Long-range replica exchange molecular dynamics guided drug repurposing against tyrosine kinase PtkA of Mycobacterium tuberculosis

p-Hydroxy benzaldehyde, a phenolic compound from Nostoc commune, ameliorates DSS-induced colitis against oxidative stress via the Nrf2/HO-1/NQO-1/NF-κB/AP-1 pathway

BACKGROUND

Ulcerative colitis (UC), a chronic idiopathic inflammatory bowel disease (IBD), presents with limited current drug treatment options. Consequently, the search for safe and effective drug for UC prevention and treatment is imperative. Our prior studies have demonstrated that the phenolic compound p-Hydroxybenzaldehyde (HD) from Nostoc commune, effectively mitigates intestinal inflammation. However, the mechanisms underlying HD's anti-inflammatory effects remain unclear.

PURPOSE

This study delved into the pharmacodynamics of HD and its underlying anti-inflammation mechanisms.

METHODS

For in vivo experiments, dextran sodium sulfate (DSS)-induced colitis mouse model was established. In vitro inflammation model was established using lipopolysaccharide (LPS)-induced RAW264.7 and bone marrow-derived macrophages (BMDMs). The protective effect of HD against colitis was determined by monitoring clinical symptoms and histological morphology in mice. The levels of inflammatory factors and oxidative stress markers were subsequently analyzed with enzyme-linked immunosorbent assay (ELISA) and biochemical kits. Furthermore, western blotting (WB), immunofluorescence (IF), luciferase reporter gene, drug affinity reaction target stability (DARTS) assay, molecular docking, and molecular dynamics (MD) simulation were used to determine the potential target and molecular mechanism of HD.

RESULTS

Our findings indicate that HD significantly alleviated the clinical symptoms and histological morphology of colitis in mice, and curtailed the production of pro-inflammatory cytokines, including TNF-α, IL-6, IFN-γ, COX-2, and iNOS. Furthermore, HD stimulated the production of SOD, CAT, and GSH-px, enhanced total antioxidant capacity (T-AOC), and reduced MDA levels. Mechanically, HD augmented the expression of Nrf2, HO-1, and NQO-1, while concurrently downregulating the phosphorylation of p65, IκBα, c-Jun, and c-Fos. ML385 and siNrf2 largely attenuated the protective effect of HD in enteritis mice and RAW 264.7 cells, as well as the promotion of HO-1 expression levels. ZnPP-mediated HO-1 knockdown reversed HD-induced inhibition of colonic inflammation. Luciferase reporter assay and IF assay confirmed the transcriptional activation of Nrf2 by HD. DARTS analysis, molecular docking, and MD results showed high binding strength, interaction efficiency and remarkable stability between Nrf2 and HD.

CONCLUSION

These outcomes extend our previous research results that HD can combat oxidative stress through the Nrf2/HO-1/NQO-1/NF-κB/AP-1 pathways, effectively alleviating colitis, and propose new targets for HD to protect against intestinal barrier damage.

Discovery of putative inhibitors of human Pkd1 enzyme: Molecular docking, dynamics and simulation, QSAR, and MM/GBSA

Polycystic kidney disease is the most prevalent hereditary kidney disease globally and is mainly linked to the overexpression of a gene called PKD1. To date, there is no effective treatment available for polycystic kidney disease, and the practicing treatments only provide symptomatic relief. Discovery of the compounds targeting the PKD1 gene by inhibiting its expression under the disease condition could be crucial for effective drug development. In this study, a molecular docking and molecular dynamic simulation, QSAR, and MM/GBSA-based approaches were used to determine the putative inhibitors of the Pkd1 enzyme from a library of 1379 compounds. Initially, fourteen compounds were selected based on their binding affinities with the Pkd1 enzyme using MOE and AutoDock tools. The selected drugs were further investigated to explore their properties as drug candidates and the stability of their complex formation with the Pkd1 enzyme. Based on the physicochemical and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties, and toxicity profiling, two compounds including olsalazine and diosmetin were selected for the downstream analysis as they demonstrated the best drug-likeness properties and highest binding affinity with Pkd1 in the docking experiment. Molecular dynamic simulation using Gromacs further confirmed the stability of olsalazine and diosmetin complexes with Pkd1 and establishing interaction through strong bonding with specific residues of protein. High biological activity and binding free energies of two complexes calculated using 3D QSAR and Schrodinger module, respectively further validated our results. Therefore, the molecular docking and dynamics simulation-based in-silico approach used in this study revealed olsalazine and diosmetin as potential drug candidates to combat polycystic kidney disease by targeting Pkd1 enzyme.

Inhibition of the Janus kinase protein (JAK1) by the A. Pyrethrum Root Extract for the treatment of Vitiligo pathology. Design, Molecular Docking, ADME-Tox, MD Simulation, and in-silico investigation

This study delves into the therapeutic efficacy of A. pyrethrum in addressing vitiligo, a chronic inflammatory disorder known for inducing psychological distress and elevating susceptibility to autoimmune diseases. Notably, JAK inhibitors have emerged as promising candidates for treating immune dermatoses, including vitiligo. Our investigation primarily focuses on the anti-vitiligo potential of A. pyrethrum root extract, specifically targeting N-alkyl-amides, utilizing computational methodologies. Density Functional Theory (DFT) is deployed to meticulously scrutinize molecular properties, while comprehensive evaluations of ADME-Tox properties for each molecule contribute to a nuanced understanding of their therapeutic viability, showcasing remarkable drug-like characteristics. Molecular docking analysis probes ligand interactions with pivotal site JAK1, with all compounds demonstrating significant interactions; notably, molecule 6 exhibits the most interactions with crucial inhibition residues. Molecular dynamics simulations over 500ns further validate the importance and sustainability of these interactions observed in molecular docking, favoring energetically both molecules 6 and 1; however, in terms of stability, the complex with molecule 6 outperforms others. DFT analyses elucidate the distribution of electron-rich oxygen atoms and electron-poor regions within heteroatoms-linked hydrogens. Remarkably, N-alkyl-amides extracted from A. pyrethrum roots exhibit similar compositions, yielding comparable DFT and Electrostatic Potential (ESP) results with subtle distinctions. These findings underscore the considerable potential of A. pyrethrum root extracts as a natural remedy for vitiligo.

Modulators targeting protein-protein interactions in Mycobacterium tuberculosis

Tuberculosis (TB) is a chronic infectious disease caused by Mycobacterium tuberculosis (M. tuberculosis), mainly transmitted through droplets to infect the lungs, and seriously affecting patients' health and quality of life. Clinically, anti-TB drugs often entail side effects and lack efficacy against resistant strains. Thus, the exploration and development of novel targeted anti-TB medications are imperative. Currently, protein-protein interactions (PPIs) offer novel avenues for anti-TB drug development, and the study of targeted modulators of PPIs in M. tuberculosis has become a prominent research focus. Furthermore, a comprehensive PPI network has been constructed using computational methods and bioinformatics tools. This network allows for a more in-depth analysis of the structural biology of PPIs and furnishes essential insights for the development of targeted small-molecule modulators. Furthermore, this article provides a detailed overview of the research progress and regulatory mechanisms of PPI modulators in M. tuberculosis, the causative agent of TB. Additionally, it summarizes potential targets for anti-TB drugs and discusses the prospects of existing PPI modulators.

Illuminating ligand-induced dynamics in nuclear receptors through MD simulations

Nuclear receptors (NRs) regulate gene expression in critical physiological processes, with their functionality finely tuned by ligand-induced conformational changes. While NRs may sometimes undergo significant conformational motions in response to ligand-binding, these effects are more commonly subtle and challenging to study by traditional structural or biophysical methods. Molecular dynamics (MD) simulations are a powerful tool to bridge the gap between static protein-ligand structures and dynamical changes that govern NR function. Here, we summarize a handful of recent studies that apply MD simulations to study NRs. We present diverse methodologies for analyzing simulation data with a detailed examination of the information each method can yield. By delving into the strengths, limitations and unique contributions of these tools, this review provides guidance for extracting meaningful data from MD simulations to advance the goal of understanding the intricate mechanisms by which ligands orchestrate a range of functional outcomes in NRs.

Enhancing tuberculosis vaccine development: a deconvolution neural network approach for multi-epitope prediction

Tuberculosis (TB) a disease caused by Mycobacterium tuberculosis (Mtb) poses a significant threat to human life, and current BCG vaccinations only provide sporadic protection, therefore there is a need for developing efficient vaccines. Numerous immunoinformatic methods have been utilized previously, here for the first time a deep learning framework based on Deconvolutional Neural Networks (DCNN) and Bidirectional Long Short-Term Memory (DCNN-BiLSTM) was used to predict Mtb Multiepitope vaccine (MtbMEV) subunits against six Mtb H37Rv proteins. The trained model was used to design MEV within a few minutes against TB better than other machine learning models with 99.5% accuracy. The MEV has good antigenicity, and physiochemical properties, and is thermostable, soluble, and hydrophilic. The vaccine's BLAST search ruled out the possibility of autoimmune reactions. The secondary structure analysis revealed 87% coil, 10% beta, and 2% alpha helix, while the tertiary structure was highly upgraded after refinement. Molecular docking with TLR3 and TLR4 receptors showed good binding, indicating high immune reactions. Immune response simulation confirmed the generation of innate and adaptive responses. In-silico cloning revealed the vaccine is highly expressed in E. coli. The results can be further experimentally verified using various analyses to establish a candidate vaccine for future clinical trials.

In silico drug design strategies for discovering novel tuberculosis therapeutics

INTRODUCTION

Tuberculosis remains a significant concern in global public health due to its intricate biology and propensity for developing antibiotic resistance. Discovering new drugs is a protracted and expensive endeavor, often spanning over a decade and incurring costs in the billions. However, computer-aided drug design (CADD) has surfaced as a nimbler and more cost-effective alternative. CADD tools enable us to decipher the interactions between therapeutic targets and novel drugs, making them invaluable in the quest for new tuberculosis treatments.

AREAS COVERED

In this review, the authors explore recent advancements in tuberculosis drug discovery enabled by in silico tools. The main objectives of this review article are to highlight emerging drug candidates identified through in silico methods and to provide an update on the therapeutic targets associated with Mycobacterium tuberculosis.

EXPERT OPINION

These in silico methods have not only streamlined the drug discovery process but also opened up new horizons for finding novel drug candidates and repositioning existing ones. The continued advancements in these fields hold great promise for more efficient, ethical, and successful drug development in the future.

Targeting neuroblastoma by small-molecule inhibitors of human ALYREF protein: mechanistic insights using molecular dynamics simulations

Neuroblastoma is a tumour of the sympathetic nervous system mainly prevalent in children. Many strategies have been employed to target several drug-targetable proteins for the clinical management of neuroblastoma. However, the heterogeneous nature of neuroblastoma presents serious challenges in drug development for its treatment. Albeit numerous medications have been developed to target various signalling pathways in neuroblastoma, the redundant nature of the tumour pathways makes its suppression unsuccessful. Recently, the quest for neuroblastoma therapy resulted in the identification of human ALYREF, a nuclear protein that plays an essential role in tumour growth and progression. Therefore, this study used the structure-based drug discovery method to identify the putative inhibitors targeting ALYREF for the Neuroblastoma treatment. Herein, a library of 119 blood-brain barrier crossing small molecules from the ChEMBL database was downloaded and docked against the predicted binding pocket of the human ALYREF protein. Based on docking scores, the top four compounds were considered for intermolecular interactions and molecular dynamics simulation analysis, which revealed CHEMBL3752986 and CHEMBL3753744 with substantial affinity and stability with the ALYREF. These results were further supported by binding free energies and essential dynamics analysis of the respective complexes. Hence, this study advocates the sorted compounds targeting ALYREF for further in vitro and in vivo assessment to develop a drug against neuroblastoma.Communicated by Ramaswamy H. Sarma.

1H-1,2,3-Triazole-4H-chromene-D-glucose hybrid compounds: Synthesis and inhibitory activity against Mycobacterium tuberculosis protein tyrosine phosphatase B

A series of 1H-1,2,3-triazole-4H-chromene-D-glucose hybrid compounds 7a-w were synthesized using click chemistry of 2-amino-7-propargyloxy-4H-chromene-3-carbonitriles 5a-w. CuNPs@montmorillonite was used as a catalyst in the presence of DIPEA as an additive for this chemistry. All synthesized 1H-1,2,3-triazoles were examined for in vitro inhibition against Mycobacterium tuberculosis protein tyrosine phosphatase B (MtbPtpB). Nine 1H-1,2,3-triazoles, including 7c-e, 7h, 7i, and 7r-t, displayed remarkable inhibitory activity against MtbPtpB with IC₅₀  < 10 μM; compound 7t exhibited the most potent inhibition in vitro with an IC₅₀ value of 0.61 μM. Kinetic studies of the three most active compounds, 7c,h,t, showed their competitive inhibition toward the MtbPtpB enzyme. Induced-fit docking and MM-GBSA studies on the enzyme (PDB: 2OZ5) revealed that the most active compound 7t was more effective against MtbPtpB. Residues Arg64, Arg136, Ash165, Arg166, and Arg63 in the binding pocket were identified as potential ligand-binding hot-spot residues for ligand 7t. The binding free energy calculation by the MM-GBSA approach for ligand 7t indicated that Coulomb, lipophilic, and van der Waals energy terms are major contributors to the inhibitor binding. Furthermore, the stability of the ligand-protein complex and the structural insights into the mode of binding were confirmed by 300-ns molecular dynamics simulation of 7t/2OZ5.

Ligand-induced shifts in conformational ensembles that describe transcriptional activation

Nuclear receptors function as ligand-regulated transcription factors whose ability to regulate diverse physiological processes is closely linked with conformational changes induced upon ligand binding. Understanding how conformational populations of nuclear receptors are shifted by various ligands could illuminate strategies for the design of synthetic modulators to regulate specific transcriptional programs. Here, we investigate ligand-induced conformational changes using a reconstructed, ancestral nuclear receptor. By making substitutions at a key position, we engineer receptor variants with altered ligand specificities. We combine cellular and biophysical experiments to characterize transcriptional activity, as well as elucidate mechanisms underlying altered transcription in receptor variants. We then use atomistic molecular dynamics (MD) simulations with enhanced sampling to generate ensembles of wildtype and engineered receptors in combination with multiple ligands, followed by conformational analysis and correlation of MD-based predictions with functional ligand profiles. We determine that conformational ensembles accurately describe ligand responses based on observed population shifts. These studies provide a platform which will allow structural characterization of physiologically-relevant conformational ensembles, as well as provide the ability to design and predict transcriptional responses in novel ligands.

Application of molecular dynamics simulation in biomedicine

Molecular dynamics (MD) simulation has been widely used in the field of biomedicine to study the conformational transition of proteins caused by mutation or ligand binding/unbinding. It provides some perspectives those are difficult to find in traditional biochemical or pathological experiments, for example, detailed effects of mutations on protein structure and protein-protein/ligand interaction at the atomic level. In this review, a broad overview on conformation changes and drug discovery by MD simulation is given. We first discuss the preparation of protein structure for MD simulation, which is a key step that determines the accuracy of the simulation. Then, we summarize the applications of commonly used force fields and MD simulations in scientific research. Finally, enhanced sampling methods and common applications of these methods are introduced. In brief, MD simulation is a powerful tool and it can be used to guide experimental study. The combination of MD simulation and experimental techniques is an a priori means to solve the biomedical problems and give a deep understanding on the relationship between protein structure and function.

Novel In Silico mRNA vaccine design exploiting proteins of M. tuberculosis that modulates host immune responses by inducing epigenetic modifications

Tuberculosis is an airborne infectious disease caused by Mycobacterium tuberculosis. BCG is the only approved vaccine. However, it has limited global efficacy. Pathogens could affect the transcription of host genes, especially the ones related to the immune system, by inducing epigenetic modifications. Many proteins of M. tuberculosis were found to affect the host's epigenome. Nine proteins were exploited in this study to predict epitopes to develop an mRNA vaccine against tuberculosis. Many immunoinformatics tools were employed to construct this vaccine to elicit cellular and humoral immunity. We performed molecular docking between selected epitopes and their corresponding MHC alleles. Thirty epitopes, an adjuvant TLR4 agonist RpfE, constructs for subcellular trafficking, secretion booster, and specific linkers were combined to develop the vaccine. This proposed construct was tested to cover 99.38% of the population. Moreover, it was tested to be effective and safe. An in silico immune simulation of the vaccine was also performed to validate our hypothesis. It also underwent codon optimization to ensure mRNA's efficient translation once it reaches the cytosol of a human host. Furthermore, secondary and tertiary structures of the vaccine peptide were predicted and docked against TLR-4 and TLR-3.Molecular dynamics simulation was performed to validate the stability of the binding complex. It was found that this proposed construction can be a promising vaccine against tuberculosis. Hence, our proposed construct is ready for wet-lab experiments to approve its efficacy.

Atomistic Simulations of Functionalized Nano-Materials for Biosensors Applications

Nanoscale biosensors, a highly promising technique in clinical analysis, can provide sensitive yet label-free detection of biomolecules. The spatial and chemical specificity of the surface coverage, the proper immobilization of the bioreceptor as well as the underlying interfacial phenomena are crucial elements for optimizing the performance of a biosensor. Due to experimental limitations at the microscopic level, integrated cross-disciplinary approaches that combine in silico design with experimental measurements have the potential to present a powerful new paradigm that tackles the issue of developing novel biosensors. In some cases, computational studies can be seen as alternative approaches to assess the microscopic working mechanisms of biosensors. Nonetheless, the complex architecture of a biosensor, associated with the collective contribution from "substrate-receptor-analyte" conjugate in a solvent, often requires extensive atomistic simulations and systems of prohibitive size which need to be addressed. In silico studies of functionalized surfaces also require ad hoc force field parameterization, as existing force fields for biomolecules are usually unable to correctly describe the biomolecule/surface interface. Thus, the computational studies in this field are limited to date. In this review, we aim to introduce fundamental principles that govern the absorption of biomolecules onto functionalized nanomaterials and to report state-of-the-art computational strategies to rationally design nanoscale biosensors. A detailed account of available in silico strategies used to drive and/or optimize the synthesis of functionalized nanomaterials for biosensing will be presented. The insights will not only stimulate the field to rationally design functionalized nanomaterials with improved biosensing performance but also foster research on the required functionalization to improve biomolecule-surface complex formation as a whole.

An immunoinformatics approach to design a multi-epitope vaccine against Mycobacterium tuberculosis exploiting secreted exosome proteins

Tuberculosis is one the oldest known affliction of mankind caused by the pathogen Mycobacterium tuberculosis. Till date, there is no absolute single treatment available to deal with the pathogen, which has acquired a great potential to develop drug resistance rapidly. BCG is the only anti-tuberculosis vaccine available till date which displays limited global efficacy due to genetic variation and concurrent pathogen infections. Extracellular vesicles or exosomes vesicle (EVs) lie at the frontier cellular talk between pathogen and the host, and therefore play a significant role in establishing pathogenesis. In the present study, an in-silico approach has been adopted to construct a multi-epitope vaccine from selected immunogenic EVs proteins to elicit a cellular as well as a humoral immune response. Our designed vaccine has wide population coverage and can effectively compensate for the genetic variation among different populations. For maximum efficacy and minimum adverse effects possibilities the antigenic, non-allergenic and non-toxic B-cell, HTL and CTL epitopes from experimentally proven EVs proteins were selected for the vaccine construct. TLR4 agonist RpfE served as an adjuvant for the vaccine construct. The vaccine construct structure was modelled, refined and docked on TLR4 immune receptor. The designed vaccine construct displayed safe usage and exhibits a high probability to elicit the critical immune regulators, like B cells, T-cells and memory cells as displayed by the in-silico immunization assays. Therefore, it can be further corroborated using in vitro and in vivo assays to fulfil the global need for a more efficacious anti-tuberculosis vaccine.

From infection niche to therapeutic target: the intracellular lifestyle of Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) is an obligate human pathogen killing millions of people annually. Treatment for tuberculosis is lengthy and complicated, involving multiple drugs and often resulting in serious side effects and non-compliance. Mtb has developed numerous complex mechanisms enabling it to not only survive but replicate inside professional phagocytes. These mechanisms include, among others, overcoming the phagosome maturation process, inhibiting the acidification of the phagosome and inhibiting apoptosis. Within the past decade, technologies have been developed that enable a more accurate understanding of Mtb physiology within its intracellular niche, paving the way for more clinically relevant drug-development programmes. Here we review the molecular biology of Mtb pathogenesis offering a unique perspective on the use and development of therapies that target Mtb during its intracellular life stage.