Current Proteomics - Online First

Recent investigation revealed that arbuscular mycorrhizal fungi (AMF) brought major changes in the transcriptome of non-host plant- Arabidopsis thaliana (A. thaliana) within the AM network constructed by the hyphae of AMF connecting multiple plant roots. Although there is enormous omics data available for A. thaliana, most AM-related information has been restricted to transcriptome studies.

We aimed to provide a comprehensive toolset for analyzing AM signaling-driven molecular interactions in A. thaliana.

We developed ten modules: 1) Epigenetic regulation in protein–nucleic acid interactions (PNI), 2) DNA structure and metal binding profiles, 3) Transcription factor (TF) binding profiles, 4) Protein domain–domain interactions (DDI), 5) Profiling of protein-metal and protein-ligand interactions with complex structures (PLP) based on alignment of similar protein structures, 6) Carbohydrate-lipid-protein interactions (CLP) – analysis of lipidome-proteome interactions, N-glycosylation/glycan structure data, and carbohydrate-active enzyme/substrate predictions, 7) Metabolic pathway analysis, 8) Multiple omics association studies, 9) Gene Ontology (GO) and Plant Ontology (PO) analysis, and 10) Medicago transcriptome and epigenetic information.

For the program demonstration, we generated various comparative datasets based on differentially expressed genes (DEGs) from Arabidopsis thaliana (A. thaliana) of non-arbuscular mycorrhizal (non-AM) and arbuscular mycorrhizal (AM) phenotypes, as well as DEGs from Medicago truncatula (M. truncatula). These datasets were analyzed using statistical methods and artificial neural networks. The program demonstrated a range of advantages in studying molecular interactions related to AM symbiosis.

To aid in the inference of AM-driven changes and the identification of AM-derived molecules during AM symbiosis, the program offers a user-friendly platform for generating datasets with key features, which can then be integrated with various downstream statistical methods. The program code is freely available for download at www.artfoundation.kr.

This study aims to gain insights into the EhSec1 binding mechanism and the corresponding amino acids responsible for interacting with the amoebic SNARE proteins, EhSyntaxin1A/1B, which would enable to create a platform for further exploration of the functions and applications of EhSec1 in managing amoebiasis.

Parasitic protozoa have long been responsible for increasing the burden on healthcare. However, the enteric protozoan Entamoeba histolytica, is dangerously neglected despite accounting for the greatest number of deaths from parasitic infection, closely after malaria and schistosomiasis. E. histolytica launches its attack via secretion of tissue degrading arsenal through vesicular transport. Sec1/Munc18-1 -like (SM) proteins are one of the key players of the vesicle transport system and, along with their interacting partners, play crucial roles in this transport machinery. This provides the basis for exploring the uncharacterized SM protein in E. histolytica, and its roles in vesicle transport.

This study aims to decode the novel SM protein, EhSec1, by performing detailed sequence and structure analysis and delving into the protein interaction studies with its partner SNARE proteins (Syntaxins) through molecular dynamic simulations and docking. The interactions will be compared with crystal structure exhibiting co-complexes of Sec1_Syntaxin to further highlight the role of EhSec1 amino acids in interacting with amoebic SNAREs, EhSyntaxin 1A/1B.

The objectives were fulfilled by performing rigorous studies on EhSec1, falling under the heads of comparative sequence and structure analysis, physicochemical studies, modeling, and molecular docking, and protein-protein interaction studies supported by molecular dynamic simulations.

EhSec1 is a thermally stable, 70kDa globular protein composed of three domains where domains 1 and 2 adopt an α-β-α fold. Domain 2 is split into 2a and 2b, separated by domain 3. This domain has two parts, 3a and 3b, at an angle of 56.7° to each other. EhSec1 shows stable interaction with Syntaxin 1 isoforms (EhSyntaxin1A/1B) and Rab GTPase (EhRabX10). Molecular simulation investigating the dynamics of EhSec1 with Syntaxin1A, showed that the interaction is stable due to the formation of 14 strong hydrogen bonds (bond length <2.4 Å). The pivotal residues of the interaction interface belong to domain 1 (53D, 60K, and 62E) and domain 3a (259K and 261R) of EhSec1; Hc region (110R and 114N) and SNARE motif (234E, 237E, 242E) of Syntaxin 1A/1B. EhRabX10 binds to EhSec1 via its G3 region, and the key interacting residues of EhSec1 (224R-225H, 490L-495F, and 518K) fall in domain 2.

Our study reveals that the Syntaxin 1 isoforms and EhRabX10 form stable complexes with EhSec1, assembling the minimal template for the SNARE-based vesicle transport of Eh. Our investigation aims to enhance comprehension of vesicle transport in Eh and establish the potential of EhSec1 as a viable drug target in future applications.

Venomous scorpions play a crucial role in medicine and public health. Buthotus saulcyi scorpion is known as one of the most populous species in East Asia and Iran, while its venom proteome has still not been fully determined.

In the current research, the proteomic profile of Buthotus saulcyi scorpion venom to determine the structural and functional characteristics of its compounds used for treatment will be examined for the first time.

2D-PAGE, HPLC, SDS-PAGE, sequencing, and MALDI-TOF MS techniques were used to investigate the properties of these peptides.

The 2D-PAGE analysis of crude toxin from B. saulcyi revealed a minimum of 96 protein spots, with isoelectric points ranging from 4 to 9 and molecular weights spanning from 3.6 to 205 kDa. Following this, HPLC was used to isolate 14 fractions of crude toxins, and the protein content of these fractions was measured. SDS-PAGE analysis identified 7 protein bands within the B. saulcyi crude toxin fractions, with molecular weights ranging from 13 to 217 kDa. Further examination of fraction 7 through amino acid sequencing resulted in the identification of two protein bands labeled peptide 3 and peptide 4. Ultimately, these protein bands were extracted, and their molecular mass and amino acid sequences were analyzed using MALDI-TOF MS.

According to our results, the alignment of P3 and P4 protein sequences revealed the highest similarity to chrysophsin 2 and pheromone-bound protein 2, respectively.

Sepsis is defined as the extreme response of a body to an infection, leading to untimely death if left untreated. The human gut microbiome is characterized by the presence of several microorganisms in the gastrointestinal tract. This study provides insight into the potential therapeutic effects of a peptide present in the human gut microbiome that helps control sepsis.

This study aimed to explore the therapeutic application of a peptide from Lactobacillus sp. in the human gut microbiome as an alternative to MRSA, which causes severe, fatal diseases like sepsis. It also elucidates the peptide-protein interactions that enhance the efficacy of infection control and treatment.

We aimed to investigatethe interactions between protein-peptide and protein-drug complexes through in silico analyses.

Molecular docking was performed using PyRx and HADDOCK tools. Next, we performed molecular simulation studies using GROMACS v2020.6 at different physiological pH values of 4, 6, and 7.4. Stability, compactness, and binding energies were analyzed usingparameters such as RMSD, Rg, and MMPBSA, among other parameters.

We observed stability on docking between Plantaricin KL-1Y, an effective bacteriocin from Lactobacillus plantarum (organism from gut microbiome), and PBP2a from Staphylococcus aureus (causative organism of sepsis). This was indicated by a binding affinity of -13.4 kcal/mol, higher than that of PBP2a-FDA-approved drug (-8 kcal/mol). The MMPBSA results of the PBP2a-Plantaricin KL-1Y complex showed a significantly higher binding affinity at pH 7.4 of -228.451 kcal/mol in comparison to -69.5747 kcal/mol for the PBP2a-Ceftaroline fosamil complex.

These results indicate the possible use of a peptide from the human gut as a potential therapeutic agent against S. aureus infection.

Necrosis, a form of uncontrolled cell death, can be triggered by a variety of stressors, including infection, injury, toxins, and ischemia. Such necrotic events, particularly when induced by pathogenic infections, can lead to severe health complications. The mixed lineage kinase domain-like pseudokinase (MLKL) has been identified as a crucial drug target for mitigating necrosis.

The objective of this study is to identify potential MLKL inhibitors that act against necroptosis via a pharmacophore model and virtual screening.

In this study, we developed a ligand-based pharmacophore model to facilitate the identification of inhibitors that target MLKL. Comprehensive ADMET analysis, virtual screening, and molecular docking were employed to identify potential therapeutic candidates. Subsequently, molecular dynamics (MD) simulations and free energy calculation of a leading candidate were conducted using GROMACS and gmxMMPBSA tool to assess the stability of the MLKL-inhibitor complex.

Our investigations identified 26 potential MLKL binders, with three compounds emerging as frontrunners on the basis of their favorable pharmacokinetic profiles, including high/low gastrointestinal absorption, optimal bioavailability, solubility, and non-hepatotoxicity. The MD simulations further corroborated the structural stability of the MLKL-drug complex.

The integrated computational approach adopted here could serve as a model for accelerating the discovery of drug candidates in other therapeutic areas as well. These findings necessitate further experimental validation before progressing to clinical trials.

Bermudagrass (Cynodon dactylon L.) simultaneously has three types of stems: shoots, stolons, and rhizomes, which lays the basis for the fast clonal growth of this important warm-season turfgrass species. However, the mechanisms underlying the differentiation, growth, and development of the three types of stems remain unclear.

In this study, the annotation information of the assembled bermudagrass genome was used to reanalyze the mass spectrometry raw data generated in the comparative proteomics analysis of bermudagrass shoots and stolons as well as stolons and rhizomes. One-way analysis of variance and the Student-Newman-Keuls test was performed to identify the Differentially Expressed Proteins (DEPs) in paired comparison of shoots versus stolons, shoots versus rhizomes, and stolons versus rhizomes.

A total of 3190 proteins were simultaneously expressed in the three types of stems, whereas 135, 1012, and 876 DEPs were identified between shoots and stolons, shoots and rhizomes, and stolons and rhizomes, respectively. Venn diagram analysis indicated that 23 DEPs were simultaneously identified in the three paired comparisons. Functional enrichment analysis indicated endocytosis and terpenoid backbone biosynthesis to be the most significantly DEP-enriched biochemical pathways among the three types of stems.

The results of this study not only provided new insights into the specialization of shoots, stolons, and rhizomes in bermudagrass, but also pointed out the importance of high-quality genome assembly and annotation in proteomics research.

In-silico study plays an important role in bioinformatics. It is a fast-expanding field to modelling, predicting and explaining biological activity at the molecular level using computational methods. Peroxidases are heme or non-heme-containing key antioxidant enzyme belonging to the oxidoreductase family. They can bioremediate the different environmental pollutants such as dioxins, petroleum hydrocarbons, synthetic dyes, herbicides, pesticides, chlorinated hydrocarbons, different phenolic and nonphenolic compounds etc. The current work aims to extend knowledge among researchers in better understanding structure of peroxidase purified from Raphanus sativus by analysing it’s physicochemical properties, secondary structure prediction, and 3D modelling of protein sequences and its validation using a variety of conventional computational methods.

Using bioinformatics techniques, it is feasible to figure out the relationship between sequence, structure, and function using enzyme protein sequences. To improve catalytic efficacy, thermostability, structure prediction, and validation, in-silico studies of the protein sequences of several industrially important enzymes have been performed recently.

The physical and chemical parameters of radish peroxidase was analysed by using protparam tool-Expasy. SOPMA, SWISS MODEL, PROCHECK, ERRAT and Verify3D tools were used for structural analysis and validation of peroxidase protein sequence of Raphanus Sativus. The Molecular Evolutionary Genetics Analysis (MEGA 11) tool was used to align the protein sequences automatically and manually using the query sequence and peroxidase from various plant sources. Interaction of Radish peroxidase with the different organic substrates like guaiacol, o-cresol, m-cresol, p-cresol, hydroquinone, catechol, resorcinol, benzaldehyde and aniline were analysed by molecular docking technique.

This research gave critical information regarding the properties and functioning of Raphanus sativus peroxidase. The computational molecular weight for the query protein sequence of radish peroxidase was found to be 37.503 KDa. The analysis of secondary structure prediction using SOPMA tool revealed that random coil (Cc) was present in the highest percentage as 39.18%. From the instability index (II) value and the aliphatic index value it was confirmed that the protein was slightly unstable but thermally stable in a wide range of temperature. The phylogenetic tree constructed by Molecular Evolutionary Genetics Analysis (MEGA 11) server revealed that the peroxidase and other plant peroxidases had been evolved from a common ancestor. Molecular docking analysis revealed that all the ligand had binding energy > -4.0 Kcal/mol. The interaction involved in the docking of radish peroxidase with selected ligands were conventional hydrogen bond, pi-cation, alkyl, pi-alkyl, pi-pi stacked, pi-sigma, carbon hydrogen bond, pi-lone pair.

In summary, these in-silico investigations provide a strong basis for carrying out wet-lab experiments to boost production, research for novel sources with a metagenomics strategy and attempt directed evolution to include desired functional features. From this study, we found the active site of the enzyme and the key amino acid residues that are used in the enzyme-ligand interaction. The novel information presented in this work will promote proteomics research and the development of novel bioinformatics techniques. The investigation of enzyme-ligand interactions will aid in the creation of a fresh approach to the synthesis of organic molecules.