For five bromomethylated azobenzenes, namely (E)-[4-(bromomethyl)phenyl][4-(dibromomethyl)phenyl]diazene, CHBrN, (E)-1,2-bis[4-(dibromomethyl)phenyl]diazene, CHBrN, (E)-[3-(bromomethyl)phenyl][3-(dibromomethyl)phenyl]diazene, CHBrN, (E)-[3-(dibromomethyl)phenyl][3-(tribromomethyl)phenyl]diazene, CHBrN, and (E)-1,2-bis[3-(dibromomethyl)phenyl]diazene, CHBrN, the computationally cheap CLP PIXEL approach and CrystalExplorer were used for calculating lattice energies and performing Hirshfeld surface analysis via the enrichment ratios of atomic contacts. The procedures and caveats are discussed in detail. The findings from these tools are contrasted with the results of geometric analysis of the structures. We conclude that an energy-based discussion of the crystal packing provides substantially more insight than one based purely on geometry, as has so long been the custom in crystallography. In addition, we find a surprising shortage of halogen-halogen interactions in these highly bromomethylated compounds.
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http://dx.doi.org/10.1107/S2053229618015309 | DOI Listing |
Bioinformatics
October 2024
Bijvoet Centre for Biomolecular Research, Faculty of Science-Chemistry, Utrecht University, Utrecht CH 3584, The Netherlands.
Motivation: Antibody-antigen complex modelling is an important step in computational workflows for therapeutic antibody design. While experimentally determined structures of both antibody and the cognate antigen are often not available, recent advances in machine learning-driven protein modelling have enabled accurate prediction of both antibody and antigen structures. Here, we analyse the ability of protein-protein docking tools to use machine learning generated input structures for information-driven docking.
View Article and Find Full Text PDFInt J Mol Sci
August 2024
HQS Quantum Simulations GmbH, Rintheimer Straße 23, 76131 Karlsruhe, Germany.
In this work, we propose a multi-level protocol for routine theoretical studies of chemical reaction mechanisms. The initial reaction paths of our investigated systems are sampled using the Nudged Elastic Band (NEB) method driven by a cheap electronic structure method. Forces recalculated at the more accurate electronic structure theory for a set of points on the path are fitted with a machine learning technique (in our case symmetric gradient domain machine learning or sGDML) to produce a semi-local reactive potential energy surface (PES), embracing reactants, products and transition state (TS) regions.
View Article and Find Full Text PDFFaraday Discuss
November 2024
Laboratoire de Chimie Théorique, Sorbonne Université and CNRS, UMR 7616, F-75005 Paris, France.
We present the first application to real molecular systems of the recently proposed linear-response theory for the density-based basis-set correction method [, , 234107 (2023)]. We apply this approach to accelerate the basis-set convergence of excitation energies in the equation-of-motion coupled-cluster singles and doubles (EOM-CCSD) method. We use an approximate linear-response framework that neglects the second-order derivative of the basis-set correction density functional and consists in simply adding to the usual Hamiltonian the one-electron potential generated by the first-order derivative of the functional.
View Article and Find Full Text PDFPsychol Rev
October 2024
Department of Experimental Psychology, University of Oxford.
The optimal way to make decisions in many circumstances is to track the difference in evidence collected in favor of the options. The drift diffusion model (DDM) implements this approach and provides an excellent account of decisions and response times. However, existing DDM-based models of confidence exhibit certain deficits, and many theories of confidence have used alternative, nonoptimal models of decisions.
View Article and Find Full Text PDFPhys Chem Chem Phys
July 2024
School of Physical, Environmental and Mathematical Sciences University College, University of New South Wales, ADFA Canberra ACT 2600, Australia.
We present a novel, and computationally cheap, way to estimate electrostatic screening lengths from simulations of restricted primitive model (RPM) electrolytes. We demonstrate that the method is accurate by comparisons with simulated long-ranged parts of the charge density, at various Bjerrum lengths, salt concentrations and ion diameters. We find substantial underscreening in low dielectric solvent, but with an "aqueous" solvent, there is instead overscreening, the degree of which increases with ion size.
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