Identification of the Candidate mGlu2 Allosteric Modulator THRX-195518 through In Silico Method and Evaluation of Its Neuroprotective Potential against Glutamate-Induced Neurotoxicity in SH-SY5Y Cell Line.

Glutamate (Glu) toxicity has been an important research topic in toxicology and neuroscience studies. In vitro and in vivo studies have shown that Group II metabotropic Glu2 (mGlu2) activators have cell viability effects. This study aims to determine a candidate ligand with high mGlu2 allosteric region activity among cytotoxicity-safe molecules using the in silico positioning method and to evaluate its cell viability effect in vitro. We investigated the candidate molecule's cell viability effect on the SH-SY5Y human neuroblastoma cell line by MTT analysis. In the study, LY 379268 (agonist) and JNJ-46281222 (positive allosteric modulator; PAM) were used as control reference molecules. Drug bank screening yielded THRX-195518 (docking score being -12.4 kcal/mol) as a potential novel drug candidate that has a high docking score and has not been mentioned in the literature so far. The orthosteric agonist LY 379268 exhibited a robust protective effect in our study. Additionally, our findings demonstrate that JNJ-46281222 and THRX-195518, identified as activating the mGlu2 allosteric region through in silico methods, preserve cell viability against Glu toxicity. Therefore, our study not only emphasizes the positive effects of this compound on cell viability against Glu toxicity but also sheds light on the potential of THRX-195518, acting as a mGlu2 PAM, based on in silico absorption, distribution, metabolism, excretion, and toxicity (ADMET) data, as a candidate drug molecule. These findings underscore the potential utility of THRX-195518 against both neurotoxicity and Central Nervous System (CNS) disorders, providing valuable insights.

Queuine as a potential multi-target drug for alzheimer's disease: insights from protein dynamics.

Alzheimer's disease (AD) is a neurodegenerative disorder with a complex pathogenesis. One promising approach to treating AD is simultaneously targeting multiple aspects of the disease using a multi-target drug (MTD). In this study, multi-target drug (MTD) potential of the nutraceutical molecule Queuine was explored using molecular docking and molecular dynamics (MD) simulations with five different protein targets engaged in AD: AChE, beta-site amyloid precursor protein cleaving enzyme-1 (BACE-1), N-methyl-D-aspartate receptor (NMDAR), monoamine oxidase A (MAO-A), and Synapsin III. Queuine revealed significant binding affinities, the docking scores being -10.1, -5.97, -5.63, -8.40, and -10.56 kcal/mol for AChE, BACE-1, NMDAR, MAO-A, and Synapsin III, respectively. MD simulations showed that Queuine formed stable complexes and preserved its stability throughout the simulation, the backbone fluctuations remaining within 2.5 Å specifically in the case of the BACE-1. Elastic network model simulations and principal component analysis were carried out to illustrate the dynamics of the protein systems. Significant hinge-bending and twisting-type motions that may be relevant to function were observed around the dimerization interfaces or binding sites. Structural clustering based on PCA analysis and cross-correlation maps demonstrated that Queuine binding altered the protein dynamics more drastically in the case of highly mobile proteins NMDAR and MAO-A. We propose that the neuroprotective effect of Queuine may stem from its prominent inhibitory action on enzymes BACE-1 and AChE. Our results suggest that Queuine may serve as a promising MTD candidate for the treatment of AD.Communicated by Ramaswamy H. Sarma.

Proposing novel natural compounds against Alzheimer's disease targeting acetylcholinesterase.

Alzheimer's disease (AD) is a neurodegenerative disorder considered as a global public health threat influencing many people. Despite the concerning rise in the affected population, there is still a shortage of potent and safe therapeutic agents. The aim of this research is to discover novel natural source molecules with high therapeutic effects, stability and less toxicity for the treatment of AD, specifically targeting acetylcholinesterase (AChE). This research can be divided into two steps: in silico search for molecules by systematic simulations and in vitro experimental validations. We identified five leading compounds, namely Queuine, Etoperidone, Thiamine, Ademetionine and Tetrahydrofolic acid by screening natural molecule database, conducting molecular docking and druggability evaluations. Stability of the complexes were investigated by Molecular Dynamics simulations and free energy calculations were conducted by Molecular Mechanics Generalized Born Surface Area method. All five complexes were stable within the binding catalytic site (CAS) of AChE, with the exception of Queuine which remains stable on the peripheral site (PAS). On the other hand Etoperidone both interacts with CAS and PAS sites showing dual binding properties. Binding free energy values of Queuine and Etoperidone were -71.9 and -91.0 kcal/mol respectively, being comparable to control molecules Galantamine (-71.3 kcal/mol) and Donepezil (-80.9 kcal/mol). Computational results were validated through in vitro experiments using the SH-SY5Y(neuroblastoma) cell line with Real Time Cell Analysis (RTCA) and cell viability assays. The results showed that the selected doses were effective with half inhibitory concentrations estimated to be: Queuine (IC50 = 70,90 µM), Etoperidone (IC50 = 712,80 µM), Thiamine (IC50 = 18780,34 µM), Galantamine (IC50 = 556,01 µM) and Donepezil (IC50 = 222,23 µM), respectively. The promising results for these molecules suggest the development of the next step in vivo animal testing and provide hope for natural therapeutic aids in the treatment of AD.

Features of large hinge-bending conformational transitions. Prediction of closed structure from open state.

We performed a detailed analysis of conformational transition pathways for a set of 10 proteins, which undergo large hinge-bending-type motions with 4-12 Å RMSD (root mean-square distance) between open and closed crystal structures. Anisotropic network model-Monte Carlo (ANM-MC) algorithm generates a targeted pathway between two conformations, where the collective modes from the ANM are used for deformation at each iteration and the conformational energy of the deformed structure is minimized via an MC algorithm. The target structure was approached successfully with an RMSD of 0.9-4.1 Å when a relatively low cutoff radius of 10 Å was used in ANM. Even though one predominant mode (first or second) directed the open-to-closed conformational transition, changes in the dominant mode character were observed for most cases along the transition. By imposing radius of gyration constraint during mode selection, it was possible to predict the closed structure for eight out of 10 proteins (with initial 4.1-7.1 Å and final 1.7-2.9 Å RMSD to target). Deforming along a single mode leads to most successful predictions. Based on the previously reported free energy surface of adenylate kinase, deformations along the first mode produced an energetically favorable path, which was interestingly facilitated by a change in mode shape (resembling second and third modes) at key points. Pathway intermediates are provided in our database of conformational transitions (http://safir.prc.boun.edu.tr/anmmc/method/1).

Conformational transition pathways explored by Monte Carlo simulation integrated with collective modes.

Conformational transitions between open/closed or free/bound states in proteins possess functional importance. We propose a technique in which the collective modes obtained from an anisotropic network model (ANM) are used in conjunction with a Monte Carlo (MC) simulation approach, to investigate conformational transition pathways and pathway intermediates. The ANM-MC technique is applied to adenylate kinase (AK) and hemoglobin. The iterative method, in which normal modes are continuously updated during the simulation, proves successful in accomplishing the transition between open-closed conformations of AK and tense-relaxed forms of hemoglobin (C(alpha)-root mean square deviations between two end structures of 7.13 A and 3.55 A, respectively). Target conformations are reached by root mean-square deviations of 2.27 A and 1.90 A for AK and hemoglobin, respectively. The intermediate conformations overlap with crystal structures from the AK family within a 3.0-A root mean-square deviation. In the case of hemoglobin, the transition of tense-to-relaxed passes through the relaxed state. In both cases, the lowest-frequency modes are effective during transitions. The targeted Monte Carlo approach is used without the application of collective modes. Both the ANM-MC and targeted Monte Carlo techniques can explore sequences of events in transition pathways with an efficient yet realistic conformational search.