Emphasis has been placed in this article dedicated to DNA damage on recent aspects of the formation and measurement of oxidatively generated damage in cellular DNA in order to provide a comprehensive and updated survey. This includes single pyrimidine and purine base lesions, intrastrand cross-links, purine 5 0 ,8-cyclonucleosides, DNA-protein adducts and interstrand cross-links formed by the reactions of either the nucleobases or the 2-deoxyribose moiety with the hydroxyl radical, one-electron oxidants, singlet oxygen, and hypochlorous acid. In addition, recent information concerning the mechanisms of formation, individual measurement, and repair-rate assessment of bipyrimidine photoproducts in isolated cells and human skin upon exposure to UVB radiation, UVA photons, or solar simulated light is critically reviewed.I n this article, we emphasize recent developments in the formation of damage to cellular DNA mediated by reactive oxygen species (ROS) and oxidizing agents, including singlet oxygen, the hydroxyl radical ( † OH), one-electron oxidants, hypochlorous acid (HOCl), and ten-eleven translocation (TET) oxygenases involved in epigenetic regulation. These advances have been possible because of the development of sensitive and powerful high-performance liquid chromatography-mass spectrometry (HPLC-MS)/ mass spectrometry (MS) methods allowing one to revise previously reported data obtained using methods such as gas chromatographymass spectrometry (GC-MS), immunoassays, and HPLC with single MS detection (Cadet et al. , 2012a. Considerable progress has also been made in the elucidation of oxidative degradation pathways of isolated DNA and related model compounds (for recent comprehensive reviews, see Gimisis and Cismaş 2006;Neeley and Essigmann 2006;Pratviel and Meunier 2006;von Sonntag 2006;Cadet et al. 2008Cadet et al. , 2010Cadet et al. , 2012bDedon 2008;Burrows 2009;Wagner and Cadet 2010). In addition, there is much complementary information on solar-radiation-induced formation of bipyrimidine photoproducts in the DNA of fibroblasts, keratinocytes, and human skin. In particular, the distribution of UVA and UVB photoproducts has been determined, allowing accurate determination of their rates of repair (Cadet et al.

Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages.

We present a substantial update to the open-source POVME binding pocket analysis software. New capabilities of POVME 3.0 include a flexible chemical coloring scheme for feature identification, post-analysis tools for comparing large ensembles of pockets (e.g., from molecular dynamics simulations), and the introduction of scripts and methods that facilitate binding pocket comparison and analysis. We envision the use of this software for visualization of binding pocket dynamics, selection of representative structures for ensemble docking, and incorporation of molecular dynamics results into ligand design efforts.

We present a methodology for defining and optimizing a general force field for classical molecular simulations, and we describe its use to derive the Open Force Field 1.0.0 smallmolecule force field, codenamed Parsley. Rather than using traditional atom typing, our approach is built on the SMIRKSnative Open Force Field (SMIRNOFF) parameter assignment formalism, which handles increases in the diversity and specificity of the force field definition without needlessly increasing the complexity of the specification. Parameters are optimized with the ForceBalance tool, based on reference quantum chemical data that include torsion potential energy profiles, optimized gas-phase structures, and vibrational frequencies. These quantum reference data are computed and are maintained with QCArchive, an opensource and freely available distributed computing and database software ecosystem. In this initial application of the method, we present essentially a full optimization of all valence parameters and report tests of the resulting force field against compounds and data types outside the training set. These tests show improvements in optimized geometries and conformational energetics and demonstrate that Parsley's accuracy for liquid properties is similar to that of other general force fields, as is accuracy on binding free energies. We find that this initial Parsley force field affords accuracy similar to that of other general force fields when used to calculate relative binding free energies spanning 199 protein−ligand systems. Additionally, the resulting infrastructure allows us to rapidly optimize an entirely new force field with minimal human intervention.

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