Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:2.7.7.49 (reverse transcriptase)
 31,746 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

A novel oxindole was discovered as an HIV non-nucleoside reverse transcriptase inhibitor via HTS using a cell-based assay. Systematic structural modifications were carried out to establish its SAR. These modifications led to the identification of oxindoles with low nanomolar potency for inhibiting HIV replication. These novel and potent oxindoles could serve as advanced leads for further optimizations.
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PMID:Design, synthesis and biological evaluations of novel oxindoles as HIV-1 non-nucleoside reverse transcriptase inhibitors. Part I. 1648 Aug 65

A novel sulfanyltriazole was discovered as an HIV-1 non-nucleoside reverse transcriptase inhibitor via HTS using a cell-based assay. Chemical modifications and molecular modeling studies were carried out to establish its SAR and understand its interactions with the enzyme. These modifications led to the identification of sulfanyltriazoles with low nanomolar potency for inhibiting HIV-1 replication and promising activities against selected NNRTI resistant mutants. These novel and potent sulfanyltriazoles could serve as advanced leads for further optimization.
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PMID:Synthesis and biological evaluations of sulfanyltriazoles as novel HIV-1 non-nucleoside reverse transcriptase inhibitors. 1678 Nov 49

In many cases at the beginning of an HTS-campaign, some information about active molecules is already available. Often known active compounds (such as substrate analogues, natural products, inhibitors of a related protein or ligands published by a pharmaceutical company) are identified in low-throughput validation studies of the biochemical target. In this study we evaluate the effectiveness of a support vector machine applied for those compounds and used to classify a collection with unknown activity. This approach was aimed at reducing the number of compounds to be tested against the given target. Our method predicts the biological activity of chemical compounds based on only the atom pairs (AP) two dimensional topological descriptors. The supervised support vector machine (SVM) method herein is trained on compounds from the MDL drug data report (MDDR) known to be active for specific protein target. For detailed analysis, five different biological targets were selected including cyclooxygenase-2, dihydrofolate reductase, thrombin, HIV-reverse transcriptase and antagonists of the estrogen receptor. The accuracy of compound identification was estimated using the recall and precision values. The sensitivities for all protein targets exceeded 80% and the classification performance reached 100% for selected targets. In another application of the method, we addressed the absence of an initial set of active compounds for a selected protein target at the beginning of an HTS-campaign. In such a case, virtual high-throughput screening (vHTS) is usually applied by using a flexible docking procedure. However, the vHTS experiment typically contains a large percentage of false positives that should be verified by costly and time-consuming experimental follow-up assays. The subsequent use of our machine learning method was found to improve the speed (since the docking procedure was not required for all compounds from the database) and also the accuracy of the HTS hit lists (the enrichment factor).
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PMID:Target specific compound identification using a support vector machine. 1734 18

A virtual screening protocol has been applied to seek non-nucleoside inhibitors of HIV-1 reverse transcriptase (NNRTIs) and its K103N mutant. First, a chemical similarity search on the Maybridge library was performed using known NNRTIs as reference structures. The top-ranked molecules obtained from this procedure plus 26 known NNRTIs were then docked into the binding sites of the wild-type reverse transcriptase (HIV-RT) and its K103N variant (K103N-RT) using Glide 3.5. The top-ranked 100 compounds from the docking for both proteins were post-scored with a procedure using molecular mechanics and continuum solvation (MM-GB/SA). The validity of the virtual screening protocol was supported by (i) testing of the MM-GB/SA procedure, (ii) agreement between predicted and crystallographic binding poses, (iii) recovery of known potent NNRTIs at the top of both rankings, and (iv) identification of top-scoring library compounds that are close in structure to recently reported NNRTI HTS hits. However, purchase and assaying of selected top-scoring compounds from the library failed to yield active anti-HIV agents. Nevertheless, the highest-ranked database compound, S10087, was pursued as containing a potentially viable core. Subsequent synthesis and assaying of S10087 analogues proposed by further computational analysis yielded anti-HIV agents with EC50 values as low as 310 nM. Thus, with the aid of computational tools, it was possible to evolve a false positive into a true active.
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PMID:Search for non-nucleoside inhibitors of HIV-1 reverse transcriptase using chemical similarity, molecular docking, and MM-GB/SA scoring. 1794 71

A HTS screen led to the identification of a benzofurano[3,2-d]pyrimidin-2-one core structure which upon further optimization resulted in 1 as a potent HIV-1 nucleotide competing reverse transcriptase inhibitor (NcRTI). Investigation of the SAR at N-1 allowed significant improvements in potency and when combined with the incorporation of heterocycles at C-8 resulted in potent analogues not requiring a basic amine to achieve antiviral activity. Additional modifications at N-1 resulted in 33 which demonstrated excellent antiviral potency and improved physicochemical properties.
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PMID:Nucleotide competing reverse transcriptase inhibitors: discovery of a series of non-basic benzofurano[3,2-d]pyrimidin-2-one derived inhibitors. 2354 7