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. We showed that despite those limitations, polarizable and non-polarizable force fields can reproduce relative cooperativity achieved using density functional theory due to error compensation mechanisms. In this contribution, we assess the performance of QM/MM methods in reproducing these phenomena. Our study highlights the significance of the QM region size and force field choice in QM/MM calculations, emphasizing the importance of parameter validation to obtain accurate interaction energy predictions.

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. New chemical understanding can be harnessed in these two new paradigms by making respective use of ML features and QC qubits. Before that happens, however, we still have hurdles to face and obstacles to overcome in both ML and QC arenas. Possible pathways to tackle these challenges are proposed. We anticipate that hierarchical modeling, in contrast to multiscale modeling, will emerge and thrive, becoming the workhorse of in silico simulations in the next few decades.

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. Chiral boron clusters may find potential applications in spintronics, such as molecular magnets.

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. In the new GEBF-DL(ITA) protocol, one can predict subsystem polarizabilities based on the corresponding molecular wave function (thus electron density and ITA quantities) and DL model rather than calculate them from the computationally intensive coupled-perturbed Hartree-Fock or Kohn-Sham equations and finally obtain the total molecular polarizability via a linear combination equation. As a proof-of-concept application, we predict the molecular polarizabilities of large proteins and protein aggregates. GEBF-DL(ITA) is shown to be as accurate enough as GEBF, with mean absolute percentage error <1%. For the largest protein aggregate (>4000 atoms), GEBF-DL(ITA) gains a speedup ratio of 3 compared with GEBF. It is anticipated that when more advanced electronic structure methods are used, this advantage will be more appealing. Moreover, one can also predict the NMR chemical shieldings of proteins with reasonably good accuracy. Overall, the cost-efficient GEBF-DL(ITA) protocol should be a robust theoretical tool for simultaneously predicting polarizabilities and NMR shieldings of large systems.

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. On the other hand, furans are among the few conjugated moieties that are easily derived from bio renewable resources. To promote sustainability, we selectively introduced furan into the conjugated backbone of a high-mobility polymer scaffold and systematically studied the effect on the microstructure and charge transport. We show that partially and selectively replacing thiophene units with furan can yield nearly comparable performance compared to the all-thiophene polymer. This strategy offers an improvement in the sustainability of the polymer by incorporating bio-sourced furan without sacrificing the high-performance characteristics. Meanwhile, polymers with incorrect or complete furan incorporation show reduced mobilities. This work serves to develop coherent structure-morphology-performance relationships; such knowledge will establish guidelines for the future development of sustainable, furan-based conjugated materials.

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. The hardness condition is investigated for its capability to gauge the (de)localization error of density functional approximations (DFAs). The analytical Fukui function, besides overcoming the difficulties in the finite difference approach in treating negatively charged systems, also showcases the errors of deviating from the straight-line behavior using fractional occupation number calculations. Subsequently, the softness kernel and its atom-condensed inverse, the hardness matrix, are accessed through the Berkowitz-Parr relation. Revisiting the softness kernel confirms and extends previous discussions on how Kohn's Nearsightedness of Electronic Matter principle can be retrieved and identified as the physicist's version of the chemist's "transferability of functional groups" concept. The accurate, analytical hardness matrix evaluation on the other hand provides further support for the basics of Nalewajski's charge sensitivity analysis. Based on Parr and Liu's functional expansion of the energy functional, a new energy decomposition is introduced with an order of magnitude analysis of the different terms for a series of simple molecules both at their equilibrium geometry and upon variation in bond length and dihedral angle. Finally, for the first time, the perturbation expansion of the energy functional is studied numerically up to second order now that all response functions and integration techniques are at hand. The perturbation expansion energies are in excellent agreement with those obtained directly from DFA calculations giving confidence in the convergence of the perturbation series and its use in judging the importance of the different terms in reactivity investigations.

The interaction between lipid and vitamin D3 impacts lipid metabolism and innate immunity in Chinese mitten crabs Eriocheir sinensis.

As a fat-soluble vitamin, vitamin D3 relies on fat to perform its biological function, affecting lipid metabolism and innate immunity. This study used different percentages of lipid and vitamin D3 diets to evaluate the synergistic effects on the growth, lipid metabolism and immunity of juvenile Eriocheir sinensis (5.83 ± 0.01 g) for 56 days, including low lipid (LL, 1.5%) and normal lipid (NL, 7.5%) and three levels of vitamin D3: low (LVD, 0 IU/kg), medium (MVD, 9000 IU/kg) and high (HVD, 27,000, IU/kg). The synergistic effect of lipid and vitamin D3 was not significant on growth but significant on ash content, total protein, hepatopancreas lipid content, hemolymph 1α,25-hydroxy vitamin D3 [1α,25(OH)2D3] content, hepatopancreas lipolysis and synthesis genes. Crabs fed normal lipid (7.5%) and medium vitamin D3 (9000 IU/kg) had the highest hepatopancreas index, hemolymph 1α,25(OH)2D3 content, antibacterial ability, immune-related genes and hepatopancreatic lipid synthesis genes expression, but down-regulated the lipolysis genes expression. In contrast, crabs fed diets with low lipid percentage (1.5%) had low growth performance, hemolymph 1α,25(OH)2D3, mRNA levels of lipid synthesis genes, antibacterial ability and immune-related gene expression. At the 1.5% lipid level, excessive or insufficient vitamin D3 supplementation led to the obstruction of ash and protein deposition, reduced growth and molting, aggravated the reduction in antioxidant capacity, hindered antimicrobial peptide gene expression and reduced innate immunity, and resulted in abnormal lipid accumulation and the risk of oxidative stress. This study suggests that diets' lipid and vitamin D3 percentage can enhance antioxidant capacity, lipid metabolism and innate immunity in E. sinensis. A low lipid diet can cause growth retardation, reduce antioxidant capacity and innate immunity, and enhance lipid metabolism disorder.

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. Applications to examine physiochemical properties in external electric fields and to evaluate polarizability for proteins and crystals are discussed. A few possible directions for future development are followed, with the special emphasis on its merger with machine learning.

Finite temperature string by K-means clustering sampling with order parameters as collective variables for molecular crystals: application to polymorphic transformation between ß-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. A K-means clustering algorithm based on the Euclidean distance and sample weight was used to smooth the initial finite temperature string (FTS), and the minimum free energy path connecting ß-CL-20 and ε-CL-20 was sketched by the string method in collective variables, and the free energy profile along the path and the nucleation kinetics were obtained by Markovian milestoning with Voronoi tessellations. In comparison with the average-based sampling, the K-means clustering algorithm provided an improved convergence rate of FTS. The simulation of transformation was independent of OP types but was affected greatly by finite-size effects. A surface-mediated local nucleation mechanism was confirmed and the configuration located at the shoulder of potential of mean force, rather than overall maximum, was confirmed to be the critical nucleus formed by the cooperative effect of the intermolecular interactions. This work provides an effective way to explore the polymorphic transformation of caged molecular crystals at the molecular level.

Multimodal integration for Barrett's esophagus.

The esophageal adenocarcinoma is facing a worldwide challenge: early prediction and risk assessment in clinical Barrett's esophagus (BE). In recent years, the growing interests have been witnessed in prediction and risk assessment in clinical BE. However, the resolution is limited, and the system is huge and expensive for the existing devices. Inspired by the principle of collaboration between human eye vision and brain cortex in data processing, here we propose multimodal learning framework to tackle tasks from various modalities, which can benefit from each other. To our findings, the experimental result indicates that low-level modality can directly affect high-level modality and form the final risk grading based on contribution, which maximizes the clinical performance of medical professionals based on our findings.

Simultaneous identification of strong and weak interactions with Pauli energy, Pauli potential, Pauli force, and Pauli charge.

Strong and weak interatomic interactions in chemical and biological systems are ubiquitous, yet how to identify them on a unified theoretical foundation is still not well established. Recently, we proposed employing Pauli energy-based indexes, such as strong covalent interaction and bonding and noncovalent interaction indexes, in the framework of density functional theory for the purpose. In this work, we extend our previous theoretical work by directly employing Pauli energy, Pauli potential, Pauli force, and Pauli charge to simultaneously identify both strong covalent bonding and weak noncovalent interactions. Our results from this work elucidate that using their signature isosurfaces, we can identify different types of interactions, either strong or weak, including single, double, triple, and quadruple covalent bonds, ionic bond, metallic bond, hydrogen bonding, and van der Waals interaction. We also discovered strong linear correlations between Pauli energy derived quantities and different covalent bond orders. These qualitative and quantitative results from our present study solidify the viewpoint that a unified approach to simultaneously identify both strong and weak interactions is possible. In our view, this work signifies one step forward towards the goal of establishing a density-based theory of chemical reactivity in density functional theory.

Cooperativity and Frustration Effects (or Lack Thereof) in Polarizable and Non-polarizable Force Fields.

Understanding cooperativity and frustration is crucial for studying biological processes such as molecular recognition and protein aggregation. Force fields have been extensively utilized to explore cooperativity in the formation of protein secondary structures and self-assembled systems. Multiple studies have demonstrated that polarizable force fields provide more accurate descriptions of this phenomenon compared to fixed-charge pairwise nonpolarizable force fields, thanks to the incorporation of polarization effects. In this study, we assess the performance of the AMOEBA polarizable force field and the AMBER and OPLS nonpolarizable pairwise force fields in capturing positive and negative cooperativity recently explored in neutral and charged molecular clusters using density functional theory. Our findings show that polarizable and nonpolarizable force fields qualitatively reproduce the relative cooperativity observed in electron structure calculations. However, AMBER and OPLS fail to describe absolute cooperativity. In contrast, AMOEBA accounts for the absolute cooperativity by considering interactions beyond pairwise interactions. According to the energy decomposition analysis, it is observed that the electrostatic interactions calculated with the AMBER and OPLS force fields seem to play an important and counterintuitive role in reproducing the adiabatic interaction energies calculated with density functional theory. However, it is important to note that these force fields, due to their nature, do not explicitly incorporate many-body effects, which limits their ability to accurately describe cooperativity. On the other hand, frustration in polarizable and nonpolarizable force fields is caused by changes in bond stretching and angle bending terms of the building blocks when they are forming a complex.

Silencing of CD147 inhibits cell proliferation, migration, invasion, lipid metabolism dysregulation and promotes apoptosis in lung adenocarcinoma via blocking the Rap1 signaling pathway.

OBJECTIVE: CD147 is an important glycoprotein that participates in the progression of diverse cancers. This study aims to explore the specific function of CD147 in lung adenocarcinoma (LUAD) and to reveal related downstream molecular mechanisms. METHODS: Followed by silencing of CD147, the viability, migration, invasion, and apoptosis of LUAD cells were measured by CCK8, wound healing, transwell assay, and flow cytometer, respectively. The expression of CD147 and two markers of lipid metabolism (FASN and ACOX1) were detected by qRT-PCR. A xenograft tumor model was constructed to investigate the function of CD147 in vivo. Then transcriptome sequencing was performed to explore the potential mechanisms. After measuring the expression of Rap1 and p-p38 MAPK/p38 MAPK by western blot, the changes of CD147 and lipid metabolism markers (FASN, ACOX1) was detected by Immunohistochemistry. Moreover, a Rap1 activator and a Rap1 inhibitor were applied for feedback functional experiments. RESULTS: CD147 was up-regulated in LUAD cells, and its silencing inhibited cell proliferation, migration, invasion, lipid metabolism dysregulation and promoted apoptosis, while overexpression of CD147 showed the opposite results. Silencing of CD147 also inhibited the growth of tumor xenografts in mice. Transcriptome sequencing revealed 834 up-regulated differentially expressed genes (DEGs) and 602 down-regulated DEGs. After functional enrichment, the Rap1 signaling pathway was selected as a potential target, which was then verified to be blocked by CD147 silencing. In addition, the treatment of Rap1 activator weakened the inhibiting effects of si-CD147 on the proliferation, migration, invasion, and lipid metabolism in LUAD cells, while the intervention of RAP1 inhibitor showed the opposite results. CONCLUSIONS: Silencing of CD147 inhibited the proliferation, migration, invasion, lipid metabolism dysregulation and promoted apoptosis of LUAD cells through blocking the Rap1 signaling pathway.

Directionality and additivity effects of molecular acidity and aromaticity for substituted benzoic acids under external electric fields.

Our recent study [M. Li et al.Phys. Chem. Chem. Phys., 2023, 25, 2595-2605] unveiled that the impact of an external electric field on molecular acidity and aromaticity for benzoic acid is directional, which can be understood using changes in frontier orbitals and partial charges. However, it is unclear if the effect will disappear when substituting groups are present and whether new patterns of changes will show up. In this work, as a continuation of our efforts to appreciate the impact of external electric fields on physiochemical properties, we find that the directionality effect is still in place for substituted benzoic acid derivatives and that there exists the additivity effect with respect to the number of substituent groups, regardless of the direction of the applied field and the type of substituting groups. We confirm the findings using electron-donating and electron-accepting groups with the electric field applied either parallelly or perpendicularly to the carboxyl group along the benzene ring. The directionality and additivity effects uncovered from this work should enrich the body of our knowledge about the impact of external electric fields on physiochemical properties and could be applicable to other systems and properties as well.

Dietary cultured supernatant mixture of Cetobacterium somerae and Lactococcus lactis improved liver and gut health, and gut microbiota homeostasis of zebrafish fed with high-fat diet.

Postbiotics have the ability to improve host metabolic disorders and immunity. In order to explore whether the postbiotics SWFC (cultured supernatant mixture of Cetobacterium somerae and Lactococcus lactis) repaired the adverse effects caused by feeding of high-fat diet (HFD), zebrafish were selected as the experimental animal and fed for 6 weeks, with dietary HFD as the control group, and HFD containing 0.3 g/kg and 0.4 g/kg SWFC as the treatment groups. The results indicated that addition of SWFC in the diet at a level of 0.3 and 0.4 g/kg didn't affect the growth performance of zebrafish (P > 0.05). Supplementation of dietary SWFC0.3 relieved lipid metabolism disorders through significant increasing in the expression of pparα and cpt1, and decreasing the expression of cebpα, pparγ, acc1 and dgat-2 genes (P < 0.05). Moreover, the content of triacylglycerol was markedly lower in the liver of zebrafish grouped under SWFC0.3 (P < 0.05). Dietary SWFC0.3 also improved the antioxidant capacity via increasing the expression level of ho-1, sod and gstr genes, and significant inducing malondialdehyde content in the liver of zebrafish (P < 0.05). Besides, dietary SWFC0.3 also notably improved the expression level of lysozyme, c3a, defbl1 and defbl2 (P < 0.05). The expression level of pro-inflammatory factors (nf-κb, tnf-α, and il-1ß) were significantly decreased and the expression level of anti-inflammatory factor (il-10) was markedly increased in the postbiotics 0.3 g/kg group (P < 0.05). Feeding with SWFC0.3 supplemented diet for 6 weeks improved the homeostasis of gut microbiota and increased the survival rate of zebrafish after challenged with Aeromonus veronii Hm091 (P < 0.01). It was worth noting that the positive effect of dietary SWFC at a level of 0.3 g/kg was considerably better than that of 0.4 g/kg. This may imply that the effectiveness and use of postbiotics is limited by dosage.

Accurate and Efficient Prediction of Post-Hartree-Fock Polarizabilities of Condensed-Phase Systems.

To accurately and efficiently predict the molecular response properties (such as polarizability) at post-Hartree-Fock levels for condensed-phase systems under periodic boundary conditions (PBC) is still an unaccomplished and ongoing task. We demonstrate that static isotropic polarizabilities can be cost-effectively predicted at post-Hartree-Fock levels by combining the linear-scaling generalized energy-based fragmentation (GEBF) and information-theoretic approach (ITA) quantities. In PBC-GEBF, the total molecular polarizability of an extended system is obtained as a linear combination of the corresponding quantities of a series of small embedded subsystems of several monomers. Here, we show that in the PBC-GEBF-ITA framework, one can obtain the molecular polarizabilities and establish linear relations to ITA quantities. Once these relations are established for smaller subsystems, one can predict the polarizabilities of larger subsystems directly from the molecular wavefunction (or electron density) via ITA quantities. Alternatively, one can determine the total molecular polarizability via a linear combination equation in PBC-GEBF. We have corroborated that this newly proposed PBC-GEBF-ITA protocol is much more efficient than the original PBC-GEBF approach but is not much less accurate and that this conclusion holds for both many-body perturbation theory and the coupled cluster calculations. Good efficiency and transferability of the PBC-GEBF-ITA protocol are demonstrated for periodic systems with several hundred atoms in a unit cell.

Rhodium-Catalyzed Asymmetric Arylation-Induced Glycolate Aldol Additions of Silyl Glyoxylates.

(Diene)Rh(I) complexes catalyze the stereoselective three-component coupling of silyl glyoxylates, arylboronic acids, and aldehydes to give glycolate aldol products. The participation of Rh-alkoxides in the requisite Brook rearrangement was established through two component Rh-catalyzed couplings of silyl glyoxylates with ArB(OH)2 to give silyl-protected mandelate derivatives. The intermediacy of a chiral Rh-enolate was inferred through enantioselective protonation using a chiral Rh-catalyst. Diastereoselective three-component couplings with aldehydes as terminating electrophiles to give racemic products were best achieved with a bulky aryl ester on the silyl glyoxylate reagent. Optimal enantioselective couplings were carried out with the tert-butyl ester variant using an anisole-derived enantiopure tricyclo[3.2.2.02,4 ]nonadiene ligand.

High-speed real-time periodic weak pulse signal detection with simplified phase-weighted stacking.

Phase-weighted stacking (PWS) is an efficient noise reduction technique widely used in exploration seismology. It uses the coherence of the instantaneous phase to enhance signals by reducing incoherent noise. However, the high computational cost makes it difficult to apply PWS for the real-time detection of weak signals with high repetition frequency. This paper proposes a novel simplified PWS method with low computational complexity. The complex plane is divided into four quadrants, and the instantaneous phases in the same quadrant are simplified to the same phase. Based on the proposed method combined with a one-bit analog-to-digital converter, a novel field-programmable gate array-based high-speed real-time periodic weak pulse signal detection technique is presented. A prototype is implemented to verify the proposed technique. For weak pulse signals with an input signal-to-noise ratio (SNR) of -21 dB to -15 dB for 2500 cycles, the results obtained show that the simplified PWS algorithm can improve the SNR of the coherently integrated signals by about 10-15 dB with a latency of about 2 µs.

Topological analysis of information-theoretic quantities in density functional theory.

We have witnessed considerable research interest in the recent literature about the development and applications of quantities from the information-theoretic approach (ITA) in density functional theory. These ITA quantities are explicit density functionals, whose local distributions in real space are continuous and well-behaved. In this work, we further develop ITA by systematically analyzing the topological behavior of its four representative quantities, Shannon entropy, two forms of Fisher information, and relative Shannon entropy (also called information gain or Kullback-Leibler divergence). Our results from their topological analyses for 103 molecular systems provide new insights into bonding interactions and physiochemical properties, such as electrophilicity, nucleophilicity, acidity, and aromaticity. We also compare our results with those from the electron density, electron localization function, localized orbital locator, and Laplacian functions. Our results offer a new methodological approach and practical tool for applications that are especially promising for elucidating chemical bonding and reactivity propensity.