Using Energetic Information Quantities from Density Functional Theory to Simultaneously Identify Both Covalent and Noncovalent Interactions.

Covalent bonding and noncovalent interactions are important chemical concepts and how to identify them has been of current interest in the literature. Within the framework of density functional theory (DFT), we recently proposed a few qualitative descriptors to categorize different types of interactions with Pauli energy and its derivatives. In this work, we expand the scope by including the quantities derived from energetic information, which were recently proposed and thoroughly investigated by us from the framework of information-theoretic approach (ITA) in DFT.

Why are information-theoretic descriptors powerful predictors of atomic and molecular polarizabilities.

Context: We rationalize the excellent performance of information-theoretic descriptors for predicting atomic and molecular polarizabilities. It seems that descriptors which capture information about the change in valence-shell structure, especially the relative Fisher information measures, are particularly useful. Using this, we can rationalize why the G3 form of the relative Fisher information, which measures the deviation of effective nuclear charge between an atom-in-a-molecule and the reference pro-atom, is especially effective as a predictor of molecular polarizability.

Information-theoretic quantities as effective descriptors of electrophilicity and nucleophilicity in density functional theory.

Context: Electrophilicity and nucleophilicity are two vastly important chemical concepts gauging the capability of atoms in molecules to accept and donate the maximal number of electrons. In our earlier studies, we proposed to simultaneously quantify them using the Kullback-Leibler divergence from the information-theoretic approach in density functional theory. However, several issues with this scheme remain to be clarified such as its general validity, predictability, and relationship with other information-theoretic quantities.

Density-based quantification of steric effects: validation by Taft steric parameters from acid-catalyzed hydrolysis of esters.

The steric effect is one of the most widely used concepts for chemical understanding in publications and textbooks, yet a well-accepted formulation of this effect is still elusive. Experimentally, this concept was quantified by the acid-catalyzed hydrolysis of esters, yielding the so-called Taft steric parameter. Theoretically, we recently proposed a density-based scheme to quantify the effect from density functional theory.

Molecular Docking of Chiral Drug Enantiomers With Different Bioactivities.

Chirality has an important role in the drug design because enantiomers may exhibit different bioactivity when interacting with macromolecules of a living organism. In our previous work, based on the analysis of a set of 100 chiral drugs, a relationship was established between the sign of chirality of enantiomers and their bioactivity. To understand the reasons for the observed patterns of chiral specificity of drug enantiomers, the interaction of 10 enantiomeric pairs of chiral drugs with the corresponding target proteins has been considered using molecular docking and further postprocessing by quantum chemistry methods.

A general and mild synthetic method for fused-ring electronic acceptors.

Fused-ring electronic acceptors (FREAs) have transformed the field of organic solar cells. However, the prevailing syntheses of FREAs suffer from low yield, difficulty in separation, and high cost. Here, we report new and streamlined syntheses with three distinctive key steps.

Conservative Binary Dynamics at Order α^{5} in Electrodynamics.

We compute the potential-photon contributions to the classical relativistic scattering angle of two charged nonspinning bodies in electrodynamics through fifth order in the coupling. We use the scattering amplitudes framework, effective field theory, and multiloop integration techniques based on integration by parts and differential equations. At fifth order, the result is expressed in terms of cyclotomic polylogarithms.

Energetic Information from Information-Theoretic Approach in Density Functional Theory as Quantitative Measures of Physicochemical Properties.

The Hohenberg-Kohn theorem of density functional theory (DFT) stipulates that energy is a universal functional of electron density in the ground state, so energy can be thought of having encoded essential information for the density. Based on this, we recently proposed to quantify energetic information within the framework of information-theoretic approach (ITA) of DFT (. , 157, 101103).

Steric Effect and Intrinsic Electrophilicity and Nucleophilicity from Conceptual Density Functional Theory and Information-Theoretic Approach as Quantitative Probes of Chemical Reactions.

Appreciating reactivity in terms of physicochemical effects for chemical processes is one of the most important undertakings in chemistry. While transition state (TS) theory provides the framework enabling the reliable calculation of the barrier height for a given elementary step, analytical tools are necessary to gain insight into key factors governing the different processes during chemical reactions. In this contribution, we partition the potential energy surface of an elementary step along the intrinsic coordinate into three segments, the so-called Pre-TS, TS, and Post-TS regions, and then determine the most important factors dictating each segment.

Digital twinning of cardiac electrophysiology for congenital heart disease.

In recent years, blending mechanistic knowledge with machine learning has had a major impact in digital healthcare. In this work, we introduce a computational pipeline to build certified digital replicas of cardiac electrophysiology in paediatric patients with congenital heart disease. We construct the patient-specific geometry by means of semi-automatic segmentation and meshing tools.

A theoretical study of Lifshitz transition for 2H-TaS.

Lifshitz transition was proposed to explain a change of the topology structure in a Fermi surface induced by continuous lattice deformation without symmetry breaking since 1960. It is well known that the anomalies of the kinetic coefficients (the coefficient of heat conduction and electrical conductivity, viscosity, sound absorption, ) are usually closely connected with the Lifshitz transition behavior. 2H-TaS is a typical representative to study its anomalies of temperature dependence of heat capacity, resistivity, Hall effect, and magnetic susceptibility.

Molecular Dynamics Simulation of Complex Reactivity with the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) Software Package.

Simulating chemically reactive phenomena such as proton transport on nanosecond to microsecond and beyond time scales is a challenging task. methods are unable to currently access these time scales routinely, and traditional molecular dynamics methods feature fixed bonding arrangements that cannot account for changes in the system's bonding topology. The Multiscale Reactive Molecular Dynamics (MS-RMD) method, as implemented in the Rapid Approach for Proton Transport and Other Reactions (RAPTOR) software package for the LAMMPS molecular dynamics code, offers a method to routinely sample longer time scale reactive simulation data with statistical precision.

C(sp)-H (N-Phenyltetrazole)thiolation as an Enabling Tool for Molecular Diversification.

Methods enabling the broad diversification of C(sp)-H bonds from a common intermediate are especially valuable in chemical synthesis. Herein, we report a site-selective (N-phenyltetrazole)thiolation of aliphatic and (hetero)benzylic C(sp)-H bonds using a commercially available disulfide to access N-phenyltetrazole thioethers. The thioether products are readily elaborated in diverse fragment couplings for C-C, C-O, or C-N construction.

Cyclic and linear trajectories of ecosystem evolution on sand dunes in Siberian taiga: A comprehensive analysis.

Extensive unforested sandy areas on the margins of floodplains and riverbeds, formed by dunes, barchans, and accumulation berms, are a ubiquitous feature across northern Eurasia and Alaska. These dynamic landscapes, which bear witness to the complex Holocene and modern climatic fluctuations, provide a unique opportunity to study ecosystem evolution. Within this heterogeneous assemblage, active dunes, characterized by their very sparse plant communities, contrast sharply with the surrounding taiga (boreal) forests common for the stabilized dunes.

Chiral Jahn-Teller Distortion in Quasi-Planar Boron Clusters.

In this work, we have observed that some chiral boron clusters (B16-, B20-, B24-, and B28-) can simultaneously have helical molecular orbitals and helical spin densities; these seem to be the first compounds discovered to have this intriguing property. We show that chiral Jahn-Teller distortion of quasi-planar boron clusters drives the formation of the helical molecular spin densities in these clusters and show that elongation/enhancement in helical molecular orbitals can be achieved by simply adding more building blocks via a linker. Aromaticity of these boron clusters is discussed.

Harvesting Chemical Understanding with Machine Learning and Quantum Computers.

It is tenable to argue that nobody can predict the future with certainty, yet one can learn from the past and make informed projections for the years ahead. In this Perspective, we overview the status of how theory and computation can be exploited to obtain chemical understanding from wave function theory and density functional theory, and then outlook the likely impact of machine learning (ML) and quantum computers (QC) to appreciate traditional chemical concepts in decades to come. It is maintained that the development and maturation of ML and QC methods in theoretical and computational chemistry represent two paradigm shifts about how the Schrödinger equation can be solved.

Relative cooperativity in neutral and charged molecular clusters using QM/MM calculations.

QM/MM methods have been used to study electronic structure properties and chemical reactivity in complex molecular systems where direct electronic structure calculations are not feasible. In our previous work, we showed that non-polarizable force fields, by design, describe intermolecular interactions through pairwise interactions, overlooking many-body interactions involving three or more particles. In contrast, polarizable force fields account partially for many-body effects through polarization, but still handle van der Waals and permanent electrostatic interactions pairwise.

Optimized Incorporation of Furan into Diketopyrrolopyrrole-Based Conjugated Polymers for Organic Field-Effect Transistors.

Flexible electronics have received considerable attention in the past decades due to their promising application in rollable display screens, wearable devices, implantable devices, and other electronic applications. In particular, conjugated polymers are favored for flexible electronics due to their mechanical flexibility and potential for solution-processed fabrication techniques, such as blade-coating, roll-to-roll printing, and high-throughput printing allowing for high-performance transistor devices. Thiophene is the prevailing conjugated unit to construct these conjugated polymers due to its favorable electronic properties.

Fragment-Based Deep Learning for Simultaneous Prediction of Polarizabilities and NMR Shieldings of Macromolecules and Their Aggregates.

Simultaneous prediction of the molecular response properties, such as polarizability and the NMR shielding constant, at a low computational cost is an unresolved issue. We propose to combine a linear-scaling generalized energy-based fragmentation (GEBF) method and deep learning (DL) with both molecular and atomic information-theoretic approach (ITA) quantities as effective descriptors. In GEBF, the total molecular polarizability can be assembled as a linear combination of the corresponding quantities calculated from a set of small embedded subsystems in GEBF.

Docking and other computing tools in drug design against SARS-CoV-2.

The use of computer simulation methods has become an indispensable component in identifying drugs against the SARS-CoV-2 coronavirus. There is a huge body of literature on application of molecular modelling to predict inhibitors against target proteins of SARS-CoV-2. To keep our review clear and readable, we limited ourselves primarily to works that use computational methods to find inhibitors and test the predicted compounds experimentally either in target protein assays or in cell culture with live SARS-CoV-2.

Some Recent Advances in Density-Based Reactivity Theory.

Establishing a chemical reactivity theory in density functional theory (DFT) language has been our intense research interest in the past two decades, exemplified by the determination of steric effect and stereoselectivity, evaluation of electrophilicity and nucleophilicity, identification of strong and weak interactions, and formulation of cooperativity, frustration, and principle of chirality hierarchy. In this Featured Article, we first overview the four density-based frameworks in DFT to appreciate chemical understanding, including conceptual DFT, use of density associated quantities, information-theoretic approach, and orbital-free DFT, and then present a few recent advances of these frameworks as well as new applications from our studies. To that end, we will introduce the relationship among these frameworks, determining the entire spectrum of interactions with Pauli energy derivatives, performing topological analyses with information-theoretic quantities, and extending the density-based frameworks to excited states.

Extending the Scope of Conceptual Density Functional Theory with Second Order Analytical Methodologies.

In the context of the growing impact of conceptual density functional theory (DFT) as one of the most successful chemical reactivity theories, response functions up to second order have now been widely applied; in recent years, among others, particular attention has been focused on the linear response function and also extensions to higher order have been put forward. As the larger part of these studies have been carried using a finite difference approach to compute these concepts, we now embarked on (an extension of) an analytical approach to conceptual DFT. With the ultimate aim of providing a complete set of analytically computable second order properties, including the softness and hardness kernels, the hardness as the simplest second order response function is scrutinized again with numerical results highlighting the difference in nature between the analytical hardness (referred to as hardness condition) and the Parr-Pearson absolute chemical hardness.

Design, Synthesis, and Evaluation of New Hybrid Derivatives of 5,6-Dihydro-4-pyrrolo[3,2,1-]quinolin-2(1)-one as Potential Dual Inhibitors of Blood Coagulation Factors Xa and XIa.

Cardiovascular diseases caused by blood coagulation system disorders are one of the leading causes of morbidity and mortality in the world. Research shows that blood clotting factors are involved in these thrombotic processes. Among them, factor Xa occupies a key position in the blood coagulation cascade.

Chemical Adjustment of Fibrinolysis.

Fibrinolysis is the process of the fibrin-platelet clot dissolution initiated after bleeding has been stopped. It is regulated by a cascade of proteolytic enzymes with plasmin at its core. In pathological cases, the balance of normal clot formation and dissolution is replaced by a too rapid lysis, leading to bleeding, or an insufficient one, leading to an increased thrombotic risk.

Finite temperature string by -means clustering sampling with order parameters as collective variables for molecular crystals: application to polymorphic transformation between β-CL-20 and ε-CL-20.

Polymorphic transformation of molecular crystals is a fundamental phase transition process, and it is important practically in the chemical, material, biopharmaceutical, and energy storage industries. However, understanding of the transformation mechanism at the molecular level is poor due to the extreme simulating challenges in enhanced sampling and formulating order parameters (OPs) as the collective variables that can distinguish polymorphs with quite similar and complicated structures so as to describe the reaction coordinate. In this work, two kinds of OPs for CL-20 were constructed by the bond distances, bond orientations and relative orientations.