Design of dual ligands using excessive pharmacophore query alignment : from 7th German Conference on Chemoinformatics: 25 CIC-Workshop Goslar, Germany, 6 - 8 November 2011

Dual- or multi-target ligands have gained increased attention in the past years due to several advantages, including more simple pharmacokinetic and phamarcodynamic properties compared to a combined application of several drugs. Furthermore multi-target ligands often possess improved efficacy. We present a new approach for the discovery of dual-target ligands using aligned pharmacophore models combined with a shape-based scoring. Starting with two sets of known active compounds for each target, a number of different pharmacophore models is generated and subjected to pairwise graph-based alignment using the Kabsch-Algorithm. Since a compound may be able to bind to different targets in different conformations, the algorithm aligns pairs of pharmacophore models sharing the same features which are not necessarily at the exactly same spatial distance. Using the aligned models, a pharmacophore search on a multi-conformation-database is performed to find compounds matching both models. The potentially “dual” ligands are scored by a shape-based comparison with the known active molecules using ShaEP. Using this approach, we performed a prospective fragment-based virtual screening for dual 5-LO/sEH inhibitors. Both enzymes play an important role in the arachidonic acid cascade and are involved in inflammatory processes, pain, cardiovascular diseases and allergic reactions. Beside several new selective inhibitors we were able to find a compound inhibiting both enzymes in low micromolar concentrations. The results indicate that the idea of aligned pharmacophore models can be successfully employed for the discovery of dual-target ligands

Design of dual ligands using excessive pharmacophore query alignment

Dual- or multi-target ligands have gained increased attention in the past years due to several advantages, including more simple pharmacokinetic and phamarcodynamic properties compared to a combined application of several drugs. Furthermore multi-target ligands often possess improved efficacy. We present a new approach for the discovery of dual-target ligands using aligned pharmacophore models combined with a shape-based scoring. Starting with two sets of known active compounds for each target, a number of different pharmacophore models is generated and subjected to pairwise graph-based alignment using the Kabsch-Algorithm. Since a compound may be able to bind to different targets in different conformations, the algorithm aligns pairs of pharmacophore models sharing the same features which are not necessarily at the exactly same spatial distance. Using the aligned models, a pharmacophore search on a multi-conformation-database is performed to find compounds matching both models. The potentially “dual” ligands are scored by a shape-based comparison with the known active molecules using ShaEP. Using this approach, we performed a prospective fragment-based virtual screening for dual 5-LO/sEH inhibitors. Both enzymes play an important role in the arachidonic acid cascade and are involved in inflammatory processes, pain, cardiovascular diseases and allergic reactions. Beside several new selective inhibitors we were able to find a compound inhibiting both enzymes in low micromolar concentrations. The results indicate that the idea of aligned pharmacophore models can be successfully employed for the discovery of dual-target ligands

The association of serotonin receptor 3A methylation with maternal violence exposure, neural activity, and child aggression

Background Methylation of the serotonin 3A receptor gene (HTR3A) has been linked to child maltreatment and adult psychopathology. The present study examined whether HTR3A methylation might be associated with mothers' lifetime exposure to interpersonal violence (IPV), IPV-related psychopathology, child disturbance of attachment, and maternal neural activity. Methods Number of maternal lifetime IPV exposures and measures of maternal psychopathology including posttraumatic stress disorder (PTSD), major depression and aggressive behavior (AgB), and a measure of child attachment disturbance known as “secure base distortion” (SBD) were assessed in a sample of 35 mothers and children aged 12–42 months. Brain fMRI activation was assessed in mothers using 30-s silent film excerpts depicting menacing adult male-female interactions versus prosocial and neutral interactions. Group and continuous analyses were performed to test for associations between clinical and fMRI variables with DNA methylation. Results Maternal IPV exposure-frequency was associated with maternal PTSD; and maternal IPV-PTSD was in turn associated with child SBD. Methylation status of several CpG sites in the HTR3A gene was associated with maternal IPV and IPV-PTSD severity, AgB and child SBD, in particular, self-endangering behavior. Methylation status at a specific CpG site (CpG2_III) was associated with decreased medial prefrontal cortical (mPFC) activity in response to film-stimuli of adult male-female interactions evocative of violence as compared to prosocial and neutral interactions. Conclusions Methylation status of the HTR3A gene in mothers is linked to maternal IPV-related psychopathology, trauma-induced brain activation patterns, and child attachment disturbance in the form of SBD during a sensitive period in the development of self-regulation

Coronary Artery Calcium Scores: Current Thinking and Clinical Applications

Most incident coronary disease occurs in previously asymptomatic individuals who were considered to be at a lower risk by traditional screening methods. There is a definite advantage if these individuals could be reclassified into a higher risk category, thereby impacting disease outcomes favorably. Coronary artery calcium scores have been recognized as an independent marker for adverse prognosis in coronary disease. Multiple population based studies have acknowledged the shortcomings of risk prediction models such as the Framingham risk score or the Procam score. The science behind coronary calcium is discussed briefly followed by a review of current thinking on calcium scores. An attempt has been made to summarize the appropriate indications and use of calcium scores

DrugBank screening revealed alitretinoin and bexarotene as liver X receptor modulators

In silico screening of DrugBank database to detect liver X receptor (LXR) agonism of marketed drugs using a self-organizing map and successive LXR-Gal4 hybrid reporter gene assay evaluation in vitro discovered alitretinoin and bexarotene as partial liver X receptor agonists. Dose-response curves demonstrated that plasma concentrations observed in clinical trials are sufficient for LXR activation and thus could account for LXR-mediated side-effects such as hypercholesterolemia and hyperlipidemia. The discovered drugs are the first reported dual LXR/RXR agonists and can serve as lead structures for LXR and dual LXR/RXR modulator development

VAMMPIRE: A Matched Molecular Pairs Database for Structure-Based Drug Design and Optimization

Structure-based optimization to improve the affinity of a lead compound is an established approach in drug discovery. Knowledge-based databases holding molecular replacements can be supportive in the optimization process. We introduce a strategy to relate the substitution effect within matched molecular pairs (MMPs) to the atom environment within the cocrystallized protein–ligand complex. Virtually Aligned Matched Molecular Pairs Including Receptor Environment (VAMMPIRE) database and the supplementary web interface (http://vammpire.pharmchem.uni-frankfurt.de) provide valuable information for structure-based lead optimization

VAMMPIRE-LORD: A Web Server for Straightforward Lead Optimization Using Matched Molecular Pairs

VAMMPIRE-LORD (lead optimization by rational design) describes an innovative strategy to improve the binding affinity of a defined lead compound using 3D matched molecular pairs (3D-MMPs). 3D-MMPs are defined as pairs of molecules that differ in exactly one structural transformation and have a known bioactive conformation. We developed a novel atom-pair descriptor (LORD_FP) that represents the ligandas well as the receptor environmentof a chemical transformation and built a predictive model based on 17 602 3D-MMPs. We demonstrate that the created model is able to extrapolate the knowledge of a chemical transformation and the associated effect on ligand affinity to any similar system. VAMMPIRE-LORD was implemented as a web server that guides the user step-by-step through the optimization process of a defined lead compound