Chemical Calculations Research Articles

Solvent-mediated modification of thermodynamics and kinetics of monoethanolamine regeneration reaction in amine-stripping carbon capture: Computational chemistry study.

A major limitation of amine-based post-combustion carbon capture technology is the necessity to regenerate amines at high temperatures, which dramatically increases operating costs. This paper concludes the effect of solvent choice as a possible route to modify the thermodynamics and kinetics characterizing the involved amine regeneration reactions and discusses whether these modifications can be economically beneficial. We report experimentally benchmarked computational chemistry calculations of monoethanolamine regeneration reactions employing aqueous and non-aqueous solvents with a wide range of dielectric constants. Unlike previous studies, our improved computational chemistry framework could accurately reproduce the right experimental activation energy of zwitterion formation. From the thermodynamics and kinetics of the predicted reactions, the use of non-aqueous solvents with small dielectric constants led to reductions in regeneration Gibbs free energies, activation barriers, and enthalpy changes. This can reduce energy consumption and give an opportunity to run desorption columns at relatively lower temperatures, thus offering the possibility of relying on low-grade waste heat as an energy input.

Recent Advancements and Developments of Molecular Dynamics Simulations in the Discovery of Anti‐protozoal Agents

AbstractMolecular dynamics simulations have been developed as the most powerful tool in the field of computational chemistry for the discovery of novel anti‐protozoal agents against malaria. In this review, the recent advancements and developments in the field of molecular dynamics simulations driven identification and optimization of promising anti‐protozoal agents have been highlighted along with the use of advanced simulation softwares, energy calculations, stability parameters, and many more. To the best of our knowledge, the present work has been the first review article to highlight the use of molecular dynamics simulations for the discovery of anti‐plasmodial agents with the aim to dig out the significant insights into the simulations having the applications for the benefit of computational and medicinal chemists.

The Role of Computational Chemistry in Exploring the Structure and Properties of Chloroquine Derivatives

The Role of Computational Chemistry in Exploring the Structure and Properties of Chloroquine Derivatives

AI in computational chemistry through the lens of a decade-long journey.

This article gives a perspective on the progress of AI tools in computational chemistry through the lens of the author's decade-long contributions put in the wider context of the trends in this rapidly expanding field. This progress over the last decade is tremendous: while a decade ago we had a glimpse of what was to come through many proof-of-concept studies, now we witness the emergence of many AI-based computational chemistry tools that are mature enough to make faster and more accurate simulations increasingly routine. Such simulations in turn allow us to validate and even revise experimental results, deepen our understanding of the physicochemical processes in nature, and design better materials, devices, and drugs. The rapid introduction of powerful AI tools gives rise to unique challenges and opportunities that are discussed in this article too.

A perspective on the future of quantum chemical software: the example of the ORCA program package.

The field of computational chemistry has made an impressive impact on contemporary chemical research. In order to carry out computational studies on actual systems, sophisticated software is required in form of large-scale quantum chemical program packages. Given the enormous diversity and complexity of the methods that need to be implementation in such packages, it is evident that these software pieces are very large (millions of code lines) and extremely complex. Most of the packages in widespread use by the computational chemistry community have had a development history of decades. Given the rapid progress in the hardware and a lack of resources (time, workforce, money), it is not possible to keep redesigning these program packages from scratch in order to keep up with the ever more quickly shifting hardware landscape. In this perspective, some aspects of the multitude of challenges that the developer community faces are discussed. While the task at hand - to ensure that quantum chemical program packages can keep evolving and make best use of the available hardware - is daunting, there are also new evolving opportunities. The problems and potential cures are discussed with the example of the ORCA package that has been developed in our research group.

Computational chemistry for water-splitting electrocatalysis.

Electrocatalytic water splitting driven by renewable electricity has attracted great interest in recent years for producing hydrogen with high-purity. However, the practical applications of this technology are limited by the development of electrocatalysts with high activity, low cost, and long durability. In the search for new electrocatalysts, computational chemistry has made outstanding contributions by providing fundamental laws that govern the electron behavior and enabling predictions of electrocatalyst performance. This review delves into theoretical studies on electrochemical water-splitting processes. Firstly, we introduce the fundamentals of electrochemical water electrolysis and subsequently discuss the current advancements in computational methods and models for electrocatalytic water splitting. Additionally, a comprehensive overview of benchmark descriptors is provided to aid in understanding intrinsic catalytic performance for water-splitting electrocatalysts. Finally, we critically evaluate the remaining challenges within this field.

Molecular mechanisms that cause cell death in LHON

Mitochondrial impairments, caused by mtDNA mutations, lead to RGC death and optic atrophy causing blindness in LHON. It was once thought that this was a disease of impaired bioenergetics. More recent thinking, considering the tempo of damage, studies in cybrids and a faithful mouse genetic model of LHON, has led to the realization that the problem is more that of the pathological generation of Reactive Oxygen Species (ROS). For example, synaptosome analysis from the brains of LHON mice show normal levels of ATP, but the blockage of Complex I activity was associated with very high levels of ROS. We hypothesized that the mtDNA mutation, specifically for 3460 in ND1, changed the atomic structures around COQ10 such that ROS were generated. In order to test that hypothesis, we conducted a series of experiments with statistical ensembles, built with Monte Carlo and Boltzmann sampling for simulations in computational chemistry. We began with the single amino acid mutation in ND1 of Complex I that switches hydrophobic alanine to hydrophilic threonine, at the entry of the Coenzyme Q10 binding channel. We explicated the mechanistic consequences of this mutation, using the tools of Molecular Dynamics and Free Energy Perturbation simulations. We showed that the mutant remained capable of binding Coenzyme Q10. Indeed, the mutated channel was even more proficient than the wild type in reducing ubiquinone to ubiquinol due to the closer average proximity of the Coenzyme Q10 headgroup to the chain of iron–sulfur clusters, from which it received electrons via quantum mechanical tunnelling. However, the mutation kinetically hindered the exit of the reduced (ubiquinol) form of Q10 from the ND1 channel, slowing the passage of its headgroup due to unfavourable electrostatics. This effect lead to overproduction of ROS via re‐oxidation of Coenzyme Q10 as electrons were sent back up the Iron–sulfur cluster chain, where the ROS production occurs. Another line of studies has shown that ROS lead to the death of RGCs affecting the smallest axons first. In those areas of the optic nerve in which larger axons are preponderate, the ROS are absorbed by the larger axons and little more happens. However, there is a dearth of large axons inferior temporally where the papillomacular bundle enters the optic nerve. Then, the ROS begins a reiterative and vicious cycle of cell death and the production of more ROS. This explains both the very peculiar spatial and temporal features of the optic neuropathy in LHON.

Theoretical Study of Natural Product Biosynthesis Using Computational Chemistry.

The biosynthetic pathways of natural products are complicated, and it is difficult to fully elucidate their details using experimental chemistry alone. In recent years, efforts have been made to elucidate the biosynthetic reaction mechanisms by combining computational and experimental methods. In this review, we will discuss the biosynthetic studies using computational chemistry for various terpene compounds such as cyclooctatin, sesterfisherol, quiannulatene, trichobrasilenol, asperterpenol, preasperterpenoid, spiroviolene, and mangicol.

Dominacijski broj za ciklooktanske lance

Introduction/purpose: Chemical structures are conveniently represented by graphs where atoms are nodes (vertices) and chemical bonds are branches (lines) in the graph. A graphical representation of a molecule provides a lot of useful information about the chemical properties of the molecule. It is known that numerous physical and chemical properties of molecules are highly correlated with theoretical invariants of graphs, which we call topological indices. One such theoretical invariant is the dominance number. The aim of this research is to determine the k-dominance number for cyclooctane chains 𝐶𝑂𝐶𝑛 1 , 𝐶𝑂𝐶𝑛 2 , 𝐶𝑂𝐶𝑛 3 and 𝐶𝑂𝐶𝑛 4 , for k ∈ {1,2,3}, n ∈ 𝑁. Methods: The cyclooctane chain is a chain of octagons connected by a single line. The vertices of the octagon are treated as nodes of the graph, and the sides and the line connecting them, as branches in the graph. Using mathematical methods, k-dominance was determined on one octagon, k∈{1,2,3}. Then, by representing the cyclooctane chains 𝐶𝑂𝐶𝑛 1 , 𝐶𝑂𝐶𝑛 2 , 𝐶𝑂𝐶𝑛 3 and 𝐶𝑂𝐶𝑛 4 , in a convenient, isomorphic way, we determined their k-dominance number, k∈{ 1,2,3}. Results: Determining k-dominance, k∈{1,2,3}, for 4 cyclooctane chains 𝐶𝑂𝐶𝑛 1 , 𝐶𝑂𝐶𝑛 2 , 𝐶𝑂𝐶𝑛 3 and 𝐶𝑂𝐶𝑛 4 , we obtained 12 different formulas to calculate their k-dominance number. All formulas are composed of several alternative algebraic expressions, the selection of which is conditioned by the divisibility of the number n by the number 2, 3 or 4, depending on the type of cyclooctane chain and k-dominance to be determined. The results of the research are fully presented in the paper through mathematically proven theorems and graphical representations. Conclusion: The results show that the k-dominance numbers, k∈{1,2,3}, on cyclooctane chains 𝐶𝑂𝐶𝑛 1 , 𝐶𝑂𝐶𝑛 2 , 𝐶𝑂𝐶𝑛 3 and 𝐶𝑂𝐶𝑛 4 , are determined and explicitly expressed by mathematical expressions. They also indicate the possibility of their application in molecular graphs of cyclooctane rings, in computational chemistry, chemical and biological industry.

NMR spectroscopy can help accelerate antiviral drug discovery programs

Small molecule drugs have an important role to play in combating viral infections, and biophysics support has been central for contributing to the discovery and design of direct acting antivirals. Perhaps one of the most successful biophysical tools for this purpose is NMR spectroscopy when utilized strategically and pragmatically within team workflows and timelines. This report describes some clear examples of how NMR applications contributed to the design of antivirals when combined with medicinal chemistry, biochemistry, X-ray crystallography and computational chemistry. Overall, these multidisciplinary approaches allowed teams to reveal and expose compound physical properties from which design ideas were spawned and tested to achieve the desired successes. Examples are discussed for the discovery of antivirals that target HCV, HIV and SARS-CoV-2.

Analysis and Design of Amine–based Materials for CO<sub>2</sub> Separation Using Computational Chemistry

Analysis and Design of Amine–based Materials for CO<sub>2</sub> Separation Using Computational Chemistry

Synergy of experimental and computational chemistry: structure and biological activity of Zn(II) hydrazone complexes.

In this paper, three different Zn(II) complexes with (E)-2-(2-(1-(6-bromopyridin-2-yl)ethylidene)hydrazinyl)-N,N,N-trimethyl-2-oxoethan-1-aminium chloride (HLCl) have been synthesized and characterized by single crystal X-ray diffraction, elemental analysis, IR and NMR spectroscopy. All complexes are mononuclear, with the ligand (L) coordinated in a deprotonated formally neutral zwitterionic form via NNO donor set atoms. Complex 1 forms an octahedral geometry with the composition [ZnL2](BF4)2, while complexes 2 [ZnL(NCO)2] and 3 [ZnL(N3)2] form penta-coordinated geometry. Density functional theory (DFT) calculations were performed to enhance our understanding of the structures of the synthesized complexes and the cytotoxic activity of the complexes was tested against five human cancer cell lines (HeLa, A549, MDA-MB-231, K562, LS 174T) and normal human fibroblasts MRC-5. Additionally, antibacterial and antifungal activity of these complexes was tested against a panel of Gram-negative and Gram-positive bacteria, two fungal strains, and a yeast strain. It is noteworthy that all three complexes show selective antifungal activity comparable to that of amphotericin B. Molecular docking analysis predicted that geranylgeranyl pyrophosphate synthase, an enzyme essential for sterol biosynthesis, is the most likely target for inhibition by the tested complexes.

Binding energies of ethanol and ethylamine on interstellar water ices: synergy between theory and experiments.

Experimental and computational chemistry are two disciplines used to conduct research in astrochemistry, providing essential reference data for both astronomical observations and modeling. These approaches not only mutually support each other, but also serve as complementary tools to overcome their respective limitations. Leveraging on such synergy, we characterized the binding energies (BEs) of ethanol (CH3CH2OH) and ethylamine (CH3CH2NH2), two interstellar complex organic molecules (iCOMs), on crystalline and amorphous water ices through density functional theory (DFT) calculations and temperature-programmed desorption (TPD) experiments. Experimentally, CH3CH2OH and CH3CH2NH2 behave similarly, in which desorption temperatures are higher on the water ices than on a bare gold surface. Computed cohesive energies of pure ethanol and ethylamine bulk structures allow describing of the BEs of the pure species deposited on the gold surface, as extracted from the TPD curve analyses. The BEs of submonolayer coverages of CH3CH2OH and CH3CH2NH2 on the water ices cannot be directly extracted from TPD due to their co-desorption with water, but they are computed through DFT calculations, and found to be greater than the cohesive energy of water. The behaviour of CH3CH2OH and CH3CH2NH2 is different when depositing adsorbate multilayers on the amorphous ice, in that, according to their computed cohesive energies, ethylamine layers present weaker interactions compared to ethanol and water. Finally, from the computed BEs of ethanol, ethylamine and water, we can infer that the snow-lines of these three species in protoplanetary disks will be situated at different distances from the central star. It appears that a fraction of ethanol and ethylamine is already frozen on the grains in the water snow-lines, causing their incorporation in water-rich planetesimals.

Digichem: computational chemistry for everyone

We describe a new and effective tool for the efficient management of computational chemistry.

Navigating the Maize: Cyclic and conditional computational graphs for molecular simulation

Many computational chemistry and molecular simulation workflows can be expressed as graphs. This abstraction is useful to modularize and potentially reuse existing components, as well as provide parallelization and ease...

Current trends of chemoinformatics and computer chemistry in drug design: A review

A crucial direction in the progress of modern medical chemistry is the development and improvement of theoretical investigation methods of drugs mechanisms of action, predicting their activity, and virtual design of new drugs. This review describes the history of targeted search for biologically active compounds, current in silico approaches and tools used in the rational design of potential drugs, in particular the main computational strategies used in modern drug design are presented and outlines the main methodologies for implementing these strategies.

Functionality optimization for effective singlet fission coupling screening in the full-dimensional molecular and intermolecular coordinate space.

In computational chemistry, accurately predicting molecular configurations that exhibit specific properties remains a critical challenge. Its intricacies become especially evident in the study of molecular aggregates, where the light-induced functionality is tied to highly structure-dependent electronic couplings between molecules. Here, we present an efficient strategy for the targeted screening of the structural space employing a "functionality optimization" technique, in which a chosen descriptor, constrained by the ground state energy expression, is optimized. The chosen algorithmic differentiation (AD) framework allows one to automatically obtain gradients without its tedious implementation. We demonstrate the effectiveness of the approach by identifying perylene bisimide (PBI) dimer motifs with enhanced effective SF coupling. Our findings reveal that certain structural modifications of the PBI monomer, such as helical twisting and bending as well as slipped-rotated packing arrangements, can significantly increase the effective SF coupling.

Strain induced reactivity of cyclic iminoboranes: the (2 + 2) cycloaddition of a 1H-1,3,2-diazaborepine with ethene.

Iminoboranes have gathered immense attention due to their reactivity and potential applications as isoelectronic and isosteric alkynes. While cyclic alkynes are well investigated and useful reagents, cyclic iminoboranes are underexplored and their existence was inferred only via trapping experiments. We report the first direct spectroscopic evidence of a cyclic seven-membered iminoborane, 1-(tert-butyldimethylsilyl)-1H-1,3,2-diazaborepine 2, under cryogenic matrix isolation conditions. The amino-iminoborane 2 was photochemically generated in solid argon at 4 K from 2-azido-1-(tert-butyldimethylsilyl)-1,2-dihydro-1,2-azaborinine (3) and was characterized using FT-IR, UV-vis spectroscopy, and computational chemistry. The characteristic BN stretching vibration (1751 cm-1) is shifted by about 240 cm-1 compared to linear amino-iminoboranes indicating a significant weakening of the bond. The Lewis acidity value determined computationally (LAB = 9.1 ± 2.6) is similar to that of boron trichloride, and twelve orders of magnitude lower than that of 1,2-azaborinine (BN-aryne, LAB = 21.5 ± 2.6), a six-membered cyclic iminoborane. In contrast to the latter, the reduced ring strain of 2 precludes nitrogen fixation, but it unexpectedly allows facile (2 + 2) cycloaddition reaction with C2H4 under matrix isolation conditions at 30 K.

Theoretical investigation of multi-spin excited states of anthracene radical-linked π-conjugated spin systems by computational chemistry.

Multi-spin excited states of chromophore radical-linked π-conjugated spin systems are investigated by molecular orbital calculations based on density functional theory (DFT). The investigated systems consist of an anthracene photosensitive unit leading to a triplet-excited-state (S = 1), π-conjugated linker to propagate spin exchange-coupling, and stable organic radical with a doublet-ground-state (S = 1/2). The intramolecular exchange coupling (JDQ), g value, and fine-structure interaction of their excited states depended on the π-conjugation network (π-topology), type of radical, and molecular structure of the π-linker (length and dihedral angle). The exchange interaction was dependent on the π-topology and the type of radical species. A decrease in the dihedral angle between the anthracene moiety and phenyl linker in the photo-excited state led to larger exchange coupling. With an increase in the π-linker length (r), the magnitude of the exchange coupling gradually decreased in the photoexcited states according to JDQ = JEx0 exp(-βr), similar to the ground-state exchange. The g values of the quartet (Q) state depended only on the radical type (independent of the linker). Conversely, the fine-structure interaction of the Q state was independent of the radical type and depended on both the linker length and the dihedral angle.

Fine-tuning large language models for chemical text mining.

Extracting knowledge from complex and diverse chemical texts is a pivotal task for both experimental and computational chemists. The task is still considered to be extremely challenging due to the complexity of the chemical language and scientific literature. This study explored the power of fine-tuned large language models (LLMs) on five intricate chemical text mining tasks: compound entity recognition, reaction role labelling, metal-organic framework (MOF) synthesis information extraction, nuclear magnetic resonance spectroscopy (NMR) data extraction, and the conversion of reaction paragraphs to action sequences. The fine-tuned LLMs demonstrated impressive performance, significantly reducing the need for repetitive and extensive prompt engineering experiments. For comparison, we guided ChatGPT (GPT-3.5-turbo) and GPT-4 with prompt engineering and fine-tuned GPT-3.5-turbo as well as other open-source LLMs such as Mistral, Llama3, Llama2, T5, and BART. The results showed that the fine-tuned ChatGPT models excelled in all tasks. They achieved exact accuracy levels ranging from 69% to 95% on these tasks with minimal annotated data. They even outperformed those task-adaptive pre-training and fine-tuning models that were based on a significantly larger amount of in-domain data. Notably, fine-tuned Mistral and Llama3 show competitive abilities. Given their versatility, robustness, and low-code capability, leveraging fine-tuned LLMs as flexible and effective toolkits for automated data acquisition could revolutionize chemical knowledge extraction.