Transglutaminases (TGs) catalyze the covalent crosslinking of proteins via isopeptide bonds. The most prominent isoform, TG2, is associated with physiological processes such as extracellular matrix (ECM) stabilization and plays a crucial role in the pathogenesis of e.g. fibrotic diseases, cancer and celiac disease. Therefore, TG2 represents a pharmacological target of increasing relevance. The glycosaminoglycans (GAG) heparin (HE) and heparan sulfate (HS) constitute high-affinity interaction partners of TG2 in the ECM. Chemically modified GAG are promising molecules for pharmacological applications as their composition and chemical functionalization may be used to tackle the function of ECM molecular systems, which has been recently described for hyaluronan (HA) and chondroitin sulfate (CS). Herein, we investigate the recognition of GAG derivatives by TG2 using an enzyme-crosslinking activity assay in combination with in silico molecular modeling and docking techniques. The study reveals that GAG represent potent inhibitors of TG2 crosslinking activity and offers atom-detailed mechanistic insights. The respective substrate pair consists of a peptide-bound glutamine residue and an amine-donor e.g. the Nε-amino group of a peptide-bound lysine  forming ε-(γ-glutamyl)-lysine isopeptide bonds. Such covalent crosslinks are stable and resistant to enzymatic, chemical and mechanical cleavage3. Besides, TGs can hydrolyse glutamine residues to glutamate and exhibit also isopeptidase activity5.Transglutaminases (TGs) are multifunctional enzymes which covalently link proteins via intra- and intermolecular isopeptide bonds2, whose activities are associated with different physiological processes such as extracellular matrix (ECM) stabilization, wound healing and inflammation, and also with serious diseases such as cancer, atherosclerosis and celiac disease6. Thus, TGs constitute interesting targets for pharmacological applications for the above-mentioned diseases8.The human genome encodes eight TG isoenzymes (TG1-7 and factor XIII)9. The β-sandwich domain contains interaction sites for the tumor suppressor protein p53 (residues 1–139) and fibronectin (residues 88–106). The α/β-transamidase domain includes the catalytic triad  and five calcium (Ca2+) binding sites (S1 (226GMVNCNDD233), S2A/B , S3A/B , S4 (151DSEEERQE158) and S5 (433RDERED438)10). Both β-barrel domains provide GTP/GDP binding sites (residues 476–478 and 538–580). It has been reported that interacting cofactors, e.g., GTP or Ca2+, are able to alter the spatial arrangement of the four TG2 domains11. The closed TG2 conformation is catalytically inactive and stabilized by GTP/GDP acting as a kind of reversible inhibitor bringing the α/β-transamidase domain in close proximity to β-barrel domains 1 and 211. On the other hand, the stretched open TG2 conformation is induced and stabilized in the presence of Ca2+ through the displacement of the β-barrel domains 1 and 212. As reported, six Ca2+ are bound to TG2 in five binding sites13. This open TG2 conformation is associated with the crosslinking activity of the enzyme14.Among the eight known isoenzymes, TG2 is the most prominent isoform being expressed in almost all cell types in the human body. TG2 is a 78 kDa protein consisting of 687 amino acids organized in four structural domains: β-sandwich (residues 1–139), α/β-transamidase (147–460), β-barrel 1 (472–583) and β-barrel 2 (591–687)16. In physiological conditions, intracellular-acting TG2 will be mostly inactive because of high GTP and low Ca2+ levels in the cell. There, TG2 interacts with nuclear, cytosolic and membrane receptors. For example, intracellular TG2 has been shown to prevent apoptosis non-reliant on its transamidase activity, but largely depending on its GTP-binding capacity17. Although the situation in the extracellular space concerning GTP and Ca2+ levels is opposite to the intracellular compartment, TG2 might also be mainly inactive there under physiological conditions18 due to redox regulation, which can lead to the formation of a vicinal disulfide bond between Cys370 and Cys37119. As described by Jin et al.20, the reduction of this disulfide bond results in an active extracellular TG2.TG2 is located intra- as well as extracellularly21. Active TG2 crosslinks many proteins (e.g. fibronectin) in order to form stable well-assembled ECM networks23. Furthermore, TG2 has been reported as a binding partner of the glycosaminoglycans (GAG) heparan sulfate (HS) and heparin (HE)26.Irrespective of its activation state, extracellular TG2 has been linked to i.a. cell adhesion, ECM stabilization and maturation, proliferation and cell motilityN-acetylated and/or O-sulfated uronic acids and glycosamines28. Based on their chemical properties, GAG can be classified into non-sulfated, e.g. hyaluronan (HA), and sulfated such as HE, HS and chondroitin sulfate (CS). GAG are important in many cellular processes as they interact and, thereby, modulate the function of extracellular proteins including cytokines and structural ECM proteins like fibronectin30. In the past, naturally occurring GAG have been chemically modified and applied in biomaterial research34. Since then, many effects of chemically sulfated GAG derivatives on cells and their ECM have been reported. Exemplarily, sulfated HA derivatives promote osteoclast cell adhesion but inhibit their resorption35 and alter fibronectin expression, conformation and matrix assembly36.GAG are linear polysaccharides consisting of disaccharide units built from alternating 24 have been previously described  derivative influenced composition and remodeling of the ECM of human bone marrow stromal cells and increased TG2 protein levels. Inspired by this, the present study investigates the impact of naturally occurring polymeric and synthetically modified polymeric and oligomeric GAG derivatives on TG2 enzymatic activity in order to clarify previously reported contradictory findings and to gain insight into the molecular mechanisms that underly this interaction.Considering TG2 in closed conformation, numerous HS/HE binding sites including the binding motif XBBXB TG2 enzymatic activity was investigated in the presence of a series of polymeric and oligomeric GAG derivatives , were calculated by non-linear regression. For a more complete description, the remaining TG2 activities at saturating GAG concentration v[M]→∞ are additionally stated in Table 50 values characterize the inhibitory efficiency. In the GAG concentration range examined, [M] = 0.1 nM–10 µM, non-sulfated HA did not have any significant effect on neither rhTG2  and 16.3 ± 1.0 nM (gpTG2)  was assessed toward gpTG2   an MC50 value of 60.0 ± 8.3 nM was calculated in our test system for gpTG2. The MC50 value of another recently published inhibitor (7b40) was calculated to be in the µM-range (2.51 ± 0.14 µM) in our setting. However, both inhibitors, 7b and Z013, bind only in the presence of Ca2+ to TG2, which is only possible once the assay mix is added.The obtained MCge Table  gave evil-lysine coating on the assay plate and, therefore, causing a smaller availability of binding sites for TG2, a coating control experiment was performed exemplarily with SH3 and gpTG2: The concentrations (4.4 and 88 nM) were chosen according to the inhibition curves—a slight inhibition (20%) and a high inhibition (80%) would have been expected if there was an interference. However, activity of gpTG2 was not significantly impaired  showed roughly the expected activity  for the GAG inhibitory capacity, non-sulfated and persulfated tetra- and hexasaccharides of HA  stabilizes the open conformation upon covalently binding to the catalytic site of TG2 . Compound 7b belongs to the chemotype of Nε-acryloyllysine piperazides40, which also inhibit TG2 in an irreversible manner. For structurally related inhibitors it has been shown by kinetic capillary electrophoresis that they also stabilize the open conformation47. Similar to the additional Ca2+ experiments (see below), an approach of subsequently adding GAG and the inhibitor Z013 or 7b  was investigated.The peptidic TG2 inhibitor Z013/7b , the inhibitory effect of both substances was additive, and even stronger in comparison to single treatment of either compound  compared to experimental settings I and II.Figure 2+ ions are needed to induce the conformational change of TG2 from the closed inactive to the open enzymatically active conformation46. In the experiments described before , TG2 and GAG were pre-incubated in the absence of Ca2+. Hence, activation did not occur before performing the TG2 activity measurement due to the included Ca2+-concentration in the assay buffer . Therefore, the influence of prior addition of 2.5–20 mM Ca2+ to TG2  was checked. Pre-activation (setting IV) did not change gpTG2 activity compared to Ctl  and only to a low extent of rhTG2  or vice versa . Furthermore, experimental setting V served to check whether GAG are preventing an opening of the TG2 3D conformation by blocking Ca2+ binding sites of the enzyme. Figure 2+ was added first. In the same setting (VI) with SH3, the inhibitory effect was completely abolished. In setting V, the inhibitory efficiency was reduced, resulting in about 80% activity for both GAG. In fact, for setting V neither a lower (2.5 mM) nor a higher (20 mM) Ca2+ concentration altered this effect for SH3 on gpTG2 , Q163, K429 and D434 , R433 10, Q599 and K663. For SH3 and HE, the common interacting residues along the three domains were K30, K265, N266, K602 and K634 , K364 and K387, among which K202, R213, S216 and R222 have been previously described as another HS/HE binding site  or K30 (for SH3 and HE)  were predicted to stabilize the closed conformation by acting as a “molecular staple” between the β-barrel 1, α/β-transamidase and β-barrel 2 domains  clearly showed that polymeric GAG reduce the crosslinking activity of TG2 in a concentration-dependent manner with MC50 values in the double to triple-digit nM range, when both were pre-incubated in the absence of Ca2+. In fact, the inhibitory effect was restricted to sulfated GAG derivatives . A further experimental setting was tested to investigate the influence of known TG2 inhibitors (Z013 and 7b) on the inhibitory behavior of sulfated GAG toward TG2 . Upon addition of Ca2+, activated TG2 (open conformation) is rapidly targeted by the irreversible inhibitors which ultimately leads to a stronger overall inhibitory effect on the transamidase activity. Therefore, TG2 transamidase activity was tested in additional settings with respect to Ca2+ activation and its influence on the inhibitory effect of GAG. The prior addition of Ca2+ (setting VI) significantly decreased the inhibitory effect of SH3 and HE on TG2 activity , the distinct residual enzymatic activity of rhTG2 at high concentrations of GAG is comprehensible. A “jump dilution” experiment44 with SH3 and rhTG2 was performed that further proved the reversible inhibition of TG2 by sulfated GAG , which has been reported as crucial residue for binding of guanine nucleotides53, in a mode that bridges this residue with the S5 Ca2+ binding site, which has not been previously described as an HE binding site. GTP and analogues therefore induce and stabilize the closed conformation. However, only sulfated GAG can be recognized by TG2 through interactions with R476 and R478, which also contribute to GTP binding50. Thus, the observed effects of the GAG on the transamidase activity could additionally originate from the interaction with R580 in combination with R476 and R478.TG2 can adopt different conformations—in fact a closed conformation upon binding of guanine nucleotides23. At the α/β-transamidase domain, binding poses of sulfated GAG interacting with R262, R263, K265 together with R28 at the β-sandwich domain were predicted, which resembles a previously reported HE binding site25. In addition, the predicted GAG interactions with the basic residues K202, K205, R209, R213 and R222, also at the α/β-transamidase domain, are fully in agreement with HS/HE binding sites previously described by Teesalu et al. and Wang et al. in the closed conformation26. These residues constituted a path for GAG recognition that bridges the β-sandwich and the α/β-transamidase domains.In addition to the GAG binding poses observed, there were also binding poses predicted in which GAG binding occurs on a single TG2 domain. In this context, for GAG hexasaccharides, binding poses along the β-barrel 2 partially resembled the previously reported HS/HE binding site by Lortat-Jacob et al. in the same TG2 conformation54 recently demonstrated that the small molecule GK921  exhibits an MC50 value of 8.93 µM towards gpTG2 (pre-incubation in the absence of Ca2+) and binds to the β-sandwich domain of TG2. Inhibition of TG2 was shown to be a result of non-covalent multimerization as a consequence of conformational changes triggered by binding of GK921.All investigated GAG derivatives were also predicted to interact with the β-sandwich domain to a different extent. In addition to their potential “molecular staple” function, the binding to the β-sandwich domain could explain their inhibitory action on the transamidase activity. Kim et al.2+ binding sites of TG2  could recognize the exposed residue K176 of the TG2 catalytic core  in the extracellular environment is probably not targeted by sulfated GAG derivatives, their interaction with TG2 in the closed conformation state could potentially already occur before the enzyme is released into the ECM since sulfated GAG derivatives have been shown to be internalized by various cell types62. In this light, the obtained results encourage further studies focusing on the applications of GAG derivatives towards the treatment of clinically relevant diseases in which TG2 is involved, such as cancer and fibrosis.This study shows for the first time that synthetically sulfated GAG derivatives reveal inhibitory effects on TG2 crosslinking activity. Importantly, the observed inhibitory effect of the GAGs critically depends on their binding to TG2 in the absence of CaTG2 Fig. . These fZ013 were obtained from Zedira . The TG2 inhibitor 7b was synthesized as described recently40 (same numbering as in40). Characteristics of the inhibitors are summarized in Table Purified guinea pig TG2 (gpTG2) was purchased from Sigma Aldrich . Purified recombinant human TG2  and the TG2 inhibitor Streptococcus, MW = 1200 kDa) from Aqua Biochem .Native CS  was obtained from Kraeber , HE  from Sigma Aldrich , and high molecular weight (MW) HA .S) based on HA and CS were synthesized as described69. The values for DS (average number of sulfate groups per disaccharide repeating unit) were determined by elemental analysis and nuclear magnetic resonance (NMR) and MW was determined by laser light scattering66. The chemical structures and characteristics of respective GAG derivatives are given in Supplementary Fig. Polymeric GAG derivatives with low, medium and high degree of sulfation  and hexahyaluronan (HA-dp3) derivatives were obtained after hyaluronidase treatment of high-MW HA. Resulting products were separated by size exclusion chromatography. Anomeric fixation (β-configuration) with an azide moiety and subsequent persulfation to the nona-sulfo-tetra- (psHA-dp2) and trideca-sulfo-hexahyaluronan (psHA-dp3) have been described before68. The final products were analyzed by 1H and 13C NMR spectroscopy and by electrospray ionization mass spectrometry to determine the DS. The chemical structures and characteristics of oligomeric HA derivatives are summarized in Supplementary Fig. Oligomeric non-sulfated and persulfated HA derivatives were synthesized according tonan HA-dp derivatil-lysine coated 96-well plate. Prior to the assay, gpTG2 was dissolved to 2 U/mL in 10 mM DTT with 1 mM EDTA, stored at 4 °C and used within two weeks. rhTG2 was dissolved according to manufacturer’s instructions to ~ 1.19 mg/mL (> 1500 U/mg) in H2O and stored until use at − 80 °C. If not stated otherwise, both enzymes were used in the tests without any pre-activation. There is an abundant amount of Ca2+ present in the actual assay buffer and, thus, the assay mix, causing the “opening” of TG2 (= activation), and, therefore, enabling the enzyme to crosslink. The different experimental settings are depicted in Fig. TG2 crosslinking activity was determined using a peroxidase-coupled colorimetric activity assay kit  according to manufacturer’s instructions. It is based on the TG2-catalyzed incorporation of Biotin-TVQQEL-OH, which acts as acyl donor substrate, onto a poly-mg/mL > 100 U/mg i2O) for 5 min at 25 °C before applying 50 µL of the reaction mixture  to the assay plate. After adding 50 µL of assay mixture (containing the substrate and Ca2+) to each well, samples were incubated for 30 min at 25 °C. Afterwards, streptavidin-peroxidase solution (1 µg/mL) was freshly prepared, added and incubated for 20 min. The reaction with 3,3′,5,5′-tetramethylbenzidine substrate  was stopped after 1–2 min followed by detection of absorbance at 450 nm with a plate reader . Negative and positive controls  were always run in parallel. Each sample was measured in duplicate. For calculation, the mean signal of the negative control was used as a blank and subtracted from further data of the same experiment. Afterwards, the signal of positive control (pure TG2) was set to 100% and the signal of TG2 in presence of GAG was related accordingly. The final concentration of GAG in the whole reaction  was used for the determination of the MC50 values41  with 20-fold MC50 of SH3 and HE (see Supplementary Table 2O to 2-fold or 0.2-fold MC50 before adding them to the assay plate. The samples were further diluted with assay mix to adjust the amount of enzyme per well to that used in the tests before (rhTG2: 39.7 ng) as well as variations of the MC50 concentration of SH3 (either 1-fold MC50 or 0.1-fold MC50). Depending on how the activity of TG2 was shifted, the inhibition mode (reversible or irreversible) could be stated. According to Copeland44, the inhibitory mechanism can be determined by incubating the enzyme at 100-fold concentration with inhibitor at a concentration equal to 10-fold of its MC50 value before diluting it to the 1-fold concentration of enzyme resulting in a 0.1-fold concentration of MC50. If the activity measured afterwards equals about 91% activity of the positive control (assuming a possible 100% inhibition), a rapidly reversible mechanism could be concluded.To evaluate the putative GAG inhibition mode, the following “jump dilution” experimentZ01345 and 7b40, were used in the same experimental setting as described above for GAG . In order to compare and evaluate the effects achieved with GAG, TG2 was not pre-activated with Ca2+ and came only in contact with the divalent cation, when assay mix was added.Inhibitors with known molecular mechanisms, 7b, Z013), whose concentration results in 80% residual activity in setting II. Each incubation step was performed for 5 min at 25 °C.To further characterize the inhibitory mechanism of GAG by investigating their possible competition with irreversible inhibitors for binding sites, a different incubation approach was used. TG2 was pre-incubated with sulfated GAG in concentrations that result in TG2 activities of 65% (sulfated GAG). This was followed by the addition of inhibitor . The experiments were performed with a supplementary amount of GAG that results in a TG2 activity of about 65% to better visualize putative additive inhibitory effects. For the sequential settings, each incubation step was performed for 5 min at 25 °C.CaGraphPad Prism 8.02 software. Outliers were identified via ROUT method (Q = 5%) and removed. If both values of one concentration in one experiment were detected as outliers, the according concentration was repeated in another experiment to complete the data set. Statistical significance (p < 0.05) was analyzed by either t test or one-way ANOVA with Bonferroni’s post-test as indicated in the diagrams.Three experiments were performed, each with separately prepared duplicates . Statistical analyses were conducted with the https://www.rcsb.org/; PDB ID 3LY670, 3.1 Å) was used as template . Modeller was used as implemented in Discovery Studio71. Modeling of the 3D structures in open conformation has been described in our previous work40.To model the three-dimensional (3D) structure of gpTG2 in closed conformation, the crystal structure of rhTG2 , SH3  and HE were prepared with Glide78 in standard precision. In the case of TG2 in closed conformation, two docking experiments involving either the α/β-transamidase and the two β-barrel domains or the α/β-transamidase, β-barrel 2 and the β-sandwich domains were carried out (see below for details on the grid boxes used). In the case of TG2 in open conformation, docking was performed on each protein domain. In addition, a partial overlap of contiguous domains to the main protein domain considered for docking runs was ensured (see below for details on the grid boxes used). Ligands were considered flexible. In proteins, dihedrals of the side chains of residues C, S, T and Y were allowed to rotate. For rhTG2 in closed conformation, the grid boxes were set up around Q96 and Y125 (β-sandwich domain), R377 and with or without including K205 (α/β-transamidase domain) in order to fully cover all regions of the α/β-transamidase domain with the β-sandwich, R592 and L688 (β-barrel 2 domain) as well as around K205 (α/β-transamidase domain), K468 and N531 (β-barrel 1 domain) and R592 (β-barrel 2 domain). For gpTG2 closed conformation, the grid boxes were set up similarly around Q96, Y125 (β-sandwich domain) and, as explained above for rhTG2, with or without including K205, R377 (α/β-transamidase domain), R595 and A690  and around K205 (α/β-transamidase domain), K467, N534 (β-barrel 1 domain) and R596 (β-barrel 2 domain). In addition, another grid box was set up around R271, R432 (α/β-transamidase domain), R515 (β-barrel 1 domain), R595 and R604 (β-barrel 2 domain). For rhTG2 in open conformation, the grid boxes were set up for the β-barrel 2 domain around D409, D553, K600, K602, E632 and E637, for the β-barrel 1 domain around N243, L462, E539 and K674, for the α/β-transamidase domain around E154, K173, L204, I323 and Q348, and for the β-sandwich domain around C98, Y125, I255 and P345 with an inner box of 40 Å × 40 Å × 40 Å and an outer box of 76 Å × 76 Å × 76 Å. Similarly, the grid boxes for the gpTG2 open conformation were set up for the β-barrel 2 domain around D409, D556, N603, K605, D635 and E640, for the β-barrel 1 domain around N243, L461, E542 and K677, for the α/β-transamidase domain around Q154, K173, L204, I323 and E348, and for the β-sandwich domain around S98, Y125, I255 and P345. The OPLS3e force field was used73. Docking results were ranked according to the obtained docking score.Blind docking studies were then carried out for each protein in closed and open conformation using Supplementary Information.


Polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS) multienzymes produce numerous high value metabolites. The protein subunits which constitute these megasynth(et)ases must undergo ordered self-assembly to ensure correct organisation of catalytic domains for the biosynthesis of a given natural product. Short amino acid regions at the N- and C-termini of each subunit, termed docking domains (DDs), often occur in complementary pairs, which interact to facilitate substrate transfer and maintain pathway fidelity. This review details all structurally characterised examples of NRPS and PKS DDs to date and summarises efforts to utilise DDs for the engineering of biosynthetic pathways. Modular polyketide synthases (PKSs) and non-ribosomal peptide synthetases (NRPSs) represent two classes of extraordinary molecular machines, responsible for the biosynthetic assembly of polyketide and non-ribosomal peptide natural products, respectively. Over the past 30 years, the chemical products of these ‘megaenzymes’ have been the focus of extensive research due to the potential of these molecules as sources of new pharmaceuticals and agrochemicals –N-terminal DD (NDD) complex, as one or both DDs within the pair may only fold correctly in the presence of its cognate partner  , and the N-terminus of the KS domain (NDD). Three α-helices (α1–α3) comprise the CDD region; α1 and α2 form a dimerisation element, and α3 is directly involved in contacts with the NDD , which forms a coiled–coil with an identical NDD in the dimeric KS  and CDD(α3)–NDD constructs were analysed by solution state NMR spectroscopy and both the structure and molecular interactions across the interface were elucidated. Interactions between the NDD α-helices forming the dimeric coiled–coil were found to be predominantly hydrophobic, though some salt bridges were present. Sequence alignments with other Class 1 NDDs showed that the residues involved in salt bridge formation were conserved across systems, indicative of their importance in creation of the coiled–coil interaction interface. Important interactions between the CDD (α3) and NDD of this interface were also identified as involving a combination of hydrophobic contacts and salt bridges. Hydrophobic contacts highlighted in Fig. 3, Y96 on α4 and L97 on α4′  is at the centre of the bundle. The two CDD α-helices both interact with the NDD coiled–coil. This interaction interface is predominantly hydrophobic, with salt bridges hypothesised to confer specificity  and lacks the primary NDD α-helix (α3) observed for CurH and Bamb_5924 NDDs. Sequence analysis shows that three N-terminal amino acids are missing from CurL, which may prevent the NDD from folding correctly. However, structurally the CurK/L complex appears closer to that of a Class 1 four α-helix bundle than that of a Class 2 system, despite its sequence aligning well to those of other Class 2 PKS DDs  in CurH  domains.Unlike trans-AT PKSs. While these DD regions occur at traditional intermodular ACP/KS subunit junctions, they are also found at many of the unusual intramodular subunit junctions responsible for ‘split module’ domain architectures  domain. Application of solution state NMR and circular dichroism spectroscopy to the isolated DHD domain revealed a limited propensity to form secondary structure elements in solution, and inherent intrinsic disorder. NMR titrations of the 15N-labelled DHD domain with the DH domain identified two interacting regions, indicating that the former interacts directly to the exterior surface of the latter. This was confirmed by carbene footprinting mass spectrometry analysis, resulting in masking of regions on the DH domain surface upon incubation with the DHD domain ; a region of protein that is structurally important at the KS–AT interface in Xenorhabdus (PAX) domains  domain, a condensation (C) domain and a PCP domain. A domains select and activate specific amino acids as aminoacyl thioesters. C domains then catalyse amide bond formation between successive PCP-bound aminoacyl thioesters resulting in assembly of a peptide chain. There are two known classes of DD that have been reported to occur exclusively in NRPS systems; communication (COM) domains  domain structure was obtained relatively serendipitously. Upon crystallisation of the final module of the surfactin NRPS  the structure of the N-terminal acceptor COM (COMA) domain was identified   embedded within the globular structure of the C domain  and SrfAC (surfactin NRPS) were found to have 88% sequence identity, while GrsB1 COMA (gramicidin NRPS) had 75% identity. Consequently, all three were found to interact with the COMD α-helix of TycA (tyrocidine NRPS) -BacB2-COMD(TycA) and SrfAC. As TycA and SrfAC interact, this led to production of dipeptide and tripeptide products  was grafted onto BacB2. This innate promiscuity of COM domains is further evidenced by crosstalk experiments employing the surfactin, tyrocidine and gramicidin S NRPS pathways. The non-cognate TycA COMD and TycC COMA domains from the tyrocidine NRPS were used to replace the cognate SrfA-A/SrfA-B COM domain pair in the surfactin NRPS in B. subtilis CC112 , the question of whether it would be possible to cleanly ‘cleave’ COMA regions for NRPS pathway engineering remains unclear. For engineering purposes, it may be more productive to focus on utilising the inherent promiscuity of COM domains and on COMD domain-based grafting studies, before attempting COMA domain-based engineering.As the COMCDD–NDD complex illuminated both the structure of the DDs and the molecular interactions across the interface. The NDD comprises a single α-helix which docks centrally within the two α-helix CDD to give a three α-helix bundle with a V-shaped overall structure malonyl-derived building blocks. These systems illustrate that, with the right tools, it may be possible to engineer pathways involving both NRPS and PKS biosynthetic machinery, greatly increasing the diversity of the products.CDD of less than 15 amino acids, interacts with the much larger N-terminal βhD domain  have been identified in both purely NRPS and hybrid PKS–NRPS pathways, at PCP/C or PCP/Cy domain interfaces  from xenoamicin producing pathways in an attempt to prevent module iteration , containing hydrophobic amino acids, usually at positions a and d, or e and g  templates are tethered to building blocks which, as complementary ssDNA-tags anneal, allows control of the order of connectivity (Goodnow et al., Xenorhabdus inexxi rhapdopeptide/xenortide-like pathway enabled interaction between the ZF-bearing modules, while a non-cognate but interacting COM domain pair enabled interaction between the ZF-lacking GrsA and downstream TycB1 (Fig. Recently, the DNA-templating methodology has been applied to the gramicidin S NRPS (Huang et al., cB1 Fig. . This sycB1 Fig. . HoweverCDD–NDD pairs, such as four α-helix bundles, eight α-helix bundles, double helix pairs and PAX DDs. In others, the CDD interacts directly with the downstream domain, such as helix-hand DDs and DHD domains, or a short peptide CDD interacts with a much larger, structured NDD, as observed in SLiM–βhD domain pairs. Perhaps additional mechanisms of interaction will begin to emerge as protein subunit junctions are studied further.Since identification of the first PKS DD in 1996, termed a linker region rather than a DD at the time, there has been a dramatic increase in the number and type of DDs identified (Aparicio et al., Experiments using DDs to engineer biosynthetic pathways have increased in success as knowledge of their compatibility and mechanisms of interaction has advanced. How malleable these systems are towards engineering, and the extent to which DDs can help to facilitate this, is not yet fully understood. In most cases, it is still not known what secondary points of contact occur across these junctions, both between pairs of catalytic domains and between DDs and catalytic domains. Once understood, those regions that should be kept consistent to enable conformational changes necessary for protein function will be clarified. This will allow higher product yields to be achieved. For simply bringing two proteins into proximity so as to enable substrate transfer, SYNZIPs are a valuable tool. However, the extent to which synthetic biology tools can be used in parallel to DDs to engineer chimeric systems is only just beginning to be understood.cis- versus trans-AT PKSs. The DDs in each type of system interact differently and this must be considered when using them for engineering. Substrate scope is also an important factor to consider in parallel to DD choice. It transpires that subtle changes are needed in the domains themselves to broaden their substrate scope and enable biosynthetic pathway engineering in its fullest sense. Indeed, recent mutagenesis studies on the active sites of KS domains from the DEBS cis-AT PKS to broaden their substrate specificity, showed that KS substrate scope is a crucial factor to consider alongside maintenance of protein–protein interactions to achieve high turnover when undertaking PKS engineering (Klaus et al., trans-AT PKSs (Jenner et al., Another factor to consider is subunit dimerisation, both in the context of NRPSs versus PKSs, but also in In conclusion, understanding of DDs, their structures, key amino acid interactions and the interfaces at which they occur has greatly increased over recent years. Use of DDs to engineer biosynthetic pathways has been undertaken with varying degrees of success. However, factors that must be maintained to successfully engineer a pathway are just beginning to be clearly defined.


The aim of this research is to investigate the molecular features and microstructure of amaranth flour (AF) fractions and their partial replacement effect of wheat flour (WF) on the chemical composition, dough dynamic rheology, technological and sensory characteristics of bread. The microstructure and molecular characteristics of AF were depending on their particle size (PS). When WF replacement increased and PS decreased the composite flour was richest in protein, lipids, and ash, while the moisture and carbohydrates of these flours decreased. Dynamic rheological behavior revealed significant variations depending on PS and replacement level. Bread volume and firmness increased when more than 15% AF from large PS replaced WF, while medium and small PS at 5–15% replacements was increased the loaf porosity. Chroma values decreased and samples became darker when the replacement level increased. Moreover, replacement of WF with various AF fractions impacted bread sensory characteristics, obtaining better acceptance for large and medium PS up to 10%. One of the solutions is a partial replacement of wheat flour with other raw materials, rich in nutritional ingredients. Composite flour technology represents the operations of mixing wheat with non-wheat flour which contains high protein components for use in bakery technology2. An important class of raw materials is pseudocereals like amaranth which has higher nutritional quality than that of cereals. Amaranth seeds contain relatively higher levels of protein (12.5‒20%) than common cereals 3, some authors found that the proportion of amaranth protein is similar to that of soy4. According to Osborne's classification, amaranth proteins consist of about 40% albumin, 20% globulin, 25–30% gluteline, and only 2–3% prolamine5. It contains a high level of protein with a balanced amino-acids profile, lipids, vitamins, minerals, and bioactive compounds6. Amaranth seeds proteins are rich in lysine, threonine, and methionine and encrypted peptides with various biological functions which have health benefits for the consumers7. Lipids contain a high level of unsaturated fatty acids such as palmitic, oleic, linoleic, and linolenic acids and tocotrienols and squalene, with an important role in lowering LDL-cholesterol in the blood9. Due to more stability to oxidation than sunflower oil10, the amaranth seeds oil has potential to development of healthy products with a longer shelf life. Amaranth seeds represent an important source of folate and starch11. The starch of amaranth consists mainly of amylopectin, 7.8–34.3%12, while the amylose content is lower: 5–7%13. Some studies have shown that the replacement of wheat flour (WF) with amaranth (AF) not only enhances its chemical composition but also improves the properties of the flour, dough and bread's quality attributes. The replacement of refined wheat flour with amaranth flour significantly enhanced the nutritional bread value resulting in high protein, mineral, fiber, and myo-inositol phosphates content of the final product15. The composition of amaranth fibers (4.9–13.5%) is similar to that of vegetables and legume seeds16. Morphology structure knowledge of amaranth seeds plays a key role in obtaining enriched fractions in certain compounds because the quality of the baked products is correlated with the compounds from flour particle size. Amaranth seeds present different external and internal morphology which lead to differences in nutrient distribution17. The amaranth seed perisperm  is high and nutrient-rich, being wrapped by a peripheric embryo17. Amaranth starch contains a big different ratio between amylose (2–12%) and amylopectin content (90–98%), which will affect the physical and chemical properties of starch18. The amylose content from amaranth seed is associated with functional properties, such as rheology  and texture properties, amaranth starch presenting good gelatinization properties19. Amaranth seeds includes also a high content of non-starch polysaccharides, like dietary fibers20. This morphology can affect the nutrient concentration distribution during the milling process due to the breakage of the seeds17 and can influence the dough’s rheological behaviour during bread-making stages and the quality attributes of baked products, respectively.In recent years, consumers have focused on their nutrition and health, giving increased attention to lifestyle. Thereby, interest in improveming the foods has been increased. Bakery products are considered the best products for improving the nutritional process due to the daily caloric requirement given by bread (more than 50% of energy intake)21. AF replacement produced modifications on the rheological and textural parameters of wheat dough due to the gluten dilution effect24. The gas retention in leaven bread is influenced by the fibers and starch content from amaranth fractions. The interactions between particle sizes and amaranth flour percentage which replaced wheat flour led to a decrease in volume, porosity, and elasticity, and an increase in firmness, with the increase of amaranth flour amount25.The replacement of gluten in bread with non-gluten raw materials represents a big challenge because it is the dough structure-building protein. Its dilution affects the dough’s property through the kneading, leavening, and baking process. The dynamic rheological methods simulate the viscoelastic behavior of the composite dough which is formed by the interactions between amaranth fractions and gluten matrix from wheat flourThere is a lack of research about the replacement of wheat flour with different amaranth particle sizes at various levels, regarding how the particle size features can influence the physicochemical characteristics of wheat flour, dough dynamic state, bread physical, and sensorial profile. Starting from those presented, we believed that the research on the molecular features and microstructure of amaranth flour fractions, chemical composition of composite flour formulations, dynamic dough rheological properties, and bread characteristics is needed because provides valuable information from nutritional and economic standpoints.Saccharomyces cerevisiae yeast  were used. Amaranth seeds were used for wheat flour substitution, after a grinding according to the protocol reported in our previous studies24. Amaranth seeds were grounded with a laboratory grinder , sifted for 30 min at 70 HZ amplitude with Retsch Vibratory Sieve Shaker AS 200 basic , and separated in three particle size (PS), as: large (L > 300 µm), medium  and small fractions (S <  180 µm).Wheat flour (WF) with an extraction rate of 65% (2020 harvest) provided a local mill , amaranth seeds and salt acquired from the market  and fresh 26 standard methods  for the following characteristics: moisture (14.08%), protein (12.45%), fat (1.41%), ash (0.69%), and Falling number index (312 s), while Romanian standard procedure27 was used to determine wet gluten (30.00%) and gluten deformation index (6.00 mm). Amaranth seeds proximate composition included: 14.00% moisture, 17.00% protein, 2.00% ash, and 8.00% fat. The proximate composition of the AF fractions was determined and reported in previous work24.The WF was analyzed according to the International Association for Cereal Chemistry (ICC)WF and AF fractions were evaluated regarding their microstructure with VEGA II LSH electron scanning microscopy , at an acceleration tension of 30 kV. Each sample was coated with a double-sided adhesive carbon band before being scanned and collected at 2000×, 1000×, 500×, and 100× magnifications.−1 by 32 scans recorded between 650 and 4000 cm−1, the graphs being evaluated with OMNIC software  based on previous studies, in order to identify the molecular characteristics of the flours28.The presence of various functional groups was assessed by Thermo Scientific Nicolet iS20  spectrometer equipped with an attenuated total reflectance ATR accessory. The FT-IR spectra of the WF and AF fractions were achieved at a spectral resolution of 4 cmRefined wheat flour was substituted in the proportion of 0%, 5%, 10%, 15%, and 20% with each amaranth fraction obtained through the milling and sieving process  and mixed with a Yucebas Y21 mixer , in order to obtain the following composite flour formulations coded as: AL_5, AL_10, AL_15, AL_20, AM_5, AM_10, AM_15, AM_20, AS_5, AS_10, AS_15, and AS_20. The sample with 0% AF was used as a control.26: moisture content (ICC 110/1), protein content, determined with a Kjeldahl device , Italy), and calculated with a general factor of 6.25 for wheat flour and 5.53 for wheat-amaranth composite flour (ICC 105/2), fat content, determined with the Soxhlet method , Italy) (ICC 136), ash content, determined by incineration at 900 °C (ICC 104/1), and total carbohydrate content was calculated by difference, as a percentage of the total mass. The composite flours color parameters were assessed using a colorimeter CR‐400  and CIELAB scale: L*—lightness/darkness (0 for black and 100 for white), a*—the intensity of green (− a* = more green) or red (+ a* = more red), and b*—the intensity of blue (− b* = more blue) or yellow (+ b* = more yellow), and Chroma (C*) was calculated according to Eq. tent ICC 10/1, pro24. When the fermentation operation is over, the fermented leaven is mixed with the second half of the flour and salt in the Kitchen Aid mixer  for 10 min. The obtained dough was left to ferment in the same conditions for 60 min. The dough was cut in 400 g/piece, molded, placed in aluminum trays for one hour to produce the final fermentation, and baked for 25 min, at 220 °C .For breadmaking was used 300 g flour, 5.40 g salt, 90 g yeast, and water . In the first stage, it was obtained a leaven from an entire quantity of water and yeast, and half quantity of flour, that was left for fermentation, 120 min, at 30 °C and relative humidity (85%), in a fermenting chamber , according to our previous method29. The flour and water were mixed until reaching the optimum consistency, in order to obtain the dough, and let it rest 5 min before testing30. The elastic modulus (G′), viscous modulus (G″), and loss tangent (tan δ) were determined by applied frequency sweep test from 0.01 to 20 Hz, at a constant strain of 0.10% and the values were considered at 1 Hz. To determine the maximum gelatinization temperature (Tmax), considered at the maximum G' value, the temperature sweep test in which dough samples were heated from 20 to 100 °C at a rate of 4 °C per min was performed.A Thermo-HAAKE, MARS 40  with parallel plate-plates geometry was used to determine the dynamic rheological behavior of dough. Dough samples were preliminarily tested for the linear viscoelastic region (LVR), by applied strain sweep tests with strain from 0.01 to 1%, at a constant oscillation frequency of 1 Hz31. The compliance parameter was determined with Eq. (−1) represent compliance, γ, the strain, and σ, the constant stress (Pa−1) applied:To evaluate the dough resistance to stress during the bread-making was applied a creep-recovery test with a constant shear stress of 25 Pa, at 20 °C, for two time periods, 60 s as creep time under stress and 180 s as recovery time after stress removed32.io (Pa−1) = instantenous compliance; Jim (Pa−1) = retarted elastic compliance or viscoelastic compliance; t (s) = phase time; λi (s) = retardation time; µCo (Pa s) = zero shear viscosity; Jmax (Pa−1) = maximum creep recovery. The recovery compliance, Jr (Pa−1) is determined from the sum of JRo and JRm.The creep-recovery test data were submitted to nonlinear equations of Burgers model, by using Eq.  for cree27 in terms of loaf volume, and porosity. Loaf specific volume (cm3) was found by employing the seed displacement procedure. Porosity was calculated based on a sample cylinder volume (60 mm height and 45.50 mm diameter).Bread physical properties were measured in triplicate, two hours after baking, in agreement with the Romanian procedureL*), red-green intensity (a*), and yellow-blue intensity (b*), whereas the Chroma (C*) was calculated using Eq. . The bread color characteristics measured were luminosity (sing Eq. .The bread was cut into slices of 50 mm thickness for the texture properties determination (in triplicate) by using a TVT-6700 texture analyzer . A 2.5 cm cylindrical stainless-steel probe was used to compress twice the sample to a penetration distance of 20% of its depth, at a test speed of 1.0 mm/s, trigger force of 5 g, with an interval of 15 s between compressions. Firmness, springiness, gumminess, and cohesiveness were registered.The sensory characteristics of the bread were evaluated using an overall acceptability descriptor based on a 9-point hedonic scale in which the following were evaluated: Overall appearance and shape, Surface and properties of the crust, Structure and elasticity of the crumb, Smell, and Taste. Samples were coded with randomly selected four-digit numbers. A 13 semi-trained panelists in sensory analysis who were experts in the field of bread technology assessed the sensory attributes of the bread trials. The panelist scored for different, 1: extremely dislike, 5: neither like nor dislike, and 9: extremely like, and between each assessment, the water and crackers have been consumed.https://www.ibm.com/products/spss-statistics). Statistically significant differences between parameters were determined by two-way analysis of variance with Tukey’s test at P ≤ 0.05 significance level. A principal component analysis (PCA) was performed to observe the similarities or dissimilarities between the evaluated parameters and formulated samples’ chemical constituents, dough rheological properties, and bread features.Statistical software SPSS 25.0   was used to calculate the means values and standard deviations for the quantitative data  and chroma (C*) color scale, and results are given in Fig. C* parameter with the increase of WF replacement and with a decrease in particle size was observed.As per the graph, moisture Fig. a was decDynamic dough rheological properties were significantly (P < 0.05) influenced by the AF particle size and WF replacement level Table .Table 1Emax) presented higher values in samples that were replaced with small PS, followed by large PS, while in samples where was incorporated medium PS, the creep compliance was lowest. The same trend was observed for all the replacement levels, which led to higher dough extensibility. Maximum creep recovery (Jrmax) was influenced significantly by both factors, PS and replacement level. Usually, this parameter tends to decrease when the WF replacement level with AF increased, and regarding particle size, it decreases in the following order: M < L < S.The elastic modulus was significantly (P < 0.001) higher when WF replacement increased in comparison with control, being highest when large fractions replaced WF. All dough samples, corresponding to a predominant viscoelastic nature behavior, G′ > G″. Significant differences (P <  0.01) on samples' loss tangent (tan δ) were recorded with the increase of WF replacement with above 10% AF, leading to a gradual decrease of this parameter, while the replacement between 5 and 10% did not have a significant effect on tan δ. Regarding PS, significant differences were registered only between medium particle size and the other two PS (L and S). Particle size influenced Tmax due to WF replacement with AF in comparison with the control, but differences between particle sizes were observed only in the samples where was incorporated medium PS. Replacement level significantly influenced this parameter when was up to 10%. Maximum creep compliance  and chroma (C*) for the bread crust-crumb varied depending of AF particle sizes and replacement levels on WF  increased gradually with the decrease of PS and decreased with the AF replacement level. Regarding crumb lightness, followed the same trend, depending on formulated factors, PS, and replacement level. Crust chroma presented an increase with the raise of replacement level, while PS lead to an increase of bread crust chroma in the following order: L < M < S. Crumb C* presented an increase compared to control when the replacement level of WF raise, whilst regarding particle size influence, C* tend to increase with the decrease of PS.The lightness  (r = 0.58), while lipids are negatively associated with loss tangent (r = ‒ 0.70), bread volume (r = ‒ 0.85), bread springiness (r = ‒ 0.82), bread cohesiveniss (r = ‒ 0.72), and with all sensorial characteristics: structure (r = ‒ 0.80), smell (r = ‒ 0.73), overall aceptability (r = ‒ 0.53). Regarding the bread texture, it was found significant (P < 0.05) correlation with dough rheology and consumer accpetance of final product. Bread firmness is positive correlated with elastic modulus (r = 0.67) and viscous modulus (r = 0.69), while with bread volume (r = ‒ 0.58), bread porosity (r = ‒ 0.70), and bread oberall aceptability (r = ‒ 0.56) is negatively associated. Bread springiness is positive correlated with loss tangent (r = 0.56), bread volume (r = 0.67), and bread structure (r = 0.74). Bread gumminess and chewiness are positve associated with elastic modulus (r = 0.59), viscous modulus (r = 0.60), while in a negative way is associated with bread volume (r = ‒ 0.65), bread porosity (r = ‒ 0.74), and sensory characteristics of bread: overall aceptability (r = ‒ 0.64).By applying Pearson's correlation analysis between assessed characteristics, a series of siginificant (P < 0.05) correlation coefficients (0.56 ˃ r < 0.98) was found. Flours humidity was strongly positive correlated with loss tangent (r = 0.67), bread springiness (r = 0.78), gumminess (r = 0.61), bread volume (r = 0.95) and bread overall aceptability (r = 0.65), bread taste (r = 0.78) and crumb structure (r = 0.81). Instead this physical parameter of flour was nevatively associated with bread gumminess and chewiness (r = ‒ 0.58). In this way, it seems that flour humidity is a good indicator for flour quality which has direct correlation with dough and bread properties. High positive correlation were found between flour lipids and bread firmness (r = 0.66) and gumminess (r = 0.67), and elastic modulus  was used to highlight the similarities or dissimilarities between the determined characteristics Fig. . The loamax) and creep-recovery compliance (Jcmax − Jrmax) have a small contribution to the data variation, as is suggested by their position on the graphic, close to the center. Instead closeness of single parameters for example flour humidity, loss tangent (tan δ), bread volume, and sensory characteristics confirms a tight pair correlation, as well as the association between elastic and viscous moduli , bread firmness, gumminess, and chewiness. The PC1 was associated with flour humidity and lipids, tan δ, bread volume and porosity, bread textural parameters, and bread sensory characteristics while PC2 was associated with flour protein, ash, and carbohydrates, elastic, and viscous moduli . It can be remarked a high opposition between protein-ash and carbohydrates, bread firmness and porosity, viscoelastic moduli and bread springiness. A strong correlation was observed between wheat flour bread and bread with medium and large PS when WF was replaced at a 5% level (AL_5 and AM_5) and 10%, respectively (AL_10). Composite flour with a 20% AF of medium and small fractions was associated with lipids, ash, and protein, whilst samples with large fractions (AL_20) were associated with viscoelastic moduli, bread firmness, gumminess, and chewiness.The dough maximum gelatinization temperature  micrographs Fig.  show the−1 can characterize the substitutions in aromatic rings (aromatic C–H bonds)36. The reflectance signal heights of each spectrum at 932–1156 cm−1 were recorded from each flour. The intensity ratios of these bands were used as convenient indexes of short-range starch structure38. The information-rich fingerprint region from 900 to 1500 cm−1 contains signals from amylose–lipid complexes present in the whole grain, amide III (1330–1230 cm−1), or structural carbohydrates such as starch and cellulose (unsaturated bonds C=C connected to the oxygen atoms O–C=C or the nitrogen atoms N–C=C)36. The bands present at 1156, 1084, and 1025 cm−1 could give information about the axial deformation vibrations of C–O in alcohols. The band heights were also studied for proteins: amide I (1658 cm−1) and amide II (1544 cm−1), vibrations, which are the most common vibration to study proteins39. Lipids influence can be observed in the bands at 2927, 2857, and 1752 cm−1 attributed to C–H stretching vibrational modes of alkylic CH2 and CH3 groups. The band at 1752 cm−1 is typical for the ester carbonyl stretching common of the esterification of fatty acids in the glycerol backbone33. Water (OH-stretching vibration) can be observed at bands 3365 cm−1 for wheat flour and at 1658 cm−1 for amaranth flour medium particle size, this variation among samples is likely due to the milling and sieving process of the samples, being correlated with their humidity. Similar spectra were obtained by Roa et al.33.Fourier transform-infrared (FT-IR) is used to characterize materials composition and to observe structural changes influenced by food processing techniques. The band's heights at 716, 770, and 866 cm40. The milling enhances the disentanglement of protein bodies in the cotyledon41. Our results are within the range of the literature values42. The highest amounts of ash from composite flour are found when the replacement level of AF is maximum and increased gradually with a decrease of PS, indicating that these small fractions could be a deposit for a high amount of minerals. The presence of the high amount of lipids in composite flour is given by the amaranth seeds fat-rich 43. Also, a high amount of lipids are observed at flour samples which were replaced with small AF particle size, which could be explained by the localization of this fraction in the embryonic part43. The lipids contents from flours lead to changes in bread hardness and aroma10. Total carbohydrates content from studied flours decreased when AF fractions became finest and replacement level increased. The desired color of wheat flours for industrial applications is a high value for luminosity and a low value for chroma44. The darkening color presented in composite flour with medium particle size can be justified by the fiber and phenols present in the embryo45.Wheat-amaranth composite flours presented lower humidity values due to the temperature increase during the process of size reduction, which lead to a drying phenomenon. The observed protein trend of the composite flours varied between 12.11 and 15.95%, which can be explained by the localization of the protein in the embryo (65%) and endosperm (25%) of the seed46. Furthermore, the complex bonds that are formed between starch granules and amaranth fibers, can contribute to the increase of viscoelastic moduli. Similar results of viscoelastic moduli were found for whole amaranth flour in some studies46. Also, the damaged starch that results in the milling process, especially from small fractions, can be correlated with high values of G', leading to firmer doughs and crumb bread  in the substrate can affect the microbial growth in sourdoughsThe use of amaranth flour to replace refined wheat flour in bread formulations is very interesting due to its valuable nutritional profile and thus will meet consumer demands in terms of nutrition. The changes that occur in the morphology of starch, lipids, and protein of amaranth flour fractions exert influence on composite flour, dough rheology, and bread characteristics. The large and medium amaranth flour fractions at the concentration of up to 10% can be used as a partial replacement for wheat flour in bread formulations without negatively affecting the dough behaviour and product sensory properties. At a higher replacement level, precessing difficulties can occur due to high viscosity. Moreover, dough samples with the small particle size show increased resistance to deformation compared to those with medium and large particle sizes. The maximum gelatinization temperature decreased for all fractions and replacement levels. The replacement of wheat flour with different amaranth flour fractions induced various influences on bread characteristics. Sensory assessment, decisive especially for the development of novel products, revealed that refined wheat flour replacement levels up to 10% with large and medium particle fractions of amaranth flour is considered suitable. A significant correlation (P < 0.05) between composite flour nutrients, dough dynamic rheological properties, and bread physical, textural, and sensory characteristics was found. The results of this study represent essential support for future bread-making optimization trials enriched with amaranth flour.


The majority of proteins in nature are composed of multiple domains connected in a single polypeptide. How these long sequences fold into functional structures without forming toxic misfolds or aggregates is poorly understood. Their folding is inextricably linked to protein synthesis and interactions with cellular machinery, making mechanistic studies challenging. Recent progress has revealed critical features of multi-domain protein folding in isolation and in the context of translation by the ribosome. In this review, we discuss challenges and progress in understanding multi-domain protein folding, and highlight how molecular interactions shape folding and misfolding pathways. With the development of new approaches and model systems, the stage is now set for mechanistically exploring the folding of large multi-domain proteins. Proteins exhibit an astonishing functional diversity, playing essential roles in all cellular processes. Strikingly, this remarkable diversity is achieved with a surprisingly small number of building blocks. So far, approximately 1,500 unique folds have been identified in all known structures . The vasInteractions between domains in a large protein  are concConnecting domains covalently into a single polypeptide results in very high local concentrations. For example, two domains connected by a flexible glycine-serine linker of 20 amino acids have an effective concentration, defined as the concentration required to achieve the same encounter rate between two untethered domains, of 4 mM . The idein vitro  relative to the noise of an optical tweezers measurement. However, overall chain elongation is apparent as an increase in length of the tethered molecule. Gradual hydrophobic collapse and partial folding was observed during synthesis of a small single-domain protein in the optical tweezers . StudiesInteractions between residues in separate unfolded domains can lead to misfolding . A tandeHowever, inter-domain misfolding is not limited to the special case of repeat proteins. Even relatively small proteins, such as the calcium-binding protein calmodulin and NCS-1, populate non-native structures that compete with productive folding . The thrThe results outlined in the preceding paragraphs were obtained with isolated proteins and suggest a general propensity of large proteins to populate non-native structures. Nascent chains appear to be at least partially protected from this type of misfolding. For EF-G, misfolding interactions are greatly reduced by the ribosome, promoting efficient sequential folding of the two N-terminal domains G and II  Figure . The impIn addition to inter-domain misfolding interactions, constituent domains in complex proteins can suffer from internal misfolding . ModelinThe G-domain of EF- G populates unstable molten-globule like states and intermediate structures upon refolding. When the protein is synthesized, however, the nascent chain remains unfolded until the entire domain is extruded from the ribosome, avoiding the formation of non-native structures . The resin vitro to the co-translational pathways that are likely relevant in vivo.Intermediates are commonly thought to be populated on the way to native state, even for relatively small domains . It is iProtein segments rich in low complexity sequences remain intrinsically disordered in solution , unlike The domain interfaces in a multi-domain protein provide opportunities for favorable interactions that stabilize unstable structures . Such stThis stabilization by interaction may be analogous to the ‘binding and folding’ model observed for several disordered proteins. For example, ACTR is largely unstructured in solution and binding to its partner, NCBD, enables it to adopt tertiary structure . AnotherNot all domain-domain interfaces have stabilizing effects. An extensive interface of domain III in EF-G with its N-terminal neighbors (domains G and II) does not contribute measurably to stability . The impNascent proteins can begin to acquire secondary and (limited) tertiary structure even before their emergence from the ribosome exit tunnel . These eIt is unclear how general the denaturing effect of an unfolded domain on a folded neighbor is. As for other aspects of co-translational folding, computer simulations and theoretical models  are poiin vivo using arrest peptides (in vitro experiments. However, despite recent advances, many questions regarding multi-domain protein folding remain: How are protein synthesis and folding tuned to each other to avoid the formation of non-functional or toxic products? How do the functional requirements for conformational flexibility compete with folding and interdomain interactions? And how do molecular chaperones rescue misfolded states of multi-domain proteins? Studies on diverse sets of authentic multi-domain proteins in vivo and in vitro will be required to define general principles of their folding.Although multi-domain proteins make up a large proportion of proteomes, a mechanistic understanding of their unique folding pathways is still lacking, in part due to experimental challenges. Methodological advances in the past few years have fueled progress in our understanding of how large proteins fold, illustrated by the examples highlighted here. Some of the complexity that results from interactions of folded and unfolded domains during multi-domain protein biogenesis is now beginning to be unraveled. The recently developed approach of following protein folding peptides  offers e


Antisense oligonucleotides (ASOs) are disease-modifying agents affecting protein-coding and noncoding ribonucleic acids. Depending on the chemical modification and the location of hybridization, ASOs are able to reduce the level of toxic proteins, increase the level of functional protein, or modify the structure of impaired protein to improve function. There are multiple challenges in delivering ASOs to their site of action. Chemical modifications in the phosphodiester bond, nucleotide sugar, and nucleobase can increase structural thermodynamic stability and prevent ASO degradation. Furthermore, different particles, including viral vectors, conjugated peptides, conjugated antibodies, and nanocarriers, may improve ASO delivery. To date, six ASOs have been approved by the US Food and Drug Administration (FDA) in three neurological disorders: spinal muscular atrophy, Duchenne muscular dystrophy, and polyneuropathy caused by hereditary transthyretin amyloidosis. Ongoing preclinical and clinical studies are assessing the safety and efficacy of ASOs in multiple genetic and acquired neurological conditions. The current review provides an update on underlying mechanisms, design, chemical modifications, and delivery of ASOs. The administration of FDA-approved ASOs in neurological disorders is described, and current evidence on the safety and efficacy of ASOs in other neurological conditions, including pediatric neurological disorders, is reviewed. Human genetic modification and the alteration of gene expression have been developed to treat several disorders. The delivery of exogenous deoxyribonucleic acids (DNAs) to cells has been tested for years to restore expression of missing genes in the context of genetic disorders. Gene editing has also emerged to insert, delete, or replace genes in order to make specific changes to DNA. More recently, oligonucleotide-based therapy is being developed in an attempt to halt the progression of numerous disorders by affecting ribonucleic acid (RNA) or protein structure. Oligonucleotides are easy to synthesize and do not require integration into the genome, making their delivery less challenging. Different oligonucleotide structures have been designed and classified as (i) aptamers, which modify peptide and protein structures or enhance drug delivery; (ii) double-stranded RNA interference (RNAi), which reduces gene expression; (iii) double-stranded small activating RNAs (saRNAs), which induce gene expression; and (iv) antisense oligonucleotides (ASOs)  1,2,3,4,3,42,3,4Oligonucleotides can decrease the levels of toxic protein , increase the level of functional protein , or alter the structure of a protein by mRNA splicing modification . Pegaptanib is the only FDA-approved aptamer to treat age-related macular degeneration by targeting vascular endothelial growth factor . The curThis review provides an update on ASO mechanisms of action, design, modification strategies, and delivery methods to enhance efficacy. Finally, we discuss the uses and outcomes of ASOs in different neurological disorders.ASOs affect mRNA and protein expression using different mechanisms. Oligonucleotides can suppress protein expression via translational arrest due to the steric hindrance of ribosomal subunit binding A, induciSCN1A mRNA transcripts sixfold and the voltage-gated sodium channel α subunit Nav.1.1 by over 50% in a dose dependent manner . O. OSCN1A SCN2A encoding Nav.1.2 or SCN8A encoding Nav.1.6 can cause DS, and ASOs decrease seizure frequency and increase survival in DS mice by reducing the expression of either SCN2A or SCN8A mRNA [Recent findings on the underlying mechanisms of DS have led to the development of other ASOs that have been successfully tested in DS mice. Studies reported that neuronal hyperexcitability due to the gain-of-function mutations in N8A mRNA ,269.Toxicity of ASOs can be caused by: (i) type I hypersensitivity after ASO injection; (ii) binding to off-target mRNAs, which may reduce the levels of off-target proteins or alter their structure to impair function; or (iii) chemical modifications which lead to ASO-protein interaction with subsequent immune reaction and aspecific adverse events, including fever, thrombocytopenia, arthralgia, nephrotoxicity, and hepatotoxicity . ReporteRNA therapy is emerging as a potential treatment for a number of neurological disorders. The objectives of preclinical studies should therefore be adjusted to provide high validity and reliability in assessing the safety and efficacy of these drugs. Induced pluripotent stem cells (iPSCs) can be generated after reprogramming patient-derived cells and converted to CNS relevant cell types in order to evaluate ASO efficacy in an in vitro setting. Furthermore, cerebral organoids derived from iPSCs can be a useful and more complex model system to investigate neurotoxicity after treatment. Humanized animal models should be tested to assess the safety and efficacy of human-specific ASOs in an in vivo setting.There are multiple preclinical studies reporting the therapeutic effects of ASOs with new target mRNAs in neurological conditions, including amyloid-β precursor protein in Alzheimer’s disease and Down syndrome; PMP22 in Charcot–Marie–Tooth type 1A; DUX4 overexpression in FSHD; expanded trinucleotide repeats in fragile X-associated tremor/ataxia syndrome and Huntington’s disease; HuR levels in neuropathic pain; and inhibition of inflammation in spinal cord injury and traumatic brain injury  74,75,8,280,281.Future studies are needed to compare the safety and efficacy of different types of oligonucleotides in neurological conditions to determine the safest and most effective RNA therapy in preclinical and clinical settings. Further delivery vehicles including nanoparticles should be developed to enhance ASO delivery in CNS disorders using less invasive routes of administration in patients. Deeper understanding of the bioavailability of each disease-specific ASO should also be evaluated in future studies.ASOs are shown to be promising disease-modifying agents in several neurological disorders and are able to reduce the level of toxic proteins, increase the level of functional protein, or modify the structure of impaired protein to improve function.


In this study, the deformation of concrete materials was evaluated using a mechanochromic sensor that detects the discoloration reaction caused by deformation. This sensor was attached by applying the Loctite adhesive to both ends in the longitudinal direction. The process of applying tensile stress to the specimens was videotaped, and the deformation and discoloration were examined through image analysis. The mechanochromic sensor was not affected by the finished surface condition, and the discoloration reaction was detected for a concrete material deformation level of up to 0.01 mm. The detected level was caused by the elongation of the sensor, and the discoloration compared with the initial color was identified. In addition, the integration behavior of the mechanochromic sensor under the deterioration of concrete members in cold areas and winter environments, as well as the discoloration reaction of the sensor in a low-temperature environment, was examined. It was found that the discoloration ability of the mechanochromic sensor exposed to a low-temperature environment was restored in 2 h after the end of the freeze–thaw test, and it was judged that the deformation and discoloration levels will be properly measured when the surface temperature of the sensor is restored to a room temperature of approximately 15 °C. This appeared to be due to the room temperature recovery of the dielectric spacer of the sensor and the deformation structure of the resonance condition. The sensor was also attached when diagonal cracks occurred in the concrete beam members to evaluate the strain and discoloration rate according to the deformation and discoloration levels. Accordingly, the cracks and deformation of the concrete materials were monitored using measured values from the discoloration of the mechanochromic sensors, and the possibility of measuring the crack width was reviewed only by real-time monitoring and imaging with the naked eye. The deterioration of structures, including civil engineering structures and buildings, causes significant damage worldwide every year. Maintenance and repair according to the service lives of structures are needed to reduce such damage, and various structural health monitoring (SHM) systems have been developed, including electronic endoscopes, wireless sensors, and radiofrequency identification devices ,2,3,4,5.Additional equipment in addition to sensors is required for most monitoring systems, and the latest sensor networking systems are in various stages of development . Kang utLee et al. developed a mechanochromic sensor that exhibits a discoloration reaction under the application of physical force, which has been used to measure the strain of homogeneous materials, such as steel, in the fields of machinery and aviation ,29. It hTherefore, in this study, whether the discoloration reaction of the mechanochromic sensor is active under the deformation of concrete materials was investigated to examine the applicability of the sensor in the construction field. The deformation due to cracks in concrete and structural damage were evaluated using the color change of the mechanochromic sensor, and the tensile deformation of specimens was videotaped for image analysis. In addition, the deformation and discoloration of the sensor attached to cement composites were analyzed through a freeze–thaw test, in which a freezing environment was used, to confirm its applicability to buildings in cold areas. Finally, the mechanochromic sensor was attached to the crack area during a crack induction experiment on a large concrete beam member to verify the accuracy of the concrete crack width measurement method. The crack width was measured using the color change, and the change in the sensor was determined through a comparison with the actual crack width.In this study, mechanochromic sensors, which were not considered in the existing construction field, were intended to be used in the crack and deformation detection field of concrete materials. Unlike conventional sensors that require power, mechanochromic sensors are non-powered discoloration sensors and can be used as highly economical sensors. In addition, it is possible to detect and monitor cracks by grasping the deformation and discoloration state of the sensor only by taking images. Through this study, it is expected to expand the field of technology based on user-centered diagnostic systems.The results of a literature search on existing structural integrity systems and smart sensing technologies are listed below.Downey et al. introduced an automatic damage detection strategy through electrical conduction and power measurement using self-sensing carbon-mixed cement materials and reviewed that the proposed Monte Carlo method could detect and locate the most noticeable damage in the structure . Chakrab3 and a tensile strength of 2700 MPa. The specimens prepared to estimate the discoloration reactivity of the attached mechanochromic sensor according to the tensile deformation of concrete were fiber-reinforced cement composites at the level of Fck 40 MPa. The specimens were prepared as shown in The mechanochromic sensor used in this study is insensitive to the angle, as it has a Fabry–Perot resonator structure composed of flat thin films. Details are presented in The mechanochromic sensor attached to identify the tensile deformation of concrete can detect microcracks, and exhibits continuous color change depending on the deformation of the attachment surface and no viewing-angle dependence . It cons2 at both ends of the sensor was attached to the concrete surface using Henkel’s Loctite SF 770 primer and 406 adhesive. An interval of approximately 30 s was provided after applying the adhesive before the attachment. The specimens with the sensor were installed in a direct tensile tester. After examining the tensile deformation of the tensile specimens and the discoloration reaction results of the sensor, an experiment on the deformation of concrete beam members was performed to confirm the usefulness of the deformation and discoloration of the mechanochromic sensor during the development of cracks in concrete beam members.The overall deformation and discoloration environment of the concrete specimens with the mechanochromic sensor is presented in The freeze–thaw test was conducted in accordance with ASTM C666/C666M-15 after attaching the mechanochromic sensor to concrete specimens to evaluate its applicability in cold areas and identify the discoloration recovery time of the sensor exposed to a low-temperature environment. In the test, one cycle was performed at temperatures ranging from −18 to 4 °C, and the temperature change process was repeated for 300 cycles. During the cycle, a direct tensile test was conducted every 30 min. The test execution time and the specimen ID by measurement time are presented in Upon the completion of the freeze–thaw test, the tensile strain of the mechanochromic sensor and concrete, as well as the discoloration of the sensor, was measured. To evaluate the time series of deformation, the deformation of the specimens was induced using a 250-kN static direct tensile tester with the stress loading speed set as 3 mm/min. A white chamber was installed to identify the discoloration of the sensor surface according to the increase in deformation. This was to prevent visual errors by allowing a certain amount of light to fall on the sensor surface. The tensile deformations of the specimen and sensor were measured at the same position from the sensor surface. A video extensometer  was used to examine the generated tensile deformation, and a quantitative measurement method satisfying the accuracy suggested in ASTM E82-10a was used. Two or more points marked with ‘+’ on the specimen surface were selected to evaluate the tensile strain of the specimen through imaging, and the tensile deformation was evaluated through image mapping. Regarding the distance between the points marked with ‘+’, two or more distances, as shown in As shown in According to these results, the tensile strains of the specimen and the attached mechanochromic sensor, as well as the discoloration reaction rate of the sensor, was calculated at each measurement time after the freeze–thaw test, and correlation analysis was performed using the Statistical Package for Social Sciences version 26 .When the H (hue) component was extracted by converting the color of the part of the mechanochromic sensor where deformation and discoloration occurred into the HSV color space, its linear relationship with the concrete specimen was confirmed. However, it is difficult to specify the deformation and discoloration range of the sensor because it is not easy to capture the images of only the deformation and discoloration part of the sensor attached to the structure, which may affect the quantitative derivation of the crack width. To extract the color range of only the sensor area from the captured images of the sensor, the color analysis range was determined in the captured images, and parts other than the sensor were removed. Among the HSV components of the mechanochromic sensor surface that appear during image capture, all the H values were within the range of 20–150, and the S (saturation) and V  exceeded 50. Therefore, the images were divided into the 100 × 300 pixel level, and the HSV component values extracted from the pixels of the deformed area were returned according to the range, as shown in minH and the highest H value as maxH, the ratio of the two values, i.e., dH, is obtained as follows:As shown in dH value and the strain. This equation can be used to quantify the discoloration and deformation characteristics of the mechanochromic sensor:Equation (2) gives the relationship between the calculated In this study, the H value and deformation were calculated using Equations (1) and (2). According to the calculations, a discoloration index and crack-width derivation formula were proposed.2 value of 0.9333, and the R2 value between the A2 area and H value was the same. The H value had a linear relationship with the deformation of the A1 and A2 areas, and the R2 value was large.2 was calculated as 0.0636 and 0.0750. As R2 may decrease slightly when sections with no discoloration reaction in the middle of the deformation process are considered, a process to supplement or correct this error will be required.dH level was insignificant, and the H value was constant. Therefore, R2 was not calculated.dH exhibited reactivity throughout the deformation process, but it was smaller than the values for the specimens not exposed to freezing and thawing. R2 was calculated to be 0.0005 or 0.0004, indicating that the reactivity of dH was low compared with the A1 and A2 strains under the severe frost damage of the sensor.dH evaluation results, and initial reaction of dH were confirmed. dH was large up to 1000 frames, but it decreased as the tensile deformation of the concrete specimen increased. This appeared to be because the discoloration reaction of the sensor became insensitive owing to frost damage. R2 was calculated to be 0.0135 and 0.0142.dH value was reduced after the initial reaction. In addition, the R2 value was not derived because the strain of A1 and A2 was not large, and the results parallel to dH were calculated.dH and the strain of A1 and A2 were calculated, and the results indicated that dH was somewhat constant. During the image capture/analysis process, green and purple colors were visually observed; thus, it was expected that the reactivity of dH could be evaluated as described in dH was found to be different. Consequently, the discoloration reaction of the mechanochromic sensor could be visually examined 3 h after the end of freezing and thawing, but it was judged that dH can be determined more accurately by designing a formula that considers the temperature coefficient of the frost-damaged sensor and environmental factors, such as the amount of time at room temperature.dH result could not always be determined after the initial reaction. During the H-value extraction process, the color yellow represented approximately a third of the sensor surface in the initial stage, and the input of the initial color value varied owing to surface frost damage. According to the divided images, the changes in the A1 area, A2 area, and H value for each frame are shown on the graphs on the right side. A color analysis of the entire area of the sensor surface indicated that no H value was extracted when the yellow section was deformed. The H value, however, was derived according to the discoloration reaction of the left deformed section that was not yellow. Accordingly, R2 was calculated to be 0.0636 and 0.075. As R2 may decrease slightly when sections with no discoloration reaction in the middle of the deformation process are considered, a process to supplement or correct this error will be required.2. In this study, the sensor was attached in the initial stage of cracking, and the crack width under loading was measured, as shown in A crack-induction experiment on large beam members was performed to validate the concrete crack width measurement method according to the aforementioned deformation and discoloration results of the mechanochromic sensor based on the tensile deformation of the concrete specimen. The experiment was conducted to identify the geometry of flexural and shear cracks in beam members according to the steel reinforcement at the concrete engineering laboratory of the Department of Civil, Architectural Engineering, and Landscape Architecture of Sungkyunkwan University. The cross-sectional area of the concrete beam was planned as H600 × B450 mm, and the clear span as D5400 mm. At the time of manufacturing the concrete beam, the slump in the unhardened state was 150 mm,150 mm, the amount of air was measured at a level of 4.5, and the amount of chloride was less than 0.30 kg/mThe widths of the cracks in the structural members were accurately measured by analyzing the discoloration image obtained by the sensor. However, it is difficult to obtain highly reliable data owing to the manufacturing condition of the sensor, discoloration in areas other than cracks, and irregular discoloration depending on the crack geometry.The relationship between the discoloration of the mechanochromic sensor and the deformation of the specimen was confirmed, and the discoloration of the sensor could be identified in real time during the progression of cracks.2 was also calculated from 1.5 h after the end of freezing and thawing, and it gradually increased.For the concrete specimen and mechanochromic sensor exposed to a freeze–thaw environment, the discoloration area was recognized in the sensor image 1.5 h after the end of freezing and thawing. R2 value 3.0 h after the end of freezing and thawing. When the sensor was not damaged in the freeze–thaw environment, the recovery time required for sensor discoloration measurement was estimated to be approximately 3 h. Accordingly, if images of the sensor surface condition are captured in cold areas, it is possible to identify deformation and discoloration most accurately using images after 3.0 h.The mechanochromic sensor exhibited the largest RThe deformation and discoloration of the mechanochromic sensor with respect to the crack development in concrete beam members was analyzed, and similar tendencies were observed for the actual crack deformation and the sensor discoloration when the crack widths based on the scale and the image analysis were proportional.When the deformation of concrete materials was monitored using the mechanochromic sensor, image analysis revealed that the degree of sensor discoloration corresponded to the degree of crack development. For more accurate monitoring, it is necessary to improve the reliability of the model and the experimental environment with consideration of data collected under various conditions, such as the sensor attachment position.Conventional SHM in the construction field requires precision and considerable manpower and has a high system cost for the detection of damage and cracking. These factors have been recognized as shortcomings of monitoring and sensing technology, and various sensor networking systems have emerged in recent years. In this study, a mechanochromic sensor that exhibited discoloration under the application of mechanical and physical stress was used to evaluate structural deformation and damage. The sensor can reduce various factors required for structural health assessments, as it can perform real-time monitoring with no power. Our experimental results for the deformation and discoloration reaction of the sensor attached to concrete specimens were as follows:This mechanochromic sensor proposes a crack deformation evaluation formula according to cracks in concrete materials, and through this, crack-width image analysis was derived. Based on these results, we plan to propose a damage index by assigning weights according to the location, shape, damage size, and range of the sensor in the future, and this research is in progress.This study reviewed the utility of a non-powered discoloration sensor in the field of detecting cracks and deformations in concrete materials, and through this, the field of technology based on a user-centered diagnosis system will be expanded.


On 12 November 2017, an earthquake occurred in Sarpol Zahab city, located on the Iraq/Iran boundary, with a moment magnitude (Mw) of 7.3. Advanced Land Observing Satellite 2 (ALOS-2) L-band (23.6 cm wavelength) and C-band Sentinel-1A data (ascending and descending) were used to detect the co-seismic displacements maps caused by this earthquake. The ALOS-2 data was utilized to reconstruct the 3D co-seismic displacements maps, as well as estimate the fault-dip and slip distribution along the rupture. The results showed the maximum surface displacement in the north, east, and up directions to be 100, 50, and 100 cm, respectively. The best-fit faulting geometry had a strike of 337.5° and a dip of 11.2° toward the northeast, at a depth of 8 km. The predicted geodetic moment was 1.15 1020 Nm, which corresponds to a magnitude of Mw 7.31. There were two significant slip sources: one in the shallower depth range of 8.5–10 km, with a peak slip of 5 m, and another in the depth range of 10.5–20 km, with a peak slip of 5.3 m. Both controlled the principal deformation signals in geodetic images. The slip was concentrated, along with a strike distance of 20 to 40 km, at a depth of 10 to 20 km. The earthquake was caused by the Zagros Mountains Front Fault (ZMFF), based on the results of 3D co-seismic deformation, inferred slip, preliminary investigation, and interpretation of the mainshock, as well as aftershock distributions. The Zagros orogenic belt is one of the salient convergent boundaries formed due to the Arabian-Eurasia continental collision . The conAccording to the U.S. Geological Survey (USGS), an earthquake of a magnitude of 7.3 struck western Iran/eastern Iraq on 12 November 2017. The earthquake’s epicenter was located near the ZMFF at 45.9° E, 34.93° N, at a depth of 20 km. The USGS suggested the mainshock was mostly northwest-trending oblique-thrust faulting with shallow dipping to northeast at mid-crustal depth (19 km), according to focal mechanism determined from seismic waveform data. However, within a month of the Sarpol Zahab earthquake, aftershocks struck at depths of 7 to 12 km ,15. The The co-seismic surface displacements caused by the Sarpol Zahab event on 12 November 2017, were measured using two ascending and two descending interferograms from the Advanced Land Observing (ALOS-2) and Sentinel-1 sensors. The ALOS-2 sensor, in ascending and descending orbits, has a radar incidence angle of 47.2° with HH polarization and pixel spacing of 20 m in range and 25 m in azimuth. The range and azimuth of the visual scene are approximately 350 km by 350 km. The ascent and descent angles are 91° and 170°, respectively. The ALOS-2 has a longer wavelength of 23.6 cm (L band) and is less affected by SAR signal temporal decorrelation. We collected SAR images before and after the Sarpol mainshock to avoid the detrimental effect of the co-seismic signal on the recovered co-seismic DInSAR deformation field. The observed timing of the SAR images closest to the 2017 Sarpol Zahab earthquake was used in the DInSAR deformation field. The detailed information and ground coverage of the employed SAR pairs are depicted in atm), the flat earth effect, the contribution from surface deformation (Δϕdef), the topography (Δϕtopo), inaccuracies in the orbit state vectors (Δϕorb), and other noise contributions (Δϕnoise). The difference in interferogram phase (ΔΦ) is measured in radians between 0 and 2π [Many scholars have described the basics of InSAR . This me0 and 2π .(1)ϕ=2πdef) in the target, in terms of line of sight (LOS) of the absolute phase difference in an interferogram (Δϕ), topographic contributions (Δϕtopo) are removed using a Digital Elevation Model (DEM). The inaccuracies come from the sensor and the data processing (ε). Suppose the atmosphere has similar spatial conditions between the two scan times. In this case, its contribution tends to be zero, and the distortion map can be obtained after removing the two-dimensional phase ambiguity in the interferometric model’s phase shift the remainder of the differential interferogram is shown in the expression below. To demonstrate the reliance of the perpendicular baseline B, we preserve the topographic phase (second term to the right of 1). We can use Equation (2) [def is the deformation within the LOS component.To find the surface deformation component (Δϕtion (2) .(2)ϕ=4πMultiple aperture interferometry is a technique that uses two SAR (Synthetic Aperture Radar) images to measure ground displacement along the satellite’s flight path (azimuth offset). The AMI is able to measure movement in the direction of flight by applying more elaborate signal processing. The main advantage of MAI is that two single-look-complex (SLC) SAR images with forward and backward looking are created by dividing the length of a synthetic aperture with signal processing. Standard InSAR processing is applied to forward- and backward-looking images, acquired at different periods, to produce a forward and backward SAR interferogram. Despite the fact that both of these interferograms indicate LOS displacement, the LOS directions are different. Subtracting the precision of the measurements is lower than that of regular DInSAR, sometimes decreasing to a few dozen centimeters . It can The LOS component was obtained by a two-pass differential method with GAMMA software, as described by . The datIn addition, phase noises were reduced on the differential interferograms by applying the Goldstein filters method. The topographic effect was removed by utilizing SRTM (DEM) with a resolution of 90 m in the phase. The removal was followed by the procedure provided in . The minThe three-dimensional co-seismic deformations were reconstructed by combining the measurements of LOS and along-track data. The imaging geometry of 3D vectors for surface deformation for the dot P in yellow color, the vector for DInSAR and MAI measurers  defined We restructured the 3D surface deformation map based on Equations (4) and (5). Surface deformation and the integration of InSAR and MAI data sets can be expressed as follows (6): Expanding Equation (6) using angles, as in The co-seismic displacement was obtained by the DInSAR method described in The InSAR measurement is sensitive and more evident in the LOS deformation than the azimuth displacement . In contWe retrieved the 3D displacement by integrating the measurements of the LOS and along-track from the ALOS-2 and Sentinel-1A data. The east, north, and up components were retrieved based on the 3D displacement field method, described in Recently, LOS deformation maps have become a source of beneficial information for elicitation of the slip along the fault plane . InversiDue to DInSAR’s limited sensitivity to azimuth deformation, all of the data show significant discrepancies between the various SAR sensors and orbits. Moreover, the strike of the co-seismic motions is parallel to the ascending orbit and crosses the descending orbit, and the fault is confirmed as a thrust fault; consequently, variations in the projected values are unavoidable. Meanwhile, because the fringe density in larger magnitude earthquakes is too great to effectively conduct phase unwrapping, the L-band ALOS-2 SAR sensor has reliability in such severe deformation monitoring. The MAI approach, based on phase differencing, performs better. From our results, we confirmed that the UD components are the most violent, and westward motion has a significant influence on horizontal motion b. The geWe inferred the 3D surface deformation of the Sarpol Zahab earthquake by combining DInSAR and MAI interferograms from co-seismic ALOS-2 and Sentinel-1A data. The observed surface displacements in the east, up, and north directions were approximately 50, 100, and 100 cm, respectively. The best-fit faulting geometry had a strike trend of 337.5°, with a dip of 11.2°.The total seismic moment was 1.151020 nm, corresponding to Mw 7.31. The dip-depth ranges were 8.5–10-km and 10.5–20 km, with a peak slip of 5 m and 5.3 m, respectively, and concentrated along a 20–40 km strike distance at a depth of 10–14 km. When compared to prior studies’ results, the 3D-based model yielded more precise parameter estimations, with significantly reduced uncertainty.