Institut de Chimie Radicalaire

Mitochondria are recognized as one of the most important targets for new drug design in cancer, cardiovascular, and neurological diseases. Currently, the most effective way to deliver drugs specifically to mitochondria is by covalent linking a lipophilic cation such as an alkyltriphenylphosphonium moiety to a pharmacophore of interest. Other delocalized lipophilic cations, such as rhodamine, natural and synthetic mitochondria-targeting peptides, and nanoparticle vehicles, have also been used for mitochondrial delivery of small molecules. Depending on the approach used, and the cell and mitochondrial membrane potentials, more than 1000-fold higher mitochondrial concentration can be achieved. Mitochondrial targeting has been developed to study mitochondrial physiology and dysfunction and the interaction between mitochondria and other subcellular organelles and for treatment of a variety of diseases such as neurodegeneration and cancer. In this Review, we discuss efforts to target small-molecule compounds to mitochondria for probing mitochondria function, as diagnostic tools and potential therapeutics. We describe the physicochemical basis for mitochondrial accumulation of lipophilic cations, synthetic chemistry strategies to target compounds to mitochondria, mitochondrial probes, and sensors, and examples of mitochondrial targeting of bioactive compounds. Finally, we review published attempts to apply mitochondria-targeted agents for the treatment of cancer and neurodegenerative diseases.

Some of the new unique features of the MOLCAS quantum chemistry package version 7 are presented in this report. In particular, the Cholesky decomposition method applied to some quantum chemical methods is described. This approach is used both in the context of a straight forward approximation of the two-electron integrals and in the generation of so-called auxiliary basis sets. The article describes how the method is implemented for most known wave functions models: self-consistent field, density functional theory, 2nd order perturbation theory, complete-active space self-consistent field multiconfigurational reference 2nd order perturbation theory, and coupled-cluster methods. The report further elaborates on the implementation of a restricted-active space self-consistent field reference function in conjunction with 2nd order perturbation theory. The average atomic natural orbital basis for relativistic calculations, covering the whole periodic table, are described and associated unique properties are demonstrated. Furthermore, the use of the arbitrary order Douglas-Kroll-Hess transformation for one-component relativistic calculations and its implementation are discussed. This section especially focuses on the implementation of the so-called picture-change-free atomic orbital property integrals. Moreover, the ElectroStatic Potential Fitted scheme, a version of a quantum mechanics/molecular mechanics hybrid method implemented in MOLCAS, is described and discussed. Finally, the report discusses the use of the MOLCAS package for advanced studies of photo chemical phenomena and the usefulness of the algorithms for constrained geometry optimization in MOLCAS in association with such studies.

In this report, we summarize and describe the recent unique updates and additions to the M olcas quantum chemistry program suite as contained in release version 8. These updates include natural and spin orbitals for studies of magnetic properties, local and linear scaling methods for the Douglas–Kroll–Hess transformation, the generalized active space concept in MCSCF methods, a combination of multiconfigurational wave functions with density functional theory in the MC‐PDFT method, additional methods for computation of magnetic properties, methods for diabatization, analytical gradients of state average complete active space SCF in association with density fitting, methods for constrained fragment optimization, large‐scale parallel multireference configuration interaction including analytic gradients via the interface to the C olumbus package, and approximations of the CASPT2 method to be used for computations of large systems. In addition, the report includes the description of a computational machinery for nonlinear optical spectroscopy through an interface to the QM/MM package C obramm . Further, a module to run molecular dynamics simulations is added, two surface hopping algorithms are included to enable nonadiabatic calculations, and the DQ method for diabatization is added. Finally, we report on the subject of improvements with respects to alternative file options and parallelization. © 2015 Wiley Periodicals, Inc.

Nonadiabatic mixed quantum-classical (NA-MQC) dynamics methods form a class of computational theoretical approaches in quantum chemistry tailored to investigate the time evolution of nonadiabatic phenomena in molecules and supramolecular assemblies. NA-MQC is characterized by a partition of the molecular system into two subsystems: one to be treated quantum mechanically (usually but not restricted to electrons) and another to be dealt with classically (nuclei). The two subsystems are connected through nonadiabatic couplings terms to enforce self-consistency. A local approximation underlies the classical subsystem, implying that direct dynamics can be simulated, without needing precomputed potential energy surfaces. The NA-MQC split allows reducing computational costs, enabling the treatment of realistic molecular systems in diverse fields. Starting from the three most well-established methods-mean-field Ehrenfest, trajectory surface hopping, and multiple spawning-this review focuses on the NA-MQC dynamics methods and programs developed in the last 10 years. It stresses the relations between approaches and their domains of application. The electronic structure methods most commonly used together with NA-MQC dynamics are reviewed as well. The accuracy and precision of NA-MQC simulations are critically discussed, and general guidelines to choose an adequate method for each application are delivered.

MOLCAS/OpenMolcas is an ab initio electronic structure program providing a large set of computational methods from Hartree-Fock and density functional theory to various implementations of multiconfigurational theory. This article provides a comprehensive overview of the main features of the code, specifically reviewing the use of the code in previously reported chemical applications as well as more recent applications including the calculation of magnetic properties from optimized density matrix renormalization group wave functions.

Understanding the properties of electronically excited states is a challenging task that becomes increasingly important for numerous applications in chemistry, molecular physics, molecular biology, and materials science. A substantial impact is exerted by the fascinating progress in time-resolved spectroscopy, which leads to a strongly growing demand for theoretical methods to describe the characteristic features of excited states accurately. Whereas for electronic ground state problems of stable molecules the quantum chemical methodology is now so well developed that informed nonexperts can use it efficiently, the situation is entirely different concerning the investigation of excited states. This review is devoted to a specific class of approaches, usually denoted as multireference (MR) methods, the generality of which is needed for solving many spectroscopic or photodynamical problems. However, the understanding and proper application of these MR methods is often found to be difficult due to their complexity and their computational cost. The purpose of this review is to provide an overview of the most important facts about the different theoretical approaches available and to present by means of a collection of characteristic examples useful information, which can guide the reader in performing their own applications.

Cyclic monomers bearing either vinyl or exomethylene groups have the ability to be polymerized through a radical pathway via a ring-opening mechanism (addition-fragmentation process), leading to the introduction of functionalities in the polymer backbone. Radical ring-opening polymerization (rROP) combines the advantages of both ring-opening polymerization and radical polymerization, that is the preparation of polymers bearing heteroatoms in the backbone but with the ease and robustness of a radical process. This current review presents a comprehensive description of rROP by detailing: (i) the various monomers that polymerize through rROP; (ii) the main parameters that govern the rROP mechanism; (iii) the copolymerization by conventional or controlled/living radical polymerization between rROP monomers and traditional vinyl monomers to obtain copolymers with advanced properties; (iv) the different applications (low shrinkage materials and preparation of (bio)degradable materials) of rROP monomer-containing materials, and (v) the main alternatives to rROP to induce degradability to materials obtained by a radical polymerization.

Abstract Summary: Reversible addition‐fragmentation chain transfer (RAFT) polymerization is a recent and very versatile controlled radical polymerization technique that has enabled the synthesis of a wide range of macromolecules with well‐defined structures, compositions, and functionalities. The RAFT process is based on a reversible addition‐fragmentation reaction mediated by thiocarbonylthio compounds used as chain transfer agents (CTAs). A great variety of CTAs have been designed and synthesized so far with different kinds of substituents. In this review, all of the CTAs encountered in the literature from 1998 to date are reported and classified according to several criteria : i) the structure of their substituents, ii) the various monomers that they have been polymerized with, and iii) the type of polymerization that has been performed (solution, dispersed media, surface initiated, and copolymerization). Moreover, the influence of various parameters is discussed, especially the CTA structure relative to the monomer and the experimental conditions (temperature, pressure, initiation, CTA/initiator ratio, concentration), in order to optimise the kinetics and the efficiency of the molecular‐weight‐distribution control. Schematic of the RAFT polymerization. magnified image Schematic of the RAFT polymerization.

Pancreatic ductal adenocarcinoma is one of the most intractable and fatal cancer. The decreased blood vessel density displayed by this tumor not only favors its resistance to chemotherapy but also participates in its aggressiveness due to the consequent high degree of hypoxia. It is indeed clear that hypoxia promotes selective pressure on malignant cells that must develop adaptive metabolic responses to reach their energetic and biosynthetic demands. Here, using a well-defined mouse model of pancreatic cancer, we report that hypoxic areas from pancreatic ductal adenocarcinoma are mainly composed of epithelial cells harboring epithelial-mesenchymal transition features and expressing glycolytic markers, two characteristics associated with tumor aggressiveness. We also show that hypoxia increases the "glycolytic" switch of pancreatic cancer cells from oxydative phosphorylation to lactate production and we demonstrate that increased lactate efflux from hypoxic cancer cells favors the growth of normoxic cancer cells. In addition, we show that glutamine metabolization by hypoxic pancreatic tumor cells is necessary for their survival. Metabolized glucose and glutamine converge toward a common pathway, termed hexosamine biosynthetic pathway, which allows O-linked N-acetylglucosamine modifications of proteins. Here, we report that hypoxia increases transcription of hexosamine biosynthetic pathway genes as well as levels of O-glycosylated proteins and that O-linked N-acetylglucosaminylation of proteins is a process required for hypoxic pancreatic cancer cell survival. Our results demonstrate that hypoxia-driven metabolic adaptive processes, such as high glycolytic rate and hexosamine biosynthetic pathway activation, favor hypoxic and normoxic cancer cell survival and correlate with pancreatic ductal adenocarcinoma aggressiveness.

Benefiting from the impressive increase in fundamental knowledge, the last 20 years have shown a continuous burst of new ideas and consequently a plethora of new catalytic methods for enantioselective radical reactions. This review aims to provide a complete survey of progress achieved over this latter period. The first part of this review focuses on the use of chiral organocatalysts, and these include catalysts covalently linked to the substrate and those that interact with the substrate by weaker interactions like hydrogen bonds. The second part of the review is devoted to transition-metal redox catalysis which is organized according to increasing atomic number for the first-row transition metals (Ti, Cr, Fe, Mn, Co, Ni, Cu). Bioinspired manganese- and iron-mediated hydroxylations and oxidations are also discussed. A specific section is dedicated to the reactivity of Ru, Rh, and Ir complexes as Lewis acids with a special focus on complexes chiral at metal. Absorption of photons result in different events such as energy transfer, single-electron transfer, and hydrogen-atom transfer facilitating the formation of radicals. Organocatalysis has been successfully combined with photocatalysts, a reactivity which has opened new pathways enlarging the number of radical precursors available. The merger of photocatalysis with organo- or metalla-photocatalysis has brought novelty and allowed for the discovery of a large number of original transformations. The use of enzyme-catalyzed reactions involving radical intermediates which also largely benefit from visible-light irradiation are included in the review. This review provides a comprehensive inventory of progress in enantioselective radical reactions with a goal of detailing the reaction mechanisms involved in these transformations such that any nonspecialist could find their own creativity to invent yet unknown applications.

A new versatile code based on Python scripts was developed to calculate spin-orbit coupling (SOC) elements between singlet and triplet states. The code, named PySOC, is interfaced to third-party quantum chemistry packages, such as Gaussian 09 and DFTB+. SOCs are evaluated using linear-response (LR) methods based on time-dependent density functional theory (TDDFT), the Tamm-Dancoff approximation (TDA), and time-dependent density functional tight binding (TD-DFTB). The evaluation employs Casida-type wave functions and the Breit-Pauli (BP) spin-orbit Hamiltonian with an effective charge approximation. For validation purposes, SOCs calculated with PySOC are benchmarked for several organic molecules, with SOC values spanning several orders of magnitude. The computed SOCs show little variation with the basis set, but are sensitive to the chosen density functional. The benchmark results are in good agreement with reference data obtained using higher-level spin-orbit Hamiltonians and electronic structure methods, such as CASPT2 and DFT/MRCI. PySOC can be easily interfaced to other third-party codes and other methods yielding CI-type wave functions.

Drug resistance and toxicity constitute challenging hurdles for cancer therapy. The application of nanotechnology for anticancer drug delivery is expected to address these issues and bring new hope for cancer treatment. In this context, we established an original nanomicellar drug delivery system based on an amphiphilic dendrimer (AmDM), which could generate supramolecular micelles to effectively encapsulate the anticancer drug doxorubicin (DOX) with high drug-loading capacity (>40%), thanks to the unique dendritic structure creating large void space for drug accommodation. The resulting AmDM/DOX nanomicelles were able to enhance drug potency and combat doxorubicin resistance in breast cancer models by significantly enhancing cellular uptake while considerably decreasing efflux of the drug. In addition, the AmDM/DOX nanoparticles abolished significantly the toxicity related to the free drug. Collectively, our studies demonstrate that the drug delivery system based on nanomicelles formed with the self-assembling amphiphilic dendrimer constitutes a promising and effective drug carrier in cancer therapy.

The developments of the open-source OpenMolcas chemistry software environment since spring 2020 are described, with a focus on novel functionalities accessible in the stable branch of the package or via interfaces with other packages. These developments span a wide range of topics in computational chemistry and are presented in thematic sections: electronic structure theory, electronic spectroscopy simulations, analytic gradients and molecular structure optimizations, ab initio molecular dynamics, and other new features. This report offers an overview of the chemical phenomena and processes OpenMolcas can address, while showing that OpenMolcas is an attractive platform for state-of-the-art atomistic computer simulations.

Biopolymers such as DNA store information in their chains using controlled sequences of monomers. Here we describe a non-natural information-containing macromolecule that can store and retrieve digital information. Monodisperse sequence-encoded poly(alkoxyamine amide)s were synthesized using an iterative strategy employing two chemoselective steps: the reaction of a primary amine with an acid anhydride and the radical coupling of a carbon-centred radical with a nitroxide. A binary code was implemented in the polymer chains using three monomers: one nitroxide spacer and two interchangeable anhydrides defined as 0-bit and 1-bit. This methodology allows encryption of any desired sequence in the chains. Moreover, the formed sequences are easy to decode using tandem mass spectrometry. Indeed, these polymers follow predictable fragmentation pathways that can be easily deciphered. Moreover, poly(alkoxyamine amide)s are thermolabile. Thus, the digital information encrypted in the chains can be erased by heating the polymers in the solid state or in solution.

With the spectacular advancement of NMR techniques and the flourishing of fluorine chemistry allowing the synthesis of various fluorinated molecules, (19)F NMR represents a compelling option for studying myriad biological events ranging from the structure and function of biomolecules, enzymatic mechanisms, and metabolic pathways, through to drug screening and discovery as well as medical imaging. In this tutorial review, we aim to provide readers with a brief overview of the recent applications of (19)F NMR in various areas relating to biological and biomedical research, together with a brief introduction of specific hardware improvements permitting the practical implementation of (19)F NMR.

Hydrogen-atom transfer (HAT) counts amongst the most widely investigated routes to carbon-centered radicals. Intramolecular processes involving 1,5-HAT are widespread to promote regioselective radical "CH activation". The aim of this review is to draw up a comprehensive inventory of the less commonly encountered 1,n-radical translocations (n≠5) with the aim to update this topic with the most recent relevant data.

Boronates, a group of organic compounds, are emerging as one of the most effective probes for detecting and quantifying peroxynitrite, hypochlorous acid, and hydrogen peroxide. Boronates react with peroxynitrite nearly a million times faster than with hydrogen peroxide. Boronate-containing fluorogenic compounds have been used to monitor real time generation of peroxynitrite in cells and for imaging hydrogen peroxide in living animals. This perspective highlights potential applications of boronates and other fluorescent probes to high-throughput analyses of peroxynitrite and hydroperoxides in toxicological studies.

Sequence-defined non-natural polyphosphates were prepared using iterative phosphoramidite protocols on a polystyrene solid support. Three monomers were used in this work: 2-cyanoethyl (3-dimethoxytrityloxy-propyl) diisopropylphosphoramidite (0), 2-cyanoethyl (3-dimethoxytrityloxy-2,2-dimethyl-propyl) diisopropylphosphoramidite (1), and 2-cyanoethyl (3-dimethoxytrityloxy-2,2-dipropargyl-propyl) diisopropylphosphoramidite (1'). Phosphoramidite coupling steps allowed rapid synthesis of homopolymers and copolymers. In particular, the comonomers (0, 1), (0, 1'), and (1, 1') were used to synthesize sequence-encoded copolymers. It was found that long encoded sequences could be easily built using phosphoramidite chemistry. ESI-HRMS, MALDI-HRMS, NMR, and size exclusion chromatography analyses indicated the formation of monodisperse polymers with controlled comonomer sequences. The polymers obtained with the comonomers (0, 1') and (1, 1') were also modified by copper-catalyzed azide-alkyne cycloaddition with a model azide compound, namely 11-azido-3,6,9-trioxaundecan-1-amine. (1)H and (13)C NMR analysis evidenced quantitative modification of the alkyne side-chains of the monodisperse copolymers. Thus, the molecular structure of the coding monomer units can be easily varied after polymerization. Altogether, the present results open up interesting avenues for the design of information-containing macromolecules.

We report and characterize ground-state and excited-state potential energy profiles using a variety of electronic structure methods along a loop lying on the branching plane associated with a conical intersection (CI) of a reduced retinal model, the penta-2,4-dieniminium cation (PSB3). Whereas the performance of the equation-of-motion coupled-cluster, density functional theory, and multireference methods had been tested along the excited- and ground-state paths of PSB3 in our earlier work, the ability of these methods to correctly describe the potential energy surface shape along a CI branching plane has not yet been investigated. This is the focus of the present contribution. We find, in agreement with earlier studies by others, that standard time-dependent DFT (TDDFT) does not yield the correct two-dimensional (i.e., conical) crossing along the branching plane but rather a one-dimensional (i.e., linear) crossing along the same plane. The same type of behavior is found for SS-CASPT2(IPEA=0), SS-CASPT2(IPEA=0.25), spin-projected SF-TDDFT, EOM-SF-CCSD, and, finally, for the reference MRCISD+Q method. In contrast, we found that MRCISD, CASSCF, MS-CASPT2(IPEA=0), MS-CASPT2(IPEA=0.25), XMCQDPT2, QD-NEVPT2, non-spin-projected SF-TDDFT, and SI-SA-REKS yield the expected conical crossing. To assess the effect of the different crossing topologies (i.e., linear or conical) on the PSB3 photoisomerization efficiency, we discuss the results of 100 semiclassical trajectories computed by CASSCF and SS-CASPT2(IPEA=0.25) for a PSB3 derivative. We show that for the same initial conditions, the two methods yield similar dynamics leading to isomerization quantum yields that differ by only a few percent.

The design of highly emissive and stable blue emitters for organic light emitting diodes (OLEDs) is still a challenge, justifying the intense research activity of the scientific community in this field. Recently, a great deal of interest has been devoted to the elaboration of emitters exhibiting a thermally activated delayed fluorescence (TADF). By a specific molecular design consisting into a minimal overlap between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) due to a spatial separation of the electron-donating and the electron-releasing parts, luminescent materials exhibiting small S 1 –T 1 energy splitting could be obtained, enabling to thermally upconvert the electrons from the triplet to the singlet excited states by reverse intersystem crossing (RISC). By harvesting both singlet and triplet excitons for light emission, OLEDs competing and sometimes overcoming the performance of phosphorescence-based OLEDs could be fabricated, justifying the interest for this new family of materials massively popularized by Chihaya Adachi since 2012. In this review, we proposed to focus on the recent advances in the molecular design of blue TADF emitters for OLEDs during the last few years.