PLM_Sol: predicting protein solubility by benchmarking multiple protein language models with the updated Escherichia coli protein solubility dataset.

Protein solubility plays a crucial role in various biotechnological, industrial, and biomedical applications. With the reduction in sequencing and gene synthesis costs, the adoption of high-throughput experimental screening coupled with tailored bioinformatic prediction has witnessed a rapidly growing trend for the development of novel functional enzymes of interest (EOI). High protein solubility rates are essential in this process and accurate prediction of solubility is a challenging task. As deep learning technology continues to evolve, attention-based protein language models (PLMs) can extract intrinsic information from protein sequences to a greater extent. Leveraging these models along with the increasing availability of protein solubility data inferred from structural database like the Protein Data Bank holds great potential to enhance the prediction of protein solubility. In this study, we curated an Updated Escherichia coli protein Solubility DataSet (UESolDS) and employed a combination of multiple PLMs and classification layers to predict protein solubility. The resulting best-performing model, named Protein Language Model-based protein Solubility prediction model (PLM_Sol), demonstrated significant improvements over previous reported models, achieving a notable 6.4% increase in accuracy, 9.0% increase in F1_score, and 11.1% increase in Matthews correlation coefficient score on the independent test set. Moreover, additional evaluation utilizing our in-house synthesized protein resource as test data, encompassing diverse types of enzymes, also showcased the good performance of PLM_Sol. Overall, PLM_Sol exhibited consistent and promising performance across both independent test set and experimental set, thereby making it well suited for facilitating large-scale EOI studies. PLM_Sol is available as a standalone program and as an easy-to-use model at https://zenodo.org/doi/10.5281/zenodo.10675340.

Sequence-based prediction of pH-dependent protein solubility using CamSol.

Solubility is a property of central importance for the use of proteins in research in molecular and cell biology and in applications in biotechnology and medicine. Since experimental methods for measuring protein solubility are material intensive and time consuming, computational methods have recently emerged to enable the rapid and inexpensive screening of solubility for large libraries of proteins, as it is routinely required in development pipelines. Here, we describe the development of one such method to include in the predictions the effect of the pH on solubility. We illustrate the resulting pH-dependent predictions on a variety of antibodies and other proteins to demonstrate that these predictions achieve an accuracy comparable with that of experimental methods. We make this method publicly available at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolph, as the version 3.0 of CamSol.

Ten Years of Extracellular Matrix Proteomics: Accomplishments, Challenges, and Future Perspectives.

The extracellular matrix (ECM) is a complex assembly of hundreds of proteins forming the architectural scaffold of multicellular organisms. In addition to its structural role, the ECM conveys signals orchestrating cellular phenotypes. Alterations of ECM composition, abundance, structure, or mechanics have been linked to diseases and disorders affecting all physiological systems, including fibrosis and cancer. Deciphering the protein composition of the ECM and how it changes in pathophysiological contexts is thus the first step toward understanding the roles of the ECM in health and disease and toward the development of therapeutic strategies to correct disease-causing ECM alterations. Potentially, the ECM also represents a vast, yet untapped reservoir of disease biomarkers. ECM proteins are characterized by unique biochemical properties that have hindered their study: they are large, heavily and uniquely posttranslationally modified, and highly insoluble. Overcoming these challenges, we and others have devised mass-spectrometry-based proteomic approaches to define the ECM composition, or "matrisome," of tissues. This first part of this review provides a historical overview of ECM proteomics research and presents the latest advances that now allow the profiling of the ECM of healthy and diseased tissues. The second part highlights recent examples illustrating how ECM proteomics has emerged as a powerful discovery pipeline to identify prognostic cancer biomarkers. The third part discusses remaining challenges limiting our ability to translate findings to clinical application and proposes approaches to overcome them. Lastly, the review introduces readers to resources available to facilitate the interpretation of ECM proteomics datasets. The ECM was once thought to be impenetrable. Mass spectrometry-based proteomics has proven to be a powerful tool to decode the ECM. In light of the progress made over the past decade, there are reasons to believe that the in-depth exploration of the matrisome is within reach and that we may soon witness the first translational application of ECM proteomics.

GATSol, an enhanced predictor of protein solubility through the synergy of 3D structure graph and large language modeling.

BACKGROUND: Protein solubility is a critically important physicochemical property closely related to protein expression. For example, it is one of the main factors to be considered in the design and production of antibody drugs and a prerequisite for realizing various protein functions. Although several solubility prediction models have emerged in recent years, many of these models are limited to capturing information embedded in one-dimensional amino acid sequences, resulting in unsatisfactory predictive performance. RESULTS: In this study, we introduce a novel Graph Attention network-based protein Solubility model, GATSol, which represents the 3D structure of proteins as a protein graph. In addition to the node features of amino acids extracted by the state-of-the-art protein large language model, GATSol utilizes amino acid distance maps generated using the latest AlphaFold technology. Rigorous testing on independent eSOL and the Saccharomyces cerevisiae test datasets has shown that GATSol outperforms most recently introduced models, especially with respect to the coefficient of determination R2, which reaches 0.517 and 0.424, respectively. It outperforms the current state-of-the-art GraphSol by 18.4% on the S. cerevisiae_test set. CONCLUSIONS: GATSol captures 3D dimensional features of proteins by building protein graphs, which significantly improves the accuracy of protein solubility prediction. Recent advances in protein structure modeling allow our method to incorporate spatial structure features extracted from predicted structures into the model by relying only on the input of protein sequences, which simplifies the entire graph neural network prediction process, making it more user-friendly and efficient. As a result, GATSol may help prioritize highly soluble proteins, ultimately reducing the cost and effort of experimental work. The source code and data of the GATSol model are freely available at https://github.com/binbinbinv/GATSol .

Chagasin from Trypanosoma cruzi as a molecular scaffold to express epitopes of TSA-1 as soluble recombinant chimeras.

Trypanosoma cruzi is the causative agent of Chagas disease, a global public health problem. New therapeutic drugs and biologics are needed. The TSA-1 recombinant protein of T. cruzi is one such promising antigen for developing a therapeutic vaccine. However, it is overexpressed in E. coli as inclusion bodies, requiring an additional refolding step. As an alternative, in this study, we propose the endogenous cysteine protease inhibitor chagasin as a molecular scaffold to generate chimeric proteins. These proteins will contain combinations of two of the five conserved epitopes (E1 to E5) of TSA-1 in the L4 and L6 chagasin loops. Twenty chimeras (Q1-Q20) were designed, and their solubility was predicted using bioinformatics tools. Nine chimeras with different degrees of solubility were selected and expressed in E. coli BL21 (DE3). Western blot assays with anti-6x-His and anti-chagasin antibodies confirmed the expression of soluble recombinant chimeras. Both theoretically and experimentally, the Q12 (E5-E3) chimera was the most soluble, and the Q20 (E4-E5) the most insoluble protein. Q4 (E5-E1) and Q8 (E5-E2) chimeras were classified as proteins with medium solubility that exhibited the highest yield in the soluble fraction. Notably, Q4 has a yield of 239 mg/L, well above the yield of recombinant chagasin (16.5 mg/L) expressed in a soluble form. The expression of the Q4 chimera was scaled up to a 7 L fermenter obtaining a yield of 490 mg/L. These data show that chagasin can serve as a molecular scaffold for the expression of TSA-1 epitopes in the form of soluble chimeras.

Streamlining heterologous expression of top carbonic anhydrases in Escherichia coli: bioinformatic and experimental approaches.

BACKGROUND: Carbonic anhydrase (CA) enzymes facilitate the reversible hydration of CO2 to bicarbonate ions and protons. Identifying efficient and robust CAs and expressing them in model host cells, such as Escherichia coli, enables more efficient engineering of these enzymes for industrial CO2 capture. However, expression of CAs in E. coli is challenging due to the possible formation of insoluble protein aggregates, or inclusion bodies. This makes the production of soluble and active CA protein a prerequisite for downstream applications. RESULTS: In this study, we streamlined the process of CA expression by selecting seven top CA candidates and used two bioinformatic tools to predict their solubility for expression in E. coli. The prediction results place these enzymes in two categories: low and high solubility. Our expression of high solubility score CAs (namely CA5-SspCA, CA6-SazCAtrunc, CA7-PabCA and CA8-PhoCA) led to significantly higher protein yields (5 to 75 mg purified protein per liter) in flask cultures, indicating a strong correlation between the solubility prediction score and protein expression yields. Furthermore, phylogenetic tree analysis demonstrated CA class-specific clustering patterns for protein solubility and production yields. Unexpectedly, we also found that the unique N-terminal, 11-amino acid segment found after the signal sequence (not present in its homologs), was essential for CA6-SazCA activity. CONCLUSIONS: Overall, this work demonstrated that protein solubility prediction, phylogenetic tree analysis, and experimental validation are potent tools for identifying top CA candidates and then producing soluble, active forms of these enzymes in E. coli. The comprehensive approaches we report here should be extendable to the expression of other heterogeneous proteins in E. coli.

Prediction of protein solubility based on sequence physicochemical patterns and distributed representation information with DeepSoluE.

BACKGROUND: Protein solubility is a precondition for efficient heterologous protein expression at the basis of most industrial applications and for functional interpretation in basic research. However, recurrent formation of inclusion bodies is still an inevitable roadblock in protein science and industry, where only nearly a quarter of proteins can be successfully expressed in soluble form. Despite numerous solubility prediction models having been developed over time, their performance remains unsatisfactory in the context of the current strong increase in available protein sequences. Hence, it is imperative to develop novel and highly accurate predictors that enable the prioritization of highly soluble proteins to reduce the cost of actual experimental work. RESULTS: In this study, we developed a novel tool, DeepSoluE, which predicts protein solubility using a long-short-term memory (LSTM) network with hybrid features composed of physicochemical patterns and distributed representation of amino acids. Comparison results showed that the proposed model achieved more accurate and balanced performance than existing tools. Furthermore, we explored specific features that have a dominant impact on the model performance as well as their interaction effects. CONCLUSIONS: DeepSoluE is suitable for the prediction of protein solubility in E. coli; it serves as a bioinformatics tool for prescreening of potentially soluble targets to reduce the cost of wet-experimental studies. The publicly available webserver is freely accessible at http://lab.malab.cn/~wangchao/softs/DeepSoluE/ .

Techno-functional properties of dry-fractionated plant-based proteins and application in food product development: a review.

Dry-fractionated protein concentrates are gaining attention because they are produced using a versatile and sustainable technology, which can be applied to a wide range of plant material. To facilitate their utilization in new product development, it is crucial to obtain a comprehensive overview of their techno-functional properties. The present review aims to examine the techno-functional properties of dry-fractionated protein concentrates and describe their primary applications in food products, considering the published works in the last decade. The techno-functional properties of proteins, including water absorption capacity, emulsifying and foaming properties, gelling ability or protein solubility, are relevant factors to consider during food formulation. However, these properties are significantly influenced by the extraction technology, the type of protein and its characteristics. Overall, dry-fractionated proteins are characterized by high protein solubility, high foaming ability and foam stability, and high gelling ability. Such properties have been exploited in the development of food, such as bakery products and pasta, with the aim of increasing the protein content and enhancing the nutritional value. Additionally, innovative foods with distinctive textural and nutritional characteristics, such as meat and dairy analogues, have been developed by using dry-fractionated proteins. The results indicate that the study of these ingredients still needs to be improved, including their application with a broader range of plant materials. Nevertheless, this review could represent an initial step to obtaining an overview of the techno-functional properties of dry-fractionated proteins, facilitating their use in foods. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Characterization and Techno-Functional Properties of High Protein Walnut Flour from an Oil by-Product.

A high protein walnut flour (HPWF) was obtained by defatting walnut flour (WF), which is a by-product of the oil industry. The objective of this study was the chemical and techno-functional characterization of HPWF. Composition, amino acid content, protein secondary structure, protein solubility and thermal transitions were measured. Besides, the techno-functional properties, emulsion activity and stability, and water holding and oil absorption capacities, of HPWF were evaluated. Also, the molecular mass of proteins under denaturing conditions and the microstructure of HPWF were evaluated by electrophoresis and confocal scanning laser microscopy, respectively. HPWF had 55.4% protein content and 21.5% total dietary fibre. In terms of HPWF amino acid composition, the limiting amino acids were the sulphurated cysteine and methionine. By FTIR analysis, the main secondary structures were ß-sheet (49%) followed by α-helix (24%); both structures are considered to be ordered. Likewise, HPWF soluble proteins increased at basic pH and HPWF proteins were separated in 11 bands with molecular masses ranging from 97 kDa to 18 kDa by electrophoresis. With respect to techno-functional properties, HPWF presented good emulsion activity (51%) and high thermal emulsion stability (46%). In addition, HPWF retained 571% and 242% of water and oil by weight, respectively. Finally, the micrograph showed the predominance of protein structures and fibre fragments, and the presence of few lipids mostly trapped. These results showed that HPWF is an interesting source of plant-based proteins and walnut flour can be used to obtain high protein ingredients from non-traditional sources.

Taylor Dispersion-Induced Phase Separation for the Efficient Characterisation of Protein Condensate Formation.

Biomolecular condensates have emerged as important structures in cellular function and disease, and are thought to form through liquid-liquid phase separation (LLPS). Thorough and efficient in vitro experiments are therefore needed to elucidate the driving forces of protein LLPS and the possibility to modulate it with drugs. Here we present Taylor dispersion-induced phase separation (TDIPS), a method to robustly measure condensation phenomena using a commercially available microfluidic platform. It uses only nanoliters of sample, does not require extrinsic fluorescent labels, and is straightforward to implement. We demonstrate TDIPS by screening the phase behaviour of two proteins that form biomolecular condensates in vivo, PGL-3 and Ddx4. Uniquely accessible to this method, we find an unexpected re-entrant behaviour at very low ionic strength, where LLPS is inhibited for both proteins. TDIPS can also probe the reversibility of assemblies, which was shown for both α-synuclein and for lysozyme, relevant for health and biotechnology, respectively. Finally, we highlight how effective inhibition concentrations and partitioning of LLPS-modifying compounds can be screened highly efficiently.

Insights into the solubility of γ D-crystallin from multiscale atomistic simulations.

The molecular basis underlying the rich phase behavior of globular proteins remains poorly understood. We use atomistic multiscale molecular simulations to model the solution-state conformational dynamics and interprotein interactions of γ D-crystallin and its P23T-R36S mutant, which drastically limits the protein solubility, at both infinite dilution and at a concentration where the mutant fluid phase and crystalline phase coexist. We find that while the mutant conserves the protein fold, changes to the surface exposure of residues in the neighborhood of residue-36 enhance protein-protein interactions and develop specific protein-protein contacts found in the protein crystal lattice.

Predicting Colloidal Stability of High-Concentration Monoclonal Antibody Formulations in Common Pharmaceutical Buffers Using Improved Polyethylene Glycol Induced Protein Precipitation Assay.

Colloidal stability is an important consideration when developing high concentration mAb formulations. PEG-induced protein precipitation is a commonly used assay to assess the colloidal stability of protein solutions. However, the practical usefulness and the current theoretical model for this assay have yet to be verified over a large formulation space across multiple mAbs and mAb-based modalities. In the present study, we used PEG-induced protein precipitation assays to evaluate colloidal stability of 3 mAbs in 24 common formulation buffers at 20 and 5 °C. These prediction assays were conducted at low protein concentration (1 mg/mL). We also directly characterized high concentration (100 mg/mL) formulations for cold-induced phase separation, turbidity, and concentratibility by ultrafiltration. This systematic study allowed analysis of the correlation between the results of low concentration assays and the high concentration attributes. The key findings of this study include the following: (1) verification of the usefulness of three different parameters (Cmid, µB, and Tcloud) from PEG-induced protein precipitation assays for ranking colloidal stability of high concentration mAb formulations; (2) a new method to implement PEG-induced protein precipitation assay suitable for high throughput screening with low sample consumption; (3) improvement in the theoretical model for calculating robust thermodynamic parameters of colloidal stability (µB and εB) that are independent of specific experimental settings; (4) systematic evaluation of the effects of pH and buffer salts on colloidal stability of mAbs in common formulation buffers. These findings provide improved theoretical and practical tools for assessing the colloidal stability of mAbs and mAb-based modalities during formulation development.

Promotion of Protein Solubility and Reduction in Stiffness in Human Lenses by Aggrelyte-1: Implications for Reversing Presbyopia.

With aging, human lenses lose the ability to focus on nearby objects due to decreases in accommodative ability, a condition known as presbyopia. An increase in stiffness or decrease in lens elasticity due to protein aggregation and insolubilization are the primary reasons for presbyopia. In this study, we tested aggrelyte-1 (S,N-diacetyl glutathione diethyl ester) for its ability to promote protein solubility and decrease the stiffness of lenses through its dual property of lysine acetylation and disulfide reduction. Treatment of water-insoluble proteins from aged human lenses (58-75 years) with aggrelyte-1 significantly increased the solubility of those proteins. A control compound that did not contain the S-acetyl group (aggrelyte-1C) was substantially less efficient in solubilizing water-insoluble proteins. Aggrelyte-1-treated solubilized protein had significant amounts of acetyllysine, as measured by Western blotting and LC-MS/MS. Aggrelytes increased the protein-free thiol content in the solubilized protein. Aged mouse (7 months) and human (44-66 years) lenses treated with aggrelyte-1 showed reduced stiffness accompanied by higher free thiol and acetyllysine levels compared with those treated with aggrelyte-1C or untreated controls. Our results suggested that aggrelyte-1 reduced lens stiffness through acetylation followed by disulfide reduction. This proof-of-concept study paves the way for developing aggrelyte-1 and related compounds to reverse presbyopia.

A Census of Hsp70-Mediated Proteome Solubility Changes upon Recovery from Heat Stress.

Eukaryotic cells respond to heat shock through several regulatory processes including upregulation of stress responsive chaperones and reversible shutdown of cellular activities through formation of protein assemblies. However, the underlying regulatory mechanisms of the recovery of these heat-induced protein assemblies remain largely elusive. Here, we measured the proteome abundance and solubility changes during recovery from heat shock in the mouse Neuro2a cell line. We found that prefoldins and translation machinery are rapidly down-regulated as the first step in the heat shock response. Analysis of proteome solubility reveals that a rapid mobilization of protein quality control machineries, along with changes in cellular energy metabolism, translational activity, and actin cytoskeleton are fundamental to the early stress responses. In contrast, longer term adaptation to stress involves renewal of core cellular components. Inhibition of the Hsp70 family, pivotal for the heat shock response, selectively and negatively affects the ribosomal machinery and delays the solubility recovery of many nuclear proteins. ProteomeXchange: PXD030069.

α-Crystallins in the Vertebrate Eye Lens: Complex Oligomers and Molecular Chaperones.

α-Crystallins are small heat-shock proteins that act as holdase chaperones. In humans, αA-crystallin is expressed only in the eye lens, while αB-crystallin is found in many tissues. α-Crystallins have a central domain flanked by flexible extensions and form dynamic, heterogeneous oligomers. Structural models show that both the C- and N-terminal extensions are important for controlling oligomerization through domain swapping. α-Crystallin prevents aggregation of damaged ß- and γ-crystallins by binding to the client protein using a variety of binding modes. α-Crystallin chaperone activity can be compromised by mutation or posttranslational modifications, leading to protein aggregation and cataract. Because of their high solubility and their ability to form large, functional oligomers, α-crystallins are particularly amenable to structure determination by solid-state nuclear magnetic resonance (NMR) and solution NMR, as well as cryo-electron microscopy.

Host-Guest Complexation by ß-Cyclodextrin Enhances the Solubility of an Esterified Protein.

The carboxyl groups of a protein can be esterified by reaction with a diazo compound, 2-diazo-2-(p-methylphenyl)-N,N-dimethylacetamide. This esterification enables the entry of the protein into the cytosol of a mammalian cell, where the nascent ester groups are hydrolyzed by endogenous esterases. The low aqueous solubility of the ensuing esterified protein is, however, a major practical challenge. Solubility screening revealed that ß-cyclodextrin (ß-CD) is an optimal solubilizing agent for esterified green fluorescent protein (est-GFP). Its addition can increase the recovery of est-GFP by 10-fold. α-CD, γ-CD, and cucurbit-7-uril are less effective excipients. 1H NMR titration experiments revealed that ß-CD encapsulates the hydrophobic tolyl group of ester conjugates with Ka = 321 M-1. Combining l-arginine and sucrose with ß-CD enables the nearly quantitative recovery of est-GFP. Thus, the insolubility of esterified proteins can be overcome with excipients.

Improved yield, stability, and cleavage reaction of a novel tobacco etch virus protease mutant.

The protease catalytic subunit of the nuclear inclusion protein A from tobacco etch virus (TEVp) is widely used to remove tags and fusion proteins from recombinant proteins. Some intrinsic drawbacks to its recombinant production have been studied for many years, such as low solubility, auto-proteolysis, and instability. Some point mutations have been incorporated in the amino acid protease sequence to improve its production. Here, a comprehensive review of each mutation reported so far has been made to incorporate them into a mutant called TEVp7M with a total of seven changes. This mutant with a His7tag at N-terminus was produced with remarkable purification yields (55 mg/L of culture) from the soluble fraction in a single step affinity purification. The stability of His7-TEVp7M was analyzed and compared with the single mutant TEVp S219V, making evident that His7-TEVp7M shows very constant thermal stability against pH variation, whereas TEVp S219V is highly sensitive to this change. The cleavage reaction was optimized by determining the amount of protease that could cleave a 100-fold excess substrate in the shortest possible time at 30 °C. Under these conditions, His7-TEVp7M was able to cleave His-tag in the buffers commonly used for affinity purification. Finally, a structural analysis of the mutations showed that four of them increased the polarity of the residues involved and, consequently, showed increased solubility of TEVp and fewer hydrophobic regions exposed to the solvent. Taken together, the seven changes studied in this work improved stability, solubility, and activity of TEVp producing enough protease to digest large amounts of tags or fusion proteins. KEY POINTS: • Production of excellent yields of a TEVp (TEVp7M) by incorporation of seven changes. • His-tag removal in an excess substrate in the common buffers used for purification. • Incorporated mutations improve polarity, stability, and activity of TEVp7M.

Foaming and Structural Studies on the Acidic Subunit of Amaranth 11S Globulin Modified with Antihypertensive Peptides as a Function of pH and Ionic Strength.

Some studies aimed at revealing the relationship between protein structure and their functional properties. However, the majority of these reports have been carried out using protein isolates. There are limited reports on the possible relationship between the functional properties and the structure of a purified protein. In this work the amaranth 11S globulin acidic subunit (AAC) and five mutations of the same protein that were modified in their variable regions with antihypertensive peptides (VYVYVYVY and RIPP), were analyzed at two ionic strength (2.9 and 17.6 g/L NaCl) and pH (3.0-7.0). Results revealed better solubility for the proteins mutated at the terminal ends (AACM.1 and AACM.4) and lower solubility for the protein inserted with RIPP peptide. Spectroscopy studies revealed an increase of ß-sheet structure at high salt concentration for all proteins. It was also observed that salt concentration acted as a modulator, which allowed a better foam features for all modified proteins limiting movement of side chains and reducing red-shifted displacement of λmax. All proteins showed foam capacity ranging from 76 to 93% although foam stability was twofold better for modified proteins than for AAC at high salt concentration. This study allowed better understanding about the structural changes that influence the foaming properties of engineered proteins.

Germination induced changes in bioactive compounds and nutritional components of millets.

The present study was conducted to compare the nutritional quality and the concentration of bioactive compounds in the flours from dehusked and germinated foxtail, barnyard, and little millets. Germinated millet flours showed significantly higher protein content (11.79-33.49%), total free amino acid content (66-334.87%) and protein solubility (13.83-34%), compared to the dehusked millet flours. The total phenols and flavonoids in the flours from the three germinated millets were significantly higher by about 142.36 and 437.20%, respectively, compared to the flours from the dehusked millets. Mineral content was also found to be higher in the flours from germinated millets in comparison to the flours from dehusked millets. The results of this study showed that the flours from the germinated millets have the potential for their application in development of novel products,because of their enhanced nutritional value. The extracts from the germinated millets have the potential for use as functional ingredients in the development of novel processed fruit beverages.

Chemical Properties Determine Solubility and Stability in ßγ-Crystallins of the Eye Lens.

ßγ-Crystallins are the primary structural and refractive proteins found in the vertebrate eye lens. Because crystallins are not replaced after early eye development, their solubility and stability must be maintained for a lifetime, which is even more remarkable given the high protein concentration in the lens. Aggregation of crystallins caused by mutations or post-translational modifications can reduce crystallin protein stability and alter intermolecular interactions. Common post-translational modifications that can cause age-related cataracts include deamidation, oxidation, and tryptophan derivatization. Metal ion binding can also trigger reduced crystallin solubility through a variety of mechanisms. Interprotein interactions are critical to maintaining lens transparency: crystallins can undergo domain swapping, disulfide bonding, and liquid-liquid phase separation, all of which can cause opacity depending on the context. Important experimental techniques for assessing crystallin conformation in the absence of a high-resolution structure include dye-binding assays, circular dichroism, fluorescence, light scattering, and transition metal FRET.