, amyloid-forming proteins become prone to aggregate due to genetic mutations, acquired environmental factors, excessive concentration, or post-translational modifications. Interestingly, amyloid aggregates are often composed of proteolytic fragments, derived from the degradation of precursor proteins by yet unidentified proteases, which display higher amyloidogenic tendency compared to precursor proteins, thus representing an important mechanism in the onset of amyloid-based diseases. In the present review, we summarize the current knowledge on the proteolytic susceptibility of three of the main human amyloidogenic proteins, i.e., transthyretin, β-amyloid precursor protein, and α-synuclein, in the onset of amyloidosis. We also highlight the role that proteolytic enzymes can play in the crosstalk between intestinal inflammation and amyloid-based diseases.

Amyloid Disassembly: What Can We Learn from Chaperones?

Protein aggregation and subsequent accumulation of insoluble amyloid fibrils with cross-β structure is an intrinsic characteristic of amyloid diseases, i.e., amyloidoses. Amyloid formation involves a series of on-pathway and off-pathway protein aggregation events, leading to mature insoluble fibrils that eventually accumulate in multiple tissues. In this cascade of events, soluble oligomeric species are formed, which are among the most cytotoxic molecular entities along the amyloid cascade. The direct or indirect action of these amyloid soluble oligomers and amyloid protofibrils and fibrils in several tissues and organs lead to cell death in some cases and organ disfunction in general. There are dozens of different proteins and peptides causing multiple amyloid pathologies, chief among them Alzheimer's, Parkinson's, Huntington's, and several other neurodegenerative diseases. Amyloid fibril disassembly is among the disease-modifying therapeutic strategies being pursued to overcome amyloid pathologies. The clearance of preformed amyloids and consequently the arresting of the progression of organ deterioration may increase patient survival and quality of life. In this review, we compiled from the literature many examples of chemical and biochemical agents able to disaggregate preformed amyloids, which have been classified as molecular chaperones, chemical chaperones, and pharmacological chaperones. We focused on their mode of action, chemical structure, interactions with the fibrillar structures, morphology and toxicity of the disaggregation products, and the potential use of disaggregation agents as a treatment option in amyloidosis.

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.

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

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

Metal-Ion-Induced Evolution of Phenylalanine Self-Assembly: Structural Polymorphism of Novel Metastable Intermediates

The self-assembly of aromatic amino acids has been widely studied due to their ability to form well-defined amyloid-like fibrillar structures. Herein, for the first time, we report the existence of different metastable intermediate states of diverse morphologies, for example, droplets, spheres, vesicles, flowers, and toroids, that are sequentially formed in aqueous medium during the self-assembly process of phenylalanine in the presence of different divalent (Zn²⁺, Cd²⁺, and Hg²⁺) and trivalent (Al³⁺, Ga³⁺, and In³⁺) metal ions having low pK_a values. Due to metal ion-amino acid coordination and strong hydrophobic interaction induced by these metal ions, spherical aggregates are obtained at the initial stage of the structural evolution and further transformed into other intermediate states. Our work may facilitate understanding of the role of metal ions in the amino acid self-assembly process and broaden future applications of the obtained nanostructures in drug delivery, tissue engineering, bioimaging, biocatalysis, and other fields.

Protein Design: From the Aspect of Water Solubility and Stability

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

Single residue modulators of amyloid formation in the N-terminal P1-region of α-synuclein

Alpha-synuclein (αSyn) is a protein involved in neurodegenerative disorders including Parkinson’s disease. Amyloid formation of αSyn can be modulated by the ‘P1 region’ (residues 36-42). Here, mutational studies of P1 reveal that Y39A and S42A extend the lag-phase of αSyn amyloid formation in vitro and rescue amyloid-associated cytotoxicity in C. elegans. Additionally, L38I αSyn forms amyloid fibrils more rapidly than WT, L38A has no effect, but L38M does not form amyloid fibrils in vitro and protects from proteotoxicity. Swapping the sequence of the two residues that differ in the P1 region of the paralogue γSyn to those of αSyn did not enhance fibril formation for γSyn. Peptide binding experiments using NMR showed that P1 synergises with residues in the NAC and C-terminal regions to initiate aggregation. The remarkable specificity of the interactions that control αSyn amyloid formation, identifies this region as a potential target for therapeutics, despite their weak and transient nature.

The authors of this work characterize the effect of amino acid substitution on α-synuclein (α-Syn) aggregation. Residues 38 and 42 (in addition to 39) within the P1 region of α-Syn affect amyloid formation. The effect of substitution at position 38 is dependent on the amino-acid introduced, suggesting that specific interactions control α -Syn aggregation.

The Possible Mechanism of Amyloid Transformation Based on the Geometrical Parameters of Early-Stage Intermediate in Silico Model for Protein Folding

The specificity of the available experimentally determined structures of amyloid forms is expressed primarily by the two- and not three-dimensional forms of a single polypeptide chain. Such a flat structure is possible due to the β structure, which occurs predominantly. The stabilization of the fibril in this structure is achieved due to the presence of the numerous hydrogen bonds between the adjacent chains. Together with the different forms of twists created by the single R- or L-handed α-helices, they form the hydrogen bond network. The specificity of the arrangement of these hydrogen bonds lies in their joint orientation in a system perpendicular to the plane formed by the chain and parallel to the fibril axis. The present work proposes the possible mechanism for obtaining such a structure based on the geometric characterization of the polypeptide chain constituting the basis of our early intermediate model for protein folding introduced formerly. This model, being the conformational subspace of Ramachandran plot (the ellipse path), was developed on the basis of the backbone conformation, with the side-chain interactions excluded. Our proposal is also based on the results from molecular dynamics available in the literature leading to the unfolding of α-helical sections, resulting in the β-structural forms. Both techniques used provide a similar suggestion in a search for a mechanism of conformational changes leading to a formation of the amyloid form. The potential mechanism of amyloid transformation is presented here using the fragment of the transthyretin as well as amyloid Aβ.

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.

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.

Effect of an Amyloidogenic SARS-COV-2 Protein Fragment on α-Synuclein Monomers and Fibrils

Aggregates of α-synuclein are thought to be the disease-causing agent in Parkinson's disease. Various case studies have hinted at a correlation between COVID-19 and the onset of Parkinson's disease. For this reason, we use molecular dynamics simulations to study whether amyloidogenic regions in SARS-COV-2 proteins can initiate and modulate aggregation of α-synuclein. As an example, we choose the nine-residue fragment SFYVYSRVK (SK9), located on the C-terminal of the envelope protein of SARS-COV-2. We probe how the presence of SK9 affects the conformational ensemble of α-synuclein monomers and the stability of two resolved fibril polymorphs. We find that the viral protein fragment SK9 may alter α-synuclein amyloid formation by shifting the ensemble toward aggregation-prone and preferentially rod-like fibril seeding conformations. However, SK9 has only a small effect on the stability of pre-existing or newly formed fibrils. A potential mechanism and key residues for potential virus-induced amyloid formation are described.

Luminescent and morphological behavior of the aromatic dipeptide pair having singular structural variability

In the present manuscript, the luminescence and the self-assembly behavior of the two aromatic dipeptides having singular structure variable are investigated. The terminally protected dipeptides tryptophan-tyrosine (WY^p ) and tryptophan-phenylalanine (WF^p ) were synthesized using standard solution phase procedure. Significant solvatochromic effect was observed for both the dipeptidyl entities; while the influence was more pronounced in case of the WY^p entity when compared to WF^p . Interesting morphological variation was observed for WF^p and WY^p , wherein discrete and interconnected nanospheres were observed for the respective dipeptides. The results obtained signifies the influence of the singular structural variation on modulating the overall functional behavior of the short peptides motifs.

A Descriptor set for Quantitative Structure-Property Relationship Prediction in Biologics

In addition to attaining the desired binding to their targets, a crucial aspect in the development of biotherapeutics is 'developability', which includes several desirable properties such as high solubility, low viscosity and aggregation, physico-chemical stability and low immunogenicity. The lack of any of these properties can lead to significant obstacles in advancing them to clinic; thus in silico methods capable of raising warning flags in earlier stages of development are highly beneficial. We have developed a computational framework based on a large and diverse set of protein specific descriptors ideal for making liability predictions using a machine-learning approach. This set offers a high degree of feature diversity classifiable by sequence, structure and surface patches. We assess the sensitivity and applicability of these descriptors in four dedicated case studies that are believed to be representative of biophysical characterizations commonly employed during the development process. In addition to data sets obtained from public sources, we have validated the descriptors on novel experimental data sets in order to address antibody developability and to generate prospective predictions on Adnectins. The results demonstrate that the descriptors are well suited to assist in the improvement of properties of systems that exhibit poor solubility or aggregation.

The amyloid state of proteins: A boon or bane?

Proteins and their aggregation is significant field of research due to their association with various conformational maladies including well-known neurodegenerative diseases like Alzheimer's (AD), Parkinson's (PD), and Huntington's (HD) diseases. Amyloids despite being given negative role for decades are also believed to play a functional role in bacteria to humans. In this review, we discuss both facets of amyloid. We have shed light on AD, which is one of the most common age-related neurodegenerative disease caused by accumulation of Aβ fibrils as extracellular senile plagues. We also discuss PD caused by the aggregation and deposition of α-synuclein in form of Lewy bodies and neurites. Other amyloid-associated diseases such as HD and amyotrophic lateral sclerosis (ALS) are also discussed. We have also reviewed functional amyloids that have various biological roles in both prokaryotes and eukaryotes that includes formation of biofilm and cell attachment in bacteria to hormone storage in humans, We discuss in detail the role of Curli fibrils' in biofilm formation, chaplins in cell attachment to peptide hormones, and Pre-Melansomal Protein (PMEL) roles. The disease-related and functional amyloids are compared with regard to their structural integrity, variation in regulation, and speed of forming aggregates and elucidate how amyloids have turned from foe to friend.

Effect of an amyloidogenic SARS-COV-2 protein fragment on α-synuclein monomers and fibrils

Using molecular dynamic simulations we study whether amyloidogenic regions in viral proteins can initiate and modulate formation of α-synuclein aggregates, thought to be the disease-causing agent in Parkinson's Disease. As an example we choose the nine-residue fragment SFYVYSRVK (SK9), located on the C-terminal of the Envelope protein of SARS-COV-2. We probe how the presence of SK9 affects the conformational ensemble of α-synuclein monomers and the stability of two resolved fibril polymorphs. We find that the viral protein fragment SK9 may alter α-synuclein amyloid formation by shifting the ensemble toward aggregation-prone and preferentially rod-like fibril seeding conformations. However, SK9 has only little effect of the stability of pre-existing or newly-formed fibrils.

The Transthyretin/Oleuropein Aglycone Complex: A New Tool against TTR Amyloidosis

The release of monomers from the homotetrameric protein transthyretin (TTR) is the first event of a cascade, eventually leading to sporadic or familial TTR amyloidoses. Thus, ligands able to stabilize TTR and inhibit monomer release are subject of intense scrutiny as potential treatments against these pathologies. Here, we investigated the interaction between TTR and a non-glycated derivative of the main olive polyphenol, oleuropein (OleA), known to interfere with TTR aggregation. We coupled fluorescence studies with molecular docking to investigate the OleA/TTR interaction using wild-type TTR, a monomeric variant, and the L55P cardiotoxic mutant. We characterized a fluorescence band emitted by OleA upon formation of the OleA/TTR complex. Exploiting this signal, we found that a poorly specific non-stoichiometric interaction occurs on the surface of the protein and a more specific stabilizing interaction takes place in the ligand binding pocket of TTR, exhibiting a K_D of 3.23 ± 0.32 µM, with two distinct binding sites. OleA interacts with TTR in different modes, stabilizing it and preventing its dissociation into monomers, with subsequent misfolding. This result paves the way to the possible use of OleA to prevent degenerative diseases associated with TTR misfolding.

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.

Using Surface Hydrophobicity Together with Empirical Potentials to Identify Protein-Protein Binding Sites: Application to the Interactions of E-cadherins

Studying the interactions within protein structures can inform about the details of how proteins of various types interact and aggregate. Empirical contact potentials have proven to be extremely important in the evaluation of individual modeled protein structures, but have found few applications to protein-protein interactions. In part, this is caused by a lack of properly formulated potentials with a proper reference state. Since the comparisons are made between different bound structures, the proper reference state should take into account other contacts. Therefore, a preferred reference state should be defined with respect to a given residue type interacting with an average residue instead of interacting with solvent as typically is used in derivation of statistical contact potentials. Here, a two-stage procedure for generating and evaluating interacting protein pairs is described, and an example of E-cadherin interactions is shown.

Chemometric Study of the Relative Aggregation Propensity of Position 19 Mutants of Aβ(1-42)

Background:

The importance of aromaticity vs. hydrophobicity of the central hydrophobic core (CHC, residues 17-20) in governing fibril formation in Aβ(1-42) has been the focus of an ongoing debate in the literature.

Introduction:

Mutations in the CHC (especially at Phe19 and Phe20) have been used to examine the relative impact of hydrophobicity and aromaticity on the degree of aggregation of Aβ(1-42). However, the results have not been conclusive.

Methods:

Partial least squares (PLS) modeling of aggregation rates, using reduced properties of a series of position 19 mutants, was employed to identify the physicochemical properties that had the greatest impact on the extent of aggregation.

Results:

The PLS models indicate that hydrophobicity at position 19 of Aβ(1-42) appears to be the primary and dominant factor in controlling Aβ(1-42) aggregation, with aromaticity having little effect.

Conclusions:

This study illustrates the value of using reduced properties of amino acids in conjunction with PLS modeling to investigate mutational effects in peptides and proteins, as the reduced properties can capture in a quantitative manner the different physicochemical properties of the amino acid side chains. In this particular study, hydrophobicity at position 19 was determined to be the dominant property controlling aggregation, while size, charge, and aromaticity had little impact.

Challenges in Experimental Methods

Experimental studies of amyloids encounter many challenges. There are many methods available for studying proteins, which can be applied to amyloids: from basic staining techniques, allowing visualization of fibers, to complex methods, e.g., AFM-IR used to their detailed biochemical and structural characterization in nanoscale. Which method is appropriate depends on the goal of an experiment: verification of aggregational properties of a peptide, distinguishing oligomers from mature fibers, or kinetic studies. Insolubility, rapid aggregation, and the need of using a high-purity peptide may be a limiting factor in studies involving amyloids. Moreover, the results obtained by various experimental methods often differ significantly, which may lead to misclassification of amyloid peptides. Due to ambiguity of experimental results, laborious and time-consuming analysis, bioinformatical methods become more widely used for amyloids.

Heterotypic amyloid interactions: Clues to polymorphic bias and selective cellular vulnerability?

The number of atomic-resolution structures of disease-associated amyloids has greatly increased in recent years. These structures have confirmed not only the polymorphic nature of amyloids but also the association of specific polymorphs to particular proteinopathies. These observations are strengthening the view that amyloid polymorphism is a marker for specific pathological subtypes (e.g. in tauopathies or synucleinopathies). The nature of this association and how it relates to the selective cellular vulnerability of amyloid nucleation, propagation and toxicity are still unclear. Here, we provide an overview of the mechanistic insights provided by recent patient-derived amyloid structures. We discuss the framework organisation of amyloid polymorphism and how heterotypic amyloid interactions with the physiological environment could modify the solubility and assembly of amyloidogenic proteins. We conclude by hypothesising how such interactions could contribute to selective cellular vulnerability.

Importance of Solvent in Guiding the Conformational Properties of an Intrinsically Disordered Peptide

Aggregated form of α-synuclein in the brain has been found to be the major component of Lewy bodies that are hallmarks of Parkinson's disease (PD), the second most devastating neurodegenerative disorder. We have carried out room-temperature all-atom molecular dynamics (MD) simulations of an ensemble of widely different α-synuclein_1-95 peptide monomer conformations in aqueous solution. Attempts have been made to obtain a generic understanding of the local conformational motions of different repeat unit segments, namely R1-R7, of the peptide and the correlated properties of the solvent at the interface. The analyses revealed relatively greater rigidity of the hydrophobic R6 unit as compared to the other repeat units of the peptide. Besides, water molecules around R6 have been found to be less structured and weakly interacting with the peptide. These are important observations as the R6 unit with reduced conformational motions can act as the nucleation site for the aggregation process, while less structured weakly interacting water around it can become displaced easily, thereby facilitating the hydrophobic collapse of the peptide monomers and their association during the nucleation phase at higher concentrations. In addition, we demonstrated presence of doubly coordinated highly ordered as well as triply coordinated relatively disordered water molecules at the interface. We believe that while the ordered water molecules can favor water-mediated interactions between different peptide monomers, the randomly ordered ones on the other hand are likely to be expelled easily from the interface, thereby facilitating direct peptide-peptide interactions during the aggregation process.

Expanding the Conformational Landscape of Minimalistic Tripeptides by Their O-Glycosylation

We report on the supramolecular self-assembly of tripeptides and their O-glycosylated analogues, in which the carbohydrate moiety is coupled to a central serine or threonine flanked by phenylalanine residues. The substitution of serine with threonine introduces differential side-chain interactions, which results in the formation of aggregates with different morphology. O-glycosylation decreases the aggregation propensity because of rebalancing of the π interactions. The glycopeptides form aggregates with reduced stiffness but increased thermal stability. Our results demonstrate that the designed minimalistic glycopeptides retain critical functional features of glycoproteins and therefore are promising tools for elucidation of molecular mechanisms involved in the glycoprotein interactome. They can also serve as an inspiration for the design of functional glycopeptide-based biomaterials.

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.

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.

On the potential of machine learning to examine the relationship between sequence, structure, dynamics and function of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) constitute a broad set of proteins with few uniting and many diverging properties. IDPs-and intrinsically disordered regions (IDRs) interspersed between folded domains-are generally characterized as having no persistent tertiary structure; instead they interconvert between a large number of different and often expanded structures. IDPs and IDRs are involved in an enormously wide range of biological functions and reveal novel mechanisms of interactions, and while they defy the common structure-function paradigm of folded proteins, their structural preferences and dynamics are important for their function. We here discuss open questions in the field of IDPs and IDRs, focusing on areas where machine learning and other computational methods play a role. We discuss computational methods aimed to predict transiently formed local and long-range structure, including methods for integrative structural biology. We discuss the many different ways in which IDPs and IDRs can bind to other molecules, both via short linear motifs, as well as in the formation of larger dynamic complexes such as biomolecular condensates. We discuss how experiments are providing insight into such complexes and may enable more accurate predictions. Finally, we discuss the role of IDPs in disease and how new methods are needed to interpret the mechanistic effects of genomic variants in IDPs.

Protein mimetic amyloid inhibitor potently abrogates cancer-associated mutant p53 aggregation and restores tumor suppressor function

Missense mutations in p53 are severely deleterious and occur in over 50% of all human cancers. The majority of these mutations are located in the inherently unstable DNA-binding domain (DBD), many of which destabilize the domain further and expose its aggregation-prone hydrophobic core, prompting self-assembly of mutant p53 into inactive cytosolic amyloid-like aggregates. Screening an oligopyridylamide library, previously shown to inhibit amyloid formation associated with Alzheimer's disease and type II diabetes, identified a tripyridylamide, ADH-6, that abrogates self-assembly of the aggregation-nucleating subdomain of mutant p53 DBD. Moreover, ADH-6 targets and dissociates mutant p53 aggregates in human cancer cells, which restores p53's transcriptional activity, leading to cell cycle arrest and apoptosis. Notably, ADH-6 treatment effectively shrinks xenografts harboring mutant p53, while exhibiting no toxicity to healthy tissue, thereby substantially prolonging survival. This study demonstrates the successful application of a bona fide small-molecule amyloid inhibitor as a potent anticancer agent.

Improvement of Biophysical Properties and Affinity of a Human Anti-L1CAM Therapeutic Antibody through Antibody Engineering Based on Computational Methods

The biophysical properties of therapeutic antibodies influence their manufacturability, efficacy, and safety. To develop an anti-cancer antibody, we previously generated a human monoclonal antibody (Ab417) that specifically binds to L1 cell adhesion molecule with a high affinity, and we validated its anti-tumor activity and mechanism of action in human cholangiocarcinoma xenograft models. In the present study, we aimed to improve the biophysical properties of Ab417. We designed 20 variants of Ab417 with reduced aggregation propensity, less potential post-translational modification (PTM) motifs, and the lowest predicted immunogenicity using computational methods. Next, we constructed these variants to analyze their expression levels and antigen-binding activities. One variant (Ab612)—which contains six substitutions for reduced surface hydrophobicity, removal of PTM, and change to the germline residue—exhibited an increased expression level and antigen-binding activity compared to Ab417. In further studies, compared to Ab417, Ab612 showed improved biophysical properties, including reduced aggregation propensity, increased stability, higher purification yield, lower pI, higher affinity, and greater in vivo anti-tumor efficacy. Additionally, we generated a highly productive and stable research cell bank (RCB) and scaled up the production process to 50 L, yielding 6.6 g/L of Ab612. The RCB will be used for preclinical development of Ab612.

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.

Physicochemical Features and Peculiarities of Interaction of AMP with the Membrane

Antimicrobial peptides (AMPs) are anti-infectives that have the potential to be used as a novel and untapped class of biotherapeutics. Modes of action of antimicrobial peptides include interaction with the cell envelope (cell wall, outer- and inner-membrane). A comprehensive understanding of the peculiarities of interaction of antimicrobial peptides with the cell envelope is necessary to perform a rational design of new biotherapeutics, against which working out resistance is hard for microbes. In order to enable de novo design with low cost and high throughput, in silico predictive models have to be invoked. To develop an efficient predictive model, a comprehensive understanding of the sequence-to-function relationship is required. This knowledge will allow us to encode amino acid sequences expressively and to adequately choose the accurate AMP classifier. A shared protective layer of microbial cells is the inner, plasmatic membrane. The interaction of AMP with a biological membrane (native and/or artificial) has been comprehensively studied. We provide a review of mechanisms and results of interactions of AMP with the cell membrane, relying on the survey of physicochemical, aggregative, and structural features of AMPs. The potency and mechanism of AMP action are presented in terms of amino acid compositions and distributions of the polar and apolar residues along the chain, that is, in terms of the physicochemical features of peptides such as hydrophobicity, hydrophilicity, and amphiphilicity. The survey of current data highlights topics that should be taken into account to come up with a comprehensive explanation of the mechanisms of action of AMP and to uncover the physicochemical faces of peptides, essential to perform their function. Many different approaches have been used to classify AMPs, including machine learning. The survey of knowledge on sequences, structures, and modes of actions of AMP allows concluding that only possessing comprehensive information on physicochemical features of AMPs enables us to develop accurate classifiers and create effective methods of prediction. Consequently, this knowledge is necessary for the development of design tools for peptide-based antibiotics.

Huprine Y - Tryptophan heterodimers with potential implication to Alzheimer's disease treatment

The search for novel and effective therapeutics for Alzheimer's disease (AD) is the main quest that remains to be resolved. The goal is to find a disease-modifying agent able to confront the multifactorial nature of the disease positively. Herewith, a family of huprineY-tryptophan heterodimers was prepared, resulting in inhibition of cholinesterase and neuronal nitric oxide synthase enzymes, with effect against amyloid-beta (Aβ) and potential ability to cross the blood-brain barrier. Their cholinesterase pattern of behavior was inspected using kinetic analysis in tandem with docking studies. These heterodimers exhibited a promising pharmacological profile with strong implication in AD.

MILAMP: Multiple Instance Prediction of Amyloid Proteins

Amyloid proteins are implicated in several diseases such as Parkinson's, Alzheimer's, prion diseases, etc. In order to characterize the amyloidogenicity of a given protein, it is important to locate the amyloid forming hotspot regions within the protein as well as to analyze the effects of mutations on these proteins. The biochemical and biological assays used for this purpose can be facilitated by computational means. This paper presents a machine learning method that can predict hotspot amyloidogenic regions within proteins and characterize changes in their amyloidogenicity due to point mutations. The proposed method called MILAMP (Multiple Instance Learning of AMyloid Proteins) achieves high accuracy for identification of amyloid proteins, hotspot localization, and prediction of mutation effects on amyloidogenicity by integrating heterogenous data sources and exploiting common predictive patterns across these tasks through multiple instance learning. The paper presents comprehensive benchmarking experiments to test the predictive performance of MILAMP in comparison to previously published state of the art techniques for amyloid prediction. The python code for the implementation and webserver for MILAMP is available at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#MILAMP.

Wobble tRNA modification and hydrophilic amino acid patterns dictate protein fate

Regulation of mRNA translation elongation impacts nascent protein synthesis and integrity and plays a critical role in disease establishment. Here, we investigate features linking regulation of codon-dependent translation elongation to protein expression and homeostasis. Using knockdown models of enzymes that catalyze the mcm5s2 wobble uridine tRNA modification (U34-enzymes), we show that gene codon content is necessary but not sufficient to predict protein fate. While translation defects upon perturbation of U34-enzymes are strictly dependent on codon content, the consequences on protein output are determined by other features. Specific hydrophilic motifs cause protein aggregation and degradation upon codon-dependent translation elongation defects. Accordingly, the combination of codon content and the presence of hydrophilic motifs define the proteome whose maintenance relies on U34-tRNA modification. Together, these results uncover the mechanism linking wobble tRNA modification to mRNA translation and aggregation to maintain proteome homeostasis.

Amyloid-Like Aggregation in Diseases and Biomaterials: Osmosis of Structural Information

The discovery that the polypeptide chain has a remarkable and intrinsic propensity to form amyloid-like aggregates endowed with an extraordinary stability is one of the most relevant breakthroughs of the last decades in both protein/peptide chemistry and structural biology. This observation has fundamental implications, as the formation of these assemblies is systematically associated with the insurgence of severe neurodegenerative diseases. Although the ability of proteins to form aggregates rich in cross-β structure has been highlighted by recent studies of structural biology, the determination of the underlying atomic models has required immense efforts and inventiveness. Interestingly, the progressive molecular and structural characterization of these assemblies has opened new perspectives in apparently unrelated fields. Indeed, the self-assembling through the cross-β structure has been exploited to generate innovative biomaterials endowed with promising mechanical and spectroscopic properties. Therefore, this structural motif has become the fil rouge connecting these diversified research areas. In the present review, we report a chronological recapitulation, also performing a survey of the structural content of the Protein Data Bank, of the milestones achieved over the years in the characterization of cross-β assemblies involved in the insurgence of neurodegenerative diseases. A particular emphasis is given to the very recent successful elucidation of amyloid-like aggregates characterized by remarkable molecular and structural complexities. We also review the state of the art of the structural characterization of cross-β based biomaterials by highlighting the benefits of the osmosis of information between these two research areas. Finally, we underline the new promising perspectives that recent successful characterizations of disease-related amyloid-like assemblies can open in the biomaterial field.

Nanoscale Assembly of Functional Peptides with Divergent Programming Elements

Self-assembling peptides are being applied both in the biomedical area and as building blocks in nanotechnology. Their applications are closely linked to their modes of self-assembly, which determine the functional nanostructures that they form. This work brings together two structural elements that direct nanoscale self-association in divergent directions: proline as a β-breaker and the β-structure-associated diphenylalanine motif, into a single tripeptide sequence. Amino acid chirality was found to resolve the tension inherent to these conflicting self-assembly instructions. Stereoconfiguration determined the ability of each of the eight possible Pro-Phe-Phe stereoisomers to self-associate into diverse nanostructures, including nanoparticles, nanotapes, or fibrils, which yielded hydrogels with gel-to-sol transition at a physiologically relevant temperature. Three single-crystal structures and all-atom molecular dynamics simulations elucidated the ability of each peptide to establish key interactions to form long-range assemblies (i,e., stacks leading to gelling fibrils), medium-range assemblies (i.e., stacks yielding nanotapes), or short-range assemblies (i.e., dimers or trimers that further associated into nanoparticles). Importantly, diphenylalanine is known to serve as a binding site for pathological amyloids, potentially allowing these heterochiral systems to influence the fibrillization of other biologically relevant peptides. To probe this hypothesis, all eight Pro-Phe-Phe stereoisomers were tested in vitro on the Alzheimer's disease-associated Aβ(1-42) peptide. Indeed, one nonfibril-forming stereoisomer effectively inhibited Aβ fibrillization through multivalent binding between diphenylalanine motifs. This work thus defined heterochirality as a useful feature to strategically develop future therapeutics to interfere with pathological processes, with the additional value of resistance to protease-mediated degradation and biocompatibility.

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.