Abstract: In this paper we review the current status of high-performance computing applications in the general area of drug discovery. We provide an introduction to the methodologies applied at atomic and molecular scales, followed by three specific examples of implementation of these tools. The first example describes in silico modeling of the adsorption of small molecules to organic and inorganic surfaces, which may be applied to drug delivery issues. The second example involves DNA translocation through nanopores with major significance to DNA sequencing efforts. The final example offers an overview of computer-aided drug design, with some illustrative examples of its usefulness.

Abstract: Designer receptors exclusively activated by designer drugs (DREADDs) derived from muscarinic receptors not only are a powerful tool to test causality in basic neuroscience but also are potentially amenable to clinical translation. A major obstacle, however, is that the widely used agonist clozapine N-oxide undergoes conversion to clozapine, which penetrates the blood-brain barrier but has an unfavorable side effect profile. Perlapine has been reported to activate DREADDs at nanomolar concentrations but is not approved for use in humans by the Food and Drug Administration or the European Medicines Agency, limiting its translational potential. Here, we report that the atypical antipsychotic drug olanzapine, widely available in various formulations, is a potent agonist of the human M4 muscarinic receptor-based DREADD, facilitating clinical translation of chemogenetics to treat central nervous system diseases.

Abstract: Background: Wilms' tumor (WT) is a common kidney tumor in early childhood which is characterized by multiple congenital anomalies and syndromes. With the continuous improvement of medical standards, the cure rate and survival period of WT have increased. However, its molecular mechanism is still elusive. Methods: A comprehensive multidimensional integration strategy was used to comprehensively analyze the mechanisms of WT. Results: By integrating the potential pathogenic genes of kidney cancer and performing co-expression analysis on the disease-related genes, 23 functional modules were obtained. All the genes were differentially expressed in WT, and were mainly involved in many biological processes and signaling pathways, such as Wnt/beta-catenin, mTOR/ERK and calcineurin. Additionally, based on the relationship between transcriptional and post-transcriptional regulatory systems, in functional modules, transcription factors (TFs) including STAT3, HDAC1 and SP1 as well as non-coding RNAs (ncRNAs) such as miR-335-5p, miR-21-5p and TUG1 were identified. Finally, potential drugs for these multifactor regulated dysfunctional modules which may have certain pharmacological or toxicological effects on WT such as cisplatin, sorafenib, and zinc were predicted. Conclusions: A multidimensional dysfunction mechanism, involving disease-related genes, TFs and ncRNAs was revealed in the pathogenesis of WT. Functional modules were used to predict potential drugs which can be used in personalized therapy and drug delivery. This study explored the pathogenesis of WT from a new perspective, and provides new candidate targets and therapeutic drugs for improving the cure rate of WT.

Abstract: Retinoid X receptor alpha (RXRalpha), a central member of the nuclear receptor superfamily and a key regulator of many signal transduction pathways, has been an attractive drug target. We previously discovered that an N-terminally truncated form of RXRalpha can be induced by specific ligands to form homotetramers, which, as a result of conformational selection, forms the basis for inhibiting the nongenomic activation of RXRalpha. Here, we report the identification and characterization of atorvastatin as a new RXRalpha tetramer stabilizer by using structure-based virtual screening and demonstrate that virtual library screening can be used to aid in identifying RXRalpha ligands that can induce its tetramerization. In this study, docking was applied to screen the FDA-approved small molecule drugs in the DrugBank 4.0 collection. Two compounds were selected and purchased for testing. We showed that the selected atorvastatin could bind to RXRalpha to promote RXRalpha-LBD tetramerization. We also showed that atorvastatin possessed RXRalpha-dependent apoptotic effects. In addition, we used a chemical approach to aid in the studies of the binding mode of atorvastatin.

Abstract: The development of new proton-pump inhibitors (PPIs) with less adverse effects by lowering the pKa values of nitrogen atoms in pyrimidine rings has been previously suggested by our group. In this work, we proposed that new PPIs should have the following features: (1) number of ring II = number of ring I + 1; (2) preferably five, six, or seven-membered heteroatomic ring for stability; and (3) 1 < pKa1 < 4. Six molecular scaffolds based on the aforementioned criteria were constructed, and R groups were extracted from compounds in extensive data sources. A virtual molecule dataset was established, and the pKa values of specific atoms on the molecules in the dataset were calculated to select the molecules with required pKa values. Drug-likeness screening was further conducted to obtain the candidates that significantly reduced the adverse effects of long-term PPI use. This study provided insights and tools for designing targeted molecules in silico that are suitable for practical applications.

Abstract: Several public databases have emerged over the past decade to enable chemo- and bio-informatics research in the field of drug development. To a naive observer, as well as many seasoned professionals, the differences among many drug databases are unclear. We assessed the availability of all pharmaceuticals with evidence of clinical testing (i.e., been in at least a Phase I clinical trial) and highlight the major differences and similarities between public databases containing clinically tested pharmaceuticals. We review a selection of the most recent and prominent databases including: ChEMBL, CRIB NME, DrugBank, DrugCentral, PubChem, repoDB, SuperDrug2 and WITHDRAWN, and found that approximately 11700 unique active pharmaceutical ingredients are available in the public domain, with evidence of clinical testing.

Abstract: Photopharmacology relies on molecules that change their biological activity upon irradiation. Many of these are derived from known drugs by replacing their core with an isosteric azobenzene photoswitch (azologization). The question is how many of the known bioactive ligands could be addressed in such a way. Here, we systematically assess the space of molecules amenable to azologization from databases of bioactive molecules (DrugBank, PDB, CHEMBL) and the Cambridge Structural Database. Shape similarity scoring functions (3DAPfp) and analyses of dihedral angles are employed to quantify the structural homology between a bioactive molecule and the cis or trans isomer of its corresponding azolog ("azoster") and assess which isomer is likely to be active. Our analysis suggests that a very large number of bioactive ligands (>40000) is amenable to azologization and that many new biological targets could be addressed with photopharmacology. N-Aryl benzamides, 1,2-diarylethanes, and benzyl phenyl ethers are particularly suited for this approach, while benzylanilines and sulfonamides appear to be less well-matched. On the basis of our analysis, the majority of azosters are expected to be active in their trans form. The broad applicability of our approach is demonstrated with photoswitches that target a nuclear hormone receptor (RAR) and a lipid processing enzyme (LTA4 hydrolase).

Abstract: Habituation is a simple form of learning where animals learn to reduce their responses to repeated innocuous stimuli [1]. Habituation is thought to occur via at least two temporally and molecularly distinct mechanisms, which lead to short-term memories that last for seconds to minutes and long-term memories that last for hours or longer [1, 2]. Here, we focus on long-term habituation, which, due to the extended time course, necessitates stable alterations to circuit properties [2-4]. In its simplest form, long-term habituation could result from a plasticity event at a single point in a circuit, and many studies have focused on identifying the site and underlying mechanism of plasticity [5-10]. However, it is possible that these individual sites are only one of many points in the circuit where plasticity is occurring. Indeed, studies of short-term habituation in C. elegans indicate that in this paradigm, multiple genetically separable mechanisms operate to adapt specific aspects of behavior [11-13]. Here, we use a visual assay in which larval zebrafish habituate their response to sudden reductions in illumination (dark flashes) [14, 15]. Through behavioral analyses, we find that multiple components of the dark-flash response habituate independently of one another using different molecular mechanisms. This is consistent with a modular model in which habituation originates from multiple independent processes, each adapting specific components of behavior. This may allow animals to more specifically or flexibly habituate based on stimulus context or internal states.

Abstract: BACKGROUND: Pharmacogenomics (PGx) studies how genomic variations impact variations in drug response phenotypes. Knowledge in pharmacogenomics is typically composed of units that have the form of ternary relationships gene variant - drug - adverse event. Such a relationship states that an adverse event may occur for patients having the specified gene variant and being exposed to the specified drug. State-of-the-art knowledge in PGx is mainly available in reference databases such as PharmGKB and reported in scientific biomedical literature. But, PGx knowledge can also be discovered from clinical data, such as Electronic Health Records (EHRs), and in this case, may either correspond to new knowledge or confirm state-of-the-art knowledge that lacks "clinical counterpart" or validation. For this reason, there is a need for automatic comparison of knowledge units from distinct sources. RESULTS: In this article, we propose an approach, based on Semantic Web technologies, to represent and compare PGx knowledge units. To this end, we developed PGxO, a simple ontology that represents PGx knowledge units and their components. Combined with PROV-O, an ontology developed by the W3C to represent provenance information, PGxO enables encoding and associating provenance information to PGx relationships. Additionally, we introduce a set of rules to reconcile PGx knowledge, i.e. to identify when two relationships, potentially expressed using different vocabularies and levels of granularity, refer to the same, or to different knowledge units. We evaluated our ontology and rules by populating PGxO with knowledge units extracted from PharmGKB (2701), the literature (65,720) and from discoveries reported in EHR analysis studies (only 10, manually extracted); and by testing their similarity. We called PGxLOD (PGx Linked Open Data) the resulting knowledge base that represents and reconciles knowledge units of those various origins. CONCLUSIONS: The proposed ontology and reconciliation rules constitute a first step toward a more complete framework for knowledge comparison in PGx. In this direction, the experimental instantiation of PGxO, named PGxLOD, illustrates the ability and difficulties of reconciling various existing knowledge sources.