A quinoline alkaloid potentially modulates the amyloidogenic structural transitions of the biofilm scaffolding small basic protein

Prediction of interface between regions of varying degrees of order or disorderness in intrinsically disordered proteins from dihedral angles

Intrinsically disordered proteins (IDPs) are proteins that do not form uniquely defined three-dimensional (3-D) structures. Experimental research on IDPs is difficult since they go against the traditional protein structure-function paradigm. Although there are several predictors of disorder based on amino acid sequences, but very limited based on the 3-D structures of proteins. Dihedral angles have a significant role in predicting protein structure because they establish a protein's backbone, which, coupled with its side chain, establishes its overall shape. Here, we have carried out atomistic Molecular Dynamics (MD) simulations on four different proteins: one ordered protein (Monellin), two partially disordered proteins (p53-TAD and Amyloid beta (Aβ1-42) peptide), and one completely disordered protein (Histatin 5). The MD simulation trajectories for the corresponding four proteins were used to conduct dihedral angle (ϕ and ѱ) analysis. Then, the average dihedral angles for each of the residues were calculated and plotted against the residue index. We noticed steep rises or falls in the average ϕ value at certain locations in the plot. These sudden shifts in the average ϕ value reflect the interface between regions of varying degrees of order or disorderness in intrinsically disordered proteins. Using this method, the probable conformer of a protein with a higher degree of disorder can be found among the ensembles of structures sampled during the MD simulations. The results of our study offer new understandings on precisely identifying regions of various degrees of disorder in intrinsically disordered proteins.Communicated by Ramaswamy H. Sarma.

The identification of cianidanol as a selective estrogen receptor beta agonist and evaluation of its neuroprotective effects on Parkinson's disease models

AIM

The present study aims to identify selective estrogen receptor beta (ERβ) agonists and to evaluate the neuroprotective mechanism in Parkinson's disease (PD) models.

MAIN METHODS

In-silico studies were carried out using Maestro and GROMACS. Neuroprotective activity and apoptosis were evaluated using cytotoxicity assay and flow cytometry respectively. Gene expression studies were carried out by reverse transcription polymerase chain reaction. Motor and cognitive functions were assessed by actophotometer, rotarod, catalepsy, and elevated plus maze. The neuronal population in the substantia nigra and striatum of rats was assessed by hematoxylin and eosin staining.

KEY FINDINGS

Cianidanol was identified as a selective ERβ agonist through virtual screening. The cianidanol-ERβ complex is stable during the 200 ns simulation and was able to retain the interactions with key amino acid residues. Cianidanol (25 μM) prevents neuronal toxicity and apoptosis induced by rotenone in differentiated SH-SY5Y cells. Additionally, cianidanol (25 μM) increases the expression of ERβ, cathepsin D, and Nrf2 transcripts. The neuroprotective effects of cianidanol (25 μM) were reversed in the presence of a selective ERβ antagonist. In this study, we found that selective activation of ERβ could decrease the transcription of α-synuclein gene. Additionally, cianidanol (10, 20, 30 mg/kg, oral) improves the motor and cognitive deficit in rats induced by rotenone.

SIGNIFICANCE

Cianidanol shows neuroprotective action in PD models and has the potential to serve as a novel therapeutic agent for the treatment of PD.

Side effects based network construction and drug repositioning of ropinirole as a potential molecule for Alzheimer's disease: an in-silico, in-vitro, and in-vivo study

Alzheimer's disease (AD) is the leading cause of dementia in older adults. Drug repositioning is a process of finding new therapeutic applications for existing drugs. One of the methods in drug repositioning is to use the side-effect profile of a drug to identify a new therapeutic indication. The drugs with similar side-effects may act on similar biological targets and could affect the same biochemical process. In this study, we explored the Food and Drug Administration-approved drugs using PROMISCUOUS database to find those that have adverse effects profile comparable with the ligands being studied or used to treat AD. Here, we found that the ropinirole, a dopamine receptor agonist, shared a maximum number of side-effects with the drugs proven beneficial for treating AD. Furthermore, molecular modelling demonstrated that ropinirole exhibited strong binding affinity (-9.313 kcal/mol) and best ligand efficiency (0.49) with sigma-1 receptor. Here, we observed that the quaternary amino group of ropinirole is essential for binding with sigma-1 receptor. Molecular dynamic simulation indicated that the movement of the carboxy-terminal helices (α4/α5) could play a major role in the receptor's physiological functions. The neurotoxicity induced by Aβ25-35 in SH-SY5Y cells was reduced by ropinirole at concentrations 10, 30, and 50 µM. The effect on spatial learning and memory was examined in mice with Aβ25-35 induced memory deficit using the radial arm maze. Ropinirole (10 and 20 mg/kg) significantly improved the short and long-term memories in the radial arm maze test. Our results suggest that ropinirole has the potential to be repositioned for AD treatment.Communicated by Ramaswamy H. Sarma.

Computational approaches screening DNA aptamers against conserved outer membrane protein W of Vibrio cholerae O1- an investigation expanding the potential for point-of-care detection with aptasensors

Foodborne outbreaks urge public health domain to upgrade diagnosis by means of simpler, quicker, and more affordable pathogen detection methods. A molecular recognition probe against an analyte of interest makes up a biosensor, along with a method for turning the recognition event into a quantifiable signal. Single-stranded DNA or RNA aptamers are promising bio-recognition molecules for a range of targets, including a wide range of non-nucleic acid targets with which they are highly specific and affine. In the proposed study, 40 DNA aptamers were screened and analyzed interactions using in-silico SELEX procedures, which can selectively interact with active sites at the extracellular region of the Outer membrane Protein W (OmpW) of Vibrio Cholerae. Multiple modeling techniques, like protein structural prediction with I-TASSER, aptamer structural modeling using M-fold, RNA composer, protein-DNA docking using HADDOCK, and large-scale (500 ns) molecular dynamics simulations through GROMACS have been employed. Out of 40, six aptamers having lowest free energy were docked against the predicted active site at the extracellular region of OmpW. VBAPT4-OmpW and VBAPT17-OmpW, the two highest-scoring Aptamer-Protein complexes, were chosen for molecular dynamics simulations. VBAPT4-OmpW is quite unable to attain its structural local minima after 500 ns. But VBAPT17-OmpW is showing great stability and is not destructive even after 500 ns. RMSF, DSSP, PCA, and Essential Dynamics all provided additional confirmation. Current findings, combined with the fabrication of biosensor devices, could pave the way for an innovative pathogen detection platform with high sensitivity, along with an effective and low-impact curative strategy for corresponding diseases.Communicated by Ramaswamy H. Sarma.