Using a Consensus Docking Approach to Predict Adverse Drug Reactions in Combination Drug Therapies for Gulf War Illness

Sulfadiazine Exerts Potential Anticancer Effect in HepG2 and MCF7 Cells by Inhibiting TNFα, IL1b, COX-1, COX-2, 5-LOX Gene Expression: Evidence from In Vitro and Computational Studies

Drug repurposing is a promising approach that has the potential to revolutionize the drug discovery and development process. By leveraging existing drugs, we can bring new treatments to patients more quickly and affordably. Anti-inflammatory drugs have been shown to target multiple pathways involved in cancer development and progression. This suggests that they may be more effective in treating cancer than drugs that target a single pathway. Cell viability was measured using the MTT assay. The expression of genes related to inflammation (TNFa, IL1b, COX-1, COX-2, and 5-LOX) was measured in HepG2, MCF7, and THLE-2 cells using qPCR. The levels of TNFα, IL1b, COX-1, COX-2, and 5-LOX were also measured in these cells using an ELISA kit. An enzyme binding assay revealed that sulfadiazine expressed weaker inhibitory activity against COX-2 (IC50 = 5.27 μM) in comparison with the COX-2 selective reference inhibitor celecoxib (COX-2 IC50 = 1.94 μM). However, a more balanced inhibitory effect was revealed for sulfadiazine against the COX/LOX pathway with greater affinity towards 5-LOX (IC50 = 19.1 μM) versus COX-1 (IC50 = 18.4 μM) as compared to celecoxib (5-LOX IC50 = 16.7 μM, and COX-1 IC50 = 5.9 μM). MTT assays revealed the IC50 values of 245.69 ± 4.1 µM and 215.68 ± 3.8 µM on HepG2 and MCF7 cell lines, respectively, compared to the standard drug cisplatin (66.92 ± 1.8 µM and 46.83 ± 1.3 µM, respectively). The anti-inflammatory effect of sulfadiazine was also depicted through its effect on the levels of inflammatory markers and inflammation-related genes (TNFα, IL1b, COX-1, COX-2, 5-LOX). Molecular simulation studies revealed key binding interactions that explain the difference in the activity profiles of sulfadiazine compared to celecoxib. The results suggest that sulfadiazine exhibited balanced inhibitory activity against the 5-LOX/COX-1 enzymes compared to the selective COX-2 inhibitor, celecoxib. These findings highlight the potential of sulfadiazine as a potential anticancer agent through balanced inhibitory activity against the COX/LOX pathway and reduction in the expression of inflammatory genes.

Design of Inhibitors That Target the Menin-Mixed-Lineage Leukemia Interaction

The prognosis of mixed-lineage leukemia (MLL) has remained a significant health concern, especially for infants. The minimal treatments available for this aggressive type of leukemia has been an ongoing problem. Chromosomal translocations of the KMT2A gene are known as MLL, which expresses MLL fusion proteins. A protein called menin is an important oncogenic cofactor for these MLL fusion proteins, thus providing a new avenue for treatments against this subset of acute leukemias. In this study, we report results using the structure-based drug design (SBDD) approach to discover potential novel MLL-mediated leukemia inhibitors from natural products against menin. The three-dimensional (3D) protein model was derived from Protein Databank (Protein ID: 4GQ4), and EasyModeller 4.0 and I-TASSER were used to fix missing residues during rebuilding. Out of the ten protein models generated (five from EasyModeller and I-TASSER each), one model was selected. The selected model demonstrated the most reasonable quality and had 75.5% of residues in the most favored regions, 18.3% of residues in additionally allowed regions, 3.3% of residues in generously allowed regions, and 2.9% of residues in disallowed regions. A ligand library containing 25,131 ligands from a Chinese database was virtually screened using AutoDock Vina, in addition to three known menin inhibitors. The top 10 compounds including ZINC000103526876, ZINC000095913861, ZINC000095912705, ZINC000085530497, ZINC000095912718, ZINC000070451048, ZINC000085530488, ZINC000095912706, ZINC000103580868, and ZINC000103584057 had binding energies of -11.0, -10.7, -10.6, -10.2, -10.2, -9.9, -9.9, -9.9, -9.9, and -9.9 kcal/mol, respectively. To confirm the stability of the menin-ligand complexes and the binding mechanisms, molecular dynamics simulations including molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) computations were performed. The amino acid residues that were found to be potentially crucial in ligand binding included Phe243, Met283, Cys246, Tyr281, Ala247, Ser160, Asn287, Asp185, Ser183, Tyr328, Asn249, His186, Leu182, Ile248, and Pro250. MI-2-2 and PubChem CIDs 71777742 and 36294 were shown to possess anti-menin properties; thus, this justifies a need to experimentally determine the activity of the identified compounds. The compounds identified herein were found to have good pharmacological profiles and had negligible toxicity. Additionally, these compounds were predicted as antileukemic, antineoplastic, chemopreventive, and apoptotic agents. The 10 natural compounds can be further explored as potential novel agents for the effective treatment of MLL-mediated leukemia.

Molecular Docking and Dynamics Simulation Studies Predict Potential Anti-ADAR2 Inhibitors: Implications for the Treatment of Cancer, Neurological, Immunological and Infectious Diseases

Altered RNA editing has been linked to several neurodevelopmental disorders, including autism spectrum disorder (ASD) and intellectual disability, in addition to depression, schizophrenia, some cancers, viral infections and autoimmune disorders. The human ADAR2 is a potential therapeutic target for managing these various disorders due to its crucial role in adenosine to inosine editing. This study applied consensus scoring to rank potential ADAR2 inhibitors after performing molecular docking with AutoDock Vina and Glide (Maestro), using a library of 35,161 compounds obtained from traditional Chinese medicine. A total of 47 compounds were predicted to be good binders of the human ADAR2 and had insignificant toxicity concerns. Molecular dynamics (MD) simulations, including the molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) procedure, also emphasized the binding of the shortlisted compounds. The potential compounds had plausible binding free energies ranging from −81.304 to −1068.26 kJ/mol from the MM/PBSA calculations. ZINC000085511995, a naphthoquinone had more negative binding free energy (−1068.26 kJ/mol) than inositol hexakisphosphate (IHP) [−873.873 kJ/mol], an agonist and a strong binder of ADAR2. The potential displacement of IHP by ZINC000085511995 in the IHP binding site of ADAR2 could be explored for possible deactivation of ADAR2. Bayesian-based biological activity prediction corroborates the neuropharmacological, antineoplastic and antiviral activity of the potential lead compounds. All the potential lead compounds, except ZINC000014612330 and ZINC000013462928, were predicted to be inhibitors of various deaminases. The potential lead compounds also had probability of activity (Pa) > 0.442 and probability of inactivity (Pi) < 0.116 values for treating acute neurologic disorders, except for ZINC000085996580 and ZINC000013462928. Pursuing these compounds for their anti-ADAR2 activities holds a promising future, especially against neurological disorders, some cancers and viral infections caused by RNA viruses. Molecular interaction, hydrogen bond and per-residue decomposition analyses predicted Arg400, Arg401, Lys519, Trp687, Glu689, and Lys690 as hot-spot residues in the ADAR2 IHP binding site. Most of the top compounds were observed to have naphthoquinone, indole, furanocoumarin or benzofuran moieties. Serotonin and tryptophan, which are beneficial in digestive regulation, improving sleep cycle and mood, are indole derivatives. These chemical series may have the potential to treat neurological disorders, prion diseases, some cancers, specific viral infections, metabolic disorders and eating disorders through the disruption of ADAR2 pathways. A total of nine potential lead compounds were shortlisted as plausible modulators of ADAR2.

Dysbiosis in gastrointestinal pathophysiology: Role of the gut microbiome in Gulf War Illness

Gulf War Illness (GWI) has been reported in 25%-35% of veterans returned from the Gulf war. Symptoms of GWI are varied and include both neurological and gastrointestinal symptoms as well as chronic fatigue. Development of GWI has been associated with chemical exposure particularly with exposure to pyridostigmine bromide (PB) and permethrin. Recent studies have found that the pathology of GWI is connected to changes in the gut microbiota, that is the gut dysbiosis. In studies using animal models, the exposure to PB and permethrin resulted in similar changes in the gut microbiome as these found in GW veterans with GWI. Studies using animal models have also shown that phytochemicals like curcumin are beneficial in reducing the symptoms and that the extracellular vesicles (EV) released from gut bacteria and from the intestinal epithelium can both promote diseases and suppress diseases through the intercellular communication mechanisms. The intestinal epithelium cells produce EVs and these EVs of intestinal epithelium origin are found to suppress inflammatory bowel disease severity, suggesting the benefits of utilizing EV in treatments. On the contrary, EV from the plasma of septic mice enhanced the level of proinflammatory cytokines in vitro and neutrophils and macrophages in vivo, suggesting differences in the EV depending on the types of cells they were originated and/or influences of environmental changes. These studies suggest that targeting the EV that specifically have positive influences may become a new therapeutic strategy in the treatment of veterans with GWI.

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.

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.

Study on the Characteristics of Small-Molecule Kinase Inhibitors-Related Drug-Induced Liver Injury

Background and Aim: More than half of the small-molecule kinase inhibitors (KIs) induced liver injury clinically. Meanwhile, studies have shown a close relationship between mitochondrial damage and drug-induced liver injury (DILI). We aimed to study KIs and the binding between drugs and mitochondrial proteins to find factors related to DILI occurrence.

Methods: A total of 1,223 oral FDA-approved drugs were collected and analyzed, including 44 KIs. Fisher’s exact test was used to analyze DILI potential and risk of different factors. A total of 187 human mitochondrial proteins were further collected, and high-throughput molecular docking was performed between human mitochondrial proteins and drugs in the data set. The molecular dynamics simulation was used to optimize and evaluate the dynamic binding behavior of the selected mitochondrial protein/KI complexes.

Results: The possibility of KIs to produce DILI is much higher than that of other types (OR = 46.89, p = 9.28E-13). A few DILI risk factors were identified, including molecular weight (MW) between 400 and 600, the defined daily dose (DDD) ≥ 100 mg/day, the octanol–water partition coefficient (LogP) ≥ 3, and the degree of liver metabolism (LM) more than 50%. Drugs that met this combination of rules were found to have a higher DILI risk than controls (OR = 8.28, p = 4.82E-05) and were more likely to cause severe DILI (OR = 8.26, p = 5.06E-04). The docking results showed that KIs had a significant higher affinity with human mitochondrial proteins (p = 4.19E-11) than other drug types. Furthermore, the five proteins with the lowest docking score were selected for molecular dynamics simulation, and the smallest fluctuation of the backbone RMSD curve was found in the protein 5FS8/KI complexes, which indicated the best stability of the protein 5FS8 bound to KIs.

Conclusions: KIs were found to have the highest odds ratio of causing DILI. MW was significantly related to the production of DILI, and the average docking scores of KI drugs were found to be significantly different from other classes. Further analysis identified the top binding mitochondrial proteins for KIs, and specific binding sites were analyzed. The optimization of molecular docking results by molecular dynamics simulation may contribute to further studying the mechanism of DILI.

Application of Reverse Docking in the Research of Small Molecule Drugs and Traditional Chinese Medicine

With the development of structural biology and data mining, computer-aided drug design (CADD) has been playing an important role in all aspects of new drug development. Reverse docking, a method of virtual screening based on molecular docking in CADD, is widely used in drug repositioning, drug rescue, and traditional Chinese medicine (TCM) research, for it can search for macromolecular targets that can bind to a given ligand molecule. This review revealed the principle of reverse docking, summarized common target protein databases and docking procedures, and enumerated the applications of reverse docking in drug repositioning, adverse drug reactions, traditional Chinese medicine, and COVID-19 treatment. Hope our work can give some inspiration to researchers engaged in drug development.

A Placebo-Controlled, Pseudo-Randomized, Crossover Trial of Botanical Agents for Gulf War Illness: Curcumin (Curcuma longa), Boswellia (Boswellia serrata), and French Maritime Pine Bark (Pinus pinaster)

This report is part of a larger study designed to rapidly and efficiently screen potential treatments for Gulf War Illness (GWI) by testing nine different botanicals. In this placebo-controlled, pseudo-randomized, crossover clinical trial of 20 men with GWI, we tested three botanical agents with putative peripheral and central anti-inflammatory actions: curcumin (Curcuma longa), boswellia (Boswellia serrata), and French maritime pine bark extract (Pinus pinaster). Participants completed 30 +/− 3 days of baseline symptom reports, followed by 30 +/− 3 days of placebo, 30 +/− 3 days of lower-dose botanical, and 30 +/− 3 days of higher-dose botanical. Participants then repeated the process with a new botanical until completing up to three botanical cycles. Data were analyzed using linear mixed models. Curcumin reduced GWI symptom severity significantly more than placebo at both the lower (p < 0.0001) and higher (p = 0.0003) dosages. Boswellia was not more effective than placebo at reducing GWI symptoms at either the lower (p = 0.726) or higher (p = 0.869) dosages. Maritime pine was not more effective than placebo at the lower dosage (p = 0.954) but was more effective than placebo at the higher dosage (p = 0.006). This study provides preliminary evidence that curcumin and maritime pine may help alleviate symptoms of GWI. As a screening study, a final determination of the efficacy of these compounds for all individuals with GWI cannot be made, and further studies will need to be conducted to determine strength and durability of effects, as well as optimal dosage. These results suggest that GWI may, at least in part, involve systemic inflammatory processes. This trial was registered on ClinicalTrials.gov (NCT02909686) on 13 September 2016.

Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches

Virtual screening (VS) is an outstanding cornerstone in the drug discovery pipeline. A variety of computational approaches, which are generally classified as ligand-based (LB) and structure-based (SB) techniques, exploit key structural and physicochemical properties of ligands and targets to enable the screening of virtual libraries in the search of active compounds. Though LB and SB methods have found widespread application in the discovery of novel drug-like candidates, their complementary natures have stimulated continued efforts toward the development of hybrid strategies that combine LB and SB techniques, integrating them in a holistic computational framework that exploits the available information of both ligand and target to enhance the success of drug discovery projects. In this review, we analyze the main strategies and concepts that have emerged in the last years for defining hybrid LB + SB computational schemes in VS studies. Particularly, attention is focused on the combination of molecular similarity and docking, illustrating them with selected applications taken from the literature.

Alterations in high-order diffusion imaging in veterans with Gulf War Illness is associated with chemical weapons exposure and mild traumatic brain injury

The complex etiology behind Gulf War Illness (GWI) has been attributed to the combined exposure to neurotoxicant chemicals, brain injuries, and some combat experiences. Chronic GWI symptoms have been shown to be associated with intensified neuroinflammatory responses in animal and human studies. To investigate the neuroinflammatory responses and potential causes in Gulf War (GW) veterans, we focused on the effects of chemical/biological weapons (CBW) exposure and mild traumatic brain injury (mTBI) during the war. We applied a novel MRI diffusion processing method, Neurite density imaging (NDI), on high-order diffusion imaging to estimate microstructural alterations of brain imaging in Gulf War veterans with and without GWI, and collected plasma proinflammatory cytokine samples as well as self-reported health symptom scores. Our study identified microstructural changes specific to GWI in the frontal and limbic regions due to CBW and mTBI, and further showed distinctive microstructural patterns such that widespread changes were associated with CBW and more focal changes on diffusion imaging were observed in GW veterans with an mTBI during the war. In addition, microstructural alterations on brain imaging correlated with upregulated blood proinflammatory cytokine markers TNFRI and TNFRII and with worse outcomes on self-reported symptom measures for fatigue and sleep functioning. Taken together, these results suggest TNF signaling mediated inflammation affects frontal and limbic regions of the brain, which may contribute to the fatigue and sleep symptoms of the disease and suggest a strong neuroinflammatory component to GWI. These results also suggest exposures to chemical weapons and mTBI during the war are associated with different patterns of peripheral and central inflammation and highlight the brain regions vulnerable to further subtle microscale morphological changes and chronic signaling to nearby glia.

PLIDflow: an open-source workflow for the online analysis of protein-ligand docking using galaxy

MOTIVATION

Molecular docking is aimed at predicting the conformation of small-molecule (ligands) within an identified binding site (BS) in a target protein (receptor). Protein-ligand docking plays an important role in modern drug discovery and biochemistry for protein engineering. However, efficient docking analysis of proteins requires prior knowledge of the BS, which is not always known. The process which covers BS identification and protein-ligand docking usually requires the combination of different programs, which require several input parameters. This is furtherly aggravated when factoring in computational demands, such as CPU-time. Therefore, these types of simulation experiments can become a complex process for researchers without a background in computer sciences.

RESULTS

To overcome these problems, we have designed an automatic computational workflow (WF) to process protein-ligand complexes, which runs from the identification of the possible BSs positions to the prediction of the experimental binding modes and affinities of the ligand. This open-access WF runs under the Galaxy platform that integrates public domain software. The results of the proposed method are in close agreement with state-of-the-art docking software.

AVAILABILITY AND IMPLEMENTATION

Software is available at: https://pistacho.ac.uma.es/galaxy-bitlab.

CONTACT

euv@uma.es.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

DRUGPATH: The Drug Gene Pathway Meta-Database

The complexity of modern-day diseases often requires drug treatment therapies consisting of multiple pharmaceutical interventions, which can lead to adverse drug reactions for patients. A priori prediction of these reactions would not only improve the quality of life for patients but also save both time and money in regards to pharmaceutical research. Consequently, the drug-gene-pathway (DRUGPATH) meta-database was developed to map known interactions between drugs, genes, and pathways among other information in order to easily identify potential adverse drug events. DRUGPATH utilizes expert-curated sources such as PharmGKB, DrugBank, and the FDA's NDC database to identify known as well as previously unknown/overlooked relationships, and currently contains 12,940 unique drugs, 3933 unique pathways, 5185 unique targets, and 3662 unique genes. Moreover, there are 59,561 unique drug-gene interactions, 77,808 unique gene-pathway interactions, and over 1 million unique drug-pathway interactions.

Consensus Analyses in Molecular Docking Studies Applied to Medicinal Chemistry

The increasing number of computational studies in medicinal chemistry involving molecular docking has put the technique forward as promising in Computer-Aided Drug Design. Considering the main method in the virtual screening based on the structure, consensus analysis of docking has been applied in several studies to overcome limitations of algorithms of different programs and mainly to increase the reliability of the results and reduce the number of false positives. However, some consensus scoring strategies are difficult to apply and, in some cases, are not reliable due to the small number of datasets tested. Thus, for such a methodology to be successful, it is necessary to understand why, when and how to use consensus docking. Therefore, the present study aims to present different approaches to docking consensus, applications, and several scoring strategies that have been successful and can be applied in future studies.

Molecular Docking: Shifting Paradigms in Drug Discovery

Molecular docking is an established in silico structure-based method widely used in drug discovery. Docking enables the identification of novel compounds of therapeutic interest, predicting ligand-target interactions at a molecular level, or delineating structure-activity relationships (SAR), without knowing a priori the chemical structure of other target modulators. Although it was originally developed to help understanding the mechanisms of molecular recognition between small and large molecules, uses and applications of docking in drug discovery have heavily changed over the last years. In this review, we describe how molecular docking was firstly applied to assist in drug discovery tasks. Then, we illustrate newer and emergent uses and applications of docking, including prediction of adverse effects, polypharmacology, drug repurposing, and target fishing and profiling, discussing also future applications and further potential of this technique when combined with emergent techniques, such as artificial intelligence.