4D-QSAR: perspectives in drug design.
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ABSTRACT:
SUBMITTER: Andrade CH
PROVIDER: S-EPMC6263259 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Four-dimensional quantitative structure-activity relationship (4D-QSAR) analysis was applied on a series of 54 2-arylbenzothiophene derivatives, synthesized by Grese and coworkers, based on raloxifene (an estrogen receptor-alpha antagonist), and evaluated as ERa ligands and as inhibitors of estrogen-stimulated proliferation of MCF-7 breast cancer cells. The conformations of each analogue, sampled from a molecular dynamics simulation, were placed in a grid cell lattice according to three trial alignments, considering two grid cell sizes (1.0 and 2.0 Å). The QSAR equations, generated by a combined scheme of genetic algorithms (GA) and partial least squares (PLS) regression, were evaluated by "leave-one-out" cross-validation, using a training set of 41 compounds. External validation was performed using a test set of 13 compounds. The obtained 4D-QSAR models are in agreement with the proposed mechanism of action for raloxifene. This study allowed a quantitative prediction of compounds' potency and supported the design of new raloxifene analogs.
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Project description:The Flavivirus Zika virus (ZIKV) is the causal agent of neurological disorders like microcephaly in newborns or Guillain-Barre syndrome. Its NS5 protein embeds a methyltransferase (MTase) domain involved in the formation of the viral mRNA cap. We investigated the structural and functional properties of the ZIKV MTase. We show that the ZIKV MTase can methylate RNA cap structures at the N-7 position of the cap, and at the 2'-O position on the ribose of the first nucleotide, yielding a cap-1 structure. In addition, the ZIKV MTase methylates the ribose 2'-O position of internal adenosines of RNA substrates. The crystal structure of the ZIKV MTase determined at a 2.01-Å resolution reveals a crystallographic homodimer. One chain is bound to the methyl donor (S-adenosyl-l-methionine [SAM]) and shows a high structural similarity to the dengue virus (DENV) MTase. The second chain lacks SAM and displays conformational changes in the ?X ?-helix contributing to the SAM and RNA binding. These conformational modifications reveal a possible molecular mechanism of the enzymatic turnover involving a conserved Ser/Arg motif. In the second chain, the SAM binding site accommodates a sulfate close to a glycerol that could serve as a basis for structure-based drug design. In addition, compounds known to inhibit the DENV MTase show similar inhibition potency on the ZIKV MTase. Altogether these results contribute to a better understanding of the ZIKV MTase, a central player in viral replication and host innate immune response, and lay the basis for the development of potential antiviral drugs.IMPORTANCE The Zika virus (ZIKV) is associated with microcephaly in newborns, and other neurological disorders such as Guillain-Barre syndrome. It is urgent to develop antiviral strategies inhibiting the viral replication. The ZIKV NS5 embeds a methyltransferase involved in the viral mRNA capping process, which is essential for viral replication and control of virus detection by innate immune mechanisms. We demonstrate that the ZIKV methyltransferase methylates the mRNA cap and adenosines located in RNA sequences. The structure of ZIKV methyltransferase shows high structural similarities to the dengue virus methyltransferase, but conformational specificities highlight the role of a conserved Ser/Arg motif, which participates in RNA and SAM recognition during the reaction turnover. In addition, the SAM binding site accommodates a sulfate and a glycerol, offering structural information to initiate structure-based drug design. Altogether, these results contribute to a better understanding of the Flavivirus methyltransferases, which are central players in the virus replication.
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Project description:Flaviviridae are small enveloped viruses hosting a positive-sense single-stranded RNA genome. Besides yellow fever virus, a landmark case in the history of virology, members of the Flavivirus genus, such as West Nile virus and dengue virus, are increasingly gaining attention due to their re-emergence and incidence in different areas of the world. Additional environmental and demographic considerations suggest that novel or known flaviviruses will continue to emerge in the future. Nevertheless, up to few years ago flaviviruses were considered low interest candidates for drug design. At the start of the European Union VIZIER Project, in 2004, just two crystal structures of protein domains from the flaviviral replication machinery were known. Such pioneering studies, however, indicated the flaviviral replication complex as a promising target for the development of antiviral compounds. Here we review structural and functional aspects emerging from the characterization of two main components (NS3 and NS5 proteins) of the flavivirus replication complex. Most of the reviewed results were achieved within the European Union VIZIER Project, and cover topics that span from viral genomics to structural biology and inhibition mechanisms. The ultimate aim of the reported approaches is to shed light on the design and development of antiviral drug leads.
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Project description:HIGHLIGHTS Many CNS targets are being explored for multi-target drug designNew databases and cheminformatic methods enable prediction of primary pharmaceutical target and off-targets of compoundsQSAR, virtual screening and docking methods increase the potential of rational drug design The diverse cerebral mechanisms implicated in Central Nervous System (CNS) diseases together with the heterogeneous and overlapping nature of phenotypes indicated that multitarget strategies may be appropriate for the improved treatment of complex brain diseases. Understanding how the neurotransmitter systems interact is also important in optimizing therapeutic strategies. Pharmacological intervention on one target will often influence another one, such as the well-established serotonin-dopamine interaction or the dopamine-glutamate interaction. It is now accepted that drug action can involve plural targets and that polypharmacological interaction with multiple targets, to address disease in more subtle and effective ways, is a key concept for development of novel drug candidates against complex CNS diseases. A multi-target therapeutic strategy for Alzheimer's disease resulted in the development of very effective Multi-Target Designed Ligands (MTDL) that act on both the cholinergic and monoaminergic systems, and also retard the progression of neurodegeneration by inhibiting amyloid aggregation. Many compounds already in databases have been investigated as ligands for multiple targets in drug-discovery programs. A probabilistic method, the Parzen-Rosenblatt Window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D1-R/D2-R/5-HT2A -R/H3-R are promising novel drug candidates with improved efficacy and beneficial neuroleptic and procognitive activities in treatment of Alzheimer's and related neurodegenerative diseases. Structural information for drug targets permits docking and virtual screening and exploration of the molecular determinants of binding, hence facilitating the design of multi-targeted drugs. The crystal structures and models of enzymes of the monoaminergic and cholinergic systems have been used to investigate the structural origins of target selectivity and to identify molecular determinants, in order to design MTDLs.
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Project description:Computational chemistry has come of age in drug discovery. Indeed, most pharmaceutical development programs rely on computer-based data and results at some point. Herein, we discuss recent applications of advanced simulation techniques to difficult challenges in drug discovery. These entail the characterization of allosteric mechanisms and the identification of allosteric sites or cryptic pockets determined by protein motions, which are not immediately evident in the experimental structure of the target; the study of ligand binding mechanisms and their kinetic profiles; and the evaluation of drug-target affinities. We analyze different approaches to tackle challenging and emerging biological targets. Finally, we discuss the possible perspectives of future application of computation in drug discovery.
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