QTAIM in Drug Discovery and Protein Modeling

Sukumar, N.; Breneman, Curt M.

doi:10.1002/9783527610709.ch18

Cited by 28 publications

(26 citation statements)

References 81 publications

(121 reference statements)

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“…Due to the relatively low computational costs, these methods (under the umbrella of Quantum Chemical Topology (QCT) [5]) have found widespread use in all fields of chemistry, ranging from drug-design [6] to catalysis [7] to large biological systems [8]. In QTAIM, the presence of a bridge of maximal electron density between two atoms, commonly referred to as a bond path or an atomic interaction line (AIL), is observed for most cases where a classical chemist would expect a chemical bond.…”

Section: Introductionmentioning

confidence: 99%

Evaluating common QTAIM and NCI interpretations of the electron density concentration through IQA interaction energies and 1D cross-sections of the electron and deformation density distributions

Cukrowski

Lange

Adeyinka

et al. 2015

Computational and Theoretical Chemistry

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Highlights• Classical steric clashes might have the same topological features as bonding interactions.• An AIL can be observed for highly attractive or repulsive interactions.• An AIL might be a result of either an inflow or outflow of density.• Locally accumulated density does not imply an attractive interaction or an inflow of density.• Nature of an interaction can change with molecular environment. Graphical abstract 2 AbstractNine kinds of inter-and intramolecular interactions were investigated by exploring the topology of electron density in the interatomic regions using standard protocols of QTAIM, IQA and NCI techniques as well as in-house developed cross-sections of the electron and deformation density distributions. The first four methods provide the properties of the resultant density distribution in a molecular system whereas the later illustrates the process, inflow or outflow of density from fragments to the interatomic region of an interaction on its formation in a molecular system. We used (i) the QTAIM-defined atomic interaction line, AIL (presence or absence), (ii) IQA-defined interaction energy, attractive to repulsive, (ii)  2 < 0 to  2 >0, or (iii) (r) > 0 to (r) < 0; hence, none of the topological indices used here, either separately or combined, can be used to definitely predict the (de)stabilizing nature of an interaction except highly repulsive ones for which the absence of AIL, interatomic density depletion and outflow of density on interaction formation are observed.

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Section: Introductionmentioning

confidence: 99%

Evaluating common QTAIM and NCI interpretations of the electron density concentration through IQA interaction energies and 1D cross-sections of the electron and deformation density distributions

Cukrowski

Lange

Adeyinka

et al. 2015

Computational and Theoretical Chemistry

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“…The transferability and additivity of the atoms defined by QTAIM have been used extensively to reconstruct the properties of large molecules from smaller fragments [See for example: (Chang and Bader 1992;Sukumar and Breneman 2007;Scheins et al 2005)]. If such reconstruction of the properties of large molecules from composing atoms and groups stored in a database, with chemical accuracy, does not constitute prediction, how would that be characterized?…”

mentioning

confidence: 99%

Special issue: Philosophical aspects and implications of the quantum theory of atoms in molecules (QTAIM)

Matta

2013

Found Chem

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“…PROFEAT, PROTEIN RECON, and PseAAC are among the most notable available tools for calculating large numbers of sequence‐based physicochemical protein features. We used principal component analysis (PCA) to compare these methods to ProtDCal (Figure ).…”

Section: Resultsmentioning

confidence: 99%

ProtDCal‐Suite: A web server for the numerical codification and functional analysis of proteins

et al. 2019

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Computational tools for the analysis of protein data and the prediction of biological properties are essential in life sciences and biomedical research. Here, we introduce ProtDCal‐Suite, a web server comprising a set of machine learning‐based methods for studying proteins. The main module of ProtDCal‐Suite is the ProtDCal software. ProtDCal translates the structural information of proteins into numerical descriptors that serve as input to machine‐learning techniques. The ProtDCal‐Suite server also incorporates a post‐processing optional stage that allows ranking and filtering the obtained descriptors by computing their Shannon entropy values across the input set of proteins. ProtDCal's codification was used in the development of models for the prediction of specific protein properties. Thus, the other modules of ProtDCal‐Suite are protein analysis tools implemented using ProtDCal's descriptors. Among them are PPI‐Detect, for predicting the interaction likelihood of protein–protein and protein–peptide pairs, Enzyme Identifier, for identifying enzymes from amino acid sequences or 3D structures, and Pred‐NGlyco, for predicting N‐glycosylation sites. ProtDCal‐Suite is freely accessible at https://protdcal.zmb.uni‐due.de.

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QTAIM in Drug Discovery and Protein Modeling

Cited by 28 publications

References 81 publications

Evaluating common QTAIM and NCI interpretations of the electron density concentration through IQA interaction energies and 1D cross-sections of the electron and deformation density distributions

Evaluating common QTAIM and NCI interpretations of the electron density concentration through IQA interaction energies and 1D cross-sections of the electron and deformation density distributions

Special issue: Philosophical aspects and implications of the quantum theory of atoms in molecules (QTAIM)

ProtDCal‐Suite: A web server for the numerical codification and functional analysis of proteins

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