Benefits of hybrid QM/MM over traditional classical mechanics in pharmaceutical systems

Kar, Rajiv K.

doi:10.1016/j.drudis.2022.103374

Cited by 15 publications

(13 citation statements)

References 57 publications

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“…To obtain the MT 1 -MLT and MT 2 -MLT complexes, molecular docking was performed using AutoDock Vina 68 . The distribution of Vina scores (in kcal/mol) from 1000 rounds of docking can be observed in Fig.…”

Section: Resultsmentioning

confidence: 99%

Quantum mechanics insights into melatonin and analogs binding to melatonin MT1 and MT2 receptors

de Lima Menezes,

Sales Bezerra,

Nobre Oliveira

et al. 2024

Sci Rep

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Melatonin receptors MT1 and MT2 are G protein-coupled receptors that mediate the effects of melatonin, a hormone involved in circadian rhythms and other physiological functions. Understanding the molecular interactions between these receptors and their ligands is crucial for developing novel therapeutic agents. In this study, we used molecular docking, molecular dynamics simulations, and quantum mechanics calculation to investigate the binding modes and affinities of three ligands: melatonin (MLT), ramelteon (RMT), and 2-phenylmelatonin (2-PMT) with both receptors. Based on the results, we identified key amino acids that contributed to the receptor-ligand interactions, such as Gln181/194, Phe179/192, and Asn162/175, which are conserved in both receptors. Additionally, we described new meaningful interactions with Gly108/Gly121, Val111/Val124, and Val191/Val204. Our results provide insights into receptor-ligand recognition’s structural and energetic determinants and suggest potential strategies for designing more optimized molecules. This study enhances our understanding of receptor-ligand interactions and offers implications for future drug development.

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Section: Resultsmentioning

confidence: 99%

Quantum mechanics insights into melatonin and analogs binding to melatonin MT1 and MT2 receptors

de Lima Menezes,

Sales Bezerra,

Nobre Oliveira

et al. 2024

Sci Rep

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“…Another alternative is to combine QM with MM (or MD) to analyze different fragments of a large chemical system at different levels of theory . In the QM/MM approach, the reactive center is treated at a QM level, whereas the remaining part of the system is simulated using MM . This approach has been helpful for studying biochemical transformations (e.g., enzymatic reactions) and complex reaction environments and mechanisms in environmental science. − A compilation of the main advantages and disadvantages, examples of applications, and software employed for each computational chemistry method is provided in Table .…”

Section: Computational Chemistry Methodsmentioning

confidence: 99%

“…QM/MM hybrid approaches combine QM calculations of the active sites and MM of the reaction environment not directly involved in the chemical reactions . While interactions within the individual QM and MM regions may be straightforward, the embedding method and boundary treatment must be appropriately considered to accurately predict the interactions between the two. ,, Interactions between the QM/MM regions can be coupled by subtractive (e.g., ONIOM) and additive (e.g., mechanical, elastic, and polarization embedding) methods. Chemical bonds within the QM/MM boundary can be capped by linking the two through a monovalent atom or by replacing the link atom with a double-occupied molecular orbital within the localized self-consistent field (LSFC) method or the generalized hybrid orbital approach (GHO) .…”

Section: Computational Chemistry Methodsmentioning

confidence: 99%

Computational Chemistry as Applied in Environmental Research: Opportunities and Challenges

Sandoval-Pauker,

Yin,

Castillo

et al. 2023

ACS EST Eng.

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The constant development of computer systems and infrastructure has allowed computational chemistry to become an important component of environmental chemistry research. In the past decade, the application of quantum and classical mechanical calculations to model and understand environmental systems has increased exponentially. In this review, we highlight various applications of computational chemistry techniques in areas of environmental chemistry research (e.g., wastewater/air treatment, sensing, biodegradation). We briefly describe each computational approach, starting with quantum chemistry principle methods followed by molecular mechanics (MM), molecular dynamics (MD), and hybrid QM/MM methods. The recent introduction of artificial intelligence and machine learning techniques and their potential to disrupt the field are also discussed. Challenges and current and future directions to address them are presented.

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“…37 Also, quantum classical hybrid models have been leveraged to accelerate explicitly atomistic drug design efforts, 38,39 with the aim to improve on the accuracy of classical MM models and to cover nonstandard chemistry by a QM approach. 40 The QM-cluster approach 41,42 is an alternative approach to deal with a large nanoscopic system. Structural constraints can be considered in these models by frozen atomic positions in the periphery, but the general mechanical behavior of, for instance, a protein will be difficult to capture.…”

Section: Introductionmentioning

confidence: 99%

“…Typical areas of application are biomolecules, 22 metalloenzymes, 8,23 symmetry defects in metals, 24 covalent 25 and metal 26 organic frameworks, carbon‐nanotubes 27 and graphene, 28 solution chemistry in studies of spectroscopy, 29 light induced processes, 30,31 solvation 32–35 and adsorption 35 chemistry, excited states, 36 and nonadiabatic dynamics 37 . Also, quantum classical hybrid models have been leveraged to accelerate explicitly atomistic drug design efforts, 38,39 with the aim to improve on the accuracy of classical MM models and to cover nonstandard chemistry by a QM approach 40 . The QM‐cluster approach 41,42 is an alternative approach to deal with a large nanoscopic system.…”

Section: Introductionmentioning

confidence: 99%

UniversalQM/MMapproaches for general nanoscale applications

Csizi

Reiher

2023

WIREs Comput Mol Sci

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Quantum mechanics/molecular mechanics (QM/MM) hybrid models allow one to address chemical phenomena in complex molecular environments. Whereas this modeling approach can cope with a large system size at moderate computational costs, the models are often tedious to construct and require manual preprocessing and expertise. As a result, transferability to new application areas can be limited and the many parameters are not easy to adjust to reference data that are typically scarce. Therefore, it is desirable to devise automated procedures of controllable accuracy, which enables such modeling in a standardized and black‐box‐type manner. Although diverse best‐practice protocols have been set up for the construction of individual components of a QM/MM model (e.g., the MM potential, the type of embedding, the choice of the QM region), automated procedures that reconcile all steps of the QM/MM model construction are still rare. Here, we review the state of the art of QM/MM modeling with a focus on automation. We elaborate on MM model parametrization, on atom‐economical physically‐motivated QM region selection, and on embedding schemes that incorporate mutual polarization as critical components of the QM/MM model. In view of the broad scope of the field, we mostly restrict the discussion to methodologies that build de novo models based on first‐principles data, on uncertainty quantification, and on error mitigation with a high potential for automation. Ultimately, it is desirable to be able to set up reliable QM/MM models in a fast and efficient automated way without being constrained by specific chemical or technical limitations. This article is categorized under: Electronic Structure Theory > Combined QM/MM Methods

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Benefits of hybrid QM/MM over traditional classical mechanics in pharmaceutical systems

Cited by 15 publications

References 57 publications

Quantum mechanics insights into melatonin and analogs binding to melatonin MT1 and MT2 receptors

Quantum mechanics insights into melatonin and analogs binding to melatonin MT1 and MT2 receptors

Computational Chemistry as Applied in Environmental Research: Opportunities and Challenges

UniversalQM/MMapproaches for general nanoscale applications

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