research articles in computational chemistry

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Computational chemistry articles from across Nature Portfolio

Computational chemistry describes the use of computer modelling and simulation – including ab initio approaches based on quantum chemistry, and empirical approaches – to study the structures and properties of molecules and materials. Computational chemistry is also used to describe the computational techniques aimed at understanding the structure and properties of molecules and materials.

Latest Research and Reviews

Designing the structure of cationic star-shaped trimeric surfactants most active in micelle formation using molecular connectivity indices

• Anna Mozrzymas

Enhancing property and activity prediction and interpretation using multiple molecular graph representations with MMGX

Reduced molecular graphs can integrate higher-level chemical information and leverage advantages from atom-level graph neural networks. Here, the authors introduce the Multiple Molecular Graph eXplainable model, investigating the effects of multiple molecular graphs, including Atom, Pharmacophore, JunctionTree, and FunctionalGroup, on model learning and interpretation from various perspectives

• Apakorn Kengkanna
• Masahito Ohue

Directional multiobjective optimization of metal complexes at the billion-system scale

A method is developed for the directional optimization of multiple properties without prior knowledge on their nature. Using a large ligand dataset, diverse metal complexes are found along the Pareto front of vast chemical spaces.

• Hannes Kneiding
• Ainara Nova
• David Balcells

Computational mechanistic investigation of the kinetic resolution of α-methyl-phenylacetaldehyde by norcoclaurine synthase

Norcoclaurine synthase from Thalictrum flavum ( Tf NCS) has been demonstrated to display high stereospecificity and yield in catalyzing the Pictet-Spengler reaction of dopamine with chiral aldehydes, however, the mechanism and factors related to this high stereospecificity remain unclear. Here, the authors conduct quantum chemical calculations and reveal the rate-limiting step and differential energy barriers for the reactions of two enantiomers of α-methylphenylacetaldehyde, as well as key residues related to stereospecificity.

• Shiqing Zhang
• Chenghua Zhang
• Xiang Sheng

The reaction mechanism of the Ideonella sakaiensis PETase enzyme

Polyethylene terephthalate (PET) can be depolymerized by the Ideonella sakaiensis PETase enzyme, however, questions remain about the precise catalytic mechanism. Here, the authors use unbiased QM/MM MD simulations to determine optimal mechanistic descriptions of the acylation and deacylation reactions, revealing the rate-limiting step and key interactions within the catalytic triad and Trp185 conformation.

• Tucker Burgin
• Benjamin C. Pollard
• H. Lee Woodcock

3D molecular generative framework for interaction-guided drug design

Designing a molecule that favorably binds to a protein pocket is a keystone of drug discovery. Zhung et al. devise DeepICL, which leverages the generalizable features of non-covalent protein-ligand interactions on a 3D molecular generative model, improving the quality of AI-designed molecules.

• Wonho Zhung
• Hyeongwoo Kim
• Woo Youn Kim

News and Comment

Just counting ten

• Chenyu Wang

Accelerating discovery in organic redox flow batteries

We highlight the challenges and opportunities in organic redox flow battery research, underscoring the need for collaborative research efforts. The synergy between computation and experimentation holds the potential to expedite progress in this field and can have far-reaching impacts beyond energy storage applications.

• Alán Aspuru-Guzik

The rise of ab initio surface thermodynamics

The ab initio atomistic thermodynamics approach, coined by Reuter and Scheffler formally in 2001, remains pivotal for understanding and predicting the stable surfaces of thermal catalysts under technical conditions.

• Aloysius Soon

A new twist to increase ion flow

The K + ion channel KCNQ2 modulates neuronal excitability and is targeted by retigabine, an anti-epileptic drug that enhances the probability of channel opening. New activators have now been discovered to increase unitary conductance through an unprecedented mechanism.

• Michael C. Sanguinetti

Modelling and advanced characterization of framework materials

Communications Chemistry is delighted to introduce a Collection of research works focused on the modelling and advanced characterization of framework materials. Here, the Guest Editors outline the themes within and look towards the future of the field.

• François-Xavier Coudert
• Claire L. Hobday
• Monique A. van der Veen

Fewer false positives in electrocatalytic nitrogen reduction by synergizing theory and experiment

The electrocatalytic nitrogen reduction reaction is a promising alternative to the Haber–Bosch process. However, the reproducibility and reliability of this process suffer from the persistence of false positives. Computational tools have the potential to alleviate this issue but several challenges must be addressed.

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Challenges and Opportunities for Computational Chemistry in the Exascale Era

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Exascale computing is defined as the capability of calculating 10 18 floating point operations per second (exaflops), which is five orders of magnitude higher than the capability of a state-of-the-art workstation. Summit and Fugaku supercomputers already marked the onset of the exascale era by ...

Keywords : High-performance computing, GPU optimization, Exascale era

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Computational Chemistry Needs To Be Sustainable, Too

By Beth Mundy

April 8, 2024

A diverse group of computational chemists is encouraging the research community to embrace a sustainable software ecosystem. That’s the message behind  a recent perspective article  published in the  Journal of Chemical Theory and Computation . The authors discuss possible scenarios of how to develop software in the face of a changing computational landscape.

“With more computing power, we can examine additional facets of chemistry,” said  Karol Kowalski , a computational chemist at  Pacific Northwest National Laboratory  (PNNL) and corresponding author of the paper. “I think that computational chemistry will play a huge role in developing our understanding of important chemical processes in the 21st century. We can use simulations to help guide and scope experimental studies in a powerful loop.”

Computing paradigms are in transition, with large-scale and quantum systems emerging as central to computing’s future. These new technologies will allow researchers to solve different and more complicated chemistry problems. But with new opportunities come new challenges, including creating integrated software that can seamlessly work together. 

“We need to ensure our approaches can fully use new developments in exascale machines, cloud computing, and quantum computing,” said Kowalski. “This requires planning for the future and anticipating the new challenges that will arise.”

What is sustainable software?

In the article, the authors defined sustainable software as a system of different software packages that can be assembled and used as a cohesive system to tackle a broad range of chemistry problems.

“As the questions we’re asking are getting more complicated, so is the process for finding suitable techniques to tackle them,” said  Niri Govind , a PNNL computational chemist and co-author of the paper. “We need to work together across different platforms to generate the most meaningful results. Using this technique effectively requires establishing standards for the field.”

The computational chemistry ecosystem represents a valuable testing ground for new methods. The problems faced by computational chemists and their software aren’t unique to chemistry—they can be found across scientific modeling efforts. As one of the most established computational environments in science, development teams have consistently been in contact and collaborated throughout recent years.

Collaborative efforts and knowledge-sharing are essential because, often, a single problem requires the use of multiple types of software to accurately capture the complexity of real-world systems. Often, research teams have a narrow focus while developing software that yields new capabilities to tackle specific problems. This ever-increasing ecosystem complexity leads to increasing collaboration as expertise narrows.

Shaping chemistry with computation

Not too long ago, computational chemistry simulations served primarily as validators of experimental findings. However, as computing power has increased, so has the ability of computational chemistry not just to validate but to solve complex problems, to guide and interpret experiments, and to enable predictions.

As the range of knowledge that can be gained from computational chemistry has expanded, it has come at a cost. The more complicated a simulation is, the more computing power and time are needed to reach a solution. Planning for the future, the authors argue, requires navigating the increasing demands of new problems, adapting to the requirements of next-generation computing architectures, and developing full interoperability.

Members of the  Computational and Theoretical Chemistry Institute (CTCI)  at PNNL are tackling this challenge through innovative, scalable solutions on current and future computational platforms.

“Through the CTCI, we have established an institutional framework to develop the next generation of computational chemistry software for leadership-class computing facilities,” said  Sotiris Xantheas, CTCI Director  and co-author of the paper. “Using a combination of computer science efforts with novel science tools, artificial intelligence, and quantum computing, the CTCI is poised to develop the next-generation molecular modeling capabilities.”

Workshopping for sustainable software

The perspective article emerged from discussions at the 2022 workshop “Sustainable Computational Chemistry Software Development and Integration,” which was supported by the Department of Energy, Office of Science, Chemical Sciences, Geosciences, and Biosciences Division, Computational and Theoretical Chemistry Program.

There, attendees discussed software infrastructure needs and investments to realize the full potential of emerging computing resources. The meeting brought together researchers from across the computational chemistry community.

During the workshop discussions, developers realized they were consistently facing similar problems adapting to new computing resources and developing integrable software. Individual teams realized they could draw on experiences from others who have already found solutions to emerging problems.

PNNL researchers have continued those conversations, working closely with academic, National Laboratory, and industry partners to create innovative new tools for scientific discovery through projects such as  TEC4 (Transferring Exascale Computational Chemistry to Cloud Computing Environment and Emerging Hardware Technologies) .

The authors concurred that sustainable software development allows the field to move faster across the board without requiring researchers to reinvent existing fixes consistently. This strategy makes investments more efficient, as collaboration also builds bridges of internal consistency across different programs. The authors recognize the need for continued adaptation of software to meet both scientific and hardware needs.

“This work comes from our current perspective,” said Govind. “This isn’t a static plan. We all need to be prepared to embrace new and evolving points of view.”

PNNL Background

Pacific Northwest National Laboratory  draws on its distinguishing strengths in  chemistry ,  Earth sciences ,  biology , and  data science  to advance scientific knowledge and address challenges in  sustainable energy  and  national security . Founded in 1965, PNNL is operated by Battelle for the Department of Energy’s Office of Science, which is the single largest supporter of basic research in the physical sciences in the United States. DOE’s Office of Science is working to address some of the most pressing challenges of our time. For more information, visit  https://energy.gov/science . For more information on PNNL, visit  PNNL’s News Center . Follow us on  Twitter ,  Facebook ,  LinkedIn  and  Instagram .

Beth Mundy  is a trained scientist and science communicator who is passionate about helping scientists communicate their work. She collaborates with colleagues across PNNL to tell stories about highly technical topics in an engaging way.

This article was initially posted on the PNLL News Site   and is reproduced here with their permission.

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Simulations track how MOFs adsorb water, one molecule at a time

By Clara Humann 2024-04-10T08:30:00+01:00

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Researchers in the US have produced remarkably realistic molecular dynamics simulations of how metal–organic frameworks (MOFs) adsorb water. 1 ‘You can almost drink our water model because it’s so realistic,’ jokes Francesco Paesani , who led the study at the University of California, San Diego. ‘You should trust the simulations because they are really very, very close to what the reality is.’

Atmospheric water harvesting has emerged as a potential strategy for tackling fresh water shortages, particularly in areas far from the coast. ‘Having a material that can just capture water from the atmosphere, even at those lower humidity ranges, could be quite transformative,’ comments Paesani.

MOFs’ large surface area and wide range of tuneable properties make them appealing materials for atmospheric water harvesting. However, previous computational studies on water harvesting with MOFs often fail to realistically reflect experimental results. ‘The main challenges of simulations of water in MOFs is that water enters as a gas but then as it fills the pore, it starts developing liquid-like and even ice-like behaviour,’ explains Paesani.

Now, Paesani’s group has shown how performing classical molecular dynamics simulations using a potential energy function developed by the team called the MB-pol data-driven many-body potential, could address such challenges. The simulations report results much closer to experimental values than previous models and can ‘provide insights into what each water molecule does when it enters the pore,’ he says.

‘The MB-pol model developed by Paesani and co-workers provides outstanding agreement with experiment for a wide variety of properties of water,’ comments Randall Snurr , an expert in MOF modelling at Northwestern University in the US.

Source: © Francesco Paesani/University of California San Diego

Snapshots of the molecular dynamics simulations for two water molecules in Ni 2 F 2 BTDD (left), Ni 2 Cl 2 BTDD (middle), and Ni 2 Br 2 BTDD (right)

Paesani’s team tested the model on Ni 2 F 2 BTDD (X = F, Cl, Br), a promising halide-exchanged MOF 2 that ‘shows the best performance in the range of relative humidity between 20–30%,’ says Paesani. ‘It is a MOF that is able to adsorb a large amount of water molecules relative to the mass of the MOF within that humidity range.’

They found that exchanging the halide atoms in Ni 2 X 2 BTDD resulted in three MOFs with different properties and water adsorption capabilities. While Ni 2 F 2 BTDD and Ni 2 Cl 2 BTDD adsorb over 100% of their weight in water at 32% relative humidity, Ni 2 Br 2 BTDD adsorbs 64% of its weight in water below 25% relative humidity; one of the best water uptake values ever reported.

What is particularly interesting, says Snurr, is the study found that ‘some properties, such as the enthalpy of adsorption, do not follow the trend of F, Cl, Br’. ‘From the molecular-level modelling reported here, the [researchers] are able to provide useful insights into these unexpected trends.’

Paesani is confident their model will influence future research on atmospheric water harvesting materials. ‘Experimentalists can use our data and be sure that what we see is exactly reflecting what they measure in experiment,’ he explains. This should ‘help speed up the development of materials without going through the synthetic process, which can be time consuming and much more expensive.’

1 K M Huntera and F Paesani, Chem. Sci. , 2024, DOI: 10.1039/d3sc06162k

2 J J Oppenheim et al , J. Am. Chem. Soc. , 2021, 143 , 16343 (DOI: 10.1021/jacs.1c07449 )

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Open Access Policy refers to a set of principles and guidelines aimed at providing unrestricted access to scholarly research and literature. It promotes the free availability and unrestricted use of research outputs, enabling researchers, students, and the general public to access, read, download, and distribute scholarly articles without financial or legal barriers. In this response, I will provide you with an overview of the history and latest resolutions related to Open Access Policy.

The article provides information about modern problems of writing the Kazakh language, the importance of its role and development in the context of mass digitization using artificial intelligence technologies and computational linguistics methods. The incorrectness of the current alphabet of the Kazakh language based o ... n the Cyrillic alphabet is proved in connection with the inclusion of Cyrillic letters in it, denoting phonemes that are not included in its sound structure. The necessity of reforming the Kazakh writing by replacing the incorrect alphabet is substantiated. Errors and contradictions are shown in the approved version of the Kazakh alphabet based on the Latin alphabet, as well as the alphabet proposed as a replacement for the approved one, in which some previous errors are repeated. In both cases, no analysis and clarification of the sound system of the Kazakh language, which is the basis of any alphabet, is carried out. In this study, to clarify the sound system of the Kazakh language, experiments were carried out to determine the articulation and acoustic features of Kazakh sounds with the help the computer programs used for many natural languages. In the articulation analysis, special attention was paid to vowels, which give rise to various contradictions in the Kazakh letter. It is proposed to use a new classification of vowels according to four binary features, rather than the traditional classification according to three binary features. Acoustic analysis uses the method of formant analysis, which is aimed at identifying certain formants in the spectrogram. The formant is obtained using a spectrograph. Quantitatively, the formants correspond to the maxima in the speech spectrum and usually appear on spectrograms as horizontal bands. After determining the composition and classification of the sound system of the Kazakh language, two variants of the alphabet based on the Latin alphabet are proposed: the first one is based on the Turkish alphabet using diacritical marks; the second is based on the English alphabet using digraphs. The second option offers ways to solve problems that arise when using digraphs. In conclusion, information is provided on the ongoing and ongoing work in Kazakhstan related to the creation of smart systems in the Kazakh language based on the methods and technologies of artificial intelligence and computational linguistics, the results of which are reflected in the list of sources. Read more

Synthetic approaches to the construction of the heterocyclic benzo[4’,5’]imidazo[2’,1’:6,1]pyrido[2,3-d]pyrimidine system based on heterocyclizations of substituted benzimidazoles and a new alternative strategy based on 2,4,6-trisubstituted pyrimidinyl-5-propanoic acids are considered. The latte ... r method has been shown to be a successful addition to previously described methods, since it allows one to bypass the significant limitations associated with the use of substituted benzimidazoles and allows the introduction of functional substituents at different positions of the heterocycle that are inaccessible by other methods. The available information on derivatives of this heterocyclic system and their biological properties is summarized. Read more

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Physical & Computational Chemistry

Physical and computational chemistry at the University of Iowa is a vibrant area of research with relevance to a wide range of interesting fundamental and applied problems and involving researchers from many fields of science.

Diverse experimental and theoretical research projects encompass interdisciplinary topics in atmospheric and environmental chemistry, biological chemistry, biophysical chemistry, laser spectroscopy, molecular dynamics, molecular modeling, nanoscience, quantum chemistry, and surface science.

Physical & computational chemistry faculty

Renee S. Cole

Aditi Bhattacherjee

Christopher M. Cheatum

Claudio J. Margulis

Alexei V. Tivanski

Bess Vlaisavljevich

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April 5, 2024 feature

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Scientists harness chemical dynamics for complex problem solving

by Tejasri Gururaj , Phys.org

At the intersection of chemistry and computation, researchers from the University of Glasgow have developed a hybrid digital-chemical probabilistic computational system based on the Belousov-Zhabotinsky (BZ) reaction which can be used for solving combinatorial optimization problems.

By harnessing the inherent probabilistic nature of BZ reactions, the system demonstrates emergent behaviors like replication and competition seen in complex systems, reminiscent of living organisms. This could pave the way for novel approaches to computational tasks that are fazed by the limitations set by modern computation.

Combining electronic control and chemical dynamics offers a way to perform efficient computation, combining the best of both towards the development of adaptive, bio-inspired computing platforms with unparalleled efficiency and scalability.

The research led by Prof. Leroy Cronin, the Regius Chair of Chemistry at the University of Glasgow, was published in Nature Communications . Prof. Cronin spoke to Phys.org about their work and stated his motivation behind pursuing the same.

"I wanted to see if we could make a new type of chemical information processing system as I am inspired by how biology can process information in wet brains," he said.

Limitations of modern computing

Modern computing relies on transistors, the building blocks of electronic devices, that are used to create logic gates and memory cells , forming the basis of digital circuits. But, the need and demand for more computational power means that transistors are getting smaller and smaller.

The miniaturization of transistors has several limitations due to constraints set by fabrications and the laws of physics. The smaller the transistor, the harder it is to manufacture and requires more power, dissipating more heat and being less and less energy efficient.

This has led scientists to explore other types of computing, such as quantum computing, which while being extremely powerful at solving problems classical computers can't suffer from scalability issues due to error correction.

On the other hand, computation based on physical processes , such as chemical reactions , uses a mixture of systems such as digital, chemical, and optical. This opens up new avenues for unconventional computing architectures with capabilities beyond traditional digital systems.

The BZ reaction

The BZ reaction is a classic example of a chemical oscillator, with the reactant and product concentrations undergoing periodic changes. It is observed in many chemical systems, such as laboratory settings and biological systems.

The BZ reaction's ability to exhibit complex, nonlinear dynamics makes it an attractive choice for studying emergent phenomena and unconventional computing paradigms.

In this research, the BZ reaction serves as the foundation for a hybrid computational system due to its inherent oscillatory behavior, adaptability, and responsiveness to external stimuli. By harnessing the dynamics of BZ reactions, researchers can emulate complex behaviors seen in natural systems, providing a versatile platform for computation.

The concentrations can serve as binary information (with 0 being low concentrations and 1 for high concentrations) and the oscillating concentrations can serve as time-dependent variables. Additionally, information can propagate between individual cells having BZ reactions through processes like diffusion.

Prof. Cronin further explained, "The reaction has two states on and off and each box [or cell] in the network can be flashing independently, in sync, or after communication. This is the process by which the system can be programmed to compute a problem which is then read out by the camera."

A hybrid programmable information processor

The core of the information processor is a 3D-printed grid of interconnected reactors. Each reactor or cell hosts the BZ reaction, making it an array of BZ reactions.

The input to this array is electronic and is controlled by magnetic stirrers capable of manipulating the reaction within these cells. There are also interfacial stirrers capable of facilitating interactions between coupled cells (via diffusion), this helps to synchronize the oscillations.

The researchers observed that the oscillations of the reactant and product concentrations occur as forced-damped oscillations, with the stirrers playing a crucial role in controlling them.

This behavior is a characteristic feature of BZ reactions, where chemical species undergo periodic changes in concentration over time. These changes are noticed by the changes in the color of the liquids.

The output processing involves two key components: a convolutional neural network (CNN) and a recognition finite state machine (rfsm). These components analyze the reactant and product concentrations within the BZ reaction, which are captured using video cameras.

The CNN classifies the concentrations into discrete chemical states, while the rfsm determines the corresponding chemical state based on this classification.

In simple terms, the discrete chemical states are classified and determined based on the concentrations of reactants and products within the BZ reaction, which are themselves probabilistic due to the nature of the reactions.

The probabilistic nature arises because the BZ reaction is non-linear, resulting in complex interactions between chemical species that exhibit inherent variability and unpredictability in their behavior over time.

The entire system operates smoothly and continuously based on a feedback loop based on the changing colors of the liquid. When the concentrations are oscillating the system is "on" indicated by blue colors and when there is a lack of oscillations, the liquids are red, meaning that the system is "off."

This loop manipulates the stirrers based on the colors, ensuring that the process is continuous with the help of "forced" or external control.

Chemical cellular automata and solving optimization problems

The researchers used the hybrid processor to showcase its computational capability by implementing chemical cellular automata (CCA) in 1D and 2D.

These are mathematical models to simulate complex systems composed of simple components interacting locally with each other according to predefined rules.

This leads to emergent behaviors such as replication and competition exhibited by "Chemits," which are multicellular entities defined by patterns of chemical concentrations within the grid of interconnected reactors hosting the BZ reaction.

These behaviors resemble those observed in living organisms and contribute to the complexity and adaptability of the computational system.

Moreover, the researchers demonstrate that their computational approach, which incorporates both electronic and chemical components, can efficiently tackle combinatorial optimization challenges, like the traveling salesman problem.

On the application side of things, hybrid systems like these could be very useful for deep learning tasks that require non-linear behavior. Chemical systems inherently offer such characteristics, making hybrid-computation architectures resource-efficient for specific problems where non-linearities and probabilistic behavior are vital.

Prof. Cornin added, "I see that a solid-state version could replace artificial intelligence hardware and be trained much easier."

In the future, he wishes to explore the miniaturization of this technology and increase the size of the grid to solve truly large problems.

Journal information: Nature Communications

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Physical Chemistry Chemical Physics

Sorting drug conformers in enzyme active sites: the xtb way †.

* Corresponding authors

a Graduate School of Engineering, Nagasaki University, Bunkyo 1-14, Nagasaki 852-8521, Japan E-mail: [email protected]

b RIKEN Center for Computational Science, 7-1-26, Minatojima-minami-machi, Chuo-ku, Kobe, Japan

In the present study, we have used the MEI196 set of interaction energies to investigate low-cost computational chemistry approaches for the calculation of binding between a molecule and its environment. Density functional theory (DFT) methods, when used with the vDZP basis set, yield good agreement with the reference energies. On the other hand, semi-empirical methods are less accurate as expected. By examining different groups of systems within MEI196 that contain species of a similar nature, we find that chemical similarity leads to cancellation of errors in the calculation of relative binding energies. Importantly, the semi-empirical method GFN1-xTB (XTB1) yields reasonable results for this purpose. We have thus further assessed the performance of XTB1 for calculating relative energies of docking poses of substrates in enzyme active sites represented by cluster models or within the ONIOM protocol. The results support the observations on error cancellation. This paves the way for the use of XTB1 in parts of large-scale virtual screening workflows to accelerate the drug discovery process.

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Sorting drug conformers in enzyme active sites: the XTB way

B. Chan, W. Dawson and T. Nakajima, Phys. Chem. Chem. Phys. , 2024, Advance Article , DOI: 10.1039/D4CP00930D

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