A theoretical insight to understand the molecular mechanism of dual target ligand CTA-018 in the chronic kidney disease pathogenesis

The potential of Mitragyna speciosa leaves as a natural source of antioxidants for disease prevention

Mitragyna speciosa is famous for its addictive effect. On the other hand, this plant has good potential as an antioxidant agent, and so far, it was not explicitly explained what the most contributing compound in the leaves to that activity is. This study has been conducted using several computational methods to determine which compounds are the most active in interacting with cytochrome P450, myeloperoxidase, and NADPH oxidase proteins. First, virtual screening was carried out based on molecular docking, followed by profiling the properties of adsorption, distribution, metabolism, excretion, and toxicity (ADMET); the second one is the molecular dynamics (MD) simulations for 100 ns. The virtual screening results showed that three compounds acted as inhibitors for each protein: (-)-epicatechin, sitogluside, and corynoxeine. The ADMET profiles of the three compounds exhibit good drug ability and toxicity. The trajectories study from MD simulations predicts that the complexes of these three compounds with their respective target proteins are stable. Furthermore, these compounds identified in this computational study can be a potential guide for future experiments aimed at assessing the antioxidant properties through in vitro testing.

Mechanistic insights into the role of vitamin D and computational identification of potential lead compounds for Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder that affects dopaminergic neurons in the midbrain. A recent study suggests that Orphan Nuclear Receptor 1 (NURR1) impairment may contribute to PD pathogenesis. Our study found three potent agonists for NURR1 protein based on structural and ligand-based screening methods. The pharmacophore is comprised of a hydrogen bond donor, a hydrophobic group, and two aromatic rings (DHRR). The Pharmacophore screening method screened 3142 compounds, of which 3 were screened using structure-based screening. An analysis of the molecules using Molecular Mechanics-Generalized Born Surface Area (binding free energy) revealed a range of -46.77 to -59.06 Kcal/mol. After that, chemical reactivity was investigated by density functional theory, and molecular dynamics simulation was performed (protein-ligand stability). Based on the computational studies, Lifechemical_16901310, Maybridge_2815310, and NPACT_392450 are promising agonists with respect to NURR1. To confirm the potency of the identified compounds, further validation and experiments must be conducted.

Deciphering the importance of MD descriptors in designing Vitamin D Receptor agonists and antagonists using machine learning

The Vitamin D Receptor (VDR) ligand-binding domain undergoes conformation change upon the binding of VDR agonists/antagonists. Helix 12 ((H)12) is one of the important helices at VDR ligand binding and its conformational changes are controlled by the binding of agonists and antagonists molecules. Various molecular modeling studies are available to explain the agonistic and antagonistic activity of vitamin D analogs. In this work, for the first time, we attempted to generate a machine learning model with fingerprints, 2D, 3D and MD descriptors that are specific to Vitamin D analogs and VDR. Initially, 2D and 3D descriptors and fingerprints of 1003 vitamin D analogs were calculated using CDK and RDKit. The machine learning model was generated using descriptors and fingerprints. Further, 80 Vitamin D analogs (40 VDR agonists + 40 VDR antagonists) were docked in the VDR active site. 50ns MD simulation was performed for each protein-ligand complex. Different MD descriptors such as Solvent Accessible Surface Area (SASA), radius of gyration, PC1 and PC2 were calculated and considered along with CDK and RDKit descriptors as features for machine learning calculations. A few other descriptors that are related to VDR conformational changes such as conformation of the (H)12, the angle at kink were considered for machine learning model generation. It was observed that the descriptors calculated from VDR conformational changes i) were able to distinguish between agonists and antagonists ii) provide key and comprehensive information about the unique binding characteristics of agonists and antagonists iii) provide a strong basis for the machine learning model generation. Overall, this study attempts the utilization of descriptors that are specific to a protein conformation will be helpful for the generation of an efficient machine learning model.

Computational prediction of small molecules with predicted binding to FGFR3 and testing biological effects in bone cells

Activating anabolic receptor-mediated signaling is essential for stimulating new bone formation and for promoting bone healing in humans. Fibroblast growth factor receptor (FGFR) 3 is reported to be an important positive regulator of osteogenesis. Presently, recombinant proteins are used to stimulate FGFR3 function but have limitations for therapy due to expense and stability. Therefore, there is a need for identification of novel small molecules binding to FGFR3 that promote biological function. In silico molecular docking and high-throughput virtual screening on zinc database identified seven compounds predicted to bind to an active site within the βC'-βE loop, specific to FGFR3. All seven compounds fall within an acceptable range of ADME/T properties. Four compounds showed a 30-65% oral absorption rate. Density functional theory analysis revealed a high HOMO-LUMO gap, reflecting high molecular stability for compounds 14977614 and 13509082. Five compounds exhibited mutagenicity, while the other three compounds presented irritability. Computational mutagenesis predicted that mutating G322 affected compound binding to FGFR3. Molecular dynamics simulation revealed compound 14977614 is stable in binding to FGFR3. Furthermore, compound 14977614, with an oral absorption rate of 60% and high molecular stability, produced significant increases in both proliferation and differentiation of bone marrow stromal cells in vitro. Anti-FGFR3 treatment completely blocked the stimulatory effect of 14977614 on BMSC proliferation. Ex vivo treatment of mouse calvaria in organ culture for seven days with 14977614 increased mineralization and expression levels of bone formation markers. In conclusion, computational analyses identified seven compounds that bind to the FGFR3, and in vitro studies showed that compound 14977614 exerts significant biological effects on osteogenic cells.

TRAF2 and NCK-Interacting Kinase Inhibitors for Colorectal Cancer: In Vitro and Theoretical Validations

TRAF2 and NCK-interacting kinase (TNIK) is a critical factor in colorectal cancer (CRC) proliferation mediated by Wnt signaling. We attempted to identify efficient TNIK inhibitors using computational high-throughput virtual screening (HTVS) from various drug banks and databases. By performing/on performing e-pharmacophore screening and molecular docking methods, from ∼700 000 molecules, compounds LC_222150, LC_112060, and LC_64796 were identified as potential leads, through molecular dynamics (MD) simulations and density functional theory (DFT). These top 3 structures were commercially procured, and their inhibitory activity was assessed in vitro. Significant TNIK inhibition was observed, with an average IC₅₀ of 18.33 ± 0.75 nM. In terms of anticancer activity, the observed average relative % activity (RPA) of 90.28 ± 1.04 for these compounds compared well with doxorubicin (86.75 ± 1.45) as a standard. Compounds LC_222150, LC_112060, and LC_64796, therefore, warrant further evaluation in vivo to assess their CRC therapeutic effects.

Structure-Based Design of Novel Peptidomimetics Targeting the SARS-CoV-2 Spike Protein

Purpose

SARS-CoV-2 is a SARS-like novel coronavirus strain first identified in December 2019 in Wuhan, China. The virus has since spread globally, resulting in the current ongoing coronavirus disease 19 (COVID-19) pandemic. SARS-CoV-2 spike protein is a critical factor in the COVID-19 pathogenesis via interactions with the host cell angiotensin-converting enzyme 2 (ACE2) PD domain. Worldwide, numerous efforts are being made to combat COVID19. In the current study, we identified potential peptidomimetics against the SARS-CoV-2 spike protein.

Methods

We utilized the information from ACE2-SARS-CoV-2 binary interactions, and based on crucial interacting interface residues, novel peptidomimetics were designed.

Results

Top scoring peptidomimetics were found to bind at the ACE2 binding site of the receptor-binding domain (RBD) of SARS-CoV-2 spike protein.

Conclusions

The current studies could pave the way for further investigations of these novel and potent compounds against the SARS-CoV-2.

Therapeutic and Mechanistic Approaches of Tridax Procumbens Flavonoids for the Treatment of Osteoporosis

Homeostasis of bone is closely regulated by the balanced activities between the bone resorbing activity of osteoclast cells and bone-forming ability of osteoblast cells. Multinucleated osteoclasts degrade bone matrix and involve in the dynamic bone remodelling in coordination with osteoblasts. Disruption of this regulatory balance between these cells or any imbalance in bone remodelling caused by a higher rate of resorption over construction of bone results in a decrease of bone matrix including bone mineral density (BMD). These osteoclast-dominant effects result in a higher risk of bone crack and joint demolition in several bone-related diseases, including osteoporosis and rheumatoid arthritis (RA). Tridax procumbens is a very interesting perennial plant and its secondary metabolites called here T. procumbens flavonoids (TPFs) are well-known phytochemical agents owing to various therapeutic practices such as anti-inflammatory, anti-anaemic and anti-diabetic actions. This review designed to focus the systematic convention concerning the medicinal property and mechanism of actions of TPFs for the management of bone-related diseases. Based on the current literature, the review offers evidence-based information of TPFs for basic researchers and clinicians for the prevention and treatment of bone related diseases, including osteoporosis. It also emphasizes the medical significance for more research to comprehend the cellular signalling pathways of TPFs for the regulation of bone remodelling and discusses the possible promising ethnobotanical resource that can convey the preclinical and clinical clues to develop the next generation therapeutic agents for the treatment of bonerelated disorders.