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

Designing Multifunctional Biomaterials via Protein Self-Assembly

Protein self-assembly is a fundamental biological process where proteins spontaneously organize into complex and functional structures without external direction. This process is crucial for the formation of various biological functionalities. However, when protein self-assembly fails, it can trigger the development of multiple disorders, thus making understanding this phenomenon extremely important. Up until recently, protein self-assembly has been solely linked either to biological function or malfunction; however, in the past decade or two it has also been found to hold promising potential as an alternative route for fabricating materials for biomedical applications. It is therefore necessary and timely to summarize the key aspects of protein self-assembly: how the protein structure and self-assembly conditions (chemical environments, kinetics, and the physicochemical characteristics of protein complexes) can be utilized to design biomaterials. This minireview focuses on the basic concepts of forming supramolecular structures, and the existing routes for modifications. We then compare the applicability of different approaches, including compartmentalization and self-assembly monitoring. Finally, based on the cutting-edge progress made during the last years, we summarize the current knowledge about tailoring a final function by introducing changes in self-assembly and link it to biomaterials' performance.

Computational Design of Peptides for Biomaterials Applications

Computer-aided molecular design and protein engineering emerge as promising and active subjects in bioengineering and biotechnological applications. On one hand, due to the advancing computing power in the past decade, modeling toolkits and force fields have been put to use for accurate multiscale modeling of biomolecules including lipid, protein, carbohydrate, and nucleic acids. On the other hand, machine learning emerges as a revolutionary data analysis tool that promises to leverage physicochemical properties and structural information obtained from modeling in order to build quantitative protein structure-function relationships. We review recent computational works that utilize state-of-the-art computational methods to engineer peptides and proteins for various emerging biomedical, antimicrobial, and antifreeze applications. We also discuss challenges and possible future directions toward developing a roadmap for efficient biomolecular design and engineering.

Molecular Modeling of Self-Assembling Peptides

Peptide epitopes mediate as many as 40% of protein-protein interactions and fulfill signaling, inhibition, and activation roles within the cell. Beyond protein recognition, some peptides can self- or coassemble into stable hydrogels, making them a readily available source of biomaterials. While these 3D assemblies are routinely characterized at the fiber level, there are missing atomistic details about the assembly scaffold. Such atomistic detail can be useful in the rational design of more stable scaffold structures and with improved accessibility to functional motifs. Computational approaches can in principle reduce the experimental cost of such an endeavor by predicting the assembly scaffold and identifying novel sequences that adopt said structure. Yet, inaccuracies in physical models and inefficient sampling have limited atomistic studies to short (two or three amino acid) peptides. Given recent developments in machine learning and advances in sampling strategies, we revisit the suitability of physical models for this task. We use the MELD (Modeling Employing Limited Data) approach to drive self-assembly in combination with generic data in cases where conventional MD is unsuccessful. Finally, despite recent developments in machine learning algorithms for protein structure and sequence predictions, we find the algorithms are not yet suited for studying the assembly of short peptides.

Computational Design of Peptide Assemblies

With the ongoing development of peptide self-assembling materials, there is growing interest in exploring novel functional peptide sequences. From short peptides to long polypeptides, as the functionality increases, the sequence space is also expanding exponentially. Consequently, attempting to explore all functional sequences comprehensively through experience and experiments alone has become impractical. By utilizing computational methods, especially artificial intelligence enhanced molecular dynamics (MD) simulation and de novo peptide design, there has been a significant expansion in the exploration of sequence space. Through these methods, a variety of supramolecular functional materials, including fibers, two-dimensional arrays, nanocages, etc., have been designed by meticulously controlling the inter- and intramolecular interactions. In this review, we first provide a brief overview of the current main computational methods and then focus on the computational design methods for various self-assembled peptide materials. Additionally, we introduce some representative protein self-assemblies to offer guidance for the design of self-assembling peptides.

Computational insights into the cross-talk between medin and Aβ: implications for age-related vascular risk factors in Alzheimer's disease

The aggregation of medin forming aortic medial amyloid is linked to arterial wall degeneration and cerebrovascular dysfunction. Elevated levels of arteriolar medin are correlated with an increased presence of vascular amyloid-β (Aβ) aggregates, a hallmark of Alzheimer's disease (AD) and vascular dementia. The cross-interaction between medin and Aβ results in the formation of heterologous fibrils through co-aggregation and cross-seeding processes both in vitro and in vivo. However, a comprehensive molecular understanding of the cross-interaction between medin and Aβ-two intrinsically disordered proteins-is critically lacking. Here, we employed atomistic discrete molecular dynamics simulations to systematically investigate the self-association, co-aggregation and also the phenomenon of cross-seeding between these two proteins. Our results demonstrated that both Aβ and medin were aggregation prone and their mixture tended to form β-sheet-rich hetero-aggregates. The formation of Aβ-medin hetero-aggregates did not hinder Aβ and medin from recruiting additional Aβ and medin peptides to grow into larger β-sheet-rich aggregates. The β-barrel oligomer intermediates observed in the self-aggregations of Aβ and medin were also present during their co-aggregation. In cross-seeding simulations, preformed Aβ fibrils could recruit isolated medin monomers to form elongated β-sheets. Overall, our comprehensive simulations suggested that the cross-interaction between Aβ and medin may contribute to their pathological aggregation, given the inherent amyloidogenic tendencies of both medin and Aβ. Targeting medin, therefore, could offer a novel therapeutic approach to preserving brain function during aging and AD by improving vascular health.

Unveiling Medin Folding and Dimerization Dynamics and Conformations via Atomistic Discrete Molecular Dynamics Simulations

Medin is a principal component of localized amyloid found in the vasculature of individuals over 50 years old. Its amyloid aggregation has been linked to endothelial dysfunction and vascular inflammation, contributing to the pathogenesis of various vascular diseases. Despite its significance, the structures of the medin monomer, oligomer, and fibril remain elusive, and the dynamic processes of medin aggregation are not fully understood. In this study, we comprehensively investigated the medin folding and dimerization dynamics and conformations using atomistic discrete molecular dynamics simulations. Our simulation results suggested that the folding initiation of the medin involved the formation of β-sheets around medin30-41 and medin42-50, with subsequent capping of other segments to their β-sheet edges. Medin monomers typically consisted of three or four β-strands, along with a dynamic N-terminal helix. Two isolated medin peptides readily aggregated into a β-sheet-rich dimer, displaying a strong aggregation propensity. Dimerization of medin not only enhanced the β-sheet conformations but also led to the formation of β-barrel oligomers. The aggregation tendencies of medin1-18 and medin19-29 were relatively weak. However, the segments of medin30-41 and medin42-50 played a crucial role as they primarily formed a β-sheet core and facilitated medin1-18 and medin19-29 to form intra- and interpeptide β-sheets. The findings highlight the critical role of the medin30-41 and medin42-50 regions in stabilizing the monomer structure and driving the medin amyloid aggregation. These regions could potentially serve as promising targets for designing antiamyloid inhibitors against amyloid aggregation of medin. Additionally, our study provides a full picture of the monomer conformations and dimerization dynamics for medin, which will help better understand the pathology of medin aggregation.

Challenges in studying the liquid-to-solid phase transitions of proteins using computer simulations

"Membraneless organelles," also referred to as biomolecular condensates, perform a variety of cellular functions and their dysregulation is implicated in cancer and neurodegeneration. In the last two decades, liquid-liquid phase separation (LLPS) of intrinsically disordered and multidomain proteins has emerged as a plausible mechanism underlying the formation of various biomolecular condensates. Further, the occurrence of liquid-to-solid transitions within liquid-like condensates may give rise to amyloid structures, implying a biophysical link between phase separation and protein aggregation. Despite significant advances, uncovering the microscopic details of liquid-to-solid phase transitions using experiments remains a considerable challenge and presents an exciting opportunity for the development of computational models which provide valuable, complementary insights into the underlying phenomenon. In this review, we first highlight recent biophysical studies which provide new insights into the molecular mechanisms underlying liquid-to-solid (fibril) phase transitions of folded, disordered and multi-domain proteins. Next, we summarize the range of computational models used to study protein aggregation and phase separation. Finally, we discuss recent computational approaches which attempt to capture the underlying physics of liquid-to-solid transitions along with their merits and shortcomings.

Experimental Insights into Conformational Ensembles of Assembled β-Sheet Peptides

Deciphering the conformations and interactions of peptides in their assemblies offers a basis for guiding the rational design of peptide-assembled materials. Here we report the use of scanning tunneling microscopy (STM), a single-molecule imaging method with a submolecular resolution, to distinguish 18 types of coexisting conformational substates of the β-strand of the 8-37 segment of human islet amyloid polypeptide (hIAPP 8-37). We analyzed the pairwise peptide-peptide interactions in the hIAPP 8-37 assembly and found 82 interconformation interactions within a free energy difference of 3.40 k_BT. Besides hIAPP 8-37, this STM method validates the existence of multiple conformations of other β-sheet peptide assemblies, including mutated hIAPP 8-37 and amyloid-β 42. Overall, the results reported in this work provide single-molecule experimental insights into the conformational ensemble and interpeptide interactions in the β-sheet peptide assembly.

Dissecting the Self-assembly Dynamics of Imperfect Repeats in α-Synuclein

The pathological aggregation of α-synuclein (αS) into amyloid fibrils is the hallmark of Parkinson's disease (PD). The self-assembly and membrane interactions of αS are mainly governed by the seven imperfect 11-residue repeats of the XKTKEGVXXXX motif around residues 1-95. However, the particular role of each repeat in αS fibrillization remains unclear. To answer this question, we studied the aggregation dynamics of each repeat with up to 10 peptides in silico by conducting multiple independent micro-second atomistic discrete molecular dynamics simulations. Our simulations revealed that only repeats R3 and R6 readily self-assembled into β-sheet-rich oligomers, while the other repeats remained as unstructured monomers with weak self-assembly and β-sheet propensities. The self-assembly process of R3 featured frequent conformational changes with β-sheet formation mainly in the non-conserved hydrophobic tail, whereas R6 spontaneously self-assembled into extended and stable cross-β structures. These results of seven repeats are consistent with their structures and organization in recently solved αS fibrils. As the primary amyloidogenic core, R6 was buried inside the central cross-β core of all αS fibrils, attracting the hydrophobic tails of adjacent R4, R5, and R7 repeats forming β-sheets around R6 in the core. Further away from R6 in the sequence but with a moderate amyloid aggregation propensity, the R3 tail could serve as a secondary amyloidogenic core and form independent β-sheets in the fibril. Overall, our results demonstrate the critical role of R3 and R6 repeats in αS amyloid aggregation and suggest their potential as targets for the peptide-based and small-molecule amyloid inhibitors.

Lipidation Alters the Structure and Hydration of Myristoylated Intrinsically Disordered Proteins

Lipidated proteins are an emerging class of hybrid biomaterials that can integrate the functional capabilities of proteins into precisely engineered nano-biomaterials with potential applications in biotechnology, nanoscience, and biomedical engineering. For instance, fatty-acid-modified elastin-like polypeptides (FAMEs) combine the hierarchical assembly of lipids with the thermoresponsive character of elastin-like polypeptides (ELPs) to form nanocarriers with emergent temperature-dependent structural (shape or size) characteristics. Here, we report the biophysical underpinnings of thermoresponsive behavior of FAMEs using computational nanoscopy, spectroscopy, scattering, and microscopy. This integrated approach revealed that temperature and molecular syntax alter the structure, contact, and hydration of lipid, lipidation site, and protein, aligning with the changes in the nanomorphology of FAMEs. These findings enable a better understanding of the biophysical consequence of lipidation in biology and the rational design of the biomaterials and therapeutics that rival the exquisite hierarchy and capabilities of biological systems.

Biomimetic mineralization based on self-assembling peptides

Biomimetic science has attracted great interest in the fields of chemistry, biology, materials science, and energy. Biomimetic mineralization is the process of synthesizing inorganic minerals under the control of organic molecules or biomolecules under mild conditions. Peptides are the motifs that constitute proteins, and can self-assemble into various hierarchical structures and show a high affinity for inorganic substances. Therefore, peptides can be used as building blocks for the synthesis of functional biomimetic materials. With the participation of peptides, the morphology, size, and composition of mineralized materials can be controlled precisely. Peptides not only provide well-defined templates for the nucleation and growth of inorganic nanomaterials but also have the potential to confer inorganic nanomaterials with high catalytic efficiency, selectivity, and biotherapeutic functions. In this review, we systematically summarize research progress in the formation mechanism, nanostructural manipulation, and applications of peptide-templated mineralized materials. These can further inspire researchers to design structurally complex and functionalized biomimetic materials with great promising applications.

Natural and Man-Made Cyclic Peptide-Based Antibiotics

In recent years, an increasing number of drug-resistant bacterial strains have been identified due to the abuse of antibiotics, which seriously threatens human and animal health. Antimicrobial peptides (AMPs) have become one of the most effective weapons to solve this problem. AMPs have little tendency to induce drug resistance and have outstanding antimicrobial effects. The study of AMPs, especially cyclic peptides, has become a hot topic. Among them, macrocyclic AMPs have received extensive attention. This mini-review discusses the structures and functions of the dominant cyclic natural and synthetic AMPs and provides a little outlook on the future direction of cyclic AMPs.

Distinct neurotoxic TDP-43 fibril polymorphs are generated by heterotypic interactions with α-Synuclein

Amyloid aggregates of specific proteins constitute important pathological hallmarks in many neurodegenerative diseases, defining neuronal degeneration and disease onset. Recently, increasing numbers of patients show comorbidities and overlaps between multiple neurodegenerative diseases, presenting distinct phenotypes. Such overlaps are often accompanied by colocalizations of more than one amyloid protein, prompting the question of whether direct interactions between different amyloid proteins could generate heterotypic amyloids. To answer this question, we investigated the effect of α-synuclein (αS) on the DNA-binding protein TDP-43 aggregation inspired by their coexistence in pathologies such as Lewy body dementia and limbic predominant age-related TDP-43 encephalopathy. We previously showed αS and prion-like C-terminal domain (PrLD) of TDP-43 synergistically interact to generate toxic heterotypic aggregates. Here, we extend these studies to investigate whether αS induces structurally and functionally distinct polymorphs of PrLD aggregates. Using αS-PrLD heterotypic aggregates generated in two different stoichiometric proportions, we show αS can affect PrLD fibril forms. PrLD fibrils show distinctive residue level signatures determined by solid state NMR, dye-binding capability, proteinase K (PK) stability, and thermal stability toward SDS denaturation. Furthremore, by gold nanoparticle labeling and transmission electron microscopy, we show the presence of both αS and PrLD proteins within the same fibrils, confirming the existence of heterotypic amyloid fibrils. We also observe αS and PrLD colocalize in the cytosol of neuroblastoma cells and show that the heterotypic PrLD fibrils selectively induce synaptic dysfunction in primary neurons. These findings establish the existence of heterotypic amyloid and provide a molecular basis for the observed overlap between synucleinopathies and TDP-43 proteinopathies.

Molecular insights into the oligomerization dynamics and conformations of amyloidogenic and non-amyloidogenic amylin from discrete molecular dynamics simulations

The amyloid aggregation of human islet amyloid polypeptide (hIAPP) is associated with pancreatic β-cell death in type 2 diabetes. The S20G substitution of hIAPP (hIAPP(S20G)), found in Japanese and Chinese people, is more amyloidogenic and cytotoxic than wild-type hIAPP. Rat amylin (rIAPP) does not have aggregation propensity or cytotoxicity. Mounting evidence suggests that soluble low-molecular-weight amyloid oligomers formed during early aggregation are more cytotoxic than mature fibrils. The self-assembly dynamics and oligomeric conformations remain unknown because the oligomers are heterogeneous and transient. The molecular mechanism of sequence-variation rendering dramatically different aggregation propensity and cytotoxicity is also elusive. Here, we investigate the oligomerization dynamics and conformations of amyloidogenic hIAPP, hIAPP(S20G), and non-amyloidogenic rIAPP using atomistic discrete molecular dynamics (DMD) simulations. Our simulation results demonstrated that all three monomeric amylin peptides mainly adopted an unstructured formation with partial dynamical helices near the N-terminus. Relatively transient β-hairpins were more abundant in hIAPP and hIAPP(S20G) than in rIAPP. The S20G-substituting mutant of hIAPP altered the turn region of the β-hairpin motif, resulting in more hydrophobic residue-pairwise contacts within the β-hairpin. Oligomerization dynamic investigation revealed that all three peptides spontaneously accumulated into helix-populated oligomers. The conformational conversion to form β-sheet-rich oligomers was only observed in hIAPP and hIAPP(S20G). The population of high-β-sheet-content oligomers was enhanced by S20G substitution. Interestingly, both hIAPP and hIAPP(S20G) could form β-barrel formations, and the β-barrel propensity of hIAPP(S20G) was three times larger than that of hIAPP. No β-sheet-rich or β-barrel formations were observed in rIAPP. Our direct observation of the correlation between β-barrel oligomer formation and cytotoxicity suggests that β-barrels might play a critically important role in the cytotoxicity of amyloidosis.

Engineering β-Sheet Peptide Coassemblies for Biomaterial Applications

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