Protein docking using spherical polar Fourier correlations

Abstract

We present a new computational method of docking pairs of proteins by using spherical polar Fourier correlations to accelerate the search for candidate low-energy conformations. Interaction energies are estimated using a hydrophobic excluded volume model derived from the notion of "overlapping surface skins," augmented by a rigorous but "soft" model of electrostatic complementarity. This approach has several advantages over former three-dimensional grid-based fast Fourier transform (FFT) docking correlation methods even though there is no analogue to the FFT in a spherical polar representation. For example, a complete search over all six rigid-body degrees of freedom can be performed by rotating and translating only the initial expansion coefficients, many unfeasible orientations may be eliminated rapidly using only low-resolution terms, and the correlations are easily localized around known binding epitopes when this knowledge is available. Typical execution times on a single processor workstation range from 2 hours for a global search (5 x 10(8) trial orientations) to a few minutes for a local search (over 6 x 10(7) orientations). The method is illustrated with several domain dimer and enzyme-inhibitor complexes and 20 large antibody-antigen complexes, using both the bound and (when available) unbound subunits. The correct conformation of the complex is frequently identified when docking bound subunits, and a good docking orientation is ranked within the top 20 in 11 out of 18 cases when starting from unbound subunits. Proteins 2000;39:178-194.

Mass spectrometric identification of lysine residues of heme oxygenase-1 that are involved in its interaction with NADPH-cytochrome P450 reductase

“…The X-ray structure of rat HO-1 (Protein Data Bank Code 1DVE) and rat BVR (Protein Data Bank Code 1GCU) were used as input to the program Hex [23]. The lowest energy solution was selected from the 50 candidate docking solutions (Fig.…”

“…The program Hex [23] was used to predict the structure of the complex of rat HO-1 (Protein Data Bank Code 1DVE) and rat BVR (Protein Data Bank Code 1GCU) as described previously [16].…”

Terminating eukaryote translation: Domain 1 of release factor eRF1 functions in stop codon recognition

“…To investigate whether the identified pockets can accommodate a model stop codon, UAA was docked into the putative binding site using a combination of the rigid-body docking program, Hex (Ritchie & Kemp, 2000), and the program Quanta (Molecular Simulations Inc+, Burlington, Massachusetts), used to adjust the trinucleotide torsion angles+ Best fit models were further refined to produce the model shown in Figure 7b+ There are no nonbonded contacts of less than 1+8 Å, yet burial of hydrophobic surfaces is very good and each base can form at least one hydrogen bond with eRF1 (U-O2 with R47 or S123 side chain; A-N6 with D128 side chain; A-N6 with V71 peptide backbone)+ No other suitable docking orientations could be identified+ The model proposed here seems the most likely on the basis of intimacy of fit, and it supports the hypothesis that the three RF pockets may represent the site of stop codon recognition+ eRF1 domain 1 codon specificity; excluding UGG tryptophan codons If the domain 1 pockets identified do represent the site of eRF1-codon interaction, they should be able to bind all three stop codons, but not the 61 sense codons+ The stop codon binding model described can explain such specificity+ For example, placing a cytosine in pocket 1 would involve replacing the conjugated uridine carbonyl O4 atom with a much more hydrophilic amino group deep in the hydrophobic pocket, which could disfavor binding+ Similarly, placing a small uracil or cytosine base in the large pocket 3 could produce insufficient desolvation of the pocket for binding; placing either of these small bases in pocket 2 would involve the loss of a hydrogen bond with D128+ These observations support the notion that a uracil base at the 59 end of the codon is a requirement for recognition by eRF1, and that pockets 2 and 3 are arranged to accept only purines+ Furthermore, we suggest this model can account for the fact that UGG signals tryptophan and not "stop+" Our modeling studies have indicated that the nucleotide backbone may be articulated to permit pockets 2 and 3 to accommodate, and hydrogen bond, purines at these positions, for instance by switching pocket 2-base hydrogen bonding from oxygen D1 of D128 to either oxygen D2 of D128 or H132 for the codons UAA, UAG, or UGA (Fig+ 8)+ In other words, the identity of the base at pocket 3 determines which eRF1 atom is used to hydrogen bond the pocket 2 base+ However, placing UGG into the eRF1 pockets would involve two opposing backbone articulations, precluding simultaneous formation of hydrogen bonds at pockets 2 and 3, and preventing UGG recognition+ Hence, the "articulated coupling" behavior of the nucleotide backbone and the limited hydrogen bonding opportunities of the binding site provide a possible mechanism to explain how eRF1 might specifically bind only the three codons, UAA, UAG, and UGA, and yet exclude the UGG tryptophan sense codon+…”

Knowledge-Guided Docking of WW Domain Proteins and Flexible Ligands

“…Two broad classifications [10] of docking algorithms are rigid docking and flexible docking. Rigid docking algorithms solve a simpler version of the protein docking problem termed bound docking by reconstruction of a protein complex from the bound structures of the two proteins that constitute the complex [5,8,14,19,23,27,28]. Docking is framed as a rigid alignment problem of two rigid objects with complementary shapes.…”