We report a global-hybrid approximation, MN15, to the exchange–correlation functional of Kohn–Sham theory with broadly accurate performance for both multi-reference and single-reference systems.

We review recent advances in the design and application of excited-state intramolecular proton-transfer (ESIPT) based fluorescent probes. These sensors and imaging agents (probes) are important in biology, physiology, pharmacology, and environmental science.

Kohn-Sham density functional theory is widely used for applications of electronic structure theory in chemistry, materials science, and condensed-matter physics, but the accuracy depends on the quality of the exchange-correlation functional. Here, we present a new local exchange-correlation functional called MN15-L that predicts accurate results for a broad range of molecular and solid-state properties including main-group bond energies, transition metal bond energies, reaction barrier heights, noncovalent interactions, atomic excitation energies, ionization potentials, electron affinities, total atomic energies, hydrocarbon thermochemistry, and lattice constants of solids. The MN15-L functional has the same mathematical form as a previous meta-nonseparable gradient approximation exchange-correlation functional, MN12-L, but it is improved because we optimized it against a larger database, designated 2015A, and included smoothness restraints; the optimization has a much better representation of transition metals. The mean unsigned error on 422 chemical energies is 2.32 kcal/mol, which is the best among all tested functionals, with or without nonlocal exchange. The MN15-L functional also provides good results for test sets that are outside the training set. A key issue is that the functional is local (no nonlocal exchange or nonlocal correlation), which makes it relatively economical for treating large and complex systems and solids. Another key advantage is that medium-range correlation energy is built in so that one does not need to add damped dispersion by molecular mechanics in order to predict accurate noncovalent binding energies. We believe that the MN15-L functional should be useful for a wide variety of applications in chemistry, physics, materials science, and molecular biology.

In this tutorial review, we will explore recent advances in the construction and application of Förster resonance energy transfer (FRET)-based small-molecule fluorescent probes.

We summarize recent progress in the development of fluorogenic enzyme probes for a variety of diseases.

Conspectus This Account describes a range of strategies for the development of fluorescent probes for detecting reactive oxygen species (ROS), reactive nitrogen species (RNS), and reactive (redox-active) sulfur species (RSS). Many ROS/RNS have been implicated in pathological processes such as Alzheimer’s disease, cancer, diabetes mellitus, cardiovascular disease, and aging, while many RSS play important roles in maintaining redox homeostasis, serving as antioxidants and acting as free radical scavengers. Fluorescence-based systems have emerged as one of the best ways to monitor the concentrations and locations of these often very short lived species. Because of the high levels of sensitivity and in particular their ability to be used for temporal and spatial sampling for in vivo imaging applications. As a direct result, there has been a huge surge in the development of fluorescent probes for sensitive and selective detection of ROS, RNS, and RSS within cellular environments. However, cellular environments are extremely complex, often with more than one species involved in a given biochemical process. As a result, there has been a rise in the development of dual-responsive fluorescent probes (AND-logic probes) that can monitor the presence of more than one species in a biological environment. Our aim with this Account is to introduce the fluorescent probes that we have developed for in vitro and in vivo measurement of ROS, RNS, and RSS. Fluorescence-based sensing mechanisms used in the construction of the probes include photoinduced electron transfer, intramolecular charge transfer, excited-state intramolecular proton transfer (ESIPT), and fluorescence resonance energy transfer. In particular, probes for hydrogen peroxide, hypochlorous acid, superoxide, peroxynitrite, glutathione, cysteine, homocysteine, and hydrogen sulfide are discussed. In addition, we describe the development of AND-logic-based systems capable of detecting two species, such as peroxynitrite and glutathione. One of the most interesting advances contained in this Account is our extension of indicator displacement assays (IDAs) to reaction-based indicator displacement assays (RIAs). In an IDA system, an indicator is allowed to bind reversibly to a receptor. Then a competitive analyte is introduced into the system, resulting in displacement of the indicator from the host, which in turn modulates the optical signal. With an RIA-based system, the indicator is cleaved from a preformed receptor–indicator complex rather than being displaced by the analyte. Nevertheless, without a doubt the most significant result contained in this Account is the use of an ESIPT-based probe for the simultaneous sensing of fibrous proteins/peptides AND environmental ROS/RNS.

Conspectus The desire to study molecular systems that are much larger than what the current state-of-the-art ab initio or density functional theory methods could handle has naturally led to the development of novel approximate methods, including semiempirical approaches, reduced-scaling methods, and fragmentation methods. The major computational limitation of ab initio methods is the scaling problem, because the cost of ab initio calculation scales nth power or worse with system size. In the past decade, the fragmentation approach based on chemical locality has opened a new door for developing linear-scaling quantum mechanical (QM) methods for large systems and for applications to large molecular systems such as biomolecules. The fragmentation approach is highly attractive from a computational standpoint. First, the ab initio calculation of individual fragments can be conducted almost independently, which makes it suitable for massively parallel computations. Second, the electron properties, such as density and energy, are typically combined in a linear fashion to reproduce those for the entire molecular system, which makes the overall computation scale linearly with the size of the system. In this Account, two fragmentation methods and their applications to macromolecules are described. They are the electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method and the automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) approach. The EE-GMFCC method is developed from the MFCC approach, which was initially used to obtain accurate protein-ligand QM interaction energies. The main idea of the MFCC approach is that a pair of conjugate caps (concaps) is inserted at the location where the subsystem is divided by cutting the chemical bond. In addition, the pair of concaps is fused to form molecular species such that the overcounted effect from added concaps can be properly removed. By introducing the electrostatic embedding field in each fragment calculation and two-body interaction energy correction on top of the MFCC approach, the EE-GMFCC method is capable of accurately reproducing the QM molecular properties (such as the dipole moment, electron density, and electrostatic potential), the total energy, and the electrostatic solvation energy from full system calculations for proteins. On the other hand, the AF-QM/MM method was used for the efficient QM calculation of protein nuclear magnetic resonance (NMR) parameters, including the chemical shift, chemical shift anisotropy tensor, and spin-spin coupling constant. In the AF-QM/MM approach, each amino acid and all the residues in its vicinity are automatically assigned as the QM region through a distance cutoff for each residue-centric QM/MM calculation. Local chemical properties of the central residue can be obtained from individual QM/MM calculations. The AF-QM/MM approach precisely reproduces the NMR chemical shifts of proteins in the gas phase from full system QM calculations. Furthermore, via the incorporat...

An electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method is developed for efficient linear-scaling quantum mechanical (QM) calculation of protein energy. This approach is based on our previously proposed GMFCC/MM method (He; et al. J. Chem. Phys. 2006, 124, 184703), In this EE-GMFCC scheme, the total energy of protein is calculated by taking a linear combination of the QM energy of the neighboring residues and the two-body QM interaction energy between non-neighboring residues that are spatially in close contact. All the fragment calculations are embedded in a field of point charges representing the remaining protein environment, which is the major improvement over our previous GMFCC/MM approach. Numerical studies are carried out to calculate the total energies of 18 real three-dimensional proteins of up to 1142 atoms using the EE-GMFCC approach at the HF/6-31G* level. The overall mean unsigned error of EE-GMFCC for the 18 proteins is 2.39 kcal/mol with reference to the full system HF/6-31G* energies. The EE-GMFCC approach is also applied for proteins at the levels of the density functional theory (DFT) and second-order many-body perturbation theory (MP2), also showing only a few kcal/mol deviation from the corresponding full system result. The EE-GMFCC method is linear-scaling with a low prefactor, trivially parallel, and can be readily applied to routinely perform structural optimization of proteins and molecular dynamics simulation with high level ab initio electronic structure theories.