Pyrone-based inhibitors of metalloproteinase types 2 and 3 may work as conformation-selective inhibitors.

Matrix metalloproteinases are zinc-containing enzymes capable of degrading all components of the extracellular matrix. Owing to their role in human disease, matrix metalloproteinase have been the subject of extensive study. A bioinorganic approach was recently used to identify novel inhibitors based on a maltol zinc-binding group, but accompanying molecular-docking studies failed to explain why one of these inhibitors, AM-6, had approximately 2500-fold selectivity for MMP-3 over MMP-2. A number of studies have suggested that the matrix-metalloproteinase active site is highly flexible, leading some to speculate that differences in active-site flexibility may explain inhibitor selectivity. To extend the bioinorganic approach in a way that accounts for MMP-2 and MMP-3 dynamics, we here investigate the predicted binding modes and energies of AM-6 docked into multiple structures extracted from matrix-metalloproteinase molecular dynamics simulations. Our findings suggest that accounting for protein dynamics is essential for the accurate prediction of binding affinity and selectivity. Additionally, AM-6 and other similar inhibitors likely select for and stabilize only a subpopulation of all matrix-metalloproteinase conformations sampled by the apo protein. Consequently, when attempting to predict ligand affinity and selectivity using an ensemble of protein structures, it may be wise to disregard protein conformations that cannot accommodate the ligand

Electron localisation in static and time-dependent one-dimensional model systems

Electron localization is the tendency of an electron in a many-body system to exclude other electrons from its vicinity. Using a new natural measure of localization based on the exact manyelectron wavefunction, we find that localization can vary considerably between different ground-state systems, and can also be strongly disrupted, as a function of time, when a system is driven by an applied electric field. We use our new measure to assess the well-known electron localization function (ELF), both in its approximate single-particle form (often applied within density-functional theory) and its full many-particle form. The full ELF always gives an excellent description of localization, but the approximate ELF fails in time-dependent situations, even when the exact Kohn-Sham orbitals are employed.Comment: 7 pages, 4 figure

The infrastructural conditions of (de-)growth: The case of the internet

Infrastructure studies represent a domain that remains significantly uncharted among degrowth scholars. This is paradoxical considering that infrastructures constitute a fundamental prerequisite for the equitable distribution of many aspects of human well-being that degrowth proponents emphasize. Nonetheless, the substantial resource and energy consumption associated with infrastructures cannot be overlooked. The internet offers an instructive case study in this sense, at its best it forges human connections and is productive of considerable societal value. The resource implications of the often-overlooked internet physical layer of data-centres and submarine cables needs to be acknowledged. Furthermore, the ways in which assumptions of perpetual growth are built into this global infrastructure via the logic layer of internet protocols and other governing mechanisms such as finance and network design need to be examined if we are to determine the extent to which such infrastructures are inherently growth dependent. In making these two arguments, we draw upon the work of both Science and Technology Studies (STS) and Large Technological System (LTS) studies on the inherent problems of large infrastructures which have thus far seen little engagement with questions of degrowth. We review the case of the internet and suggest a number of scenarios that illustrate potential roles for such infrastructures in any planned reduction of economic activity

Novel cruzain inhibitors for the treatment of Chagas' disease.

The protozoan parasite Trypanosoma cruzi, the etiological agent of Chagas' disease, affects millions of individuals and continues to be an important global health concern. The poor efficacy and unfavorable side effects of current treatments necessitate novel therapeutics. Cruzain, the major cysteine protease of T. cruzi, is one potential novel target. Recent advances in a class of vinyl sulfone inhibitors are encouraging; however, as most potential therapeutics fail in clinical trials and both disease progression and resistance call for combination therapy with several drugs, the identification of additional classes of inhibitory molecules is essential. Using an exhaustive virtual-screening and experimental validation approach, we identify several additional small-molecule cruzain inhibitors. Further optimization of these chemical scaffolds could lead to the development of novel drugs useful in the treatment of Chagas' disease

Non-bisphosphonate inhibitors of isoprenoid biosynthesis identified via computer-aided drug design.

The relaxed complex scheme, a virtual-screening methodology that accounts for protein receptor flexibility, was used to identify a low-micromolar, non-bisphosphonate inhibitor of farnesyl diphosphate synthase. Serendipitously, we also found that several predicted farnesyl diphosphate synthase inhibitors were low-micromolar inhibitors of undecaprenyl diphosphate synthase. These results are of interest because farnesyl diphosphate synthase inhibitors are being pursued as both anti-infective and anticancer agents, and undecaprenyl diphosphate synthase inhibitors are antibacterial drug leads

Role of long-range exact exchange in polaron charge transition levels: The case of MgO

Predicting the degree of localization and calculating the trapping energies of polarons in insulators by density functional theory (DFT) is challenging. Hybrid functionals are often reparametrized to obtain accurate results and the a priori selection of these parameters is still an open question. Here we test the accuracy of several range-separated hybrid functionals, all reparametrized to produce an accurate band gap, by calculating the charge transition levels (CTLs) of experimentally well-studied hole polaron defect centers in MgO. We show that the functional with screened long-range exact exchange is moderately but consistently more accurate than functionals which do not include long-range exact exchange. We provide evidence that the source of the improved accuracy is the eigenvalue associated with the valence band maximum of the bulk material. We discuss the extent to which this accuracy relates to Koopmans' compliance of the defect energy level

Gypsum-DL: an open-source program for preparing small-molecule libraries for structure-based virtual screening

Computational techniques such as structure-based virtual screening require carefully prepared 3D models of potential small-molecule ligands. Though powerful, existing commercial programs for virtual-library preparation have restrictive and/or expensive licenses. Freely available alternatives, though often effective, do not fully account for all possible ionization, tautomeric, and ring-conformational variants. We here present Gypsum-DL, a free, robust open-source program that addresses these challenges. As input, Gypsum-DL accepts virtual compound libraries in SMILES or flat SDF formats. For each molecule in the virtual library, it enumerates appropriate ionization, tautomeric, chiral, cis/trans isomeric, and ring-conformational forms. As output, Gypsum-DL produces an SDF file containing each molecular form, with 3D coordinates assigned. To demonstrate its utility, we processed 1558 molecules taken from the NCI Diversity Set VI and 56,608 molecules taken from a Distributed Drug Discovery (D3) combinatorial virtual library. We also used 4463 high-quality protein-ligand complexes from the PDBBind database to show that Gypsum-DL processing can improve virtual-screening pose prediction. Gypsum-DL is available free of charge under the terms of the Apache License, Version 2.0

Towards the development of novel Trypanosoma brucei RNA editing ligase 1 inhibitors

Abstract Background Trypanosoma brucei (T. brucei) is an infectious agent for which drug development has been largely neglected. We here use a recently developed computer program called AutoGrow to add interacting molecular fragments to S5, a known inhibitor of the validated T. brucei drug target RNA editing ligase 1, in order to improve its predicted binding affinity. Results The proposed binding modes of the resulting compounds mimic that of ATP, the native substrate, and provide insights into novel protein-ligand interactions that may be exploited in future drug-discovery projects. Conclusions We are hopeful that these new predicted inhibitors will aid medicinal chemists in developing novel therapeutics to fight human African trypanosomiasis