452 research outputs found

    From Sensors to Silencers: Quinoline- and Benzimidazole-Sulfonamides as Inhibitors for Zinc Proteases

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    Derived from the extensive work in the area of small molecule zinc(II) ion sensors, chelating fragment libraries of quinoline- and benzimidazole-sulfonamides have been prepared and screened against several different zinc(II)-dependent matrix metalloproteinases (MMPs). The fragments show impressive inhibition of these metalloenzymes and preferences for different MMPs based on the nature of the chelating group. The findings show that focused chelator libraries are a powerful strategy for the discovery of lead fragments for metalloprotein inhibition

    X‐Ray Crystallography and Free Energy Calculations Reveal the Binding Mechanism of A2A Adenosine Receptor Antagonists

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    We present a robust protocol based on iterations of free energy perturbation (FEP) calculations, chemical synthesis, biophysical mapping and X‐ray crystallography to reveal the binding mode of an antagonist series to the A2A adenosine receptor (AR). Eight A2AAR binding site mutations from biophysical mapping experiments were initially analyzed with sidechain FEP simulations, performed on alternate binding modes. The results distinctively supported one binding mode, which was subsequently used to design new chromone derivatives. Their affinities for the A2AAR were experimentally determined and investigated through a cycle of ligand‐FEP calculations, validating the binding orientation of the different chemical substituents proposed. Subsequent X‐ray crystallography of the A2AAR with a low and a high affinity chromone derivative confirmed the predicted binding orientation. The new molecules and structures here reported were driven by free energy calculations, and provide new insights on antagonist binding to the A2AAR, an emerging target in immuno‐oncologyThis work was financially supported by the Swedish Research Council (Grant 521‐2014‐2118); Consellería de Cultura, Educación e Ordenación Universitaria of the Galician Government (Grant ED431B2017/70); Centro Singular de Investigación de Galicia accreditation 2016–2019 (Grant ED431G/09), and the European Regional Development Fund (ERDF). Additional support from the Swedish strategic research program eSSENCE is acknowledged. The computations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC). This research program has been developed in the frame of the European COST action ERNEST (Grant CA 18133) and GLISTEN (Grant CA 1207)S

    Evaluation of machine-learning methods for ligand-based virtual screening

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    Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it is little different in screening performance from a previously described kernel that had been developed specifically for the analysis of binary fingerprint representations of molecular structure. We then evaluate the performance of an NBC when the training-set contains only a very few active molecules. In such cases, a simpler approach based on group fusion would appear to provide superior screening performance, especially when structurally heterogeneous datasets are to be processed

    Structure-Based Discovery of A2A Adenosine Receptor Ligands

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    The recent determination of X-ray structures of pharmacologically relevant GPCRs has made these targets accessible to structure-based ligand discovery. Here we explore whether novel chemotypes may be discovered for the A(2A) adenosine receptor, based on complementarity to its recently determined structure. The A(2A) adenosine receptor signals in the periphery and the CNS, with agonists explored as anti-inflammatory drugs and antagonists explored for neurodegenerative diseases. We used molecular docking to screen a 1.4 million compound database against the X-ray structure computationally and tested 20 high-ranking, previously unknown molecules experimentally. Of these 35% showed substantial activity with affinities between 200 nM and 9 microM. For the most potent of these new inhibitors, over 50-fold specificity was observed for the A(2A) versus the related A(1) and A(3) subtypes. These high hit rates and affinities at least partly reflect the bias of commercial libraries toward GPCR-like chemotypes, an issue that we attempt to investigate quantitatively. Despite this bias, many of the most potent new ligands were novel, dissimilar from known ligands, providing new lead structures for modulation of this medically important target

    Small molecule binding sites on the Ras:SOS complex can be exploited for inhibition of Ras activation.

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    Constitutively active mutant KRas displays a reduced rate of GTP hydrolysis via both intrinsic and GTPase-activating protein-catalyzed mechanisms, resulting in the perpetual activation of Ras pathways. We describe a fragment screening campaign using X-ray crystallography that led to the discovery of three fragment binding sites on the Ras:SOS complex. The identification of tool compounds binding at each of these sites allowed exploration of two new approaches to Ras pathway inhibition by stabilizing or covalently modifying the Ras:SOS complex to prevent the reloading of Ras with GTP. Initially, we identified ligands that bound reversibly to the Ras:SOS complex in two distinct sites, but these compounds were not sufficiently potent inhibitors to validate our stabilization hypothesis. We conclude by demonstrating that covalent modification of Cys118 on Ras leads to a novel mechanism of inhibition of the SOS-mediated interaction between Ras and Raf and is effective at inhibiting the exchange of labeled GDP in both mutant (G12C and G12V) and wild type Ras
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