Center-of-mass distance between subdomains II-B and I-A/B+II-A in Langevin Dynamics.

<p>Center-of-mass distance between subdomains II-B and I-A/B+II-A in Langevin Dynamics.</p

Eigenvectors of NBD.

<p>(A) The first eigenvector of NBD essential dynamics (ED) involves a shearing motion of the domains I and II. <i>Left</i> – side view of the NBD, in which ED vectors of domains I and II are colored blue and red, respectively. <i>Right</i> – front view of the NBD. The shearing motion of domains I and II is manifested through the two helices at the interface of subdomains I-A and II-A, as indicated in the circle. (B) Second eigenvector of NBD ED involves a rotating motion of primarily subdomain II-B, which may change the distance between subdomains I-B and II-B. Subdomain II-B is colored red, and the other three subdomains are in blue.</p

Conserved residues in subdomains II-A/II-B hinge region of DnaK NBD.

<p>Identity above 90% are highlighted.</p

Residues with strong correlation to nucleotide in NBD LD simulations.

<p>Residues with strong correlation to nucleotide in NBD LD simulations.</p

Activity of DnaK and its mutants.

a<p>ref. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003279#pcbi.1003279-Chang1" target="_blank">[21]</a>.</p

Ramachandran plots of residues in different nucleotide-bound states.

<p>(A) G223, (B) L227, (C) G228, and (D) G229. These residues had clusters of φ-ψ torsion angles that were significantly different in the ADP/P_i state compared to the apo state and ATP-bound state. (E) The locations of these nucleotide-sensitive residues are shown in red.</p

Comparison of the open and closed conformations of Hsp70/DnaK nucleotide-binding domain.

<p>(A) Light grey cartoon represents Hsc70's NBD (PDB: 1BUP) in the “closed” conformation and the green cartoon is DnaK's NBD (PDB: 1DKG) in the “open” conformation. Most of the conformational difference stems from the position of subdomain II-B relative to I-B. (B) Conformational change in the α-helix (residues 257–274) of NBD subdomain II-B. The most common conformation of the α-helix of subdomain II-B, as observed in most Hsp70 crystal structures. Bending of the α-helix near residue 262 was observed in several LD simulations (red arrow).</p

CSAR Benchmark Exercise of 2010: Combined Evaluation Across All Submitted Scoring Functions

As part of the Community Structure-Activity Resource (CSAR) center, a set of 343 high-quality, protein–ligand crystal structures were assembled with experimentally determined <i>K</i>_d or <i>K</i>_i information from the literature. We encouraged the community to score the crystallographic poses of the complexes by any method of their choice. The goal of the exercise was to (1) evaluate the current ability of the field to predict activity from structure and (2) investigate the properties of the complexes and methods that appear to hinder scoring. A total of 19 different methods were submitted with numerous parameter variations for a total of 64 sets of scores from 16 participating groups. Linear regression and nonparametric tests were used to correlate scores to the experimental values. Correlation to experiment for the various methods ranged <i>R</i>² = 0.58–0.12, Spearman ρ = 0.74–0.37, Kendall τ = 0.55–0.25, and median unsigned error = 1.00–1.68 p<i>K</i>_d units. All types of scoring functionsforce field based, knowledge based, and empiricalhad examples with high and low correlation, showing no bias/advantage for any particular approach. The data across all the participants were combined to identify 63 complexes that were poorly scored across the majority of the scoring methods and 123 complexes that were scored well across the majority. The two sets were compared using a Wilcoxon rank-sum test to assess any significant difference in the distributions of >400 physicochemical properties of the ligands and the proteins. Poorly scored complexes were found to have ligands that were the same size as those in well-scored complexes, but hydrogen bonding and torsional strain were significantly different. These comparisons point to a need for CSAR to develop data sets of congeneric series with a range of hydrogen-bonding and hydrophobic characteristics and a range of rotatable bonds

CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes

A major goal in drug design is the improvement of computational methods for docking and scoring. The Community Structure Activity Resource (CSAR) aims to collect available data from industry and academia which may be used for this purpose (www.csardock.org). Also, CSAR is charged with organizing community-wide exercises based on the collected data. The first of these exercises was aimed to gauge the overall state of docking and scoring, using a large and diverse data set of protein–ligand complexes. Participants were asked to calculate the affinity of the complexes as provided and then recalculate with changes which may improve their specific method. This first data set was selected from existing PDB entries which had binding data (<i>K</i>_d or <i>K</i>_i) in Binding MOAD, augmented with entries from PDBbind. The final data set contains 343 diverse protein–ligand complexes and spans 14 p<i>K</i>_d. Sixteen proteins have three or more complexes in the data set, from which a user could start an inspection of congeneric series. Inherent experimental error limits the possible correlation between scores and measured affinity; <i>R</i>² is limited to ∼0.9 when fitting to the data set without over parametrizing. <i>R</i>² is limited to ∼0.8 when scoring the data set with a method trained on outside data. The details of how the data set was initially selected, and the process by which it matured to better fit the needs of the community are presented. Many groups generously participated in improving the data set, and this underscores the value of a supportive, collaborative effort in moving our field forward