A systematic pairwise comparison of geometric parameters obtained by X-ray and neutron diffraction

Allen, Frank H.

doi:10.1107/s0108768186097823

Cited by 188 publications

(129 citation statements)

References 27 publications

(43 reference statements)

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“…The hydrogen atoms were moved outward along the X-H bond directions to adjust the bond lengths to the values expected from neutron diffraction studies (26). The atomic positions and anisotropic thermal displacement parameters were refined (alternatively) further with fixed multipole and partial net charge parameters transferred from the database.…”

Section: Methodsmentioning

confidence: 99%

Accurate protein crystallography at ultra-high resolution: Valence electron distribution in crambin

Jelsch

Teeter

Lamzin

et al. 2000

Proc. Natl. Acad. Sci. U.S.A.

213

171

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The charge density distribution of a protein has been refined experimentally. Diffraction data for a crambin crystal were measured to ultra-high resolution (0.54 Å) at low temperature by using shortwavelength synchrotron radiation. The crystal structure was refined with a model for charged, nonspherical, multipolar atoms to accurately describe the molecular electron density distribution. The refined parameters agree within 25% with our transferable electron density library derived from accurate single crystal diffraction analyses of several amino acids and small peptides. The resulting electron density maps of redistributed valence electrons (deformation maps) compare quantitatively well with a high-level quantum mechanical calculation performed on a monopeptide. This study provides validation for experimentally derived parameters and a window into charge density analysis of biological macromolecules.T he electronic charge density distribution of a molecule carries information (1) that determines its intermolecular interactions. For example, the charge distribution of an enzyme complements that of the substrate it recognizes and binds. The electrostatic potential and electric moments derivable from the charge density (1-3) provide maps that can guide the design of molecules for specified interactions. Furthermore, powerful insights into the nature and strength of hydrogen bonding and ionic interactions result from analysis of the electron density gradient and Laplacian (4-6). Extension of such analyses to proteins would permit a unique understanding of the driving forces between biomolecules as well as the subtleties of enzymatic reactions (7).Experimental electron density distributions are obtained by analysis of single-crystal x-ray diffraction data measured to ultra-high resolution, typically to a diffraction resolution limit d min Ϸ 0.5 Å (1,8,9). The crystallographic studies usually map and analyze the deformation density, which is the difference between the actual electron density of the molecule and the density calculated for the promolecule, a molecular superposition of spherical, neutral, i.e., free, atoms. The deformation density thus reveals the redistribution of valence electron density caused by chemical bonding and intermolecular interactions and also is used to calibrate theoretical electron density calculations (10). However, a difficulty in crystallography is the separation of the anisotropic atomic mean-square displacements from the static molecular electron distribution (11). Proper experimental deconvolution requires very accurate diffraction data to ultrahigh resolution. Thus, charge density studies have so far been limited to small-unit-cell crystals, and proteins still await study.We have shown (12, 13) that effective thermal displacement deconvolution and meaningful deformation density distributions can be achieved for larger structures at lower resolution by transferring average experimental electron density parameters. We have built a database of such parameters derived from ultra-high ...

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Section: Methodsmentioning

confidence: 99%

Accurate protein crystallography at ultra-high resolution: Valence electron distribution in crambin

Jelsch

Teeter

Lamzin

et al. 2000

Proc. Natl. Acad. Sci. U.S.A.

213

171

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“…The starting parameters for NADP ϩ were from the charge density analysis of NAD ϩ (11), and spherical atom scattering factors were used for the IDD594 inhibitor compound. All hydrogen atoms were displaced along the XOH bonds to standard bond distances obtained by neutron diffraction studies (17) and were subsequently kept fixed.…”

Section: Methodsmentioning

confidence: 99%

Electrostatic complementarity in an aldose reductase complex from ultra-high-resolution crystallography and first-principles calculations

Muzet

Guillot

Jelsch

et al. 2003

Proc. Natl. Acad. Sci. U.S.A.

106

109

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The electron density and electrostatic potential in an aldose reductase holoenzyme complex have been studied by density functional theory (DFT) and diffraction methods. Aldose reductase is involved in the reduction of glucose in the polyol pathway by using NADPH as a cofactor. The ultra-high resolution of the diffraction data and the low thermal-displacement parameters of the structure allow accurate atomic positions and an experimental charge density analysis. Based on the x-ray structural data, order-N DFT calculations have been performed on subsets of up to 711 atoms in the active site of the molecule. The charge density refinement of the protein was performed with the program MOPRO by using the transferability principle and our database of charge density parameters built from crystallographic analyses of peptides and amino acids. Electrostatic potentials calculated from the charge density database, the preliminary experimental electron density analysis, DFT computations, and atomic charges taken from the AMBER software dictionary are compared. The electrostatic complementarity between the cofactor NADP ؉ and the active site shows up clearly. The anchoring of the inhibitor is due mainly to hydrophobic forces and to only two polar interaction sites within the enzyme cavity. The potentials calculated by x-ray and DFT techniques agree reasonably well. At the present stage of the refinement, the potentials obtained directly from the database are in excellent agreement with the experimental ones. In addition, these results demonstrate the significant contribution of electron lone pairs and of atomic polarization effects to the host and guest mechanism.

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“…Actually among 700,000 crystal structures from monatomic metals to proteins and viruses systematically collected from the late 1960s and early 1970s are available in five comprehensive and fully retrospective world depositories: Cambridge Structural Database (CSD), Worldwide Protein Data Bank (wPDB), Nucleic acid database (NDB), Metals and intermetalics database (CRYSTMET) and Inorganic Crystal Structure Database (ICSD) only about 10% are structures of APIs and targets. The largest database, CSD, nowadays contains over 500,000 structures ("small molecules" -less than 1000 atoms) of which 99% were determined by XRD [61,62]. The number of drug-like structures in CSD exceeds 60,000.…”

Section: Discussionmentioning

confidence: 99%

“…Expansion of the atom-centred spherical-harmonic functions is the main idea of this so-called multipole approach. Another solution is modelling with the use of independent atoms [62], or partial optimisation using quantum chemistry methods ab initio or DFT [63]. However, irrespective of the method, the final result becomes in fact not purely experimental.…”

Section: Xrdmentioning

confidence: 99%

Towards Understanding Drugs on the Molecular Level to Design Drugs of Desired Profiles

Latosińska¹,

Latosińska²

2011

Drug Discovery and Development - Present and Future

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A systematic pairwise comparison of geometric parameters obtained by X-ray and neutron diffraction

Cited by 188 publications

References 27 publications

Accurate protein crystallography at ultra-high resolution: Valence electron distribution in crambin

Accurate protein crystallography at ultra-high resolution: Valence electron distribution in crambin

Electrostatic complementarity in an aldose reductase complex from ultra-high-resolution crystallography and first-principles calculations

Towards Understanding Drugs on the Molecular Level to Design Drugs of Desired Profiles

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