This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.

The importance of interactions between the brain and the gastrointestinal tract has been increasingly recognized in recent years. It has been proposed that dysregulation and abnormalities in the brain-gut axis contribute to the etiology of a variety of central nervous system disorders. Particularly, dysbiosis, or impaired microbiota, has been implicated in multiple neurological and psychological disorders. The present paper reviews current evidence and theories concerning the possible mechanisms by which microbiota dysfunction contributes to the pathogenesis of schizophrenia and major depressive disorder. Clinical trials that investigated the possibility of treating both illnesses by correcting and rebalancing microbiota with probiotics are also reviewed. Overall, despite the accumulated knowledge in this field, more studies are warranted and required to further our understanding of the brain-gut axis and the possibility of targeting microbiota as a treatment option for schizophrenia and major depressive disorder.

ObjectivesAnxiety has been suggested to be associated with poor outcomes in patients with acute coronary syndrome (ACS). However, results of previous follow-up studies were inconsistent. The aim of this meta-analysis was to evaluate the association between anxiety and clinical outcomes in patients with ACS, and to investigate the potential role of depression underlying the above association.DesignA meta-analysis of prospective follow-up studies.SettingHospitals.ParticipantsPatients with ACS.InterventionsWe included related prospective follow-up studies up through 20 July 2019 that were identified by searching PubMed and Embase databases. A random-effect model was used for the meta-analysis. Anxiety was evaluated by validated instruments at baseline.Primary and secondary outcome measuresWe determined the association between anxiety and risks of mortality and adverse cardiovascular events (MACEs) in patients with ACS.ResultsOur analysis included 17 studies involving 39 038 patients wqith ACS. Anxiety was independently associated with increased mortality risk (adjusted risk ratio (RR) 1.21, 95% CI 1.07 to 1.37, p=0.002) and MACEs (adjusted RR 1.47, 95% CI 1.24 to 1.74, p<0.001) in patients with ACS. Subgroup analyses showed that depression may at least partly confound the association between anxiety and poor outcomes in patients with ACS. Adjustment of depression significantly attenuated the association between anxiety and MACEs (adjusted RR 1.25, 95% CI 1.04 to 1.52, p=0.02). Moreover, anxiety was not significantly associated with mortality risk after adjusting for depression (adjusted RR 0.88, 95% CI 0.66 to 1.17, p=0.37).ConclusionsAnxiety is associated with increased risk of mortality and MACEs in patients with ACS. However, at least part of the association may be confounded by concurrent depressive symptoms in these patients.

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