Potential Inhibitors of Galactofuranosyltransferase 2 (GlfT2): Molecular Docking, 3D-QSAR, and In Silico ADMETox Studies

An in-silico receptor-pharmacophore based multistep molecular docking and simulation study to evaluate the inhibitory potentials against NS1 of DENV-2

DENV-2 strain is the most fatal and infectious of the five dengue virus serotypes. The non-structural protein NS1 encoded by its genome is the most significant protein required for viral pathogenesis and replication inside the host body. Thus, targeting the NS1 protein and designing an inhibitor to limit its stability and secretion is a propitious attempt in our fight against dengue. Four novel inhibitors are designed to target the conserved cysteine residues (C55, C313, C316, and C329) and glycosylation sites (N130 and N207) of the NS1 protein in an attempt to halt the spread of the dengue infection in the host body altogether. Numerous computer-aided drug designing techniques including molecular docking, molecular dynamics simulation, virtual screening, principal component analysis, and dynamic cross-correlation matrix were employed to determine the structural and functional activity of the NS1-inhibitor complexes. From our analysis, it was evident that the extent of structural and atomic level fluctuations of the ligand-bound protein exhibited a declining trend in contrast to unbound protein which was prominently noticeable through the RMSD, RMSF, Rg, and SASA graphs. The ADMET analysis of the four ligands revealed a promising pharmacokinetics and pharmacodynamic profile, along with good bioavailability and toxicity properties. The proposed drugs when bound to the targeted cavities resulted in stable conformations in comparison to their unbound state, implying they have good affinity promising effective drug action. Thus, they can be tested in vitro and used as potential anti-dengue drugs.Communicated by Ramaswamy H. Sarma.

Antinociceptive effect of LMH-2, a new sigma-1 receptor antagonist analog of haloperidol, on the neuropathic pain of diabetic mice

This study evaluates the antiallodynic and antihyperalgesic effects of LMH-2, a new haloperidol (HAL) analog that acts as sigma-1 receptor (σ1 R) antagonist, in diabetic mice using a model of neuropathic pain induced by chronic hyperglycemia. Additionally, we compared its effects with those of HAL. Hyperglycemia was induced in mice by nicotinamide-streptozotocin administration (NA-STZ, 50-130 mg/kg). Four weeks later, mechanical allodynia was assessed using the up-down method, and hyperalgesia was evoked with formalin 0.5%. We evaluated antiallodynic and antihyperalgesic effects of LMH-2 (5.6-56.2 mg/kg), HAL (0.018-0.18 mg/kg) and gabapentin (GBP, 5.6-56.2 mg/kg). The results showed that LMH-2 had a more significant antiallodynic effect compared to HAL and GBP (90.4±8.7 vs 75.1±3.1 and 41.9±2.3%, respectively; P<0.05), as well as an antihyperalgesic effect (96.3±1.2 vs 86.9±7.41 and 86.9±4.8%, respectively; P<0.05). Moreover, the antiallodynic and antihyperalgesic effect of both LMH-2 and HAL were completely abolished by PRE-084 (σ1 R agonist); and partially by pramipexole (a D2-like receptor agonist). Finally, the effect of all treatments on the rotarod test, barra, open field and exploratory behaviors showed that LMH-2 did not alter the animals' balance or the exploratory behavior, unlike as HAL or GBP. The molecular docking included indicate that LMH-2 has lower affinity to the D2R than HAL. These results provide evidence that LMH-2 exerts its antinociceptive effects as a σ1 R antagonist without the adverse effects induced by HAL or GBP. Consequently, LMH-2 can be considered a good and safe strategy for treating neuropathic pain caused by hyperglycemia in patients with diabetes.

Proteome-Based Investigation Identified Potential Drug Repurposable Small Molecules Against Monkeypox Disease

Monkeypox Virus (MPXV), the causative agent of Monkeypox (MPX) disease, is an emerging zoonotic pathogen spreading in different endemic and non-endemic nations and creating outbreaks. MPX treatment mainly includes Cidofovir and Tecovirimat but they have several side effects and solely depending on these drugs may promote the emergence of drug-resistant variants. Hence, new drugs are required to control the spread of the disease. In this study, we explored the MPXV proteome to suggest repurposable drugs. DrugBank screening revealed drugs such as Brinzolamide, Dorzolamide, Methazolamide, Zidovudine, Gemcitabine, Hydroxyurea, Fludarabine, and Tecovirimat as controls. Structural analogs of these compounds were extracted from ChEMBL Database. After Molecular docking and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET)-based screening, we identified Zidovudine (binding affinity-5.9 kcal/mol) and a Harmala alkaloid (2S,4R)-4-(9H-Pyrido[3,4-b]indol-1-yl)-1,2,4-butanetriol (binding affinity - 6.6 kcal/mol) against L2R receptor (Thymidine Kinase). Moreover, Fludarabine (binding affinity - 6.4 kcal/mol) and 5'-Dehydroadenosine (binding affinity - 6.4 kcal/mol) can strongly interact with the I4L receptor (Ribonucleotide reductase large subunit R1). Molecular Dynamics (MD) simulations suggest all of these compounds can change the C-alpha backbone, residue mobility, compactness, and solvent accessible surface area of L2R and I4L. Our results strongly suggest that these drug repurposing small molecules are worth exploring in vivo and in vitro for clinical applications.

Correlation of Experimental and Calculated Inhibition Constants of Protease Inhibitor Complexes

Predicting the potency of inhibitors is key to in silico screening of promising synthetic or natural compounds. Here we describe a predictive workflow that provides calculated inhibitory values, which concord well with empirical data. Calculations of the free interaction energy ΔG with the YASARA plugin FoldX were used to derive inhibition constants Ki from PDB coordinates of protease-inhibitor complexes. At the same time, corresponding KD values were obtained from the PRODIGY server. These results correlated well with the experimental values, particularly for serine proteases. In addition, analyses were performed for inhibitory complexes of cysteine and aspartic proteases, as well as of metalloproteases, whereby the PRODIGY data appeared to be more consistent. Based on our analyses, we calculated theoretical Ki values for trypsin with sunflower trypsin inhibitor (SFTI-1) variants, which yielded the more rigid Pro14 variant, with probably higher potency than the wild-type inhibitor. Moreover, a hirudin variant with an Arg1 and Trp3 is a promising basis for novel thrombin inhibitors with high potency. Further examples from antibody interaction and a cancer-related effector-receptor system demonstrate that our approach is applicable to protein interaction studies beyond the protease field.

Applying the bioisosterism strategy to obtain lead compounds against SARS-CoV-2 cysteine proteases: An in-silico approach

SARS-CoV-2 cysteine proteases are essential nonstructural proteins due to their role in the formation of the virus multiple enzyme replication-transcription complex. As a result, those functional proteins are extremely relevant targets in the development of a new drug candidate to fight COVID-19. Based on this fact and guided by the bioisosterism strategy, the present work has selected 126 out of 1050 ligands from DrugBank website. Subsequently, 831 chemical analogs containing bioisosteres, some of which became structurally simplified, were created using the MB-Isoster software, and molecular docking simulations were performed using AutoDock Vina. Finally, a study of physicochemical properties, along with pharmacokinetic profiles, was carried out through SwissADME and ADMETlab 2.0 platforms. The promising results obtained with the molecules encoded as DB00549_BI_005, DB04868_BI_003, DB11984_BI_002, DB12364_BI_006 and DB12805_BI_004 must be confirmed by molecular dynamics studies, followed by in vitro and in vivo empirical tests that ratify the advocated in-silico results.

Antimicrobial peptides grafted onto the surface of N-acetylcysteine-chitosan nanoparticles can revitalize drugs against clinical isolates of Mycobacterium tuberculosis

Tuberculosis is caused by Mycobacterium tuberculosis (MTB) and is the leading cause of death from infectious diseases in the World. The search for new antituberculosis drugs is a high priority, since several drug-resistant TB-strains have emerged. Many nanotechnology strategies are being explored to repurpose or revive drugs. An interesting approach is to graft antimicrobial peptides (AMPs) to antibiotic-loaded nanoparticles. The objective of the present work was to determine the anti-MTB activity of rifampicin-loaded N-acetylcysteine-chitosan-based nanoparticles (NPs), conjugated with the AMP Ctx(Ile21)-Ha; against clinical isolates (multi- and extensively-drug resistant) and the H37Rv strain. The modified chitosan and drug-loaded NPs were characterized with respect to their physicochemical stability and their antimycobacterial profile, which showed potent inhibition (MIC values <0.977 μg/mL) by the latter. Furthermore, their accumulation within macrophages and cytotoxicity were determined. To understand the possible mechanisms of action, an in silico study of the peptide against MTB membrane receptors was performed. The results presented herein demonstrate that antibiotic-loaded NPs grafted with an AMP can be a powerful tool for revitalizing drugs against multidrug-resistant M. tuberculosis strains, by launching multiple attacks against MTB. This approach could potentially serve as a novel treatment strategy for various long-term diseases requiring extended treatment periods.

Identification of Novel EGFR Inhibitors for the Targeted Therapy of Colorectal Cancer Using Pharmacophore Modelling, Docking, Molecular Dynamic Simulation and Biological Activity Prediction

BACKGROUND

Colorectal cancer (CRC) is considered the second deadliest cancer in the world. One of the reasons for the occurrence of this cancer is the deregulation of the Epidermal Growth Factor Receptor (EGFR), which plays a critical role in regulating cell division, persistence, differentiation, and migration. The overexpression of the EGFR protein leads to its dysregulation and causes CRC.

OBJECTIVES

Hence, this work aims to identify and validate novel EGFR inhibitors for the treatment of colorectal cancer employing various computer aided techniques such as pharmacophore modeling, docking, molecular dynamic simulation and Quantitative Structure-Activity Relationship (QSAR) analysis.

METHODS

In this work, a shared-featured ligand-based pharmacophore model was generated using the known inhibitors of EGFR. The best model was validated and screened against ZincPharmer and Maybridge databases, and 143 hits were obtained. Pharmacokinetic and toxicological properties of these hits were studied, and the acceptable ligands were docked against EGFR. The best five protein-ligand complexes with binding energy less than -5 kcal/mol were selected. The molecular dynamic simulation studies of these complexes were conducted for 100 nanoseconds (ns), and the results were analyzed. The biological activity of this ligand was calculated using QSAR analysis.

RESULTS

The best complex with Root Mean Square Deviation (RMSD) 3.429 Å and Radius of Gyration (RoG) 20.181 Å was selected. The Root Mean Square Fluctuations (RMSF) results were also found to be satisfactory. The biological activity of this ligand was found to be 1.38 μM.

CONCLUSION

This work hereby proposes the ligand 2-((1,6-dimethyl-4-oxo-1,4-dihydropyridin-3-yl)oxy)-N- (1H-indol-4-yl)acetamide as a potential EGFR inhibitor for the treatment of colorectal cancer. The wet lab analysis must be conducted, however, to confirm this hypothesis.

Revolutionizing Tuberculosis Treatment: Uncovering New Drugs and Breakthrough Inhibitors to Combat Drug-Resistant Mycobacterium tuberculosis

Tuberculosis (TB) is a global health threat that causes significant mortality. This review explores chemotherapeutics that target essential processes in Mycobacterium tuberculosis, such as DNA replication, protein synthesis, cell wall formation, energy metabolism, and proteolysis. We emphasize the need for new drugs to treat drug-resistant strains and shorten the treatment duration. Emerging targets and promising inhibitors were identified by examining the intricate biology of TB. This review provides an overview of recent developments in the search for anti-TB drugs with a focus on newly validated targets and inhibitors. We aimed to contribute to efforts to combat TB and improve therapeutic outcomes.

Molecular Design of Novel Inhibitor by Targeting IL-6Rα using Combined Pharmacophore and Experimentally Verified Plant Products with Scaffold-Hopping Techniques: A Dual Therapeutic Strategy for COVID-19 and Cancer

The IL-6/IL-6R/gp130 complex serves as a significant indicator of cytokine release syndrome in COVID-19 and chronic inflammation, increasing the risk of cancer. Therefore, we identified IL-6Rα as a potential target to block gp130 interaction. Notably, there has been no reception of approval for an orally available drug to serve this purpose, to date. In this study, we targeted IL-6Rα to inhibit IL-6Rα/gp130 interaction. The selection of the lead candidate L821 involved the amalgamation of three drug discovery approaches. This library was screened employing tertiary structure-based pharmacophore models followed by molecular docking models, scaffold-hopping, MM/PBSA as well as MM/GBSA analysis, and assessments of pKi and ADMET properties. After evaluating the binding interactions with key amino acids, 15 potential ligands were chosen, with the top ligand undergoing further investigation by means of molecular dynamics simulations. Considering the stability of the complexes, the strong interactions observed between ligand and residues of IL-6Rα/gp130, and the favorable binding free energy calculations, L821 emerged as the prime candidate for inhibiting IL-6Rα. Notably, L821 exhibited a docking-based binding affinity of -9.5 kcal/mol. Our study presents L821 as a promising inhibitor for future in vitro analysis, potentially combatting SARS-CoV-2-related cytokine storms and serving as an oncogenic drug therapy.

Cheminformatics identification of modulators of key carbohydrate-metabolizing enzymes from C. cujete for type-2 diabetes mellitus intervention

Purpose

The therapeutic use of oral hypoglycaemic agents in the management of type-2 diabetes mellitus (T2DM) is without adverse effects; thus, calls for alternative and novel candidates from natural products in medicinal plants.

Method

The study explored molecular docking and molecular dynamics (MD) simulation approaches to identify key antidiabetic metabolites from Crescentia cujete.

Results

Molecular docking results identified four and/or five best compounds against each target enzyme (alpha-glucosidase, dipeptidyl peptidase-IV, aldose reductase, and protein tyrosine phosphatase-1B (PTP-1B)) implicated in diabetes. The resulting complexes (except against PTP-1B) had higher docking scores above respective standards (acarbose, Diprotin A, ranirestat). The MD simulation results revealed compounds such as benzoic acid (-48.414 kcal/mol) and phytol (-45.112 kcal/mol) as well as chlorogenic acid (-42.978 kcal/mol) and naringenin (-31.292 kcal/mol) had higher binding affinities than the standards [acarbose (-28.248 kcal/mol), ranirestat (-21.042 kcal/mol)] against alpha-glucosidase and aldose reductase, respectively while Diprotin A (-45.112 kcal/mol) and ursolic acid (-18.740 kcal/mol) presented superior binding affinities than the compounds [luteolin (-41.957 kcal/mol and naringenin (-16.518 kcal/mol)] against DPP-IV and PTP-1B respectively.

Conclusion

While isoflavone (alpha-glucosidase), xylocaine (DPP-IV), luteolin (aldose reductase,) and chlorogenic acid (PTP-1B) were affirmed as the best inhibitors of respective enzyme targets, luteolin, and chlorogenic acid may be suggested and proposed as probable candidates against T2DM and related retinopathy complication based on their structural stability, compactness and affinity for three (DPP-IV, aldose reductase, and PTP-1B) of the four targets investigated. Further studies are warranted in vitro and in vivo on the antihyperglycaemic effects of these drug candidates.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01249-7.

Anti-quorum sensing effects of batatasin III: in vitro and in silico studies

The spread of multidrug resistant bacteria has fueled the development of new antibiotics to combat bacterial infections. Disrupting the quorum sensing (QS) mechanism with biomolecules is a promising approach against bacterial infections. Plants used in Traditional Chinese Medicine (TCM) represent a valuable resource for the identification of QS inhibitors. In this study, the in vitro anti-QS activity of 50 TCM-derived phytochemicals against the biosensor Chromobacterium violaceum CV026 was tested. Among the 50 phytochemicals, 7-methoxycoumarin, flavone, batatasin III, resveratrol, psoralen, isopsoralen, and rhein inhibited violacein production and showed good QS inhibitory effects. Batatasin III was selected as the best QS inhibitor based on drug-likeness, physicochemical properties, toxicity, and bioactivity score prediction analyses using SwissADME, PreADMET, ProtoxII, and Molinspiration. At 30 μg/ mL, Batatasin III inhibited violacein production and biofilm formation in C. violaceum CV026 by more than 69% and 54% respectively without affecting bacterial growth. The in vitro cytotoxicity evaluation by MTT assay demonstrated that batatasin III reduced the viability of 3T3 mouse fibroblast cells to 60% at 100 μg/mL. Furthermore, molecular docking studies showed that batatasin III has strong binding interactions with the QS-associated proteins CViR, LasR, RhlR, PqsE, and PqsR. Molecular dynamic simulation studies showed that batatasin III has strong binding interactions with 3QP1, a structural variant of CViR protein. The binding free energy value of batatasin III-3QP1 complex was -146.295 ± 10.800 KJ/mol. Overall results suggested that batatasin III could serve as a lead molecule that could be developed into a potent QS inhibitor.Communicated by Ramaswamy H. Sarma.

Assessing Squarates as Amine-Reactive Probes

Probes that covalently label protein targets facilitate the identification of ligand-binding sites. Lysine residues are prevalent in the proteome, making them attractive substrates for covalent probes. However, identifying electrophiles that undergo amine-specific, regioselective reactions with binding site lysine residues is challenging. Squarates can engage in two sequential conjugate addition-elimination reactions with amines. Nitrogen donation reduces the second reaction rate, making the mono squaramide a mild electrophile. We postulated that this mild electrophilicity would demand a longer residence time near the amine, affording higher selectivity for binding site lysines. Therefore, we compared the kinetics of squarate and monosquaramide amine substitution to alternative amine bioconjugation handles. The data revealed that N-hydroxy succinimidyl esters react 4 orders of magnitude faster, consistent with their labeling promiscuity. Squarate reactivity can be tuned by a substitution pattern. Electron-withdrawing groups on the vinylogous ester or amide increase reaction rates. Dithionosquarates react more rapidly than squarates, while vinylogous thioester analogs, dithiosquarates, react more slowly. We assessed squarate selectively using the UDP-sugar processing enzyme GlfT2 from Mycobacterium tuberculosis, which possesses 21 surface-exposed lysines. The reaction predominately modified one lysine proximal to a binding site to afford covalent inhibition. These findings demonstrate the selectivity of squaric esters and squaramides, which is a critical feature for affinity-based chemoproteomic probes.

A knowledge-guided pre-training framework for improving molecular representation learning

Learning effective molecular feature representation to facilitate molecular property prediction is of great significance for drug discovery. Recently, there has been a surge of interest in pre-training graph neural networks (GNNs) via self-supervised learning techniques to overcome the challenge of data scarcity in molecular property prediction. However, current self-supervised learning-based methods suffer from two main obstacles: the lack of a well-defined self-supervised learning strategy and the limited capacity of GNNs. Here, we propose Knowledge-guided Pre-training of Graph Transformer (KPGT), a self-supervised learning framework to alleviate the aforementioned issues and provide generalizable and robust molecular representations. The KPGT framework integrates a graph transformer specifically designed for molecular graphs and a knowledge-guided pre-training strategy, to fully capture both structural and semantic knowledge of molecules. Through extensive computational tests on 63 datasets, KPGT exhibits superior performance in predicting molecular properties across various domains. Moreover, the practical applicability of KPGT in drug discovery has been validated by identifying potential inhibitors of two antitumor targets: hematopoietic progenitor kinase 1 (HPK1) and fibroblast growth factor receptor 1 (FGFR1). Overall, KPGT can provide a powerful and useful tool for advancing the artificial intelligence (AI)-aided drug discovery process.

Towards targeting EGFR and COX-2 inhibitors: comprehensive computational studies on the role of chlorine group in novel thienyl-pyrazoline derivative

To enhance the effectiveness of chemotherapy and overcome resistance, scientists must develop novel drugs or scaffolds that have a combined effect, such as the inhibition of EGFR and COX-2. This research employed virtual screening techniques, such as docking, and dynamics simulation, to predict chlorinated thienyl-pyrazoline derivatives that inhibit these proteins. The study proposed eleven (11) ligands with binding energies ranging from -7.8 kcal/mol to -8.7 kcal/mol for EGFR and -6.4 kcal/mol to -8.4 kcal/mol for COX-2. Ligands P1 and P11 exhibited the highest binding affinity for both proteins. The results of RMSD, RMSF, RoG, SASA the number of hydrogen bonds, and BAR free binding energy demonstrated the good stability of ligands P1 and P11 when binding to both proteins over 180 ns simulations. In addition, the absorption, distribution, metabolism, excretion, and toxicity properties of the selected ligands were assessed to predict their toxicity and drug likeliness. Based on the results, these compounds can be proposed for further synthesis and in vitro studies.Communicated by Ramaswamy H. Sarma.

Evaluation of Acute and Sub-Acute Toxicity, Oxidative Stress and Molecular Docking of Two Nitrofuranyl Amides as Promising Anti-Tuberculosis Agents

Tuberculosis (TB) remains a widespread infectious disease and one of the top 10 causes of death worldwide. Nevertheless, despite significant advances in the development of new drugs against tuberculosis, many therapies and preventive measures do not lead to the expected favorable health results for various reasons. The aim of this study was to evaluate the acute and sub-acute toxicity and oxidative stress of two selected nitrofuranyl amides with high in vitro antimycobacterial activity. In addition, molecular docking studies were performed on both compounds to elucidate the possibilities for further development of new anti-tuberculosis candidates with improved efficacy, selectivity, and pharmacological parameters. Acute toxicity tests showed that no changes were observed in the skin, coat, eyes, mucous membranes, secretions, and vegetative activity in mice. The histological findings include features consistent with normal histological architecture without being associated with concomitant pathological conditions. The observed oxidative stress markers indicated that the studied compounds disturbed the oxidative balance in the mouse liver. Based on the molecular docking, compound DO-190 showed preferable binding energies compared to DO-209 in three out of four targets, while both compounds showed promising protein-ligand interactions. Thus, both studied compounds displayed promising activity with low toxicity and can be considered for further evaluation and/or lead optimization.

Advances in computational frameworks in the fight against TB: The way forward

Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its "End TB" strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for-early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.

Multi-dimensional structural footprint identification for the design of potential scaffolds targeting METTL3 in cancer treatment from natural compounds

CONTEXT

[Formula: see text]-adenosine-methyltransferase (METTL3) is the catalytic domain of the 'writer' proteins which is involved in the post modifications of [Formula: see text]-methyladinosine ([Formula: see text]). Though its activities are essential in many biological processes, it has been implicated in several types of cancer. Thus, drug developers and researchers are relentlessly in search of small molecule inhibitors that can ameliorate the oncogenic activities of METTL3. Currently, STM2457 is a potent, highly selective inhibitor of METTL3 but is yet to be approved.

METHODS

In this study, we employed structure-based virtual screening through consensus docking by using AutoDock Vina in PyRx interface and Glide virtual screening workflow of Schrodinger Glide. Thermodynamics via MM-PBSA calculations was further used to rank the compounds based on their total free binding energies. All atom molecular dynamics simulations were performed using AMBER 18 package. FF14SB force fields and Antechamber were used to parameterize the protein and compounds respectively. Post analysis of generated trajectories was analyzed with CPPTRAJ and PTRAJ modules incorporated in the AMBER package while Discovery studio and UCSF Chimera were used for visualization, and origin data tool used to plot all graphs.

RESULTS

Three compounds with total free binding energies higher than STM2457 were selected for extended molecular dynamics simulations. The compounds, SANCDB0370, SANCDB0867, and SANCDB1033, exhibited stability and deeper penetration into the hydrophobic core of the protein. They engaged in relatively stronger intermolecular interactions involving hydrogen bonds with resultant increase in stability, reduced flexibility, and decrease in the surface area of the protein available for solvent interactions suggesting an induced folding of the catalytic domain. Furthermore, in silico pharmacokinetics and physicochemical analysis of the compounds revealed good properties suggesting these compounds could serve as promising MEETL3 entry inhibitors upon modifications and optimizations as presented by natural compounds. Further biochemical testing and experimentations would aid in the discovery of effective inhibitors against the berserk activities of METTL3.

Intermolecular And Dynamic Investigation of The Mechanism of Action of Reldesemtiv on Fast Skeletal Muscle Troponin Complex Toward the Treatment of Impaired Muscle Function

Muscle weakness as a secondary feature of attenuated neuronal input often leads to disability and sometimes death in patients with neurogenic neuromuscular diseases. These impaired muscle function has been observed in several diseases including amyotrophic lateral sclerosis, Charcot-Marie-Tooth, spinal muscular atrophy and Myasthenia gravis. This has spurred the search for small molecules which could activate fast skeletal muscle troponin complex as a means to increase muscle strength. Discovered small molecules have however been punctuated by off-target and side effects leading to the development of the second-generation small molecule, Reldesemtiv. In this study, we investigated the impact of Reldesemtiv binding to the fast skeletal troponin complex and the molecular determinants that condition the therapeutic prowess of Redesemtiv through computational techniques. It was revealed that Reldesemtiv binding possibly potentiates troponin C compacting characterized by reduced exposure to solvent molecules which could favor the slow release of calcium ions and the resultant sensitization of the subunit to calcium. These conformational changes were underscored by conventional and carbon hydrogen bonds, pi-alkyl, pi-sulfur and halogen interactions between Reldesemtiv the binding site residues. Arg113 (-3.96 kcal/mol), Met116 (-2.23 kcal/mol), Val114 (-1.28 kcal/mol) and Met121 (-0.63 kcal/mol) of the switch region of the inhibitory subunit were among the residues that contributed the most to the total free binding energy of Reldesemtiv highlighting their importance. These findings present useful insights which could lay the foundation for the development of fast skeletal muscle small molecule activators with high specificity and potency.

Naturally-occurring carboxylic acids from traditional antidiabetic plants as potential pancreatic islet FABP3 inhibitors. A molecular docking-aided study

The antidiabetic action of traditional plants is mostly attributed to their antioxidant and anti-inflammatory properties. These plants are still having some secrets, making them an attractive source that allows for investigating new drugs or uncovering precise pharmacologic antidiabetic functions of their constituents. In diabetes, which is a lipid disease, long-term exposure of pancreatic islet beta cells to fatty acids (FAs) increases basal insulin release, reduces glucose-stimulated insulin secretion, causes islet beta cell inflammation, failure and apoptosis. Pancreatic islet beta cells express fatty acid binding protein 3 (FABP3) that receives long-chain FAs and traffics them throughout different cellular compartments to be metabolized and render their effects. Inhibition of this FABP3 may retard FA metabolism and protect islet beta cells. Since FAs interact with FABPs by their carboxylic group, some traditionally-known antidiabetic plants were reviewed in the present study, searching for their components that have common features of FABP ligands, namely carboxylic group and hydrophobic tail. Many of these carboxylic acids were computationally introduced into the ligand-binding pocket of FABP3 and some of them exhibited FABP3 ligand possibilities. Among others, the naturally occurring ferulic, cleomaldeic, caffeic, sinapic, hydroxycinnamic, 4-p-coumaroylquinic, quinoline-2-carboxylic, chlorogenic, 6-hydroxykynurenic, and rosmarinic acids in many plants are promising candidates for being FABP3-specific inhibitors. The study shed light on repurposing these phyto-carboxylic acids to function as FABP inhibitors. However, more in-depth biological and pharmacological studies to broaden the understanding of this function are needed.

Targeting envelope proteins of poxviruses to repurpose phytochemicals against monkeypox: An in silico investigation

The monkeypox virus (MPXV) has become a major threat due to the increasing global caseload and the ongoing multi-country outbreak in non-endemic territories. Due to limited research in this avenue and the lack of intervention strategies, the present study was aimed to virtually screen bioactive phytochemicals against envelope proteins of MPXV via rigorous computational approaches. Molecular docking, molecular dynamic (MD) simulations, and MM/PBSA analysis were used to investigate the binding affinity of 12 phytochemicals against three envelope proteins of MPXV, viz., D13, A26, and H3. Silibinin, oleanolic acid, and ursolic acid were computationally identified as potential phytochemicals that showed strong binding affinity toward all the tested structural proteins of MPXV through molecular docking. The stability of the docked complexes was also confirmed by MD simulations and MM/PBSA calculations. Results from the iMODS server also complemented the findings from molecular docking and MD simulations. ADME analysis also computationally confirmed the drug-like properties of the phytochemicals, thereby asserting their suitability for consumption. Hence, this study envisions the candidature of bioactive phytochemicals as promising inhibitors against the envelope proteins of the MPXV, serving as template molecules that could further be experimentally evaluated for their efficacy against monkeypox.

Bioinsecticidal activity of actinomycete secondary metabolites against the acetylcholinesterase of the legume’s insect pest Acyrthosiphon pisum: a computational study

Background

Acyrthosiphon pisum or pea aphid is an insect of the Aphididae family, which attacks various species of legumes such as beans and peas. This pest causes economically heavy crop losses around the world. The use of conventional chemical insecticides is the only way to control its development. However, the harmful consequences of these chemicals are well known. They pollute various compartments of the environment, thus constituting a major risk for human and environmental health. The search for a more ecological alternative, respectful of the environment is, therefore, a necessity. Actinomycetes represent a source of biologically active secondary metabolites, such as antibiotics and biopesticidal agents. In this study, 150 secondary metabolites of actinomycetes have made the objective of an in silico research by molecular docking, by screening their potential inhibitors against the enzyme acetylcholinesterase (AChE) of A. pisum.

Results

The 3D structure of AChE, unavailable in the PDB database, was first modeled using the Modeller program, then the stereochemical quality of the model was validated. The molecular docking performed by the Autodock Vina algorithm allowed the selection of two metabolites giving binding energy equal to or lower than that of the co-crystallized inhibitor tetrahydro-acridine (−10.3Kcal/mol). The top-two metabolites are diazepinomicine (−10.9 Kcal/mol), and hygromycin (−10.3 Kcal/mol). These components have shown numerous interactions with the key residues of the catalytic site of the AChE enzyme, indicating their potential to inhibit its biological activity. The environmental and health safety of these components, as well as their bioavailability, were also studied by the verification of several pharmacokinetic and ADMET criteria. Diazepinomicine has shown excellent results verifying most of the criteria studied. A 50-ns MD simulation was also performed in order to test the stability of the complexes formed.

Conclusions

In addition to its favorable pharmacokinetic properties, the special chemical structure of diazepinomicin allows this molecule to interact intensely with AChE notably through the involvement of its two groups farnesyl diphosphate and dibenzodiazepinone which ensure several hydrogen and hydrophobic interactions, that offers very high stability to the complex AChE diazepinomicin. In conclusion, diazepinomicin can be suggested as a potential bioinsecticidal agent against the pest A. pisum.

Anti-liver fibrosis activity of curcumin/chitosan-coated green silver nanoparticles

Liver fibrosis results from the hepatic accumulation of the extracellular matrix accompanied by a failure of the mechanisms responsible for matrix dissolution. Pathogenesis of liver fibrosis is associated with many proteins from different cell types. In the present study, in silico molecular docking analysis revealed that curcumin may inhibit the fibrosis-mediating proteins PDGF, PDGFRB, TIMP-1, and TLR-9 by direct binding. Nano-formulation can overcome curcumin problems, increasing the efficacy of curcumin as a drug by maximizing its solubility and bioavailability, enhancing its membrane permeability, and improving its pharmacokinetics, pharmacodynamics and biodistribution. Therefore, green silver nanoparticles (AgNPs) were synthesized in the presence of sunlight by means of the metabolite of Streptomyces malachiticus, and coated with curcumin-chitosan mixture to serve as a drug delivery tool for curcumin to target CCl₄-induced liver fibrosis mouse model. Fibrosis induction significantly increased hepatic gene expression of COL1A1, α-SMA, PDGFRB, and TIMP1, elevated hepatic enzymes, increased histopathological findings, and increased collagen deposition as determined by Mason's trichrome staining. Treatment with naked AgNPs tended to increase these inflammatory effects, while their coating with chitosan, similar to treatment with curcumin only, did not prevent the fibrogenic effect of CCl₄. The induction of liver fibrosis was reversed by concurrent treatment with curcumin/chitosan-coated AgNPs. In this nano form, curcumin was found to be efficient as anti-liver fibrosis drug, maintaining the hepatic architecture and function during fibrosis development. This efficacy can be attributed to its inhibitory role through a direct binding to fibrosis-mediating proteins such as PDGFRB, TIMP-1, TLR-9 and TGF-β.

Consensus docking and MM-PBSA computations identify putative furin protease inhibitors for developing potential therapeutics against COVID-19

The coronavirus disease 2019 (COVID-19) is a pandemic that has severely posed substantial health challenges and claimed millions of lives. Though vaccines have been produced to stem the spread of this disease, the death rate remains high since drugs used for treatment have therapeutic challenges. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the disease, has a slew of potential therapeutic targets. Among them is the furin protease, which has a cleavage site on the virus’s spike protein. The cleavage site facilitates the entry of the virus into human cells via cell–cell fusion. This critical involvement of furin in the disease pathogenicity has made it a viable therapeutic strategy against the virus. This study employs the consensus docking approach using HYBRID and AutoDock Vina to virtually screen a pre-filtered library of 3942 natural product compounds of African origin against the human furin protease (PDB: 4RYD). Twenty of these compounds were selected as hits after meeting molecular docking cut-off of − 7 kcal.mol⁻¹, pose alignment inspection, and having favorable furin-ligand interactions. An area under the curve (AUC) value of 0.72 was computed from the receiver operator characteristic (ROC) curve, and Boltzmann-enhanced discrimination of the ROC curve (BEDROC) value of 0.65 showed that AutoDock Vina was a reasonable tool for selecting actives for this target. Seven of these hits were proposed as potential leads having had bonding interactions with catalytic triad residues Ser368, His194, and Asp153, and other essential residues in the active site with plausible binding free energies between − 189 and − 95 kJ/mol from the Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculations as well as favorable ADME/Tox properties. The molecules were also predicted as antiviral, anti-inflammatory, membrane permeability inhibitors, RNA synthesis inhibitors, cytoprotective, and hepatoprotective with probable activity (Pa) above 0.5 and probable inactivity values below 0.1. Some of them also have anti-influenza activity. Influenza virus has many similarities with SARS-CoV-2 in their mode of entry into human cells as both are facilitated by the furin protease. Pinobanksin 3-(E)-caffeate, one of the potential leads is a propolis compound. Propolis compounds have shown inhibitory effects against ACE2, TMPRSS2, and PAK1 signaling pathways of SARS-CoV-2 in previous studies. Likewise, quercitrin is structurally similar to isoquercetin, which is currently in clinical trials as possible medication for COVID-19.

Recent Progress in the Development of Novel Mycobacterium Cell Wall Inhibitor to Combat Drug-Resistant Tuberculosis

Despite decades of research in drug development against TB, it is still the leading cause of death due to infectious diseases. The long treatment duration, patient noncompliance coupled with the ability of the tuberculosis bacilli to resist the current drugs increases multidrug-resistant tuberculosis that exacerbates the situation. Identification of novel drug targets is important for the advancement of drug development against Mycobacterium tuberculosis. The development of an effective treatment course that could help us eradicates TB. Hence, we require drugs that could eliminate the bacteria and shorten the treatment duration. This review briefly describes the available data on the peptidoglycan component structural characterization, identification of the metabolic pathway, and the key enzymes involved in the peptidoglycan synthesis, like N-Acetylglucosamine-1-phosphate uridyltransferase, mur enzyme, alanine racemase as well as their inhibition. Besides, this paper also provides studies on mycolic acid and arabinogalactan synthesis and the transport mechanisms that show considerable promise as new targets to develop a new product with their inhibiter.

In Silico Screening of Cinnamon (Cinnamomum burmannii) Bioactive Compounds as Acetylcholinesterase Inhibitors

Alzheimer’s is a progressive and neurodegenerative disease that mainly affects people aged 65 years and older. The pathophysiology of Alzheimer’s is possibly related to the depletion of the neurotransmitter acetylcholine (ACh) due to beta-amyloid plaques and neurofibrillary tangles. Secondary metabolites found in cinnamon bark (Cinnamomum burmannii) have the potential as anticholinesterases to treat Alzheimer’s symptoms. This study aimed to identify the potency of bioactive compounds from cinnamon bark as AChE inhibitors in silico through analysis of binding energy, inhibition constants, and types of interactions. The research was conducted by screening virtually 60 test ligands using the PyRx program and molecular docking using the Autodock Tools program. The results of the ligand-receptor interaction analysis showed that 12 of the 15 tested ligands had potential as AChE inhibitors. Epicatechin and medioresinol are the ligands with the best potential for AChE inhibition with affinity close to the natural ligand or donepezil. Epicatechin has a binding energy of −10.0 kcal/mol and inhibition constant of 0.0459 M, with four hydrogen bonds and seven hydrophobic bonds. Meanwhile, medioresinol has −9.9 kcal/mol binding energy and inhibition constant of 0.0543 M, with one hydrogen bond and thirteen hydrophobic bonds.

Synthetic Derivatives against Wild-Type and Non-Wild-Type Sporothrix brasiliensis: In Vitro and In Silico Analyses

Recently, the well-known geographically wide distribution of sporotrichosis in Brazil, combined with the difficulties of effective domestic feline treatment, has emphasized the pressing need for new therapeutic alternatives. This work considers a range of synthetic derivatives as potential antifungals against Sporothrix brasiliensis isolated from cats from the hyperendemic Brazilian region. Six S. brasiliensis isolates from the sporotrichotic lesions of itraconazole responsive or non-responsive domestic cats were studied. The minimum inhibitory concentrations (MICs) of three novel hydrazone derivatives and eleven novel quinone derivatives were determined using the broth microdilution method (M38-A2). In silico tests were also used to predict the pharmacological profile and toxicity parameters of these synthetic derivatives. MICs and MFCs ranged from 1 to >128 µg/mL. The ADMET computational analysis failed to detect toxicity while a good pharmacological predictive profile, with parameters similar to itraconazole, was obtained. Three hydrazone derivatives were particularly promising candidates as antifungal agents against itraconazole-resistant S. brasiliensis from the Brazilian hyperendemic region. Since sporotrichosis is a neglected zoonosis currently spreading in Latin America, particularly in Brazil, the present data can contribute to its future control by alternative antifungal drug design against S. brasiliensis, the most virulent and prevalent species of the hyperendemic context.

Computational study of quinoline-based thiadiazole compounds as potential antileishmanial inhibitors

Leishmaniasis is a severe disease caused by protozoan parasites of the genus Leishmania and it is accountable for sizable morbidity and mortality worldwide.

Iminosugars as glycosyltransferase inhibitors

Iminosugars are naturally occurring carbohydrate analogues known since 1967. These natural compounds and hundreds of their synthetic derivatives prepared over five decades have been mainly exploited to inhibit the glycosidases, the enzymes catalysing the glycosidic bond cleavage, in order to find new drugs for the treatment of type 2 diabetes and other diseases. However, iminosugars are also inhibitors of glycosyltransferases, the enzymes responsible for the synthesis of oligosaccharides and glycoconjugates. The selective inhibition of specific glycosyltransferases involved in cancer or bacterial infections could lead to innovative therapeutic agents. The synthesis and biological properties of all the iminosugars assayed to date as glycosyltransferase inhibitors are reviewed in the present article.

Structure-based in silico approaches for drug discovery against Mycobacterium tuberculosis

Mycobacterium tuberculosis is the causative agent of TB and was estimated to cause 1.4 million death in 2019, alongside 10 million new infections. Drug resistance is a growing issue, with multi-drug resistant infections representing 3.3% of all new infections, hence novel antimycobacterial drugs are urgently required to combat this growing health emergency. Alongside this, increased knowledge of gene essentiality in the pathogenic organism and larger compound databases can aid in the discovery of new drug compounds. The number of protein structures, X-ray based and modelled, is increasing and now accounts for greater than > 80% of all predicted M. tuberculosis proteins; allowing novel targets to be investigated. This review will focus on structure-based in silico approaches for drug discovery, covering a range of complexities and computational demands, with associated antimycobacterial examples. This includes molecular docking, molecular dynamic simulations, ensemble docking and free energy calculations. Applications of machine learning onto each of these approaches will be discussed. The need for experimental validation of computational hits is an essential component, which is unfortunately missing from many current studies. The future outlooks of these approaches will also be discussed.

Protection against peripheral artery disease injury by Ruan Jian Qing Mai formula via metabolic programming

Ruan Jian Qing Mai formula (RJQM), a multicomponent herbal formula, has been widely used to treat peripheral arterial disease (PAD) in China. However, its active compounds and mechanisms of action are still unknown. First, RNA sequencing analysis of 15 healthy and 16 PAD samples showed that 524 PAD differential genes were significantly enriched in Go Ontology (ribonucleotide metabolic process, oxidoreductase complex, and electron transfer activity), Kyoto Encyclopedia of Genes and Genomes (KEGG) and GSEA pathways (OXPHOS and TCA cycle), miRNA (MIR183), and kinase (PAK6). Fifty-three active ingredients in RJQM had similar structures to the seven drug molecules in CLUE. Then, network topology analysis of the 53 components-target-pathway-disease network yielded 10 active ingredients. Finally, computational toxicity estimations showed that the median lethal dose (LD50) of the 10 active ingredients was above 1000 mg/kg, and eight of them did not cause hepatotoxicity, mutagenicity, carcinogenicity, cytotoxicity, and immunotoxicity nor activate 12 toxic pathways. In conclusion, RJQM has a protection effect on PAD by regulating a complex molecular network. Part of the mechanism is associated with the regulation of OXPHOS by 10 active components, which may alleviate mitochondrial dysfunction and pathological metabolic programming.

Molecular Docking of Red Betel (Piper crocatum Ruiz & Pav) Bioactive Compounds as HMG-CoA Reductase Inhibitor

Cholesterol plaque buildup in artery walls occurs due to oxidation of Low-Density Lipoprotein (LDL) molecules by free radicals, which are a risk factor for coronary heart disease. Piper crocatum contains active compounds that can act as HMG-CoA reductase inhibitors, such as flavonoids, alkaloids, polyphenols, tannins, and essential oils. This study aimed to predict the potential of Piper crocatum extract and fraction compounds as HMG-CoA reductase inhibitors by investigating the ligand affinity to the HMG-CoA reductase enzyme. Ligand and receptor preparation was conducted using BIOVIA Discovery Studio Visualizer v16.1.0.15350 and AutoDock Tools v.1.5.6. Molecular docking used AutoDock Vina, while ligand visualization and receptor binding used PyMOL(TM) 1.7.4.5.Edu. The receptor used was HMG-CoA reductase (PDB code: 1HWK) with atorvastatin as a control ligand. Catechin, schisandrin B, and CHEMBL216163 had the highest inhibition with affinity energies of -7.9 kcal/mol, -8.2 kcal/mol, -8.3 kcal/mol, respectively. Amino acid residues that played a role in ligand and receptor interactions were Ser684, Asp690, Lys691, Lys692.

Protection against COVID-19 injury by qingfei paidu decoction via anti-viral, anti-inflammatory activity and metabolic programming

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A novel FUNP analysis on QFPD function.

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QFPD act on COVID-19 via anti-viral, anti-inflammatory and metabolic programming.

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9 QFPD ingredients presented good molecular docking score for 2019-nCov.

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SGMH, MXSG and Others are the top 3 efficient formula for COVID-19.

Qingfei Paidu decoction (QFPD), a multi-component herbal formula, has been widely used to treat COVID-19 in China. However, its active compounds and mechanisms of action are still unknown. Firstly, we divided QFPD into five functional units (FUs) according to the compatibility theory of traditional Chinese medicine. The corresponding common targets of the five FUs were all significantly enriched in Go Ontology (oxidoreductase activity, lipid metabolic process, homeostatic process, etc.), KEGG pathways (steroid biosynthesis, PPAR signaling pathway, adipocytokine signaling pathway, etc.), TTD diseases (chronic inflammatory diseases, asthma, chronic obstructive pulmonary Disease, etc.), miRNA (MIR183), kinase (CDK7) and TF (LXR). QFPD contained 257 specific targets in addition to HCoV, pneumonia and ACE2 co-expression proteins. Then, network topology analysis of the five components-target-pathway-disease networks yielded 67 active ingredients. In addition, ADMET estimations showed that 20 compounds passed the stringent lead-like criteria and in silico drug-likeness test with high gastrointestinal absorption and the median lethal dose (LD50 > 1600 mg/kg). Moreover, 4 specific ingredients (M3, S1, X2 and O2) and 5 common ingredients (MS1, MX16, SX1, WO1 and XO1) of QFPD presented good molecular docking score for 2019-nCov structure and non-structure proteins. Finally, drug perturbation of COVID-19 network robustness showed that all five FUs may protect COVID-19 independently, and target 8 specifically expressed drug-attacked nodes which were related to the bacterial and viral responses, immune system, signaling transduction, etc. In conclusion, our new FUNP analysis showed that QFPD had a protection effect on COVID-19 by regulating a complex molecular network with safety and efficacy. Part of the mechanism was associated with the regulation of anti-viral, anti-inflammatory activity and metabolic programming.

Biosynthesis of Galactan in Mycobacterium tuberculosis as a Viable TB Drug Target?

While target-based drug design has proved successful in several therapeutic areas, this approach has not yet provided compelling outcomes in the field of antibacterial agents. This statement remains especially true for the development of novel therapeutic interventions against tuberculosis, an infectious disease that is among the top ten leading causes of death globally. Mycobacterial galactan is an important component of the protective cell wall core of the tuberculosis pathogen and it could provide a promising target for the design of new drugs. In this review, we summarize the current knowledge on galactan biosynthesis in Mycobacterium tuberculosis, including landmark findings that led to the discovery and understanding of three key enzymes in this pathway: UDP-galactose mutase, and galactofuranosyl transferases GlfT1 and GlfT2. Moreover, we recapitulate the efforts aimed at their inhibition. The predicted common transition states of the three enzymes provide the lucrative possibility of multitargeting in pharmaceutical development, a favourable property in the mitigation of drug resistance. We believe that a tight interplay between target-based computational approaches and experimental methods will result in the development of original inhibitors that could serve as the basis of a new generation of drugs against tuberculosis.