Exploring chemistry with the fragment molecular orbital method

Fedorov, Dmitri G.; Nagata, Takeshi; Kitaura, Kazuo

doi:10.1039/c2cp23784a

Cited by 352 publications

(372 citation statements)

References 250 publications

(287 reference statements)

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“…These developments have taken place aiming to overcome limitations of the original schemes and provide more chemical significance to the energy components, which are not uniquely defined. We can cite, for example, CSOV (Constrained Space Orbital Variations) [107], RVS (Reduced Variational Space Self-Consistent-Field) [108], SAPT (Symmetry-Adapted Perturbation Theory) [109], NEDA (Natural Energy Decomposition Analysis) [110][111][112], LMOEDA (Localized Molecular Orbital Energy Decomposition Analysis) [113], ALMO-EDA (Absolutely Localized Molecular Orbital [114]), FMO (Fragment Molecular Orbital [115][116][117]) and a Morokuma-type EDA developed by Ziegler and Rauk [118][119][120]. Certainly, this list is not exhaustive, but recalls some popular currently used EDA schemes.…”

Section: Energy Decomposition Analysismentioning

confidence: 99%

Electronic structure theory to decipher the chemical bonding in actinide systems

Dognon

2017

Coordination Chemistry Reviews

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International audienceThe chemical bonding in actinide compounds is usually analysed by inspecting the shape and the occupation of the orbitals or by calculating bond orders which are based on orbital overlap and occupation numbers. However, this may not give a definite answer because the choice of the partitioning method may strongly influence the result possibly leading to qualitatively different answers. In this review, we summarized the state-of-the-art of methods dedicated to the theoretical characterisation of bonding including charge, orbital, quantum chemical topology and energy decomposition analyses. This review is not exhaustive but aims to highlight some of the ways opened up by recent methodological developments. Various examples have been chosen to illustrate this progress

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Section: Energy Decomposition Analysismentioning

confidence: 99%

Electronic structure theory to decipher the chemical bonding in actinide systems

Dognon

2017

Coordination Chemistry Reviews

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“…Mixed QM/MM schemes [171], widely used to model large systems, can significantly improve protein-ligand binding prediction directly, through explicit energy calculations [172], or indirectly [173] by re-calculating ligand's atomic charges in an attempt to model ligand polarization effects. An alternative, more accurate but slower approach to large systems, is the fragment molecular orbital (FMO) method [174]. FMO divides a system in N non-overlapping fragments (e.g.…”

Section: Protein-ligand Binding Redesignmentioning

confidence: 99%

Molecular Modeling in Enzyme Design, Toward In Silico Guided Directed Evolution

Monza

Acebes

Lucas

et al. 2017

Directed Enzyme Evolution: Advances and Applications

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Directed evolution creates diversity in subsequent rounds of mutagenesis in the quest of increased protein stability, substrate binding and catalysis. Although this technique does not require any structural/mechanistic knowledge of the system, the frequency of improved mutations is usually low. For this reason, computational tools are increasingly used to focus the search in sequence space, enhancing the efficiency of laboratory evolution. In particular, molecular modeling methods provide a unique tool to grasp the sequence/structure/function relationship The final publication is available at Springer via https://link.springer.com/chapter/10.1007/978-3-319-50413-1_10/fulltext.html of the protein to evolve, with the only condition that a structural model is provided. With this book chapter, we tried to guide the reader through the state of art of molecular modeling, discussing their strengths, limitations and directions. In addition, we suggest a possible future template for in silico directed evolution where we underline two main points: a hierarchical computational protocol combining several different techniques, and a synergic effort between simulations and experimental validation. IntroductionBiotechnology needs catalysts that can work under harsh conditions, catalyze a broad range of substrates, generate maximum amount of product, and tolerate changes in the environment. Enzymes, which are biodegradable and reusable catalysts [1], in addition to remarkable reaction rates, can work in environmentally friendly pH and temperature ranges, and display control over stereochemistry and regioselectivity which makes them ideal for many applications [2,3]. When thinking about enzymes, people normally associate them to expressions such as "perfect catalysts" or "outstanding reaction rate". In fact, there are examples of enzymes that catalyze reactions at extremely high rates such as triose phosphate isomerase, superoxide dismutase or carbonic anhydrase [4]. These are often limited only by the rate of ligand diffusion into the active site (diffusion-controlled rate). Nevertheless, an extensive analysis by Bar-Even et al., of nearly 2000 enzymes, showed that the median maximal turnover rate value over all measured enzymes is about 10 s −1 nowhere close to the values of 10 5 or 10 6 normally associated with catalysts [5,6].So, it would appear that natural enzymes are "just good enough" for the function they must perform in a given organism [7]. One might conclude that if they had evolved to their optimum performance then trying to improve them (from a kinetic point of view) would be attempting the impossible. On the contrary, as seen by the distribution of reaction rates, k cat , most enzymes function at a lower rate than the diffusion-limit and thus, there is space to further increase their kinetic properties to meet industrial needs. Additionally, we need enzymes capable of catalyzing reactions for which no known enzymes exist, to work with different substrates and for particular conditions that are industrially...

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“…31 Exceptions to this include use of the fragment molecular orbital (FMO) framework [39][40][41] in schemes such as the PIEDA. 42 Recently, work has been published 43 investigating 18 class A GPCR-ligand crystal structures using the FMO-MP2 (second order Møller-Plesset perturbation theory) 44 PIEDA method with the 6-31G* basis set, demonstrating the components of the interactions and hence the high suitability of EDA to the field of drug design especially in the case of large drug-protein systems.…”

Section: Introductionmentioning

confidence: 99%

Energy Decomposition Analysis Based on Absolutely Localized Molecular Orbitals for Large-Scale Density Functional Theory Calculations in Drug Design

Phipps

Fox

Tautermann

et al. 2016

J. Chem. Theory Comput.

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We report the development and implementation of an energy decomposition analysis (EDA) scheme in the ONETEP linear-scaling electronic structure package. Our approach is hybrid as it combines the localised molecular orbital EDA (Su, P. and Li, H., J. Chem. Phys., 2009, 131, 014102) and the absolutely localised molecular orbital EDA (Khaliullin, R. Z. et al. J.Phys. Chem. A, 2007, 111, 8753-8765) to partition the intermolecular interaction energy into chemically distinct components (electrostatic, exchange, correlation, Pauli-repulsion, polarisation and charge transfer). Limitations shared in EDA approaches such as the issue of basis set dependence in polarisation and charge transfer are discussed and a remedy to this problem is proposed that exploits the strictly localised property of the ONETEP orbitals. Our method is validated on a range of complexes with interactions relevant to drug design. We demonstrate the capabilities for large-scale calculations with our approach on complexes of thrombin with an inhibitor comprised of up to 4975 atoms. Given the capability of ONETEP for large-scale calculations, such as on entire proteins, we expect that our EDA scheme can be applied in a large range of biomolecular problems, especially in the context of drug design.

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Exploring chemistry with the fragment molecular orbital method

Cited by 352 publications

References 250 publications

Electronic structure theory to decipher the chemical bonding in actinide systems

Electronic structure theory to decipher the chemical bonding in actinide systems

Molecular Modeling in Enzyme Design, Toward In Silico Guided Directed Evolution

Energy Decomposition Analysis Based on Absolutely Localized Molecular Orbitals for Large-Scale Density Functional Theory Calculations in Drug Design

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