Enhanced semiempirical QM methods for biomolecular interactions

Yilmazer, Nusret Duygu; Korth, Martin

doi:10.1016/j.csbj.2015.02.004

Cited by 66 publications

(48 citation statements)

References 176 publications

(188 reference statements)

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“…[9] Kohn-Sham density functional theory (KS-DFT or simply DFT) draws the connection between the energy of as ystem and its electron density.W ith the introduction of reasonable approximations,D FT methods can routinely provide accurate PES for systems with up to af ew hundred atoms. [10] Latest developments in the field of semiempirical quantum-mechanical (SQM) [11,12] methods have further extended the treatable molecular size with special attention regarding the computation of geometries, frequencies,and non-covalent interactions (GFN). [13,14] Within the extended tight-binding (xTB) theoretical framework, equilibrium-structure optimizations and molecular-dynamics (MD) simulations are feasible for large molecular systems, aiming at acomparable accuracy as DFT.…”

Section: Introductionmentioning

confidence: 99%

Robust Atomistic Modeling of Materials, Organometallic, and Biochemical Systems

Spicher

Grimme

2020

Angewandte Chemie

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Modern chemistry seems to be unlimited in molecular size and elemental composition. Metal‐organic frameworks or biological macromolecules involve complex architectures and a large variety of elements. Yet, a general and broadly applicable theoretical method to describe the structures and interactions of molecules beyond the 1000‐atom size regime semi‐quantitatively is not self‐evident. For this purpose, a generic force field named GFN‐FF is presented, which is completely newly developed to enable fast structure optimizations and molecular‐dynamics simulations for basically any chemical structure consisting of elements up to radon. The freely available computer program requires only starting coordinates and elemental composition as input from which, fully automatically, all potential‐energy terms are constructed. GFN‐FF outperforms other force fields in terms of generality and accuracy, approaching the performance of much more elaborate quantum‐mechanical methods in many cases.

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Section: Introductionmentioning

confidence: 99%

Robust Atomistic Modeling of Materials, Organometallic, and Biochemical Systems

Spicher

Grimme

2020

Angewandte Chemie

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“…; 39 by these reasons more advanced procedures above PM3 have been introduced recent years. 40,41 Most likely, the protein structures obtained in Ref. ( 23 ) in the molecular dynamics simulations with the QM(PM3)/MM potentials are not correct.…”

Section: New Piecesmentioning

confidence: 99%

Hydrolysis of Guanosine Triphosphate (GTP) by the Ras·GAP Protein Complex: Reaction Mechanism and Kinetic Scheme

et al. 2015

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Molecular mechanisms of hydrolysis of guanosine triphosphate (GTP) to guanosine diphosphate (GDP) and inorganic phosphate (Pi) by the Ras·GAP protein complex are fully investigated by using modern modeling tools. The previously hypothesized stages of the cleavage of the phosphorus-oxygen bond in GTP and the formation of the imide form of catalytic Gln61 from Ras upon creation of Pi are confirmed by using the higher-level quantum-based calculations. The steps of the enzyme regeneration are modeled for the first time, providing a comprehensive description of the catalytic cycle. It is found that for the reaction Ras·GAP·GTP·H 2 O → Ras·GAP·GDP·Pi the highest barriers correspond to the process of regeneration of the active site, but not to the process of substrate cleavage. The specific shape of the energy profile is responsible for an interesting kinetic mechanism of the GTP hydrolysis. The analysis of the process using the first-passage approach and consideration of kinetic equations suggest that the overall reactions rate is a result of the balance between relatively fast transitions and low probability of states from which these transitions are taking place. Our theoretical predictions are in excellent agreement with available experimental observations on GTP hydrolysis rates.3

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“…Although QM methods are reasonably accurate and suitable for general use when compared with empirical force fields, treating more than a few thousand atoms, remains challenging. To allow for large scale QM calculations, the development of semi‐empirical methods, [ 1–4 ] composite electronic structure approaches, [ 5 ] and other novel approximations [ 6 ] including linear‐scaling techniques [ 7–11 ] have shown remarkable progress. Recent advances in establishing sophisticated QM codes, which can be adjusted for utilizing highly parallel computing architectures [ 6,12 ] or graphical processing units, [ 13–15 ] represent another notable research direction.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical parallelization of divide‐and‐conquer density functional tight‐binding molecular dynamics and metadynamics simulations

Nishimura

Nakai

2020

J Comput Chem

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Massively parallel divide‐and‐conquer density functional tight‐binding (DC‐DFTB) molecular dynamics and metadynamics simulations are efficient approaches for describing various chemical reactions and dynamic processes of large complex systems via quantum mechanics. In this study, DC‐DFTB simulations were combined with multi‐replica techniques. Specifically, multiple walkers metadynamics, replica exchange molecular dynamics, and parallel tempering metadynamics methods were implemented hierarchically into the in‐house Dcdftbmd program. Test simulations in an aqueous phase of the internal rotation of formamide and conformational changes of dialanine showed that the newly developed extensions increase the sampling efficiency and the exploration capabilities in DC‐DFTB configuration space.

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Enhanced semiempirical QM methods for biomolecular interactions

Cited by 66 publications

References 176 publications

Robust Atomistic Modeling of Materials, Organometallic, and Biochemical Systems

Robust Atomistic Modeling of Materials, Organometallic, and Biochemical Systems

Hydrolysis of Guanosine Triphosphate (GTP) by the Ras·GAP Protein Complex: Reaction Mechanism and Kinetic Scheme

Hierarchical parallelization of divide‐and‐conquer density functional tight‐binding molecular dynamics and metadynamics simulations

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