Protein electrostatics

Neves‐Petersen, Maria Teresa; Petersen, Steffen B.

doi:10.1016/s1387-2656(03)09010-0

Cited by 78 publications

(32 citation statements)

References 62 publications

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“…In protein-protein interactions, electrostatic complementarity can significantly contribute to the binding affinity (87–91). We calculated the electrostatic potential of the TAP models, focusing on the role of charged residues in peptide/substrate binding to TAP.…”

Section: Resultsmentioning

confidence: 99%

The Human Transporter Associated with Antigen Processing

Corradi

Singh

Tieleman

2012

Journal of Biological Chemistry

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Background: The transporter associated with antigen processing (TAP) is an ABC transporter whose experimental structure is not known.Results: We have modeled TAP based on the crystal structures of three related ABC transporters.Conclusion: We identified a possible peptide binding conformation in the transport cycle of TAP.Significance: These models help interpret experimental data and give information about the transport cycle of ABC transporters in general.

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Section: Resultsmentioning

confidence: 99%

The Human Transporter Associated with Antigen Processing

Corradi

Singh

Tieleman

2012

Journal of Biological Chemistry

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“…In contrast to strong covalent bonds, these rather weak intermolecular contacts comprise a variety of interactions that do not involve sharing electrons. Key interactions between ligands and macromolecules include hydrogen bonds [1, 2] , π-π aromatic stacking [3, 4] , cation-π interactions [5, 6] , hydrophobic effects [7, 8] , halogen bonds [9, 10] , and salt bridges [11, 12] . A significant effort is directed to study the geometrical properties and energetics of these non-covalent bonds because of their paramount importance in molecular recognition and practical applications in drug discovery [8, 13, 14] .…”

Section: Introductionmentioning

confidence: 99%

Aromatic interactions at the ligand–protein interface: Implications for the development of docking scoring functions

Bryliński

2017

Chem Biol Drug Des

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The ability to design and fine-tune non-covalent interactions between organic ligands and proteins is indispensable to rational drug development. Aromatic stacking has long been recognized as one of the key constituents of ligand-protein interfaces. In this communication, we employ a two-parameter geometric model to conduct a large-scale statistical analysis of aromatic contacts in the experimental and computer-generated structures of ligand-protein complexes, considering various combinations of aromatic amino acid residues and ligand rings. The geometry of interfacial π-π stacking in crystal structures accords with experimental and theoretical data collected for simple systems, such as the benzene dimer. Many contemporary ligand docking programs implicitly treat aromatic stacking with van der Waals and Coulombic potentials. Although this approach generally provides a sufficient specificity to model aromatic interactions, the geometry of π-π contacts in high-scoring docking conformations could still be improved. The comprehensive analysis of aromatic geometries at ligand-protein interfaces lies the foundation for the development of type-specific statistical potentials to more accurately describe aromatic interactions in molecular docking. A Perl script to detect and calculate the geometric parameters of aromatic interactions in ligand-protein complexes is available at https://github.com/michal-brylinski/earomatic. The dataset comprising experimental complex structures and computer-generated models is available at https://osf.io/rztha/.

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“…The electrostatic energy and nuclear forces in these dielectric continuum models can then be computed with the Poisson-Boltzmann Method and the Boundary Element Method, or approximated with the Generalized Born and the Surface Generalized Born models. 17,18 Instead of using a dielectric background for the protein and its environment, one may also treat electronic polarization explicitly. This can be done by introducing inducible dipoles at the nuclei of polarizable atoms, and by allowing atomic charges to fluctuate due to changes in the electrostatic potential.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Atomic Charge Models for Gas-Phase Computations on Polypeptides

Verstraelen

Pauwels

Proft³

et al. 2012

J. Chem. Theory Comput.

127

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Abstract. The concept of the atomic charge is extensively used to model the electrostatic properties of proteins. Atomic charges are not only the basis for the electrostatic energy term in biomolecular force fields, but are also derived from quantum mechanical (QM) computations on protein fragments to get more insight into their electronic structure. Unfortunately there are many atomic charge schemes which lead to significantly different results, and it is not trivial to determine which scheme is most suitable for biomolecular studies. Therefore, we present an extensive methodological benchmark using a selection of atomic charge schemes (Mulliken, Natural, RESP, Hirshfeld-I, EEM and SQE) applied to two sets of penta-alanine conformers. Our analysis clearly shows that Hirshfeld-I charges offer the best compromise between transferability (robustness with respect to conformational changes) and the ability to reproduce electrostatic properties of the penta-alanine. The benchmark also considers two charge equilibration models (EEM and SQE), which both clearly fail to describe the locally charged moieties in the zwitterionic form of penta-alanine. This issue is analyzed in detail because charge equilibration models are computationally much more attractive than the Hirshfeld-I scheme. Based on the latter analysis, a straightforward extension of the SQE model is proposed, SQE+Q 0 , that is suitable to describe biological systems bearing many locally charged functional groups.

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Protein electrostatics

Cited by 78 publications

References 62 publications

The Human Transporter Associated with Antigen Processing

The Human Transporter Associated with Antigen Processing

Aromatic interactions at the ligand–protein interface: Implications for the development of docking scoring functions

Assessment of Atomic Charge Models for Gas-Phase Computations on Polypeptides

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