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

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          Abstract

          Gulf War Illness (GWI) is a chronic multisymptom illness characterized by fatigue, musculoskeletal pain, and gastrointestinal and cognitive dysfunction believed to stem from chemical exposures during the 1990–1991 Persian Gulf War. There are currently no treatments; however, previous studies have predicted a putative multi-intervention treatment composed of inhibiting Th1 immune cytokines followed by inhibition of the glucocorticoid receptor (GCR) to treat GWI. These predictions suggest the use of specific monoclonal antibodies or suramin to target interleukin-2 and tumor necrosis factor α , followed by mifepristone to inhibit the GCR. In addition to this putative treatment strategy, there exist a variety of medications that target GWI symptomatology. As pharmaceuticals are promiscuous molecules, binding to multiple sites beyond their intended targets, leading to off-target interactions, it is key to ensure that none of these medications interfere with the proposed treatment avenue. Here, we used the drug docking programs AutoDock 4.2, AutoDock Vina, and Schrödinger’s Glide to assess the potential off-target immune and hormone interactions of 43 FDA-approved drugs commonly used to treat GWI symptoms in order to determine their putative polypharmacology and minimize adverse drug effects in a combined pharmaceutical treatment. Several of these FDA-approved drugs were predicted to be novel binders of immune and hormonal targets, suggesting caution for their use in the proposed GWI treatment strategy symptoms.

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          Most cited references35

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          The role of inflammation in depression: from evolutionary imperative to modern treatment target.

          Crosstalk between inflammatory pathways and neurocircuits in the brain can lead to behavioural responses, such as avoidance and alarm, that are likely to have provided early humans with an evolutionary advantage in their interactions with pathogens and predators. However, in modern times, such interactions between inflammation and the brain appear to drive the development of depression and may contribute to non-responsiveness to current antidepressant therapies. Recent data have elucidated the mechanisms by which the innate and adaptive immune systems interact with neurotransmitters and neurocircuits to influence the risk for depression. Here, we detail our current understanding of these pathways and discuss the therapeutic potential of targeting the immune system to treat depression.
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            Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median

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              Ligand docking and binding site analysis with PyMOL and Autodock/Vina

              Docking of small molecule compounds into the binding site of a receptor and estimating the binding affinity of the complex is an important part of the structure-based drug design process. For a thorough understanding of the structural principles that determine the strength of a protein/ligand complex both, an accurate and fast docking protocol and the ability to visualize binding geometries and interactions are mandatory. Here we present an interface between the popular molecular graphics system PyMOL and the molecular docking suites Autodock and Vina and demonstrate how the combination of docking and visualization can aid structure-based drug design efforts.
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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                26 October 2018
                November 2018
                : 19
                : 11
                : 3355
                Affiliations
                [1 ]Institute for Neuro-Immune Medicine, Nova Southeastern University, Fort Lauderdale, FL 33314, USA; rj426@ 123456nova.edu (R.J.); nklimas@ 123456nova.edu (N.K.); Gordon.Broderick@ 123456rochesterregional.org (G.B.)
                [2 ]Department of Psychology & Neuroscience, Nova Southeastern University, Fort Lauderdale, FL 33314, USA
                [3 ]Department of Clinical Immunology, Nova Southeastern University, Fort Lauderdale, FL 33314, USA
                [4 ]Pharmaceuticals and Bioengineering Department, Southwest Research Institute, San Antonio, TX 78238, USA; jonathan.bohmann@ 123456swri.org
                [5 ]Pharmaceuticals and Bioengineering, Chemistry and Chemical Engineering Division, Southwest Research Institute, San Antonio, TX 78238, USA; gloria.gutierrez@ 123456swri.org
                [6 ]Miami Veterans Affairs Medical Center, Miami, FL 33125, USA
                [7 ]Centre for Clinical Systems Biology, Rochester General Hospital Research Institute, Rochester, NY 14617, USA
                [8 ]Rochester Institute of Technology, Rochester, NY 14623, USA
                [9 ]Department of Computer Science, Nova Southeastern University, Fort Lauderdale, FL 33314, USA
                Author notes
                [* ]Correspondence: tcraddock@ 123456nova.edu
                Author information
                https://orcid.org/0000-0001-7223-4322
                https://orcid.org/0000-0002-3588-8252
                https://orcid.org/0000-0001-7244-6317
                Article
                ijms-19-03355
                10.3390/ijms19113355
                6274917
                30373189
                2858074d-7f79-44a6-9777-ace13e4bf9c5
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 22 August 2018
                : 16 October 2018
                Categories
                Article

                Molecular biology
                gulf war illness,consensus docking,off-target interactions,side effects,multi-drug therapy,polypharmacology,treatment course design

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