ARCTIC-3D: automatic retrieval and clustering of interfaces in complexes from 3D structural information

The formation of a stable complex between proteins lies at the core of a wide variety of biological processes and has been the focus of countless experiments. The huge amount of information contained in the protein structural interactome in the Protein Data Bank can now be used to characterise and classify the existing biological interfaces. We here introduce ARCTIC-3D, a fast and user-friendly data mining and clustering software to retrieve data and rationalise the interface information associated with the protein input data. We demonstrate its use by various examples ranging from showing the increased interaction complexity of eukaryotic proteins, 20% of which on average have more than 3 different interfaces compared to only 10% for prokaryotes, to associating different functions to different interfaces. In the context of modelling biomolecular assemblies, we introduce the concept of "recognition entropy", related to the number of possible interfaces of the components of a protein-protein complex, which we demonstrate to correlate with the modelling difficulty in classical docking approaches. The identified interface clusters can also be used to generate various combinations of interface-specific restraints for integrative modelling. The ARCTIC-3D software is freely available at github.com/haddocking/arctic3d and can be accessed as a web-service at wenmr.science.uu.nl/arctic3d.

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.

An antibiotic from an uncultured bacterium binds to an immutable target

Antimicrobial resistance is a leading mortality factor worldwide. Here, we report the discovery of clovibactin, an antibiotic isolated from uncultured soil bacteria. Clovibactin efficiently kills drug-resistant Gram-positive bacterial pathogens without detectable resistance. Using biochemical assays, solid-state nuclear magnetic resonance, and atomic force microscopy, we dissect its mode of action. Clovibactin blocks cell wall synthesis by targeting pyrophosphate of multiple essential peptidoglycan precursors (C55PP, lipid II, and lipid IIIWTA). Clovibactin uses an unusual hydrophobic interface to tightly wrap around pyrophosphate but bypasses the variable structural elements of precursors, accounting for the lack of resistance. Selective and efficient target binding is achieved by the sequestration of precursors into supramolecular fibrils that only form on bacterial membranes that contain lipid-anchored pyrophosphate groups. This potent antibiotic holds the promise of enabling the design of improved therapeutics that kill bacterial pathogens without resistance development.

A new antibiotic from an uncultured bacterium binds to an immutable target

Antimicrobial resistance is a leading mortality factor worldwide. Here we report the discovery of clovibactin, a new antibiotic, isolated from uncultured soil bacteria. Clovibactin efficiently kills drug-resistant bacterial pathogens without detectable resistance. Using biochemical assays, solid-state NMR, and atomic force microscopy, we dissect its mode of action. Clovibactin blocks cell wall synthesis by targeting pyrophosphate of multiple essential peptidoglycan precursors (C 55 PP, Lipid II, Lipid WTA ). Clovibactin uses an unusual hydrophobic interface to tightly wrap around pyrophosphate, but bypasses the variable structural elements of precursors, accounting for the lack of resistance. Selective and efficient target binding is achieved by the irreversible sequestration of precursors into supramolecular fibrils that only form on bacterial membranes that contain lipid-anchored pyrophosphate groups. Uncultured bacteria offer a rich reservoir of antibiotics with new mechanisms of action that could replenish the antimicrobial discovery pipeline.

Structural Biology in the Clouds: The WeNMR-EOSC Ecosystem

Structural biology aims at characterizing the structural and dynamic properties of biological macromolecules at atomic details. Gaining insight into three dimensional structures of biomolecules and their interactions is critical for understanding the vast majority of cellular processes, with direct applications in health and food sciences. Since 2010, the WeNMR project (www.wenmr.eu) has implemented numerous web-based services to facilitate the use of advanced computational tools by researchers in the field, using the high throughput computing infrastructure provided by EGI. These services have been further developed in subsequent initiatives under H2020 projects and are now operating as Thematic Services in the European Open Science Cloud portal (www.eosc-portal.eu), sending >12 millions of jobs and using around 4,000 CPU-years per year. Here we review 10 years of successful e-infrastructure solutions serving a large worldwide community of over 23,000 users to date, providing them with user-friendly, web-based solutions that run complex workflows in structural biology. The current set of active WeNMR portals are described, together with the complex backend machinery that allows distributed computing resources to be harvested efficiently.

Information-driven modeling of biomolecular complexes

Proteins play crucial roles in every cellular process by interacting with each other, nucleic acids, metabolites, and other molecules. The resulting assemblies can be very large and intricate and pose challenges to experimental methods. In the current era of integrative modeling, it is often only by a combination of various experimental techniques and computations that three-dimensional models of those molecular machines can be obtained. Among the various computational approaches available, molecular docking is often the method of choice when it comes to predicting three-dimensional structures of complexes. Docking can generate particularly accurate models when taking into account the available information on the complex of interest. We review here the use of experimental and bioinformatics data in protein-protein docking, describing recent software developments and highlighting applications for the modeling of antibody-antigen complexes and membrane protein complexes, and the use of evolutionary and shape information.

An overview of data-driven HADDOCK strategies in CAPRI rounds 38-45

Our information-driven docking approach HADDOCK has demonstrated a sustained performance since the start of its participation to CAPRI. This is due, in part, to its ability to integrate data into the modeling process, and to the robustness of its scoring function. We participated in CAPRI both as server and manual predictors. In CAPRI rounds 38-45, we have used various strategies depending on the available information. These ranged from imposing restraints to a few residues identified from literature as being important for the interaction, to binding pockets identified from homologous complexes or template-based refinement/CA-CA restraint-guided docking from identified templates. When relevant, symmetry restraints were used to limit the conformational sampling. We also tested for a large decamer target a new implementation of the MARTINI coarse-grained force field in HADDOCK. Overall, we obtained acceptable or better predictions for 13 and 11 server and manual submissions, respectively, out of the 22 interfaces. Our server performance (acceptable or higher-quality models when considering the top 10) was better (59%) than the manual (50%) one, in which we typically experiment with various combinations of protocols and data sources. Again, our simple scoring function based on a linear combination of intermolecular van der Waals and electrostatic energies and an empirical desolvation term demonstrated a good performance in the scoring experiment with a 63% success rate across all 22 interfaces. An analysis of model quality indicates that, while we are consistently performing well in generating acceptable models, there is room for improvement for generating/identifying higher quality models.

Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment

We present the results for CAPRI Round 46, the third joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo-oligomers and 6 heterocomplexes. Eight of the homo-oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher-order assemblies. These were more difficult to model, as their prediction mainly involved "ab-initio" docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance "gap" was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template-based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.

Less Is More: Coarse-Grained Integrative Modeling of Large Biomolecular Assemblies with HADDOCK

Predicting the 3D structure of protein interactions remains a challenge in the field of computational structural biology. This is in part due to difficulties in sampling the complex energy landscape of multiple interacting flexible polypeptide chains. Coarse-graining approaches, which reduce the number of degrees of freedom of the system, help address this limitation by smoothing the energy landscape, allowing an easier identification of the global energy minimum. They also accelerate the calculations, allowing for modeling larger assemblies. Here, we present the implementation of the MARTINI coarse-grained force field for proteins into HADDOCK, our integrative modeling platform. Docking and refinement are performed at the coarse-grained level, and the resulting models are then converted back to atomistic resolution through a distance restraints-guided morphing procedure. Our protocol, tested on the largest complexes of the protein docking benchmark 5, shows an overall ∼7-fold speed increase compared to standard all-atom calculations, while maintaining a similar accuracy and yielding substantially more near-native solutions. To showcase the potential of our method, we performed simultaneous 7 body docking to model the 1:6 KaiC-KaiB complex, integrating mutagenesis and hydrogen/deuterium exchange data from mass spectrometry with symmetry restraints, and validated the resulting models against a recently published cryo-EM structure.

MARTINI-Based Protein-DNA Coarse-Grained HADDOCKing

Modeling biomolecular assemblies is an important field in computational structural biology. The inherent complexity of their energy landscape and the computational cost associated with modeling large and complex assemblies are major drawbacks for integrative modeling approaches. The so-called coarse-graining approaches, which reduce the degrees of freedom of the system by grouping several atoms into larger “pseudo-atoms,” have been shown to alleviate some of those limitations, facilitating the identification of the global energy minima assumed to correspond to the native state of the complex, while making the calculations more efficient. Here, we describe and assess the implementation of the MARTINI force field for DNA into HADDOCK, our integrative modeling platform. We combine it with our previous implementation for protein-protein coarse-grained docking, enabling coarse-grained modeling of protein-nucleic acid complexes. The system is modeled using MARTINI topologies and interaction parameters during the rigid body docking and semi-flexible refinement stages of HADDOCK, and the resulting models are then converted back to atomistic resolution by an atom-to-bead distance restraints-guided protocol. We first demonstrate the performance of this protocol using 44 complexes from the protein-DNA docking benchmark, which shows an overall ~6-fold speed increase and maintains similar accuracy as compared to standard atomistic calculations. As a proof of concept, we then model the interaction between the PRC1 and the nucleosome (a former CAPRI target in round 31), using the same information available at the time the target was offered, and compare all-atom and coarse-grained models.

Thioredoxin-1 Negatively Modulates ADAM17 Activity Through Direct Binding and Indirect Reductive Activity

AIMS

A disintegrin and metalloprotease 17 (ADAM17) modulates signaling events by releasing surface protein ectodomains such as TNFa and the EGFR-ligands. We have previously characterized cytoplasmic thioredoxin-1 (Trx-1) as a partner of ADAM17 cytoplasmic domain. Still, the mechanism of ADAM17 regulation by Trx-1 is unknown, and it has become of paramount importance to assess the degree of influence that Trx-1 has on metalloproteinase ADAM17.

RESULTS

Combining discovery and targeted proteomic approaches, we uncovered that Trx-1 negatively regulates ADAM17 by direct and indirect effect. We performed cell-based assays with synthetic peptides and site-directed mutagenesis, and we demonstrated that the interaction interface of Trx-1 and ADAM17 is important for the negative regulation of ADAM17 activity. However, both Trx-1^K72A and catalytic site mutant Trx-1^C32/35S rescued ADAM17 activity, although the interaction with Trx-1^C32/35S was unaffected, suggesting an indirect effect of Trx-1. We confirmed that the Trx-1^C32/35S mutant showed diminished reductive capacity, explaining this indirect effect on increasing ADAM17 activity through oxidant levels. Interestingly, Trx-1^K72A mutant showed similar oxidant levels to Trx-1^C32/35S, even though its catalytic site was preserved. We further demonstrated that the general reactive oxygen species inhibitor, Nacetylcysteine (NAC), maintained the regulation of ADAM17 dependent of Trx-1 reductase activity levels; whereas the electron transport chain modulator, rotenone, abolished Trx-1 effect on ADAM17 activity.

INNOVATION

We show for the first time that the mechanism of ADAM17 regulation, Trx-1 dependent, can be by direct interaction and indirect effect, bringing new insights into the cross-talk between isomerases and mammalian metalloproteinases.

CONCLUSION

This unexpected Trx-1^K72A behavior was due to more dimer formation and, consequently, the reduction of its Trx-1 reductase activity, evaluated through dimer verification, by gel filtration and mass spectrometry analysis. Antioxid. Redox Signal. 29, 717-734.

Calcium and magnesium ions modulate the oligomeric state and function of mitochondrial 2-Cys peroxiredoxins in Leishmania parasites

Leishmania parasites have evolved a number of strategies to cope with the harsh environmental changes during mammalian infection. One of these mechanisms involves the functional gain that allows mitochondrial 2-Cys peroxiredoxins to act as molecular chaperones when forming decamers. This function is critical for parasite infectivity in mammals, and its activation has been considered to be controlled exclusively by the enzyme redox state under physiological conditions. Herein, we have revealed that magnesium and calcium ions play a major role in modulating the ability of these enzymes to act as molecular chaperones, surpassing the redox effect. These ions are directly involved in mitochondrial metabolism and participate in a novel mechanism to stabilize the decameric form of 2-Cys peroxiredoxins in Leishmania mitochondria. Moreover, we have demonstrated that a constitutively dimeric Prx1m mutant impairs the survival of Leishmania under heat stress, supporting the central role of the chaperone function of Prx1m for Leishmania parasites during the transition from insect to mammalian hosts.

The molecular motor Myosin Va interacts with the cilia-centrosomal protein RPGRIP1L

Myosin Va (MyoVa) is an actin-based molecular motor abundantly found at the centrosome. However, the role of MyoVa at this organelle has been elusive due to the lack of evidence on interacting partners or functional data. Herein, we combined yeast two-hybrid screen, biochemical studies and cellular assays to demonstrate that MyoVa interacts with RPGRIP1L, a cilia-centrosomal protein that controls ciliary signaling and positioning. MyoVa binds to the C2 domains of RPGRIP1L via residues located near or in the Rab11a-binding site, a conserved site in the globular tail domain (GTD) from class V myosins. According to proximity ligation assays, MyoVa and RPGRIP1L can interact near the cilium base in ciliated RPE cells. Furthermore, we showed that RPE cells expressing dominant-negative constructs of MyoVa are mostly unciliated, providing the first experimental evidence about a possible link between this molecular motor and cilia-related processes.

Abstract 307: Structural Characterization of Calcineurin A-Calsarcin 1 Assembly

Signaling by the calcium-dependent phosphatase calcineurin (Cn) plays key roles in regulating cardiac development, hypertrophy, and pathological remodeling. Cn binds to and is negatively regulated by calsarcins (CS), a family of muscle-specific proteins. However, the molecular mechanisms involved in the inhibition of Cn by CS remain unclear. Understanding the architecture and structure of Cn-CS complex is critical to unravel the regulation of Cn by CS. Here we combined biochemical assays, chemical cross-linking coupled to mass spectrometry experiments (MS/MS), mutational analysis and a modeling strategy for structural characterization of CnA-CS1 assembly. The MS/MS data obtained from the cross-linked peptides of both proteins were used to guide an in silico docking of their polypeptide models. The protein complex models with the smallest estimated binding energy were clustered according to structural similarity and submitted to molecular dynamics simulation. The interacting surface of CnA was mapped in a pocket between the 1st and 3rd α-helixes and surrounding loops, while the corresponding surface of CS1 was mapped to the carboxyterminal loops within the Leu179-Phe185, Phe195-Ser199 and Thr250-Leu264 regions. Notably, the region of CnA that interacts with CS1 was found to be located in close proximity, but not coincident, to the β-sheet 14, the main binding site for the PxIxIT sequence of NFAT. Experiments performed with several CnA (FLAG-CnA) and CS1 (myc-CS1) mutants were used to validate the structural model of the CnA-CS1 assembly. The Lys40 (CnA) and Glu254 (CS1) residues were identified as critical for the complex stability. The model that emerges from this study supports the notion that CS1 interacts with an allosteric site to inhibit the activity of CnA. Alternatively, the close proximity of the CS1 to NFAT interacting site supports an interference of CS1 on the ability of CnA to bind and activate NFAT.

KVFinder: steered identification of protein cavities as a PyMOL plugin

Background

The characterization of protein binding sites is a major challenge in computational biology. Proteins interact with a wide variety of molecules and understanding of such complex interactions is essential to gain deeper knowledge of protein function. Shape complementarity is known to be important in determining protein-ligand interactions. Furthermore, these protein structural features have been shown to be useful in assisting medicinal chemists during lead discovery and optimization.

Results

We developed KVFinder, a highly versatile and easy-to-use tool for cavity prospection and spatial characterization. KVFinder is a geometry-based method that has an innovative customization of the search space. This feature provides the possibility of cavity segmentation, which alongside with the large set of customizable parameters, allows detailed cavity analyses. Although the main focus of KVFinder is the steered prospection of cavities, we tested it against a benchmark dataset of 198 known drug targets in order to validate our software and compare it with some of the largely accepted methods. Using the one click mode, we performed better than most of the other methods, staying behind only of hybrid prospection methods. When using just one of KVFinder’s customizable features, we were able to outperform all other compared methods. KVFinder is also user friendly, as it is available as a PyMOL plugin, or command-line version.

Conclusion

KVFinder presents novel usability features, granting full customizable and highly detailed cavity prospection on proteins, alongside with a friendly graphical interface. KVFinder is freely available on http://lnbio.cnpem.br/bioinformatics/main/software/.

Mechanistic strategies for catalysis adopted by evolutionary distinct family 43 arabinanases

Arabinanases (ABNs, EC 3.2.1.99) are promising catalysts for environmentally friendly biomass conversion into energy and chemicals. These enzymes catalyze the hydrolysis of the α-1,5-linked L-arabinofuranoside backbone of plant cell wall arabinans releasing arabino-oligosaccharides and arabinose, the second most abundant pentose in nature. In this work, new findings about the molecular mechanisms governing activation, functional differentiation, and catalysis of GH43 ABNs are presented. Biophysical, mutational, and biochemical studies with the hyperthermostable two-domain endo-acting ABN from Thermotoga petrophila (TpABN) revealed how some GH43 ABNs are activated by calcium ions via hyperpolarization of the catalytically relevant histidine and the importance of the ancillary domain for catalysis and conformational stability. On the other hand, the two GH43 ABNs from rumen metagenome, ARN2 and ARN3, presented a calcium-independent mechanism in which sodium is the most likely substituent for calcium ions. The crystal structure of the two-domain endo-acting ARN2 showed that its ability to efficiently degrade branched substrates is due to a larger catalytic interface with higher accessibility than that observed in other ABNs with preference for linear arabinan. Moreover, crystallographic characterization of the single-domain exo-acting ARN3 indicated that its cleavage pattern producing arabinose is associated with the chemical recognition of the reducing end of the substrate imposed by steric impediments at the aglycone-binding site. By structure-guided rational design, ARN3 was converted into a classical endo enzyme, confirming the role of the extended Arg(203)-Ala(230) loop in determining its action mode. These results reveal novel molecular aspects concerning the functioning of GH43 ABNs and provide new strategies for arabinan degradation.

P-I class metalloproteinase from Bothrops moojeni venom is a post-proline cleaving peptidase with kininogenase activity: insights into substrate selectivity and kinetic behavior

Snake venom metalloproteinases (SVMPs) belonging to P-I class are able to hydrolyze extracellular matrix proteins and coagulation factors triggering local and systemic reactions by multiple molecular mechanisms that are not fully understood. BmooMPα-I, a P-I class SMVP from Bothrops moojeni venom, was active upon neuro- and vaso-active peptides including angiotensin I, bradykinin, neurotensin, oxytocin and substance P. Interestingly, BmooMPα-I showed a strong bias towards hydrolysis after proline residues, which is unusual for most of characterized peptidases. Moreover, the enzyme showed kininogenase activity similar to that observed in plasma and cells by kallikrein. FRET peptide assays indicated a relative promiscuity at its S2-S'2 subsites, with proline determining the scissile bond. This unusual post-proline cleaving activity was confirmed by the efficient hydrolysis of the synthetic combinatorial library MCA-GXXPXXQ-EDDnp, described as resistant for canonical peptidases, only after Pro residues. Structural analysis of the tripeptide LPL complexed with BmooMPα-I, generated by molecular dynamics simulations, assisted in defining the subsites and provided the structural basis for subsite preferences such as the restriction of basic residues at the S2 subsite due to repulsive electrostatic effects and the steric impediment for large aliphatic or aromatic side chains at the S1 subsite. These new functional and structural findings provided a further understanding of the molecular mechanisms governing the physiological effects of this important class of enzymes in envenomation process.

Structural insights into functional overlapping and differentiation among myosin V motors

Myosin V (MyoV) motors have been implicated in the intracellular transport of diverse cargoes including vesicles, organelles, RNA-protein complexes, and regulatory proteins. Here, we have solved the cargo-binding domain (CBD) structures of the three human MyoV paralogs (Va, Vb, and Vc), revealing subtle structural changes that drive functional differentiation and a novel redox mechanism controlling the CBD dimerization process, which is unique for the MyoVc subclass. Moreover, the cargo- and motor-binding sites were structurally assigned, indicating the conservation of residues involved in the recognition of adaptors for peroxisome transport and providing high resolution insights into motor domain inhibition by CBD. These results contribute to understanding the structural requirements for cargo transport, autoinhibition, and regulatory mechanisms in myosin V motors.

Identification of novel interaction between ADAM17 (a disintegrin and metalloprotease 17) and thioredoxin-1

ADAM17, which is also known as TNFα-converting enzyme, is the major sheddase for the EGF receptor ligands and is considered to be one of the main proteases responsible for the ectodomain shedding of surface proteins. How a membrane-anchored proteinase with an extracellular catalytic domain can be activated by inside-out regulation is not completely understood. We characterized thioredoxin-1 (Trx-1) as a partner of the ADAM17 cytoplasmic domain that could be involved in the regulation of ADAM17 activity. We induced the overexpression of the ADAM17 cytoplasmic domain in HEK293 cells, and ligands able to bind this domain were identified by MS after protein immunoprecipitation. Trx-1 was also validated as a ligand of the ADAM17 cytoplasmic domain and full-length ADAM17 recombinant proteins by immunoblotting, immunolocalization, and solid phase binding assay. In addition, using nuclear magnetic resonance, it was shown in vitro that the titration of the ADAM17 cytoplasmic domain promotes changes in the conformation of Trx-1. The MS analysis of the cross-linked complexes showed cross-linking between the two proteins by lysine residues. To further evaluate the functional role of Trx-1, we used a heparin-binding EGF shedding cell model and observed that the overexpression of Trx-1 in HEK293 cells could decrease the activity of ADAM17, activated by either phorbol 12-myristate 13-acetate or EGF. This study identifies Trx-1 as a novel interaction partner of the ADAM17 cytoplasmic domain and suggests that Trx-1 is a potential candidate that could be involved in ADAM17 activity regulation.

Bactericidal activity identified in 2S Albumin from sesame seeds and in silico studies of structure-function relations

Pathogenic bacteria constitute an important cause of hospital-acquired infections. However, the misuse of available bactericidal agents has led to the appearance of antibiotic-resistant strains. Thus, efforts to seek new antimicrobials with different action mechanisms would have an enormous impact. Here, a novel antimicrobial protein (SiAMP2) belonging to the 2S albumin family was isolated from Sesamum indicum kernels and evaluated against several bacteria and fungi. Furthermore, in silico analysis was conducted in order to identify conserved residues through other 2S albumin antimicrobial proteins (2S-AMPs). SiAMP2 specifically inhibited Klebsiella sp. Specific regions in the molecule surface where cationic (RR/RRRK) and hydrophobic (MEYWPR) residues are exposed and conserved were proposed as being involved in antimicrobial activity. This study reinforces the hypothesis that plant storage proteins might also play as pathogen protection providing an insight into the mechanism of action for this novel 2S-AMP and evolutionary relations between antimicrobial activity and 2S albumins.