Adhesion and colonization of host cells by pathogenic bacteria depend on protein–protein interactions (PPIs). These interactions are interesting from the pharmacological point of view since new molecules that inhibit host-pathogen PPIs would act as new antimicrobials. Most of these interactions are discovered using high-throughput methods that may display a high false positive rate. The absence of curation of these databases can make the available data unreliable. To address this issue, a comprehensive filtering process was developed to obtain a reliable list of domains and motifs that participate in PPIs between bacteria and human cells. From a structural point of view, our analysis revealed that human proteins involved in the interactions are rich in alpha helix and disordered regions and poorer in beta structure. Disordered regions in human proteins harbor short sequence motifs that are specifically recognized by certain domains in pathogenic proteins. The most relevant domain–domain interactions were validated by AlphaFold, showing that a proper analysis of host-pathogen PPI databases can reveal structural conserved patterns. Domain–motif interactions, on the contrary, were more difficult to validate, since unstructured regions were involved, where AlphaFold could not make a good prediction. Moreover, these interactions are also likely accommodated by post-translational modifications, especially phosphorylation, which can potentially occur in 25–50% of host proteins. Hence, while common structural patterns are involved in host–pathogen PPIs and can be retrieved from available databases, more information is required to properly infer the full interactome. By resolving these issues, and in combination with new prediction tools like Alphafold, new classes of antimicrobials could be discovered from a more detailed understanding of these interactions. Protein–protein interactions (PPIs) play a fundamental role in most biological processes. Infectious diseases are no exception, as pathogens rely on PPIs to attach to and infect host cells ,2,3. In Even more important, is a proper understanding of the conserved structural patterns in host–pathogen PPIs. A deeper study of these interactions, i.e., the prediction of the three-dimensional structures of the interacting proteins, will allow us to characterize pathogenesis at the molecular level and identify the most promising pharmacological targets.Protein domains are regions that can fold, function, and evolve independently and are used as building blocks that can be combined to build proteins with different functions. Various databases such as iPfam , 3did 1, or the Although domains are important in characterizing PPIs, many of the interactions occur between domains and unstructured, more discrete elements, known as motifs. Motifs are short  conserved and regulatory protein components that provide low-affinity interaction interfaces, and are usually found in intrinsically disordered regions (IDRs) . These cHere, a new filtering pipeline was created to screen PPIs between host and pathogenic bacteria (hereafter host-pathogen PPIs) by considering enriched protein domains and motifs to identify central interactions for pathogenesis. The refined list of domain–domain and domain–motif interactions enriched in host–pathogen PPIs shows that the number of statistically relevant interactions in these datasets is limited, suggesting that more data is required to define the host–pathogen interactome. Notwithstanding, several structural patterns can be obtained from current databases that may help to pave the way for the development of new antimicrobials.Our goal was to retrieve the relevant structural information from host–pathogen PPI databases, minimizing noise interference. The Pathogen-Host Interaction Search Tool (PHISTO) database currently represents the most comprehensive repository of human–bacterial interactions . For thiTo find domains and motifs involved in host–pathogen PPIs, 9.333 PPIs between bacteria and human proteins were retrieved from the PHISTO database, 9.027 of which were unique interactions. These interactions are formed by 2.716 bacterial proteins and 3.737 human proteins. Here, InterProScan  was usedAcinetobacter baumanii, several virulence factors  were found to interact with cytoskeleton proteins, including plectin [Listeria monocytogenes, used to invade mammalian cells via cadherins transmembrane proteins [A total of 48 host and 69 pathogen domains  were fou plectin . Enricheproteins . LPXTG cproteins . A GO enAdditionally, the human proteins involved in host–pathogen PPIs were inspected for specific structural and physicochemical properties. For this, protein sequences were inspected with Clever Machine , an algoAs many PPIs are driven by domain interactions, certain domain associations might be privileged in host–pathogen PPIs. To do this, the frequency of all occurring domain–domain (DD) associations were calculated and compared with the expected frequency if associations would occur at random. The 10 most enriched DD associations are depicted in obs/fexp) of the enriched motifs were less marked than domains. The most enriched motifs were the WDR5-binding motif (ELM000364) and the COP1 E3 ligase-binding degron motif, involved in histone methylation and ubiquitination, respectively. Many processes in the cell, such as phosphorylation or ubiquitination, are mediated by transient PPIs that occur via domain–motif (DM) interactions. As human proteins involved in host–pathogen PPIs contain large, disordered regions, these proteins were further scanned for enriched motifs. Among the human proteins involved in host–pathogen PPIs, 29 enriched motifs were found A. The raA total of 75 enriched domain–motif (DM) associations were found in the database. . Among tMotifs are susceptible to modulation by post-translational modifications, which can notably modify the interactions. Hence, we investigated whether the motifs present in DM associations could be modified. We used the MusiteDeep  tool thaFrom the 21 enriched DD and 75 DM interactions, representative complexes were modeled using AlphaFold Multimer ,38. We rThe validation of DM interactions was more challenging. As motifs are located in disordered regions, our threshold for protein structure quality (less than 10% of residues with pLDDT score < 0.5) removed more than 75% of the total entries. From the 27 PPIs containing a DM association, the only accurate models correspond to yopM-ABHD17A (pTM score = 0.62), mtaD-HADHA (pTM score = 0.61), yopM-IGHG1 (pTM score = 0.56), and tuf-ENKD1 (pTM score = 0.55). In all cases, the motifs were located in highly flexible regions and not always in close proximity to the domain . Only yoWe decided to analyze in more detail the complexes between IpaH and sspH2 with ubiquitin UBA52. These interactions involve the association of the ubiquitin domain in UBA52 with the catalytic domain of ubiquitin–protein ligase E3, both in IpaH and sspH2. The structure of IpaH and sspH2 is similar, with a ubiquitin–protein ligase domain and several leucine-rich repeats except for the additional domain at the N-terminus of sspH2. The ubiquitin ligase activity of these proteins is most likely not restricted to UBA52. In fact, the interaction between IpaH and UBC is also described in PHISTO and, when inspected with Alphafold, both proteins can potentially interact with other forms of ubiquitin, such as polyubiquitin B.To analyze the degree of conservation of the interacting regions, we use Consurf . The anaYersinia pestis (UP000000815), Bacillus anthracis (UP000000594), and Francisella tularensis (UP000001174), were downloaded from Uniprot Proteomes in FASTA format.Host–pathogen PPIs were retrieved from the PHISTO database (accessed 11 February 2022)  by accesInterProScan v5.56  was run https://github.com/normandavey/ProcessedAlphafold, accessed on 21 February 2022). A cut-off value higher than 0.55 was used to define whether a residue belongs to an IDR. A Python script (host_motifs.py) was built to select the disordered regions for each human protein given the per-residue surface accessibility scores, picking regions with a minimum length of 5 residues. The IDR regions for every human protein were stored in separate files. The same script was used to fetch all the motifs contained in IDRs for each human protein. The script searches for ELM patterns in disordered regions, as previously identified, and retrieves the positions of the matches.The list of ELM classes was downloaded in TSV format from the ELM database (accessed 21 February 2022) . This liDD and DM combinations were obtained by a brute force approach using Python (clean_phisto.py). The idea behind this approach was to iterate through every single PPI contained in the PHISTO database and generate all the possible domain–motif and domain–domain combinations. Then, all these possible combinations were processed to filter out the non-significant interactions by statistical analysis.To find which observed motifs, domains, DD, and DM combinations were enriched in the PHISTO database, their relative frequencies (observed frequencies) were calculated and compared to the relative frequencies that would result from random sampling (expected frequencies). All statistical calculations were performed in R. The observed frequencies of all the commented elements were computed by iterating through all the output files containing the motif/domain and counting how many times each element was observed in the PHISTO database with respect to the total number of elements. The results of this step were stored in text files containing the number of times a particular element appeared, the identifiers, and the relative frequencies.Y. pestis, 33% B. anthracis, and 17% F. tularensis), in each bootstrap iteration, a random sampling of these proteomes, with identical percentages, was used to simulate as much as possible the conditions of the PHISTO database.To calculate the expected frequencies for human domains and motifs, 3.737 proteins from the human proteome were randomly picked to count how many times each domain or motif was observed with respect to the total number of elements. This step was repeated 1000 times using bootstrapping to get the expected frequency. For pathogen proteins, a single proteome would not be representative of the database, so a mixed proteome was created. Since 94% of the bacterial proteins registered in the PHISTO database belong to three bacterial species  to select those elements whose p-values were below the significance level (α = 0.05) and whose effect sizes were above 0.5. The ratio between the observed frequency and the expected frequency (fobs/fexp) was computed for all the elements to classify them as enriched (fobs/fexp > 1) or depleted (fobs/fexp < 1). Only the enriched elements were further analyzed.Observed and expected frequencies were compared using the one-way Wilcoxon test. The output files containing the https://supfam.mrc-lmb.cam.ac.uk/SUPERFAMILY/cgi-bin/dcenrichment.cgi, accessed on 29 June 2022). The GO terms were later processed in REVIGO [http://revigo.irb.hr).Gene Ontology (GO) Biological Process terms for the enriched human and pathogenic domains, as well as from the enriched DD combinations, were obtained using the Pfam identifiers in dcGO  .The enriched DD and DM interactions were further explored using Alphafold Multimer ,38. ProtYersinia pestis or Edwardiella ictaluri (Y. pestis and E. ictaluri have a high degree of similarity with the sspH2 protein, which increases the reliability of these predictions (In this study, we have demonstrated the usefulness of using statistical tools to detect structural associations in PPIs databases that may contain many false positives. Using these tools, we were able to generate a list of domain–domain and domain–motif associations with a high degree of confidence. This information may be useful to validate or predict new bacterial proteins involved in infection, as shown in the case of virulence factors associated with ubiquitin–protein ligase activity. Through sequence alignment on the identified motif, possible virulence factors can be detected in other species, such as ictaluri C. The prdictions D. HoweveAlphafold allows us to also evaluate if an interaction could be accurate. In our case, all the interactions predicted by Alphafold with a high degree of confidence confirmed that the identified domain–domain associations were consistent with the prediction. It is important to note here that there are limitations to this approach. The presence of important unstructured regions in human proteins involved in host–pathogen PPIs makes the predictions less confident. The high degree of flexibility of these structures means that these interactions can be, in many cases, transient. Unless they are part of loops connecting defined secondary structures, with limited flexibility, the prediction will almost certainly be poor.The increase in the ability to predict new host–pathogen PPIs at the structural level opens the door to the in silico design of new drugs that inhibit these interactions. Considering that infections caused by resistant bacteria are a major public health problem, these new molecules could be a formidable contribution to the arsenal of already available antimicrobials.


The aim of this study, medicinal applications of banana peel flour, was used to estimate nutrition value and minerals content. The results indicated that banana peel flour was safe for food application, and it was lower in protein and fat and higher in dietary fiber and total carbohydrate which were 52.68 and 67.25%, respectively. Moreover, the minerals content of phosphorous, potassium, sodium, manganese, and calcium were 217.92, 110.24, 96.43, 85.25, and 80.27 mg/100 g, respectively. Furthermore, the problem of the study investigated the effect of banana peel flour incorporation with wheat flour with 72% extraction to produce biscuit blends at different ratios of 5.0, 10.0, 15.0, and 20.0%, respectively. The nutrition value and mineral content of banana peel flour in biscuits increased gradually in the blends, according to the results. The methods of study of the four biscuit blends were prepared with banana peel flour substituted and wheat flour extraction of 72 percent, and they were compared to a control biscuit. Sensory properties reported that the control biscuit was the highest score followed by blends which had contained 5, 10, and 15% banana peel flour. Meanwhile, the blend of biscuit fortified with 20% was not accepted by panelists. From the color biscuits, the blends containing 5, 10, and 15% banana peel flour had acceptable color, and the blends' color was not acceptable. This may be caused by dark color and high dietary fiber. The texture profile analyzer and physical characteristics were confirmed and gave the same results. The result is that it could be recommended that the banana peel flour, which has high fiber content, produce acceptable biscuits fortified with 5, 10, and 15% and become functional foods. Panelists did not find the 20% blend biscuits to be particularly appealing. Recovering fruit and vegetable waste into foods enhances the sustainability of the diet system. The transformation of horticultural waste into value-added ingredients and food products could lead to better human nutrition and food security .Due to rising consumer interest in vitamins, minerals, unsaturated fatty acids, bioactive compounds, and fiber in food, there has been a boom in consumer interest in these nutrients in recent years. The focus is on consumer health and functional food products' wellbeing. Banana waste is repurposed. As a result, peeling could increase raw material yield.Musa, Musella, and Ensete) belonging to the Musaceae family. In addition, Musa acuminata and Musella balbisiana are the edible bananas [The banana contained three genera , the consumption of dietary fiber was identified as a protective factor for the risk of total or cause-specific death due to various chronic diseases such as cancer, cardiovascular diseases, and diabetes mellitus, among others . The reaIn addition to its nutritional benefits, the flour from banana varieties can possibly be used to produce ready-to-eat products that offer a high to combine bioactive compounds that are missing nutrients in these products , 12. NexTherefore, this study aims to estimate the nutritional values of banana peel as a by-product and, moreover, evaluate the quality of wheat flour and banana peel flour at different addition to produce biscuits determining chemical nutrition, color, texture analysis, and acceptability for consumers.Banana, wheat flour with 72% extraction, ingredient of biscuits, and reagent-grade chemicals and food-grade polythene were obtained from the local market at Taif region, Kingdom of Saudi Arabia.Male albino mice were used to study acute oral toxicity, and eighteen mice weighing 20–30 g were obtained from the Pharmacy College at King Saud University. Mice were housed and fed on a basal diet according to .Musa sapientum) have been washed in clean water to remove other undesirables. The bananas were peeled with the skins cut into small slices. Then, the slices were evaporated to destroy the enzymes presented and dried at 65°C for 8 hours. After that, it was cooled to room temperature and ground to obtain fine flour. Banana flour is stored in plastic bags to decompose and support biscuits.Bananas  according to .The four blends of biscuits were prepared from banana peel flour substituted with wheat flour with 72% extraction, and it was compared with the control biscuit. The control biscuit was made from wheat flour with 72% extraction. The first, second, third, and fourth blends contained 5, 10, 15, and 20% banana peel flour, substituted from wheat flour.The different blends were mixed with ingredient of biscuits separately and combined well to produce appropriate dough. It was cut and then cooked for 10 to 15 min at 180 to 210°C and left to cool before being packaged in plastic bags according to .Chemical composition, total dietary fiber (TDF), and its fractions and minerals content were determined in different blends of biscuits according to the above previous method.Different blends of biscuits were evaluated for their sensory properties for twenty panelists' staff from the Food Science and Nutrition Department, College Science-Taif University, Kingdom of Saudi Arabia. Different blends of biscuits were evaluated for color, appearance, flavor, taste, texture, and overall acceptability by a nine-point Hedonic scale according to .L∗, a∗, and b∗.The different blends of biscuits measured the color with a Hunter Lab Colorimeter  according to . The colDifferent blends of biscuits were determined using a texture profile analyzer (TPA) according to .Biscuits were measured for high (mm), diameter (mm), and spread ratio according to . Spread p 0.05) were utilized to compare the means. The analysis was achieved by utilizing the ANOVA procedure for the statistical analysis system [The findings were presented for analysis of variance; Duncan's multiple tests at the (s system .From the oral toxicity assay result from banana peel flour, it showed that all tested mice appeared normal and no mortality occurred for two weeks. There were no considerable variations for the body weight gain in all mice; the autopsy showed no significant pathological changes between treated mice and control mice. These results confirmed that the banana peel was indicating its safety for food application.Chemical analysis, total dietary, soluble, and insoluble dietary and, in addition, minerals content were determined in banana peel flour, and the results in Dietary, soluble, and insoluble dietary fiber from banana peel flour in this study were 52.68, 10.39, and 42.29 g/100d dry weight, respectively. Other studies have reported even higher values for dietary fiber content in banana peel flour, reaching 55.5% , 29. TheMoreover, the minerals content in banana peel flour with high amounts of phosphorous, potassium, sodium, manganese, and calcium were 217.92, 110.24, 96.43, 85.25, and 80.27 mg/100 g, respectively.  found thEach value represents the mean ± SD.Chemical analysis and total dietary fiber, as well as soluble and insoluble, were determined in biscuits with different blends, and the results in The increase in the fat content of the different blends when the level of banana peel flour increases is due to a high-fat content in the banana peel flour . The carTotal dietary, soluble, and insoluble dietary fiber contents in different blends of biscuits are given in the same table. The total dietary fiber content was considerably greater with the increase in the different blends of biscuit, and the banana peel flour can be used as a substitute. The value of the total dietary fiber content in the biscuits ranged between 3.65 and 14.19%. Insoluble and soluble dietary fibers were the dominant fiber fraction in all biscuit blends. Soluble fiber is recognized to reduce cholesterol and help lower the risk of colon cancer; in addition, insoluble fiber showed the benefits of regulating the bowels and increasing stool volume. .Minerals content were determined in different blends of biscuits, and the results in Potassium's high concentration in the banana peel can assist in maintaining blood pressure and balancing bodily fluids, as well as controlling kidney failure, cardiac difficulties, and respiratory difficulties. Because iron transports oxygen to cells, it is required for energy production, collagen formation, and the normal functioning of the immune system. Manganese aids in the development of skeletal and cartilage tissue .The sensory properties were determined in the control biscuit and its blends, and the results in This may be due to high protein in the flour which has contained high gluten. Contrary, the utilization of flour containing low protein will give crispy biscuits. This confirmed that good flour for making biscuits is wheat flour which contains low protein .L∗, a∗, and b∗ values of different biscuits blends fortified with banana peel compared with control biscuit prepared from wheat flour. The results observed the significant differences between the colors of control biscuits and those fortified with banana peel flour.b∗ value of the fortified biscuit ranges from 28.08 to 17.38 with partial replacement of wheat flour with amaranth, respectively, at levels of 5, 10, and 15% of substitution.This shows that there was a noticeable color difference in different blends of biscuits fortified with banana peel flour at levels 5, 10, 15, and 20. The change in color may be caused by the extent of Maillard's reaction for the reason that banana peels contain sucrose and protein . FurtherThe texture quality is an important quality feature of biscuits; therefore, the textures of the four best blends of banana peel were tested against that of wheat flour biscuits, and the results are reported in There were considerably various in the biscuits' texture parameters. This increase was caused by the fiber content of banana peel flour which affects its toughness and other structural features. Mechanical variations referred to the substitute of wheat flour with banana flour in biscuits are associated with an increase in crude fiber, insoluble dietary fiber, fat, and a reduction in carbohydrates. Previous studies  found thThe results of springiness, gumminess, and chewiness observed that there was a considerably various between the control biscuits and biscuits made from banana peel flour at different levels containing a high amount of insoluble dietary fiber. Moreover, the addition of banana peel flour to the composition of food products does not negatively affect organoleptic attributes such as texture, taste, and smell , and it The physical properties like diameter, high, and spread ratio were determined in control biscuit made from wheat flour with 72% extraction and its blends fortified with banana peel flour at 5, 10, 15, and 20%, and the results in The study contribution is a banana peel flour containing a high amount of dietary fiber and a rich source of mineral content. These bioactive compounds were used to prepare biscuits as functional foods fortified at levels 5, 10, 15, and 20% from banana peel flour. The color, texture properties, physical analysis, and sensory properties were determined by different blends of biscuits. The different blends prepared from banana peel flour in 5, 10, and 15% levels were acceptable for panelists, while the blend containing 20% banana peel flour was not acceptable and may be caused by dark color and high dietary fiber.


The commercial production of soy milk renders a large quantity of wet soybean by-product (SMB), which is typically dumped, incinerated, or partially used as animal fodder. This wet SMB has a high moisture content that is rich in nutritional and biologically active compounds. This study aimed to characterise the composition and properties of a flour milled from SMB dried at 100 °C (SMB100) and assess its possible application as a fibre substitute in white bread. The results showed that SMB100 has high levels of dietary fibre (40.6%) and protein (26.5%). It also contains high levels of saponins (31.4 mg/g) and isoflavones (698.0 µg/g). SMB100 has a light-yellow colour with low moisture content and water activity . The results also indicated that replacement of wheat flour with SMB100 at 10 or 12.5% by flour weight negatively impacted the raising volume, density, and texture of white bread. Alternatively, substituting wheat flour with 5% of SMB100, did not significantly impact the physical properties of white bread, while significantly improving its dietary fibre content in comparison with the control, revealing that SMB100 is a potential substitute of wheat flour for improvement of dietary fibre in bread. Future studies are needed to optimise bread formulation and improve the processing condition which produces quality white bread with high dietary fibre using SMB100. Soybean is considered a globally important commodity due to its high nutrient and economic value, which leads to its vast utilisation . Soy milWet SMB has a moisture content of approximately 85%, leaving it susceptible to rapid microbiological and enzymatic degradation. This contributes to the low utilisation of this industrial by-product, along with other compounding factors. As a result, the majority of wet SMB is dumped in land fills or incinerated, with minor volumes being used as animal feeds , therebyAs many compounds in wet SMB are susceptible to oxidation, drying is needed to remove water to reduce degradation, while retaining the nutrient content and phytochemicals in SMB. Our recent study tested different drying conditions and revealed that the most suitable drying condition of SMB is the application of a fan forced (FF) oven at 100 °C. SMB dried by this simple method has an acceptable colour and high levels of bioactive compounds and antioxidant capacity, as compared to vacuum oven and freeze drying, and can be achieved without the need for highly specific drying equipment [The inclusion of fibre in bread is not new to the bread industry, with the availability of additives such as wheat brans, wheat fibre, hi-maize starch and modified starches. Evžen, Miroslava  determinPrevious studies have incorporated both wet and dry SMB into flour, such as wheat and gluten-free flours, and have utilised SMB to make biscuits and cookies, soy crackers, cakes, sausages, frankfurters, beef patties, noodles, a cheese analogue, vegetable paste and peanut butter . Several3), calcium carbonate, ethanol (EtOH), methanol (MeOH), sulphuric acid (H2SO4), phenol, sodium phosphate monobasic, sodium phosphate dibasic, potassium persulfate (K2S2O8), boric acid, methyl red, methylene blue, daidzin, daidzein, genistin, genistein, and total dietary fibre analysis kit.Soybeans of medium size and clear hilum were purchased online from Australian Wheatgrass . All other food stuffs were purchased from local markets. Analytical and HPLC grade chemicals were purchased from Sigma : hydrochloric acid (HCl), sodium hydroxide (NaOH), hexane, sodium carbonate (NaCOw/v) in the soy milk machine, followed by pasteurisation of the milk and SMB slurry at 95 °C for 1 min. Soy milk was separated from its by-product through a fine sieve bag, with the remaining soy milk being pressed out by hand. The SMB was laid out on trays and dried in a convection oven at 100 °C as described in our previous study [SMB was produced in the laboratory using a small commercial soy milk machine and followed the process set out by Guimarães, Silva , with so3 until effervescence ceased. The volume was made up to 40 mL with DI water, followed by centrifugation at 760× g force for 30 min. A 0.05 mL aliquot of the supernatant was added to 0.95 mL of DI water and 0.5 mL of phenol solution (5%), followed by the rapid addition of 2.5 mL of concentrated H2SO4, to induce a colour change, and allowed to develop for 25 min at 25 °C. The absorbance was measured at 490 nm using a UV–vis spectrophotometer , and results were calculated against a standard curve of D-glucose and reported as grams of glucose equivalents per 100 g of SMB (g GE/100 g).Total carbohydrates of SMB were determined using the phenol sulphuric acid method, AOAC Method 44.1.30, described in previous studies , with soTotal fat content was analysed using the Randall modification of the Soxhlet method  and the 2SO4 with two copper (ll) catalytic tablets at 430 °C for 2 h in a Velp DKL 12 automatic digestion unit (Velp Scientifica). Digestion was cooled and diluted to 100 mL. For distillation, a 25 mL aliquot of digested solution was alkalised with 25 mL of 32% NaOH, before distillation into a 2% boric acid trap with Tashiro’s indicator . Titration of the distillate was carried out with 0.02 M HCl till end point colour change was observed, with results adjusted for a reagent blank [Total protein content was determined using the semi-micro Kjeldahl method with adaption of the AOAC method 960.52 . Sample nt blank . Proteinnt blank , and wasThe total dietary fibre (TDF), soluble fibre (SF) and insoluble fibre (IF) were determined using enzymatic gravimetric methods, AOAC 991.43 and AACC 32–07.01, described by others ,26, withg force for 20 min and then stored at −18 °C for further determination of the total phenolic, saponin and isoflavone content.SMB100 (0.25 g) was extracted in 10 mL of 50% MeOH using an ultrasonic bath  set at 30 °C, with 150 W for 1 h with agitation once every 5 min. The extract was then centrifuged at 760× 3 solution was added, re-vortexed and allowed to incubate for 1 hr at RT in a darkroom covered with foil. Absorbance was tested at 765 nm, baseline set by reagent control in a UV–vis spectrophotometer , with results compared to a gallic acid standard curve and reported as milligrams gallic acid equivalents mg/g (GAE mg/g).The method described by Vuong, Hirun  was usedw/v) vanillin in MeOH solution was mixed with 5 mL of 72% H2SO4. Samples were then incubated in a water bath at 60 °C for 1 h, cooled on ice to room temperature before measurement of the absorbance of solutions at 560 nm. Escin was used as the standard, with the results expressed as mg of escin equivalents per gram by dry weight (ESE mg/g).The concentration of saponins in flour was assessed by the process set out by Hiai, Oura . A 0.5 mUp to 12 different isoflavones have been isolated from soybean, with the same being possible from SMB . This st®, Pullman, WA, USA). The bulk density (ρB), the tapped bulk density (ρT), Carr’s compressibility index (CI) and Hausner ratio (HR) were determined as described by Barretto, Buenavista [The moisture content of the flour was determined by mass difference following drying using a fan forced laboratory oven  at 105 °C until constant weight. Water activity was analysed by Aqualab Pawkit water activity meter  × 100/m1, where m1 is the initial sample mass of powder and m2 is the mass of the dried supernatant. The swelling capacity (SC), water holding capacity (WHC), water absorbance capacity (WAC) and oil binding capacity (OBC) were determined according to a previous study [−1 (b/a)) and chroma (C = The water solubility index (WSI) was measured following Hang et al. (2020) . The watus study  to deterturation .Bread dough formulation and baking methods were developed based on previous studies ,35, withTo form the dough, all ingredients were added to a planetary mixer fitted with a dough hook and allowed to form a homogenous mixture for 2 min at low speed. The speed then increased to approximately 120 rpm to rapidly promote gluten formation and was sustained for 13 min. Dough was placed in an air tight container and allowed to ferment at 40 °C for 90 min, with a fermentation schedule of 20 min, first punch, 20 min, second punch, followed by moulding, tinning and a final proofing for 50 min. Loaves were then baked at 200 °C for 22 min, cooled, and assessed the following day for mass, volume, relative density, colour and textural profile.n = 3) of each loaf were stored in an airtight container until tested. A 5 N load cell fitted with a 12.5 mm cylinder probe, with a cross head speed of 10 mm/sec, was used, with a two bite, 50% compression (10 mm), textural profile analysis (TPA) to measure hardness (N), chewiness (N) and cohesiveness (%) using Trapezium X © material testing operation software.All loaves were weighed on a top loader balance, with the mass recoded, before measurement of volume by the rapeseed displacement method . The relHue angle (H°) and chroma (C) of crust and crumb were determined as discussed above. The change in colour from the control loaf was determined by total colour change (ΔE = 2−(ΔC)2) .® Pro statistical software 14.0.0  with a statistically significant level of p < 0.05.All experiments were performed in at least triplicates and results were determined as the means ± standard deviations (SD). One-way ANOVA  and all pairs Tukey HSD were used to compare the means and to determine the connecting letters report using JMPThe wet SMB before drying had a moisture content of 83.4 ± 0.3%. After drying and grinding through 0.8 mm mesh, the nutrient content, phytochemicals, and physical properties of SMB100 flour are shown in SMB100 was shown to have high levels of phytochemicals . SMB100 The presence of these components, particularly the presence of isoflavones, demonstrate the benefits of utilising this by-product for human consumption rather than the current methods of disposal. This is further true when considering the current adjuncts used to fortify dietary staples such as breads. While using modified starches provides fibre addition with tailored rheological properties, they require intervention to produce these components, with limited or no other nutritional benefit. Reports suggest that isoflavones can act as antioxidants to retard the oxidation of fats, provide benefits to cardiovascular health and some cancers, and act as an estrogen supplement for post-menopausal women .The physical properties of the milled flour were studied to highlight the bulk storage and distribution capacity, interactions with water and oil, and a qualitative description of colour . After mThe ability of a powder to interact with liquids can highlight functional characteristics for further application. The ability to hold water can influence the textural qualities of a food product, which can lead to both advantages and limitations. In bread, additions which are high in fibre can affect the rheological properties of both dough and baked loaf. During dough formation, fibre can absorb water and thus result in incomplete hydration of glutenous proteins, which leads to lower loaf volume and a firmer crumb texture. Therefore, the ability of flour to hold water can improve the shelf life of baked bread and slow the action of syneresis . When SMDuring this study, bread was successfully formulated with the addition of SMB100 flour with varying results. With an aim of increasing the fibre content in bread while utilising an industry by-product, bread was formulated with SMB 100. The increase in fibre content was determined from the ingredients used. SMB 5% had a calculated fibre content of 26.6 g/loaf, while SMB 10% and SMB 12.5% had levels of 35.7 and 40.3 g/loaf respectively. This is an increase from the standard formulation (control), which only had 17.5 g of fibre per loaf. The WHO has recommended that an adult diet contains greater than 25 g of dietary fibre per day. A serving (two slices) of SMB 5% would contribute 3.3 g of dietary fibre while 10% SMB would contribute 4.4 g/serving, which equates to 12.7% and 16.9% of the recommended daily intake of fibre . Furtherp > 0.05) in their mass, with a range of 754–773.8 g. The inclusion of SMB100 flour did significantly (p < 0.05) influence the volume of all loaves, with the largest volume from control loaves at 3816.7 mL. From the results (p > 0.05) in loaf density, with 0.20 and 0.23 g/mL, respectively. Both SMB 10% and 12.5% had significantly higher densities than that of control and SMB 5%. A reduction in volume in combination with an increase in density has been reported in other studies where composite flours were integrated with wheat flour in bread [The impact of SMB100 flour substitution on volume and relative density of white bread is presented in  results A the vol results A, the coTo further determine the effects of inclusion of SMB100 in white bread on the forces that are required to bite and chew a slice of white bread, a textural profile analysis was undertaken. The textural profile is shown in p > 0.05) at 57% and 53%, respectively. While loaves formulated with 10% and 12.5% had cohesiveness of 44% and 39%, respectively, which were statistically different from other measurements. Chewiness has a relationship with both hardness and cohesiveness. Chewiness increased statistically once inclusion reached 10% and higher. From the textural characteristics of bread substituted with SMB100, it can be asserted that as the inclusion rate increases, the hardness, cohesiveness, and chewiness will be affected in a negative manner. At an inclusion rate of 5%, it is possible to produce bread that is similar in textural qualities to the control. Noticeably, substitution of SMB can be increased, but the density and texture may not be accepted by the consumers, as a recent study found that bread made of wheat, millet and SMB has low hedonic score [Hardness is the maximum force (peak 1 max (N)) required to deform a sample during the first compression cycle. The results B showed ic score . TherefoChanges in volume, density and textural properties of bread formulated with composite flours has been reported to result from a reduction in gluten due to the substitution. During mixing of the dough for the current study, it was noted that as substitution increased, the dough became increasingly dryer. As SMB100 flour has a high proportion of fibre, it was inferred that this component absorbed moisture. This has been observed by others . As suchp < 0.05) from control and SMB 5%. There were no statistical differences (p > 0.05) in hue angle and chroma of crust, revealing the colour is similar across the treatments. To highlight any changes in colour and saturation for crust colour, compared to control loaves, ΔE, ΔC, ΔH° were assessed. For ΔE and ΔH°, the total colour change and change in hue showed the same trend. From p > 0.05). Bread with 12.5% substitution rates had the largest shift from control with 1.34, which was significantly different from SMB 5% alone. There was no significant difference between the change in chroma for any treatment for crust colour. Overall SMB100 flour had minimal effect on the colour of the crust of white bread. Lightness (L*) was the only measure that was affected, which is considered in the calculations for ΔE and ΔH°. It may be possible to suggest that the production of higher coloured Maillard reaction end products were retarded during baking.Colour is an important characteristic of any food item. The inclusion of SMB100 flour had various effects on the colour of baked bread loaves during this study. The results  show thap > 0.05) was shown for control (65.2), SMB 5% (65.2) and SMB 10% (68.9), while SMB 12.5% (70.8) was reported to be different (p < 0.05) from control and SMB 5% but shared similarity with SMB 10%. The H° for all loaves were affected by inclusion, with statistical differences (p < 0.05) for the mean of each treatment. The angle changed from 87.2 for control to 81.3 for 12.5%, which shows a shift towards the red spectrum as more flour was substituted. The intensity of the colours also changed in a similar manner, with values for chroma changing from the control at 14.5 through to 19.7 for SMB 10%, with all treatments significantly different (p < 0.05) from control. When comparing the shift of total colour, hue angle and saturation, SMB 5% showed the least change from control, with results of 2.79 for ΔE, 2.62 for ΔH°, and 0.75 for ΔC. Overall, the results for SMB 10% and 12.5% were statistically independent (p > 0.05) from SMB 5%, except for ΔC for SMB 12.5%, which shared similarities with both treatments.As observed in crumb colour, the internal crumb lightness (L*) showed an increasing trend as inclusion of SMB100 flour increased. From the results , statistAs SMB100 flour has a mild yellow colour, the inclusion of SMB100 flour can have an impact on the colour of the crumb of white bread. Unlike the outer crust of bread, which experiences high temperature, leading to the formation of crust colour, the internal crumb retains moisture, retarding this change in colour, and, as such, there was minimal change in lightness, but a general change in hue angle. This trend in colour changes was not observed by others ,57.It can be concluded that SMB dried in a fan forced oven at 100 °C can be successfully milled to a flour for applications in food as a nutrient substitute, especially for improvement of protein and fibre content. In particular, the physicochemical profile showed high proportions of dietary fibre (38.4% IF and 2.2% SF) and proteins (26.5%), highlighting the nutritional value of SMB100 flour. The low water activity (0.55) indicates a shelf stable powder, which, along with a capacity to absorb water with limited solubility, makes SMB100 a very promising wheat flour substitute.When incorporated as a white wheat flour replacement in bread, physical properties were affected as substitution levels increased. This was particularly evident in SMB 10% and 12.5%, where loaf volume, relative density and texture profile analysis were negatively affected. However, bread formulated with 5% SMB100 flour exhibited minimal influence on all physical properties tested. Changes in colour of bread were also observed; however, this was most evident in variation of crumb colour. Overall, crust colour was not significantly affected. Considering these results together, it can be asserted that SMB100 can be used as a flour for simple substitute in bread at a rate of 5% (by mass) of white wheat flour. As the test conditions used for this project only considered simple substitution of wheat flour, future studies should be undertaken to optimise the formulation and processing conditions to improve the physical and textural qualities of bread with potentially higher substitution rates. Achieving this would allow the production of a white wheat bread which could be classed as a high fibre food.


In vitro starch digestibility, in vitro protein digestibility of wholemeal flour, total flavonoids content, and total phenolics content of digestive juice were used to evaluate the bioaccessibility, and a significant variation (p < 0.05) was noted. Results showed that steam explosion enhanced the gastric protein digestibility ranged from 5.67 to 6.92% and the intestinal protein digestibility ranged from 16.77 to 49.12%. Steam-exploded wholemeal flour  had the highest protein digestibility and rapidly digestible starch content. Compared with native flour, steam explosion  contributed to a 0.72-fold and 0.33-fold increment of total flavonoids content and total phenolics content in digestible juice. Chemical changes of wholemeal flour, induced by steam explosion, caused the changes in the solvent retention capacity, rheological property of wholemeal flour, and altered the falling number (and liquefaction number). An increasing tendency to solid-like behavior and the gel strength of wholemeal flour was significantly enhanced by the steam explosion at 0.5 MPa for 5 min, while the gluten was not weakened. This study indicated that steam-exploded wholemeal flour  could serve as a potential ingredient with the noticeable bioaccessibility and physicochemical properties in cereal products.Whole grain contains many health-promoting ingredients, but due to its poor bioaccessibility and processibility, it is not widely accepted by consumers. The steam explosion was exploited to modify the nutritional bioaccessibility and the physicochemical properties of wholemeal flour in this study.  Wheat is one of the most important grain crops worldwide, which provides the essential dietary components for many individuals daily, such as energy, proteins, dietary fibers, and phytochemicals . The conThermal treatments could increase the soluble dietary fiber content and the bioaccessibility of bioactive compounds from cereal bran together with some technological benefits , 18. RecThis study aimed to investigate the effect of steam explosion on the bioaccessibility of wholemeal flour, which was evaluated by starch digestibility, protein digestibility of wholemeal flour, total flavonoids content, and total phenolics content of digestive juice. And the effects of steam explosion on the physicochemical properties of wholemeal flour, including color profiles, chemical compounds, solvent retention capacity, and rheological properties were analyzed.The steam explosion was performed using a self-designed batch vessel , which cin vitro protein digestibility following gastric (pepsin) and intestinal (trypsin) digestion. Briefly, 2 g of wholemeal flour was mixed with 20 ml of distilled water, and added 1 mol/L HCl to adjust pH = 2, then incubated with 1 g of pepsin  in 100 ml of 0.01 mol/L HCl at 37°C for 2 h and neutralized with 1 mol/L NaHCO3. This was followed by the addition of 0.4 g of trypsin , 2.5 g of bile powder in 100 ml of 0.1 mol/L NaHCO3, and incubated at 37°C for 2 h.Method , 24 adopIn vitro starch digestibility was determined by the previous report  and 3 ml of deionized water to prepare digestive enzyme solution. Wholemeal flours (500 mg) were mixed with 14 ml of deionized water and boiled in a water bath for 5 min. Then 1 ml of digestive enzyme solution was added, shaken, and incubated at 37°C. Sample solutions (0.2 ml) were added with 80% of ethanol solution (5 ml) immediately, after 20, 60, 120, 180, and 240 min, respectively.s report –29 with The total phenolics content of digestive juice after protein digestion was analyzed using the Folin-Ciocalteu colorimetric method described by Veronica et al. . The totAspergillus niger, 1 × 105 U/ml, 200 μl) were added and incubated at 60°C for 45 min.The protein content of wholemeal flour was analyzed using the AACC method 46-08. Total arabinoxylans and water-extractable arabinoxylans content were determined using the Hashimoto’s method . The staThe Hagberg-Perten falling number (FN) of all samples was determined using an FN-IV instrument  according to the manufacturer’s instructions. Liquefaction number (LN) was calculated using the following formula: LN = 6,000/(FN-50).The color profiles of native and steam-exploded wholemeal flours were measured with a chromameter . L* means lightness of the flour, a* indicates green or red-purple color, and b* indicates yellow or blue color . Chroma The solvent retention capacity (SRC) tests that included 5% lactic acid (LA), 5% sodium carbonate (SC), 50% sucrose (Suc), and water (W) were measured according to the AACC International Approved Method 56-11.02.The dynamic rheological property of all samples was investigated using an HR-1 Rheometer  based on a method , 36. An p < 0.05). The results were reported as mean ± standard deviation.Three replicated tests were performed, and the average values were reported. Experimental data were processed by one-way analysis of variance using IBM SPSS Statistics 20  with Duncan’s multiple range test . During the intestinal stage, protein digestibility of wheat flour ranged from 6.81 to 49.12%. Protein digestibility of native wheat flour (6.81%) increased significantly (p < 0.05) after the steam explosion. The highest ultimate protein digestibility (49.12%) of steam-exploded wholemeal flour was obtained under the condition of the steam explosion at 0.5 MPa for 5 min. The steam explosion broke cell walls and promoted the breakdown of proteins into smaller units, which might improve the digestibility and bioaccessibility of wheat flour  by the steam explosion at 0.5 MPa for 3–5 min, whereas slowly digestible starch and resistant starch content decreased to 7.92–11.77% and 30.63–33.77%, respectively. A proper and reasonable steam explosion disrupted the cell wall structure and promoted enzyme access starch, and the starch was gelatinized during steam explosion processing, thus enhancing starch susceptibility and bioaccessibility. Wholemeal modification by the steam explosion at 0.5 MPa for 5 min had the highest rapidly digestible starch (58.31%), lowest slowly digestible starch (7.92%), and resistant starch (33.77%) contents, respectively.The rapidly digestible starch, slowly digestible starch, and resistant starch contents of native wholemeal flour were 51.47, 5.43, and 43.10%, respectively . The rapin vitro (p < 0.05) enhanced total phenolics, flavonoids contents, and DPPH radical scavenging activity  in protein and starch content were found among the native and all steam-exploded wholemeal flours (p < 0.05) increased to reach a peak (0.74%) by steam explosion. The water-extractable arabinoxylans content increased with increasing pressure to reach a peak at 0.7 MPa for 5 min. At 0.5 MPa, the content showed a peak at 0.5 MPa for 5 min, and after 5 min, it decreased. The outer layer of the wheat kernel was surrounded by the thick non-lignified cell walls, which were composed mainly of dietary fiber, with the predominance of arabinoxylans  decreased by the steam explosion to reach a peak at 0.7 MPa for 5 min. Liquefaction numbers could be used in the milling and baking industries to calculate the mixing ratio of flour to be blended with a known falling number (p > 0.05) in liquefaction number found among the native and all steam-exploded wholemeal flours at 0.3 MPa for 5 min and 0.5 MPa for 3–5 min. In general, the data suggested that the steam explosion might enhance the susceptibility of starch to digestive enzyme hydrolysis and increase the damage of wheat starch, which together contributed to the decrease of the falling number values.The falling number apparatus has been widely used in the rapid determination of α-amylase activity in grain, which was quantified by reducing the viscosity of the flour paste . The falg number , 55. Liqp > 0.05), which indicated the stability of color in wholemeal flours. The Hue angle values increased from 0.54 to 0.57–0.61 during the steam explosion process at 0.3 MPa for 5 min and 0.5 MPa for 3 min. It suggested increment from a greener color to an orange-red color of steam-exploded wholemeal. These results indicated that the partial steam explosion affected the color quality of wholemeal flour and produced more browning compound(s). There was a remarkable positive relationship (p < 0.01) between b* and Hue value (r = 0.948). The steam explosion at 0.5 MPa for 5 min had better color performance than other conditions, which was conducive in maintaining the color acceptability of native wholemeal.The color profiles of L*, a*, and b* values of wholemeal flours are shown in p < 0.05) increased by the steam explosion (p < 0.05) increased with the steam explosion treatment time extended at 0.5 MPa from 3 to 7 min. W-SRC also increased with the extension of steam explosion treatment pressure from 0.3 to 0.7 MPa for 5 min. This might be caused by the fracture of wholemeal under the high pressure and high temperature of steam explosion, which exposed more hydrophilic groups and allowed the flour more water-binding capacity (p < 0.05) increased with the steam explosion treatment time extended at 0.5 MPa from 3 to 7 min. However, Suc-SRC decreased with the increase in pressure from 0.3 to 0.7 MPa for 5 min. Compared to native flour, LA-SRC was significantly (p < 0.05) increased by steam explosion. The LA-SRC of steam-exploded flour showed no change when the treatment was at 0.5 MPa for 5 min. SC-SRC increased significantly (p < 0.05) with the extending of steam explosion pressure from 0.3 to 0.7 MPa for 5 min, which might be attributed to the increase of damaged starch content induced by steam explosion. GPI might be a proper predictive index of the gluten property influenced by all the components in wheat flour (p > 0.05) on the GPI of wholemeal flour, except for the condition at 0.3 MPa for 5 min, which showed that steam explosion was conducive to maintaining the gluten strength. According to the results above, the steam explosion was beneficial in improving the SRC values of wholemeal flour while the gluten was not weakened.Solvent retention capacity (SRC) was deemed to be an efficient method to evaluate wheat flour quality; it is a special method for predicting the flour function by estimating the relative contributions of individual flour compounds to water absorption, which is also used to evaluate oat flour properties . The difxplosion . W-SRC scapacity . Steam eat flour . The steBoth the storage modulus and the loss modulus of wholemeal flour increased with the increase of frequency, and the elasticity and viscosity were frequency-dependent . The stop < 0.05) correlations with the DPPH radical scavenging activity of wholemeal extracts. A positive correlation was found between the Suc-SRC and loss modulus . The water-extractable arabinoxylans and total phenolics content were significantly (p < 0.05) correlated with LA-SRC. Total phenolics content was positively related to the W-SRC (r = 0.99), LA-SRC (r = 0.97), and SC-SRC (r = 0.98), whereas negatively connected to the falling number (r = –0.89). Protein content was positively related to the intestinal protein digestion, viscosity, storage modulus, and loss modulus, whereas negatively connected to the loss factor. The falling number showed a strong negative relationship with the liquefaction number, while the falling number positively correlated with the total flavonoids content.Elucidating the correlations of bioaccessibility and physicochemical properties of wholemeal flour as shown in The bioaccessibility and physicochemical properties of wholemeal flour were altered by the thermal-mechanical action of steam explosion. The cell wall was broken by facilitating the conversion of water-unextractable to water-extractable arabinoxylans. As a result, steam explosion treatment improved protein digestibility, starch digestibility, and phenolics bioaccessibility of wholemeal flour. Compared with native wholemeal flour, steam-exploded wholemeal flour existed the highest protein digestibility and the hydrolysis rate of starches at 0.5 MPa for 5 min. And steam explosion contributed to the increase of total flavonoids content, total phenolics content, and DPPH radical scavenging activity in digestible juice. Above chemical changes in wholemeal flour induced by steam explosion caused the physicochemical property changes of wholemeal flour, including the color profiles, solvent retention capacity, and rheological property. Results showed steam explosion was beneficial in improving the solvent retention capacity values while the gluten was not weakened. An increasing tendency to solid-like behavior and the gel strength of wholemeal flour was significantly enhanced by the steam explosion at 0.5 MPa for 5 min. These phenomena demonstrated that steam explosion induced physicochemical property changes of wholemeal flour depending on the chemical constituent change, such as arabinoxylans and starch. This study provided an effective strategy that could be employed to improve the nutritional bioaccessibility and modify the physicochemical property of cereal flour.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.FK and XG: conceptualization, resources, and supervision. FK, YL, and QZ: methodology and validation. FK: software, formal analysis, data curation, writing-original draft preparation, writing-review and editing, project administration, and funding acquisition. QZ, FK, YZ, and YL: investigation. QZ and FK: visualization. All authors have read and agreed to the published version of the manuscript.


One of the food industry’s challenges is to enhance bread quality from a nutritional point of view without impacting negatively sensorial characteristics and consumer decisions on product choice. This study aimed to assess the baking characteristics of wheat bread supplemented with quinoa flour (QF) of large, medium and small particle sizes at typical doses previously established based on an optimization process, and to evaluate the optimal bread from a physical, textural, nutritional, and sensorial point of view. The results showed a decrease in the Falling number index, water absorption, dough stability, speed of protein weakening, dough extensibility, and creep-recovery compliances for optimal wheat–quinoa composite samples with large and medium particle sizes; meanwhile, for the samples with small particle sizes an opposite trend was recorded, with the exception of dough extensibility. Dough fermentation parameters and bread volume rose for all optimal formulations, while firmness decreased compared to wheat bread. All optimal bread samples presented an improved nutritional profile depending on the particle size. The protein content was up to 19% higher, ash up to 13.8%, and lipids up to fifteen times higher. A noticeable enrichment in minerals  and essential amino acids (with 13.53%) was also obtained for all optimal breads. From an acceptability point of view, the highest score (8.70) was recorded for the optimal bread with a QF of medium particle size. These findings offer processors new information which will be useful for diversifying bakery products with an enhanced nutritional profile. Cereals and cereal products have been the major component of the human diet throughout the world since ancient times. Wheat represents one of the most important cereals in terms of human nutrition, being from a nutritional point of view an important source of complex carbohydrates, group B vitamins, iron, and trace minerals, especially calcium, phosphorus, iron, potassium, and dietary fibers, with low lipid content . HoweverBread has a fundamental role in nutrition due to the adequate balance of macronutrients in its composition; in addition, it offers some minerals and micronutrients. White bread, available in most global markets, has a low content of nutrients due to the use of refined wheat flour as a raw material for its manufacture. Nowadays, consumers are more and more interested in their health, and buy foods with beneficial effects on health; to accommodate this, the baking industry is trying to provide functional food with pro-health properties. At the same time, there is a need to develop bakery products with new organoleptic properties which meet the needs of the market. The use of composite flour for the manufacture of bread has gradually gained importance for various economic and nutritional reasons. Different studies have been carried out on the influence of wheat–pseudocereal composite flour on the physico-chemical properties of bakery products, and their relationship with sensory properties and nutritional advantages ,4,5. AddAn enrichment of wheat flour with minerals, and implicitly, an increase in the biological value of bread, can be achieved by adding quinoa flour. Wang et al.  studied Various studies have revealed quinoa flour’s potential to improve the rheological behavior of wheat flour dough and the quality of finite products. However, there is a lack of reports on the effects of the optimal wheat–quinoa composite flour of three different QF particle sizes on the rheological properties of dough and the features of bread. Thus, the purpose of this work is to ascertain the effect of optimal composite wheat–quinoa flour of large, medium and, small QF particle sizes on bread quality parameters in terms of chemical, physical, textural and sensory characteristics. This study could shed new light on aspects of the practical use of different quinoa particle sizes to substitute wheat flour.The distribution of chemical components of optimal wheat–quinoa composite flours with large, medium, and small particle sizes  compared to wheat flour (WF) is shown in p > 0.05) regarding moisture (p < 0.05) was found between wheat flour and optimal composite flours with small and medium QF particle sizes (p < 0.05) higher than the lipid content of wheat flour (1.40%). A remarkable difference was found also between the ash content of the optimal composite flours (0.85–0.95%) and wheat flour (0.65%). The optimal wheat–quinoa composite flours did not show significant differences (moisture . The prole sizes . The lipp < 0.05) were observed regarding iron content for all studied flours, varying between 1.80–8.12%. Regarding the flours’ zinc content, there were no significant differences between samples. The results regarding the macro- and micro-elements of optimal wheat–quinoa composite flour vs. wheat flour were presented in The variation in macro- and micro-elements showed an increased content for the optimal wheat–quinoa composite flour corresponding to the large, medium and small particle sizes of quinoa flour compared to wheat flour, and the highest values were found in composite flour with large particle size (OF_QL).The amino acid content of the optimal wheat–quinoa composite flour compared to that of wheat flour is shown in The optimal wheat–quinoa composite flour presented considerable higher amounts for essential amino acids isoleucine (5.69–5.91%), methionine (7.23–7.92), phenylalanine (7.41–8.32%), tryptophan (12.39–12.59%) a, and noThe baking characteristics of the optimal wheat–quinoa composite flour for each quinoa flour particle size achieved by using different devices  in order to make a complete evaluation are shown in The formulation of wheat–quinoa composite flours with the optimal addition doses typical of each QF particle size aimed to obtain the best technological and quality characteristics in bread. The results indicated a slight increase in the Falling number index in the optimal composite flour with small particles when compared to the wheat flour. Water absorption capacity and C1-2 and C5-4 torques indicated a slight decrease for optimal wheat–quinoa flour with large and medium particle sizes, while dough development time and C3-4 torque raised comparatively with values registered for wheat flour. Alveographic parameters indicated an increase in tenacity and alveographic P/L ratio for all the optimal composite flour, while extensibility and deformation energy decreased compared to the control. The fermentation behavior of the composite flour doughs indicated an improvement in terms of gas formation and retention capacity compared to the wheat flour dough. max) indicated a substantial decrease compared to wheat flour  and the maximum gelatinization temperature (Tat flour . A highep < 0.05) between the samples. The appearance and section of the bread samples with the optimal dose of quinoa flour corresponding to the large, medium, and small particle size  compared to wheat flour bread are shown in the The physical characteristics, volume, specific volume, porosity, and elasticity of the bread obtained are presented in For the bread samples made from optimal composite flour, all the particle sizes which substitute wheat flour at typical doses improved the samples volume, specific volume, porosity, and elasticity . The besThe color parameters of the optimal bread crust were considerably influenced by the particle size, the crust lightness of the wheat flour bread being much higher than that of the optimal bread crust. The lightness of the optimal bread samples decreased with decreasing particle size .L*) of the bread samples also decreased depending on particle size, and the lowest values was found for optimal bread with medium QF particles. The variation of redness (a*) and yellowish (b*) color parameters showed an irregular trend (The crumb lightness (ar trend . The totp < 0.05) decreased in the optimal wheat–quinoa composite bread compared to wheat flour bread, while the cohesiveness did not present considerable differences between the bread samples, even though a slight decrease was observed with the increase in particle size. (p < 0.05) compared to the control sample (5.71 N), the highest value being found in bread with large quinoa flour, while the lowest value was obtained for the bread with small quinoa flour particle size (4.39 N). The highest values of crumb masticability after wheat flour-based bread are offered by the bread with a medium quinoa flour particle size. Evaluation of the optimal wheat–quinoa flour typical to each particle size’s effect on the bread textural parameters is valuable because it indicates consumers’ perception when they chew the bread.The firmness, springiness, gumminess, and masticability significantly  among themselves and compared to wheat flour. The moisture content of the optimal bread presented a slight increase, especially in the optimal bread with medium particle size  content in optimal bread samples corresponding to large, medium, and small particle size is presented in The amino acid content of the bread samples obtained from the optimal wheat–quinoa composite flour varied as follows: isoleucine (5.58–6.23%), leucine (3.73–7.47%), methionine (7.38–7.94%), phenylalanine (8.54–9.28%), threonine (7.90–9.25%), valine (3.99–9.26%), alanine (5.36–5.87%), aspartic acid (24.56–43.28%), glutamic acid (10.83–55.45%), glutamine (108.26–128.24%), glycine (2.79–12.48 %), serine (6.37–7.05%), tyrosine (10.05–11.30%), asparagine (6.53–6.78%), proline (7.56–8.01%), thioproline (12.49–20.69%), hydroxyproline (9.60–14.26%). According to the data presented, the wheat flour bread showed significantly lower amounts of essential amino acids  compared to the optimal bread with quinoa flour particle sizes. The bread obtained from composite flour with medium and small quinoa particle sizes presented generally higher levels of essential amino acids compared to the bread with the large quinoa particle size. Generally, among the non-essential amino acids, the highest amounts were found for aspartic and glutamic acid, and thioproline. The highest amounts of aspartic acid and hydroxyproline were recorded in the optimal bread with small particle size, and the highest amount of serine was recorded in the optimal bread with medium particle size.The macro- and micro-element content of the bread samples obtained from the optimal wheat–quinoa composite flours showed variation depending on quinoa particle size composition .For bread made from optimal wheat–quinoa composite flour, an increase in mineral content was obtained in the sample with medium-sized particles, followed by the sample with small-sized particles, and then by the one with large-sized particles. The results of the sensory analysis revealed some improvements in terms of overall acceptability, appearance, core structure, taste, and smell of the bread samples made from the optimal composite flours containing medium and large quinoa flour particles, compared to the wheat flour bread .From the all optimal breads, the bread with the small particle size of quinoa flour was the least preferred, registering a lower score for overall acceptability .In order to demonstrate comprehensively the similarities and/or differences between the evaluated variables, a multivariate technique, principal components analysis (PCA), was applied. The relationships between dough rheological parameters, bread proximate composition, physical, textural and sensorial characteristics in the bread samples formulated are shown in The variation of the optimal wheat–quinoa composite flour protein content was in accordance with the results obtained by other authors ,21. ThisThe variation in the Falling number index for optimal composite flour is related to the quinoa starch. Despite the fact that the specific surface area of quinoa starch is higher than wheat starch, it is more sensitive to α-amylase hydrolysis than wheat starch . AdditioThe addition of quinoa flour of medium and small particle size to the composite flour led to a firmer dough, which was possibly due to the high protein content of the smallest quinoa flour particle sizes. In bread in which a quantity of wheat flour is replaced by gluten-free flour, the dough viscosity before the starch gelatinization is decisive in preventing the sedimentation of the flour particles so that the gas cells grow and thus maintain a homogeneous system during the fermentation and baking process until starch gelatinization ,35,36. TFor the bread made from optimal composite flour, the best results in terms of technological parameters were obtained for the optimal bread with a large particle size, but all fractions positively influenced the volume of the samples, being significantly higher than the wheat bread volume. Bread volume and crumb structure depend on a number of factors, such as dough viscosity, amylose/amylopectin ratio, presence of surfactants, and/or protein denaturation (hydrolysis) upon heating ,35. The The partial replacement of wheat flour with quinoa flour produced redder, yellower, and lighter bread as indicated by the ∆E values. The high ∆E values of optimal wheat–quinoa bread indicate that color changes could easily be perceived without closer visual inspection, in comparison to wheat flour bread. The decrease in the lightness of crust and crumb of the bread can be explained by Maillard reaction products which are influenced by the distribution of water and the reaction between reducing sugars and amino acids. Carotenoids, chlorophyll, and lignin from quinoa seeds influence the color of the flour and, indirectly, the color of the finite products . The texture parameters are interdependent of the mouthfeel of bread. For all optimal breads, a more desirable firmness was observed in comparison with wheat bread. The obtained results can be explained by the lower content of starch and higher content of fiber from quinoa flour, which could restrain starch retrogradation. This phenomenon involves the reorganisation of starch component molecules into an ordered structure. The rate of retrogradation is influenced by the availability of water, since the crystallization of amylopectin needs to incorporate water molecules into crystallites .An improvement of the nutritional profile was also obtained in the case of optimal wheat–quinoa composite flour bread related to the quinoa flour particle sizes. The protein and lipid content increased considerably for all optimal bread samples compared to the wheat flour bread. This improvement can be explained by the high content of proteins and lipids, especially in the medium-sized particles of quinoa flour . SimilarThe increase in mineral content in the optimal bread formulated with quinoa flour could be due to higher mineral content in quinoa seeds compared to wheat. These results are also in agreement with those reported by El-Sohaimy et al. , who fouThe increase in essential amino acid content in the optimal bread corresponding to study particle sizes may be due to the high content of these amino acids in quinoa seeds, which have a higher essential amino acid content than wheat protein . Until nReplacing wheat flour with different quinoa particle sizes at typical doses had a significant effect on the sensory quality of bread, i.e., the taste, smell, crumb structure, appearance, and overall acceptability. Our results fall in line with other research studies that highlight that bread with 5 and 20% quinoa flour proportion had an overall acceptable sensory quality ,49.p < 0.05) between the evaluated parameters. Very strong correlations (0.95 < r < 0.99) were obtained between the dough rheological parameters and the chemical constituents, physical parameters, texture and sensory characteristics of the bread. Positive correlations were found between the protein content and elastic and viscous moduli of dough , but protein was negatively correlated with bread firmness (r = −0.96), while the bread lipids negatively influenced only its cohesiveness (r = −0.95). An indirect relationship was found between the viscosity factor and the lipid content of the bread (r = −0.96). The formation of amylose–lipid complexes alters the gelatinization characteristics of starch [The Pearson correlation analysis revealed significant correlations , with the protein and lipid content of the bread, the bread textural parameters , physical properties (volume and porosity), and the sensory characteristics, appearance and taste. The second principal component (PC2) was associated with maximum creep compliance, bread moisture and carbohydrate content, bread chewiness, and overall bread acceptability.By using the principal component analysis (PCA), the relationships between the assessed parameters and the type of the sample were highlighted on the two principal components of the bi-plot. The first principal component (PC1) was associated with the dynamic dough rheological parameters  (ash content max. 0.65%) , fresh yeast , salt, quinoa seeds  and water. Quinoa seeds (Chenopodium quinoa Willd.) of the following composition: protein (14.12%), lipids (5.61%), and ash (2.00%), reported to dried substances, were used as an enrichment ingredient. Quinoa seeds purchased from the local supermarket  were milled with a laboratory ultra-centrifugal mill  and sieved with a Retsch Vibratory Sieve Shaker AS 200 basic  for half hour at 70 Hz amplitude to obtain the following quinoa flour particle sizes: large, QL , medium, QM  and small, QS (<180 µm) which then were packed into sealed zip plastic bags and stored at 4 ± 1 °C for further use. The materials used were wheat flour  were prepared by adding the optimal doses of 9.13, 10.57, and 10.25% quinoa flour—established for large, medium and small particle size, respectively, in a previous study —to wheatThe dough was obtained from 300 g of flour, 12 g of yeast, 5.4 g of salt, and water until the dough reach the optimum consistency determined at Mixolab  . When thThe flours were analyzed according to the International Association for Cereal Chemistry standard methods ; the moiThe K, Ca, Mg, Na, Zn, Fe, Mn, and Cu elements contents of the wheat flour, optimal wheat–quinoa composite flour and bread were determined by flame atomic absorption spectrometry (FAAS) . The analysis of the sample involved two stages: the mineralization of the sample and the metal dosage by spectrophotometry. During mineralization, the organic matter from the sample (5.00 ± 0.001 g) is destroyed by carbonization and combustion in a muffle furnace , with the temperature gradually increasing from 250 to 450 °C, up to 900 °C, for 8 h. 5 mL HCl 6 mol/L (STAS 13013/1-91) is added to the ash obtained, and then the acid is evaporated using a sand bath, and the residue is dissolved with 730 µL HNO3 69% and brought to the mark (50 mL) with deionized water. Deionized water was used as a control sample, following the same procedure. The spectrophotometric determination involved the following steps: activating the hollow cathode lamp corresponding to the elements , adjusting the operational parameters , activating and adjusting the flame, as well as establishing the curve standard by absorbing four working standard solutions of different concentrations. The calibration curve made for each element covers the range of 0.5–5.0 mg/L Ca, 0.5–2.5 mg/L Cu, 0.5–5.0 mg/L Fe, 0.05–0.30 mg/L Mg, 0.5–3.0 mg/L Mn, 0.05–0.60 mg/L Zn, 0.1–0.5 mg/L Na, and 0.2–1.0 mg/L K. The wavelengths taken into account when determining Ca, Cu, Fe, Mg, Mn, Zn, K and Na elements correspond to 422.7, 342.7, 248.3, 285.2, 279.5, 213.8, 589.0, and 766.5 nm. Air-acetylene as the flame type, a gas flow rate of 15.0 L/min, a pre-spray time of 10 s, an integration time of 5 s, and a response time of 1 s were also included as working conditions. The mineral elements are expressed as mg/100 g of flour and were calculated with Equation (1):For the extraction and quantification of the amino acids from the wheat flour, the optimal wheat–quinoa composite flour, and the bread, 3.70 ± 0.1 g of sample was mixed with 30 mL of 15% trichloroacetic acid (TCA). The pH of the solution was adjusted to 2.2 with sodium hydroxide solution and diluted with 50 mL of 15% TCA . Then, tmax), and creep-recovery compliance .Dough dynamic rheological properties were assessed by using a Thermo-HAAKE, MARS 40  with parallel plate–plate geometry. The dynamic parameters measured were elastic modulus (G′), viscous modulus (G″), viscosity factor (tan δ), maximum gelatinization temperature  of the wheat flour and optimal wheat–quinoa composite flour related to each studied particle size of QF was determined using a Falling number device  in order to determine the amylolytic activity.Mixolab Chopin equipment  was used for a complete rheological test of wheat and optimal wheat–quinoa composite flour following the ICC 173, AACC 54-60.01 method . The MixThe rheological properties during dough biaxial extension, tenacity (P), extensibility (L), dough strength (W), and alveograpic ratio (P/L) were determined with Alveograph Chopin equipment  following the ICC 121 method . 2 production (VT), the volume of the gas retained in the dough at the end of the test (VR), and the retention coefficient (CR).The fermentation test of dough was performed with the rheofermentometer device  following the AACC 89–01.01 method . The detThe physical characteristics of the bread samples made from optimal wheat–quinoa composite flour and wheat flour, bread volume (BV), specific volume (Sp_Volume), porosity, and elasticity were determined according to the Romanian standard SR 90: 2007 . A TVT-6L*, a*, b* values, when L* indicates the lightness, a*, chromaticity on a green (−) to red (+), and b*, chromaticity on a blue (−) to yellow (+). Crumb and crust color analysis was performed at room temperature according to the reflectance method with a CR-700 colorimeter , by measuring at five different points on the surface, respectively, in the center of the middle slice of bread. The parameters of the colorimeter in the reflection mode were set as follows: a standard illuminant D65, observation angle of 10°, and an aperture of 30 mm. The total color differences (ΔE) were calculated according to the methods of [The procedure for bread color assessment is based on the determination of the CIE thods of , with EqThe evaluation of bread sensory attributes was performed in accordance with the Romanian Standard SR ISO 11035:2007 . The 13 p < 0.05. A principal component analysis (PCA) was applied to highlight the relationships between the wheat–quinoa flour dough, bread proximate composition, textural characteristics and acceptability, and to observe similarities or dissimilarities between them. The data were shown as mean with standard deviation, and for every sample, the experiments were conducted at least in duplicate. SPSS software 25.0   was employed to conduct the statistical analysis of the data. Statistically significant differences between samples were determined by a one-way ANOVA. The relationships among the studied parameters were tested by using Pearson’s coefficient at Compared to the wheat bread, the physical characteristics of the bread made from optimal wheat–quinoa composite flour showed an improvement in volume, porosity, and elasticity, and also in firmness, springiness, and chewiness for all particle sizes, while the lightness of the bread crust and crumb decreased. The highest values for volume, porosity and crumb elasticity were found for optimal bread with medium quinoa particle sizes (OB_QM), while firmness decreased, indicating an improvement for this bread. The nutritional composition of optimal bread revealed a considerable increase in protein, lipid, ash, total amino acids, and mineral content, whereas carbohydrates decreased compared to wheat bread. The optimal bread with medium particles presented the highest values for nutritional composition, while the energy value was the lowest. The mineral content was up to 2.3 times higher in the optimal bread compared to wheat flour bread; the highest value registered was from bread with a medium particle size. The essential amino acid content followed the same trend and represented up to 14.80% of the total amino acid content; the highest value was registered for bread with a medium particle size, which also presented the highest protein content. Sensory evaluation analysis showed that optimal bread with medium and large particles of quinoa flour exhibited an increase in scores for overall acceptability, appearance, crumb structure, taste, and smell. Of all optimal breads, the bread with medium particles, presenting a score higher than 8.8 for the general acceptability, was the one very well accepted. Considering the nutritional improvement and the consumers’ acceptance of bread with medium quinoa particle size, we can conclude that this optimal bread is the most suitable for the needs of the market. This study demonstrated that the partial substitution of wheat bread with quinoa flour of different particle sizes at typical doses has the potential to improve the physical textural, nutritional, and sensorial properties of formulated bread.


For that purpose, structural domains are the typical level of analysis, but shorter segments, such as subdomains and supersecondary structures, are insightful as well. Here, we propose SWORD2, a web server for exploring how an input protein structure may be decomposed into ‘Protein Units’ that can be hierarchically assembled to delimit structural domains. For each partitioning solution, the relevance of the identified substructures is estimated through different measures. This multilevel analysis is achieved by integrating our previous work on domain delineation, ‘protein peeling’ and model quality assessment. We hope that SWORD2 will be useful to biologists searching for key regions in their proteins of interest and to bioinformaticians building datasets of protein structures. The web server is freely available online:   The first step of protein structure analysis usually consists in breaking down the complex protein structure into simpler yet structurally and functionally relevant units called structural domains that can be further characterized individually. Elementary units of protein structures have already been identified at different levels: starting from several residues in case of secondary structures, to several tens of residues in domains, as well as elements of intermediate size called super secondary structures or Protein Units (PUs) ,2. The iet al.  , we offehttps://github.com/molstar/pdbe-molstar) was used for the 3D protein viewer. The Features Viewer was developed by the RCSB PDB group, Saguaro 1D Feature Viewer project (https://github.com/rcsb/rcsb-saguaro) (https://plotly.com/javascript/). Fetching, parsing and analysis of protein structures was done with Prody  . Plotly th Prody . The bacSWORD2 web server takes a protein structure coordinates file in PDB  format aThe first hierarchical level of analysis proposed by SWORD2 is the secondary structures. They are assigned using DSSP ,25. The α atoms using a logistic function in order to avoid hard threshold cut-off for definition of the inter-residue contacts.The second step of analysis proposed by SWORD2 is the Protein Units (PUs). Protein Peeling  identifiS) and compactness (C). High value of Si,j indicates a high number of contacts between PUs i and j, meaning that these PUs are good candidates to be merged. The compactness criterion Ci,j measures the contact density of the protein domain resulting from merge of PUs i and j. A high value indicates that merging PUs i and j is a favorable event. Therefore, SWORD returns all the domain partitions falling in the acceptance range of separation and compactness values. Acceptable delineations at a given level of partionning  are sorted according to the compactness criterion of the domains C. Finally, the optimal partitioning is selected as the one which (i) has the largest number of domains, (ii) falls in the acceptance range (based on S and C) and (iii) has the highest compactness compared to the other delineations at this level.The third analysis is determined by SWORD, which uses the PUs identified by Protein Peeling to reconstruct domains by gradually merging them until finding the optimal domain delineation based on separation  scoring method /σ and, therefore, expresses the distance (in standard deviations σ) between the pseudo-energy of the domain E and those of the random decoys. To provide users a direct interpretation of the Z-score value, SWORD2 outputs the probability estimated by Chebyshev's inequality that we call Autonomous Unit Likelihood (AUL). Thus, for a substructure with a Z-score of −2.0, the probability of not observing the same pseudo-energy for a randomly delineated domain reaches 75%. This probability of being native reaches 94% for a domain with a Z-score of −4.0. The higher the probability, the more likely it is that the region under consideration is capable of autonomous folding.To estimate the likelihood that a delimited domain is an independent protein fragment , SWORD2 uses our recent g method , which ag method : for eacA if A of its dN domain partitions have a quality of at least A, and the other (dN – A) domains each have a quality lower than A. Therefore, a low A-index is neither good nor bad, as a protein with few high-quality domains and a protein with many low-quality domains will both have a low A-index.A-index is a measure of structural ambiguity that we devised in SWORD’s seminal article . It is aThe web server is completely free to use for any user without login. Users can either provide a PDB code, or upload a structure file  and specify a protein chain. The user can provide an email address to receive the results when computation is completed.If the uploaded file does not correspond to a valid PDB structure or the provided PDB code is incorrect, the job is canceled with an explicit error message.A is assigned by default. Once the file is fully parsed, non-standard residues, heteroatoms and residues having insertion codes are removed and the residues are renumbered starting from 1. As a consequence, users should note that any gap in the original PDB file would not appear in the results page.SWORD2 and its dependencies require a protein chain name to be provided, otherwise chain https://alphafold.ebi.ac.uk/) by using the field ‘AlphaFold Uniprot Accession Id’.Finally, a user can also submit an ID from the AlphaFold Protein Structure Database ,28  to highest number of domains (bottom). We also highlight the inter-PUs junctions , corresponding to the extremities of the different PUs used by SWORD to build the domains. ‘Counts’ is the number of times a junction is found among all SWORD2 alternative partitions. ‘Frequency’ represents the junction count, standardized by the total number of domain delineations produced. ‘Weights’ represents the frequency weighted by the delineation quality and standardized by the total number of identified domain delineations. Domain delineations and Protein Units delineations are clickable. A click on a domain or a PU (colored rectangle) triggers a notification for the user and makes 3D viewer focus and highlight the selected domain or PU delineation, while simultaneously coloring the corresponding sequence fragment (Domain or PU) on top of the viewer and updating the contact probability map in the ‘Contact probability maps’ tab, with either all the PUs used to build the domain or the single PU selected.Two different color sets are used consistently in the results page. Domains are assigned a set of dark tone colors while PUs are represented by a set of lighter tone colors to better distinguish both types.These colors are used in the Summary, the 3D viewer (Sequence + 3D Protein view), the partitions section (Domains & Protein Units), the contact probability maps, and the histogram. Thus, a domain colored in orange will always be referenced with the same color on the results page. Same rule applies for Protein Units.For each identified domain decomposition, the aforementioned quality measure is represented by a color bar gauge ranging from one to five (five is best). Users can visualize a certain SWORD partition by clicking on its dedicated display button which will color the protein domains accordingly in the 3D Viewer as well as in the sequence viewer.Z-score, are provided. Also, like in the Summary, clicking on an individual domain or PU (color badge) will focus and color it in the 3D viewer and also update the contact probability map tab with the corresponding figure (see ‘Contact probability map’ section). The PU(s) that compose a domain are unveiled when clicking on it as well as their corresponding AUL score and Z-score.For each identified domain, the ranges of residue numbers of the PUs composing them, together with their respective aforementioned AUL score and The ‘Protein Units’ tab shows the exhaustive set of PUs determined by the Peeling algorithm at different levels. A low Peeling level reveals few and rather long PUs, whereas higher Peeling levels present more and shorter PUs. Colored badges represent the residue range of PUs that were used by SWORD for the hierarchical construction of the domains of the different alternative partitionings, while a black color badge means it was unused.For each Peeling level, an entropy-derived measure allows the assessment of PUs compactness: the Compaction Index (CI) . This inJunctions correspond to the extremities of the different Protein Units used by SWORD to build the domains. The junctions correspond to zones of probable cuts in the structure, whether these cuttings are of structural, evolutionary or functional origin. The ‘Junctions’ tab provides detailed information on their respective positions in the sequence, the number of times they are found among all SWORD partitionings, their frequencies and weighted frequencies (see ‘Output summary’ section). The statistics of junctions extracted from all SWORD partitionings can bring interesting insights over the quality of delineations, such as the robustness of domains or on the contrary, highlight the ambiguity underlying some portions of the protein which can not be unequivocally defined.The 3D protein viewer is built using the PDBe's implementation of Mol*  with a lThe contact probability maps of PUs, domains and SWORD partitions are provided under the ‘Contact probability maps’ tab. All figures can be accessed inside the downloadable archive of the results. The PUs and domains are traced on the figure using the same color as the one they refer to in the whole results page for consistency (see ‘Protein Peeling’ section).The count of domains in all the identified alternative SWORD partitionings is represented as an histogram under the ‘Frequency of Protein Domains identified by SWORD’ section. Bars are ordered by descending frequency from left to right allowing users to quickly identify the most frequently occuring domains, which are potentially the most robust. The Plotly interactive plot allows users to select a particular domain (color bar). Users can use the tools of the plot to select particular columns, zoom in a particular region, reset the view, as well as download the plot as a .png file.Multiple domain decompositions and different metrics provided by SWORD2 are particularly interesting for the analysis of proteins with complex structure-function relationships often reflected by multiple domain annotations in different databases. Here we present two examples of such proteins and biological insights provided by SWORD2.For DNA polymerase IV PDB: 1jx4) there exists a number of different domain annotations in manual and semi-manual data banks. SWORD2 successfully identifies all of them in terms of Jones criterions : the twojx4 thereMoreover, quality measures assigned by SWORD2 also correlate perfectly with the information contained in the explored databases. Indeed, all the annotations from CATH, SCOP and ECOD identified the region 237–335 as a domain and the consistency histogram reported by SWORD2 Figure  indicateZ-score of –0.8; Figure SWORD2 also provides important insights for the analysis of the Trp repressor (PDB: 1jhgA), in particular thanks to the AUL assessments and junction evaluation illustrated in figure SWORD2 is a web server, which brings together several methods that we previously developed to annotate protein structures at different architectural levels: secondary structures, intermediate-sized independent units called Protein Units and domains.SWORD2 proposes multiple and valuable possible delineations of domains, enables a hierarchical visualization of protein structures, and provides insights into difficult and ambiguous cases. The additional statistics on junctions delimiting Protein Units and domains deliver new meaningful protein annotations. Finally, an estimation of the ability of each defined Protein Unit and domain to fold autonomously is also proposed.https://www.dsimb.inserm.fr/SWORD2.The web server is freely available online without login requirement: