A recently proposed charge-transfer (CT) index and some related quantities aimed to the description of CT excitations in push-pull donor-acceptor model systems were computed in vacuum and in ethanol by the direct symmetry-adapted cluster-configuration interaction (SAC-CI) method including solvent effects by means of the nonequilibrium state-specific approach. The effects of both solvation and electron correlations on these quantities were found to be significant. The present results are also in line with previous time-dependent (TD) density functional theory calculations and they demonstrate that SAC-CI provides a description of the excitation character close to that of TD-PBE0. Indeed, CT indices evaluated by the SAC-CI and TD-PBE0 would be useful in the field of materials chemistry, for the design and development of novel molecular materials.
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http://dx.doi.org/10.1002/jcc.23423 | DOI Listing |
Langmuir
January 2025
Department of Chemical Engineering, Technion-IIT, Haifa 32000, Israel.
A comprehensive approach enabling a quantitative interpretation of poly-l-arginine (PARG) adsorption kinetics at solid/electrolyte interfaces was developed. The first step involved all-atom molecular dynamics (MD) modeling of physicochemical characteristics yielding PARG molecule conformations, its contour length, and the cross-section area. It was also shown that PARG molecules, even in concentrated electrolyte solutions (100 mM NaCl), assume a largely elongated shape with an aspect ratio of 36.
View Article and Find Full Text PDFAcc Chem Res
January 2025
State Key Laboratory of Organometallic Chemistry, Shanghai Institute of Organic Chemistry, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, China.
ConspectusIn recent years, our research group has dedicated significant effort to the field of asymmetric organometallic electrochemical synthesis (AOES), which integrates electrochemistry with asymmetric transition metal catalysis. On one hand, we have rationalized that organometallic compounds can serve as molecular electrocatalysts (mediators) to reduce overpotentials and enhance both the reactivity and selectivity of reactions. On the other hand, the conditions for asymmetric transition metal catalysis can be substantially improved through electrochemistry, enabling precise modulation of the transition metal's oxidation state by controlling electrochemical potentials and regulating the electron transfer rate via current adjustments.
View Article and Find Full Text PDFHuman epidermal growth factor receptor 2 (HER2, also known as ERBB2) signaling promotes cell growth and differentiation, and is overexpressed in several tumor types, including breast, gastric and colorectal cancer. HER2-targeted therapies have shown clinical activity against these tumor types, resulting in regulatory approvals. However, the efficacy of HER2 therapies in tumors with HER2 mutations has not been widely investigated.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Department of Life Science Informatics and Data Science, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Friedrich-Hirzebruch-Allee 5/6, Bonn D-53115, Germany.
Explaining the predictions of machine learning models is of critical importance for integrating predictive modeling in drug discovery projects. We have generated a test system for predicting isoform selectivity of phosphoinositide 3-kinase (PI3K) inhibitors and systematically analyzed correct predictions of selective inhibitors using a new methodology termed MolAnchor, which is based on the "anchors" concept from explainable artificial intelligence. The approach is designed to generate chemically intuitive explanations of compound predictions.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Theory and Simulation of Complex Systems, Institute of Physical Chemistry, Heinrich-Heine Universität, Universitätsstr. 1, 40225 Düsseldorf, Germany.
Understanding and analyzing large-scale reaction networks is a fundamental challenge due to their complexity and size, often beyond human comprehension. In this paper, we introduce AUTOGRAPH, the first web-based tool designed for the interactive three-dimensional (3D) visualization and construction of reaction networks. AUTOGRAPH emphasizes ease of use, allowing users to intuitively build, modify, and explore individual reaction networks in real time.
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