Interpretable Attribution Assignment for Octanol–Water Partition Coefficient

With the increasing development of machine learning models, their credibility has become an important issue. In chemistry, attribution assignment is gaining relevance when it comes to designing molecules and debugging models. However, attention has only been paid to which atoms are important in the prediction and not to whether the attribution is reasonable. In this study, we developed a graph neural network model, a highly interpretable attribution model in chemistry, and modified the integrated gradients method. The credibility of our approach was confirmed by predicting the octanol–water partition coefficient (logP) and evaluating the three metrics (accuracy, consistency, and stability) in the attribution assignment

Description of Solvatochromism of Peak Broadening in Absorption Spectra in Solution Using the Reference Interaction Site Model Self-Consistent Fields Spatial Electron Density Distribution

We quantified and subsequently analyzed bandwidth of ultraviolet and visible photoabsorption spectral lines in solution by applying time-dependent first-order perturbation theory using the Born–Oppenheimer adiabatic potential calculated using the multistate extended-multi-configurational quasi-degenerated second-order perturbation theory (MS-XMCQDPT2) coupled with the reference interaction site model self-consistent field spatial electron density distribution (RISM-SCF-cSED). The proposed method was implemented for 2-thiocytosine in solution, and solvatochromism of the bandwidth of the πSπ* transition was clearly observed. The standard deviation of a characteristic electronic excitation was decomposed into the contributions of the characteristic vibrational mode of 2-thiocytosine. The main vibrational modes contributing to peak broadening were found to be for acetonitrile, methanol, and the aqueous phase. We concluded that the mechanism for peak broadening is qualitatively different for phases of protic and aprotic solvents because of the structural variation in 2-thiocytosine driven by the breakage of the resonance structures

Theoretical Study on Nonradiative Decay of Dimethylaminobenzonitrile through Triplet State in Gas-Phase, Nonpolar, and Polar Solutions

The control of radiative and nonradiative decay is important in the design of bioimaging molecules. Dimethylaminobenzonitrile (DMABN) is a suitable model molecule to study radiative and nonradiative decay processes and has been investigated by theoretical and experimental methods. However, an atomistic understanding of the nonradiative decay in solutions remains to be achieved. In this study, we investigated the potential-energy surfaces in excited states along the rotation of the dimethylamino group and found that the degeneration between S1 and T1 states is one of the key factors in the nonradiative decay in polar solvents. In addition, we found that the degeneration is precisely controlled by a fundamental physical property, exchange integral. Although DMABN is a simple molecule, the understanding of the nonradiative decay process on the basis of physical properties should be useful in the design of more complicated imaging molecules

Interpretable Attribution Assignment for Octanol–Water Partition Coefficient

With the increasing development of machine learning models, their credibility has become an important issue. In chemistry, attribution assignment is gaining relevance when it comes to designing molecules and debugging models. However, attention has only been paid to which atoms are important in the prediction and not to whether the attribution is reasonable. In this study, we developed a graph neural network model, a highly interpretable attribution model in chemistry, and modified the integrated gradients method. The credibility of our approach was confirmed by predicting the octanol–water partition coefficient (logP) and evaluating the three metrics (accuracy, consistency, and stability) in the attribution assignment

Interpretable Attribution Assignment for Octanol–Water Partition Coefficient

With the increasing development of machine learning models, their credibility has become an important issue. In chemistry, attribution assignment is gaining relevance when it comes to designing molecules and debugging models. However, attention has only been paid to which atoms are important in the prediction and not to whether the attribution is reasonable. In this study, we developed a graph neural network model, a highly interpretable attribution model in chemistry, and modified the integrated gradients method. The credibility of our approach was confirmed by predicting the octanol–water partition coefficient (logP) and evaluating the three metrics (accuracy, consistency, and stability) in the attribution assignment

Theoretical Understanding of the Nonlinear Raman Shift of CN Stretching Vibration of <i>p</i>‑Aminobenzonitrile in Supercritical Water

Subcritical and supercritical fluids (SCF) have attracted significant attention in the past few decades because of their unique properties. In a previous study, a nonlinear Raman shift of the CN stretching vibration of p-aminobenzonitrile (p-ABN) with respect to the supercritical water (SCW) density was observed [K. Osawa et al., J. Phys. Chem. A 2009, 113, 3143–3154]. Although a plausible mechanism of the nonlinear Raman shift was proposed in the study, the discussion at the atomistic level was inadequate. To elucidate the nonlinear Raman shift mechanism of the CN stretching vibration of p-ABN in SCW from a theoretical viewpoint, we employed RISM–SCF–cSED, which is the hybrid method between quantum mechanics and statistical mechanics. We discovered that the hydrogen-bonding effect is dominant at low- and middle-density regions, while the packing effect is dominant at the high-density region. The balances of these effects determine the Raman shift of p-ABN in SCF

Theoretical Study of Raman Intensities of <i>p</i>‑Nitroaniline in Different Solvent Conditions by Using a Reference Interaction Site Model Self-Consistent Field Explicitly Including Constrained Spatial Electron Density Distribution

Raman spectroscopy is one of the most powerful tools to understand and characterize the states and structures of systems in several environments. To obtain highly accurate changes in Raman intensities of systems in solution, theoretical treatment, which can deal with not only the states and structures of systems but also the environment around molecules, proves to be significant. Hence, in this study, we developed the calculation of changes in Raman intensities of systems in different solvent conditions by using the reference interaction site model self-consistent field study explicitly including constrained spatial electron density distribution; this model is designed based on elements from both quantum mechanics and statistical mechanics. We showed that our calculation method could reproduce the changes in Raman intensities of p-nitroaniline (pNA) under different solvent conditions, including supercritical water, which has been observed in previous experimental studies. Based on the analysis of the calculation results, we observed that the ratio of the Raman intensity change of pNA in different solvent conditions is strongly correlated with the charge-transfer character of pNA

Spin–Orbit Coupling Calculation Combined with the Reference Interaction Site Model Self-Consistent Field Explicitly Including Constrained Spatial Electron Density Distribution

Studying the radiative and non-radiative decay processes of molecules in a solution is an important issue in the design of organic and functional molecules. Theoretical approaches have great potential for revealing this decay process through computation of various parameters, such as the energy surfaces at the excited state and spin–orbit coupling (SOC). The development of quantum chemical programs has enabled the calculation of SOC values to become popular for the gas phase. However, SOC calculations in solution have some difficulties that need to be overcome. In the present study, the authors combined the SOC calculations with the reference interaction site model self-consistent field explicitly including constrained spatial electron density distribution. To validate the reliability of our method, the decay process of dimethylaminobenzonitrile in cyclohexane and acetonitrile was studied. By computing the SOC values in both solution systems, the authors were able to investigate the decay process at the atomistic level. Furthermore, a natural transition orbital analysis and the measurement of the decomposed SOC values were found to provide a clear understanding of intersystem crossing

Understanding of the Off–On Response Mechanism in Caged Fluorophores Based on Quantum and Statistical Mechanics

For many years, numerous fluorescent probes have been synthesized and applied to visualize molecules and cells. The development of such probes has accelerated biological and medical investigations. As our interests have been focused on more complicated systems in recent years, the search for probes with sensitive environment off–on response becomes increasingly important. For the design of such sophisticated probes, theoretical analyses of the electronically excited state are inevitable. Especially, understanding of the nonradiative decay process is highly desirable, although this is a challenging task. In this study, we propose an approach to treat the solvent fluctuation based on the reference interaction site model. It was applied to selected bioimaging probes to understand the importance of solvent fluctuation for their off–on response. We revealed that the this switching process involves the nonradiative decay through the charge transfer state, where the solvent relaxation supported the transition between excited and charge transfer states. In addition, energetically favorable solvent relaxation paths were found due to the consideration of multiple solvent configurations. Our approach makes it possible to understand the nonradiative decay facilitated by a detailed analysis and enables the design of novel fluorescent switching probes considering the effect of solvent fluctuation

Förster Resonance Energy Transfer between Fluorescent Proteins: Efficient Transition Charge-Based Study

Toward a better understanding of the Förster resonance energy transfer (FRET) utilized in genetically encoded biosensors we theoretically examined the excitonic coupling between cyan fluorescent protein (CFP) and yellow FP (YFP) with time-dependent density functional theory (TD-DFT). Going beyond the dipole–dipole (dd) approximation in the original Förster theory, we adopted a transition charge from the electrostatic potential (TrESP) method that approximates the excitonic coupling as classical Coulomb interaction between the transition charges derived from the transition density for each FP fluorophore. From the TD-DFT calculations with embedded point charges for the trajectory generated by classical molecular dynamics (MD) simulations we found that the thermal fluctuation of the fluorophore geometry in FP and the protein electrostatic interactions do not significantly affect the Coulomb interaction between the FP pairs. The TrESP calculations utilizing the Poisson equation indicate that the screening and local field effects by solvent dielectric environment reduce the Coulomb interaction by an almost constant factor of 0.51. Based on these results, we developed a more efficient Frozen-TrESP method that calculates the structure-dependent Coulomb interaction using the reference transition charges preliminarily determined for the isolated fluorophore in the gas phase and confirmed its validity for the evaluation of the Coulomb interaction in the thermally fluctuating CFP-YFP dimer. Finally, we demonstrated the usefulness of the Frozen-TrESP to examine the dependence of the Coulomb interaction on the alignment of YFP with respect to CFP and provide the list of the reference transition charges for the other representative fluorophores of various FPs, which offers guidance on the optimal design of the FRET-based biosensors