Discovery of potential TAAR1 agonist targeting neurological and psychiatric disorders: An in silico approach

Trace amine-associated receptor 1 (TAAR1) is a G-protein-coupled receptor which is primarily expressed in the brain. It is activated by trace amines which play a role in regulating neurotransmitters like dopamine, serotonin and norepinephrine. TAAR1 agonists have potential applications in the treatment of neurological and psychiatric disorders, especially schizophrenia. In this study, we have used a structure-based virtual screening approach to identify potential TAAR1 agonist(s). We have modelled the structure of TAAR1 and predicted the binding pocket. Further, molecular docking of a few well-known antipsychotic drugs was carried out with TAAR1 model, which showed key interactions with the binding pocket. From screening a library of 5 million compounds from the Enamine REAL Database using structure-based virtual screening method, we shortlisted 12 compounds which showed good docking score, glide energy and interactions with the key residues. One lead compound (Z31378290) was finally selected. The lead compound showed promising binding affinity and stable interactions with TAAR1 during molecular dynamics simulations and demonstrated better van der Waals and binding energy than the known agonist, ulotaront. Our findings suggest that the lead compound may serve as a potential TAAR1 agonist, offering a promising avenue for the development of new therapies for neurological and psychiatric disorders.

Identification of a novel drug molecule for neurodegenerative disease from marine algae through in-silico analysis

Cognitive functions are lost due to the rapid hydrolysis of acetylcholine including Acetylcholinesterase (AChE) and Butyrylcholinesterase (BChE). Marine algae-derived compounds were reported for their neuroprotective activities and hence they can be utilised for treating neurodegenerative ailments like Alzheimer's Disease and Parkinson's Disease which are due to the loss of cognitive functions. Major attention is currently paid to seaweeds due to their health benefits and high nutritional values. Sea weeds are of a rich sense of natural bioactive compounds which antioxidants, pharmaceutical compounds, flavonoids and alkaloids. They also contain a high amount of vitamins A, D, E, C and Ca, K, Mg and Fe. Regular consumption of a marine algae-based diet may boost immunities. In searching for natural cholinesterase inhibitors, the present study is focussed on some marine bioactive compounds reported from brown, red and green algae. Molecular docking studies have been carried out along with molecular dynamics simulations studies and binding energy calculations resulting in three best bioactive compounds when AChE is used as the target. The results are compared with cocrystal studies. Two best compounds, namely, Diphlorethohydroxycarmalol and Phlorofucofuroeckol from the brown seaweeds are identified as the potential lead compounds for neurodegenerative diseases, Alzheimer's and Parkinson's.Communicated by Ramaswamy H. Sarma.

Evaluation of action of steroid molecules on SARS-CoV-2 by inhibiting NSP-15, an endoribonuclease

Many countries in the world have recently experienced an outbreak of COVID-19, turned out to be a pandemic which significantly affected the world economy. Among many attempts to treat/control infection or to modulate host immunity, many small molecules including steroids were prescribed based on their use against other viral infection or inflammatory conditions. A recent report established the possibility of usage of a corticosteroid against the virus through inhibiting NSP-15; an mRNA endonuclease of SARS-CoV-2 and thereby viral replication. This study aimed to identify potential anti-viral agents for the virus through computational approaches and to validate binding properties with the protein target through molecular dynamics simulation. Unlike the conventional approaches, dedicated data base of steroid like compounds was used for initial screening along with dexamethasone and cortisone, which are used in the treatment of COVID-19 affected population in some countries. Molecular docking was performed for three compounds filtered from data base in addition to dexamethasone and Cortisone followed by molecular dynamics simulation analysis to validate the dynamics of binding at the active site. In addition, analysis of ADME properties established that these compounds have favorable drug-like properties. Based on docking, molecular dynamics simulation studies and various other trajectory analyses, compounds that are identified could be suggested as therapeutics or precursors towards designing new anti-viral agents against SARS-CoV-2, to combat COVID-19. Also, this is an attempt to study the impact of steroid compounds on NSP-15 of SARS-CoV-2, since many steroid like compounds are used during the treatment of COVID-19 patients.

Orphan receptor GPR88 as a potential therapeutic target for CNS disorders - an in silico approach

The G-protein-coupled receptors are a part of the largest and most physiologically relevant family of membrane proteins. One-third of the medications, now on the market, target the GPCR receptor family, which is one of the most important therapeutic targets for many disorders. In the reported work, we have focussed on orphan GPR88 receptor which is a part of the GPCR protein family and a potential target for central nervous system disorders. GPR88 is known to show the highest expression in the striatum, which is a key region in motor control and cognitive functions. Recent studies have reported that GPR88 is activated by two agonists, 2-PCCA and RTI-13951-33. In this study, we have predicted the three-dimensional protein structure for the orphan GPR88 using the homology modeling approach. We then used shape-based screening techniques based on known agonists and structure-based virtual screening methods employing docking to uncover novel GPR88 ligands. The screened GPR88-ligand complexes were further subjected to molecular dynamics simulation studies. The selected ligands could fasten the development of novel treatments for the vast list of movement and central nervous system disorders.Communicated by Ramaswamy H. Sarma.

Structure-based pharmacophore modeling, virtual screening approaches to identifying the potent hepatitis C viral protease and polymerase novel inhibitors

Hepatitis C is an infectious disease that leads to acute and chronic liver illnesses. Currently, there are no effective vaccines against this deadly virus. Direct acting antiviral (DAA) drugs are given in the combination with ribavirin and pegylated interferon which lead to adverse effects. Through in silico analysis, the structure-based docking study was performed against NS3/4A protease and NS5B polymerase proteins of HCV. In the current study, multiple e-pharmacophore-based virtual screening methods such as HTVS, SP, and XP were carried out to screen natural compounds and enamine databases. Our result outcomes revealed that CID AE-848/13196185 and CID AE-848/36959205 compounds show good binding interactions with protease protein. In addition, CID 15081408 and CID 173568 show better binding interactions with the polymerase protein. Further to validate the docking results, we performed molecular dynamics simulation for the top hit compounds bound with protease and polymerase proteins to illustrate conformational differences in the stability compared with the active site of the cocrystal inhibitor. Thus, the current study emphasizes these compounds could be an effective drug to treat HCV.

Identification of a Chlorogenic Ester as a Monoamine Oxidase (MAO-B) Inhibitor by Integrating "Traditional and Machine Learning" Virtual Screening and In Vitro as well as In Vivo Validation: A Lead against Neurodegenerative Disorders?

Parkinson's disease (PD) is the furthermost motor disorder of adult-onset dementia connected to memory and other cognitive abilities. Monoamine oxidases (MAOs) have gained significant attention in recent years owing to their possible therapeutic use against PD. Expression of MAO-B has been found to be elevated in PD patients for increased uptake of dopamine, producing hydrogen peroxide and finally causing neuronal injury. In this work, two new compounds have been identified as leads against MAO-B, and one of those compounds has been validated in vitro and in vivo. From the Protein Data Bank, MAO-B protein structures complexed with selegiline, 6-hydroxy-N-propargyl-1(R)-aminoindan, or a chromen derivative have been selected as templates for shape-based virtual screening (SB-VS) against the Traditional Chinese Medicinal (TCM) natural database. In parallel, using machine learning, a molecular-descriptor-based support vector model (SVM) was prepared and screened. For this purpose, naïve Bayesian, logistic regression, and random forest strategies were employed with the best specific molecular descriptor, which yielded a model with an overall accuracy (Q) of 0.81. Two common hit compounds lead-1 and lead-2 resulting from both shape and SVM screenings were analyzed through molecular docking and molecular dynamics (MD) simulation (200 ns). Also, from trajectory analysis such as molecular mechanics generalized Born surface area (MMGB/SA) and the residual interaction network (RIN) analyzer, both leads were found to bind at the active site with a favorable correlated motion, including domain movements. Lead-2, which is a chlorogenic ester, was synthesized and found to have no cytotoxic effect up to 50 μg/mL on Neuro-2A cells. The significant reactive oxygen species (ROS) scavenging activity by lead-2 could be correlated to its neuroprotective efficacy. Its capacity to inhibit human MAO-B through a competitive mode could be observed. An experimental zebra fish model confirms the neuroprotection by lead-2 by assessing the locomotor activities under malathion influence and treatment of lead-2. Also, histopathology analysis revealed that lead-2 could slow down degeneration in the brain. The present study emphasizes that integrating machine learning in parallel with traditional virtual screening may be useful to identify effective lead compounds for a given target.

Screening of potential drug for Alzheimer's disease: a computational study with GSK-3 β inhibition through virtual screening, docking, and molecular dynamics simulation

The global impact of Alzheimer's disease (AD) necessitates intensive research to find appropriate and effective drugs. Many studies in AD suggested beta-amyloid plaques and neurofibrillary tangles-associated tau protein as the key targets for drug development. On the other hand, it is proved that triggering of Glycogen Synthase Kinase-3β (GSK-3β) also cause AD, therefore, GSK-3β is a potential drug target to combat AD. We, in this study, investigated the ability of small molecules to inhibit GSK-3β through virtual screening, Absorption, Distribution, Metabolism, and Excretion (ADME), induced-fit docking (IFD), molecular dynamics simulation, and binding free energy calculation. Besides, molecular docking was performed to reveal the binding and interaction of the ligand at the active site of GSK-3β. We found two compounds such as 6961 and 6966, which exhibited steady-state interaction with GSK-3β for 30 ns in molecular dynamics simulation. The compounds (6961 and 6966) also achieved a docking score of -9.05 kcal/mol and -8.11 kcal/mol, respectively, which is relatively higher than the GSK-3β II inhibitor (-6.73 kcal/mol). The molecular dynamics simulation revealed that the compounds have a stable state during overall simulation time, and lesser root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) values compared with co-crystal. In conclusion, we suggest the two compounds (6966 and 6961) as potential leads that could be utilized as effective inhibitors of GSK-3β to combat AD.

Identification of new BACE1 inhibitors using Pharmacophore and Molecular dynamics simulations approach

Inhibition of β-Secretase (BACE1) is crucial for the treatment of Alzheimer's disease (AD). Availability of BACE1 crystal structures in both apo and complexed forms enables to find structure-based BACE1 inhibitors for controlling AD. There are two catalytic aspartates (ASP32 and ASP228) presents in the active domain of BACE1. In order to understand the binding mechanism and structure-activity relationship of amidine-containing BACE1 inhibitors, molecular docking, and pharmacophore and 3D-QSAR studies have been carried out with 34 amidine derivatives to develop a pharmacophore model. Pharmacophore-based virtual screening (PBVS) has been performed against BACE1 (PDB ID: 2FDP), using three chemical databases (CoCoCo, Enamine, Zinc), which yielded 6000 hit compounds. These compounds were further analyzed using structure-based docking in hierarchical filtering approaches of Glide such as HTVS, SP, and XP precision modes. The docking results show that binding orientations of the inhibitors at Asp dyad active site amino acid residues of β-Secretase. Results from glide XP docking and induced fit docking showed that four leads (Lead1, Lead3, Lead4 and Lead5) have good interactions with the target protein in comparison with cocrystal (amino-ethylene BACE1 inhibitor). Further, molecular dynamics (MD) simulation for these leads bound with BACE1 shows conformational stability and difference in dynamical flap behaviors of the active site with cocrystal inhibitor. Binding free energetic using MM-GB/SA approaches suggest lead 1 and lead 3 has comparably favorable binding to cocrystal inhibitor. Thus, the present study emphasizes these leads for an effective drug to treat Alzheimer disease.