Interaction landscape of a 'CαNN' motif with arsenate and arsenite: a potential peptide-based scavenger of arsenic

In Silico Insights into the Arsenic Binding Mechanism Deploying Application of Computational Biology-Based Toolsets

An assortment of environmental matrices includes arsenic (As) in its different oxidation states, which is often linked to concerns that pose a threat to public health worldwide. The current difficulty lies in addressing toxicological concerns and achieving sustained detoxification of As. Multiple conventional degradation methods are accessible; however, they are indeed labor-intensive, expensive, and reliant on prolonged laboratory evaluations. Molecular interaction and atomic level degradation mechanisms for enzyme-As exploration are, however, underexplored in those approaches. A feasible approach in this case for tackling this accompanying concern of As might be to cope with undertaking multivalent computational methodologies and tools. This work aimed to provide molecular-level insight into the enzyme-aided As degradation mechanism. AutoDock Vina, CABS-flex 2.0, and Desmond high-performance molecular dynamics simulation (MDS) were utilized in the current investigation to simulate multivalent molecular processes on two protein sets: arsenate reductase (ArsC) and laccase (LAC) corresponding arsenate (ART) and arsenite (AST), which served as model ligands to comprehend binding, conformational, and energy attributes. The structural configurations of both proteins exhibited variability in flexibility and structure framework within the range of 3.5-4.5 Å. The LAC-ART complex exhibited the lowest calculated binding affinity, measuring -5.82 ± 0.01 kcal/mol. Meanwhile, active site residues ILE-200 and HIS-206 were demonstrated to engage in H-bonding with the ART ligand. In contrast to ArsC, the ligand binding affinity of this bound complex was considerably greater. Additional validation of docked complexes was carried out by deploying Desmond MDS of 100 ns to capture protein and ligand conformation behavior. The system achieved stability during the 100 ns simulation run, as confirmed by the average P-L RMSD, which was ∼1 Å. As a preliminary test of the enzyme's ability to catalyze As species, corresponding computational insights might be advantageous for bridging gaps and regulatory consideration.

Trigonella foenum-graecum (fenugreek) differentially regulates antioxidant potential, photosynthetic, and metabolic activities under arsenic stress

Arsenic (As) contamination is continuously increasing in the groundwaters and soils around the world causing toxicity in the plants with a detrimental effect on physiology, growth, and yield. In a hydroponic system, thirty-day-old plants of Trigonella foenum-graecum were subjected to 0, 50, or 100 µM NaHAsO₄0.7 H₂O for 10 days. The magnitude of oxidative stress increased, whereas growth indices and photosynthetic parameters decreased in a dose-dependent manner. The efficiency of photosystem II in terms of Hill reaction activity (HRA) or chlorophyll-a was adversely affected by As stress. The antioxidant potential of plants regarding ferric reducing antioxidant power (FRAP) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) assays was enhanced, indicating the augmented resistance mechanism in plants to counter As stress. The metabolite analysis of leaf extracts revealed many As responsive metabolites including amino acids, organic acids, sugars/polyols, and others. Phenylalanine and citrulline were highly accumulated at 50 or 100 µM As, salicylic acid accumulated more at 50 µM of As while ascorbic acid notably increased at 100 µM of As. At 50 or 100 µM As, the glucose and fructose contents increased while the sucrose content decreased. At both As doses, tagatose and glucitol contents were 13 times higher than controls. Varied accumulation of metabolites could be associated with the different As doses that represent the range of tolerance in T. foenum-graecum towards As toxicity. Pathway analysis of metabolites revealed that amino acid and carbohydrate metabolism and the citrate cycle play important roles under As stress. This study helps in a better metabolomic understanding of the dose-dependent toxicity and response of As in T. foenum-graecum.

Role of sulfur in combating arsenic stress through upregulation of important proteins, and in-silico analysis to study the interaction between phosphate transporter (PHO1), arsenic and phosphate in spinach

An adequate amount of Sulfur (S) is essential for proper plant growth and defence against abiotic stresses including metals and metalloids. Arsenic (As) contamination is increasing in agricultural soils rapidly due to anthropogenic activities. Sulfur deficiency and arsenic stress could be more harmful than these individual stresses alone. To understand the impact of S-deficiency and arsenic (31 ppm Na₃AsO₄ of soil) on ecophysiology, growth, inorganic phosphate level, and proteomic profile of spinach, the present study was conducted. Interaction of arsenic with phosphate transporters, phytochelatins, and glutathione was also analyzed in silico. Comparative 2D MS/MS proteomics helped in the identification of important proteins which might be the key players under S-deficiency and As stress. Upregulation and downregulation of 36 and 21 proteins under As stress; 19 and 36 proteins under S-deficiency; 38 and 31 proteins under combined stress, respectively was observed. A total, 87 proteins subjected to identification via MS/MS ion search were found to be associated with important plant functions. PHO1 abundance was highly influenced by As stress; hence an in-silico homology modeling based molecular docking was performed which indicated high interaction between PHO1 and As/phosphate. Varied proximity of arsenic with phosphate transporters, phytochelatin, and glutathione revealed these components as a potential target of As toxicity/detoxification in Spinach, reflecting sulfur as an important criterion for arsenic tolerance.

New facets of larger Nest motifs in proteins

The Nest is a concave-shaped structural motif in proteins formed by consecutive enantiomeric left-handed (L) and right-handed (R) helical conformation of the backbone. This important motif subsumes many turn and helix capping structures and binds electron-rich ligands. Simple Nests are either RL or LR. Larger Nests (>2 residues long) may be RLR, LRL, RLRL, and so forth, being considered as composed of overlapping simple Nests. The larger Nests remain under-explored despite their widely known contributions to protein function. In our study, we address whether the recurrence of enantiomeric geometry in the larger Nests constrains the peptide backbone such that distinct compositional and conformational preferences are seen compared to simple Nests. Our analysis reveals the critical role of the L helical torsion angle in the formation of larger Nests. This can be observed through the higher propensity of residue or secondary structure combinations in LR and LRL backbone conformation in comparison to RL or RLR, although LR/LRL is considerably lower by occurrence. We also find that the most abundant doublets and triplets in Nests have a propensity for particular secondary structures, suggesting a strong sequence-structure relationship in the larger Nest. Overall, our analysis corroborates distinct features of simple and the larger Nests. Such insights would be helpful towards in-vitro design of peptides and peptidomimetic studies.

Design of a Peptide-Based Model Leads for Scavenging Anions

Among several peptide-based anion recognition motifs, the "CαNN" motif containing C-1 α, N0, and N+1 of three consecutive residues is unique in its mode of interaction. Having a spatial geometry of βαα or βαβ, this motif occurs in the N terminus of a helix and often found at the functional interface of a protein, mediating crucial biological significance upon interaction with anion(s). The interaction of anion(s) with chimeric peptide sequences containing the naturally occurring "CαNN" motif (CPS224Ac, CPS226, and CPS228) reported in our previous attempts strongly confirms that the information regarding the interaction is embedded within the local sequences of the motif segment. At these prevailing circumstances, an effort has been pursued to design novel scaffolds based on the "CαNN" motif for achieving better recognition of anion(s). Exploring the existing data set of the "CαNN" motif available in the FSSP database, four novel peptide-based scaffolds have been designed (DS1, DS2, DS3, and DS4), and preliminary screenings have been performed using computational approaches. Our initial work suggests that two (DS1 and DS3) out of the four scaffolds are potential candidates for better anion recognition. By employing biophysical characterization using both qualitative and quantitative measures, in this present study, we report the interaction of sulfate and phosphate ions with these two designed scaffolds, in which there is much better recognition of anions by these scaffolds than the natural sequences, justifying their logical engineering. Our observation strongly suggests that these designed scaffolds are better potential candidates than those of the naturally occurring "CαNN" motif in terms of anion recognition and could be utilized for the scavenging of anion(s) for different purposes.