D3R grand challenge 4: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.

The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and affinity of BACE1 ligands were assessed. Following the completion of Stage 1, all BACE1 co-crystal structures were released, and Stage 2 tested affinity rankings with co-crystal structures. We provide an analysis of the results and discuss insights into determined best practice methods.

D3R Grand Challenge 3: blind prediction of protein-ligand poses and affinity rankings.

The Drug Design Data Resource aims to test and advance the state of the art in protein-ligand modeling by holding community-wide blinded, prediction challenges. Here, we report on our third major round, Grand Challenge 3 (GC3). Held 2017-2018, GC3 centered on the protein Cathepsin S and the kinases VEGFR2, JAK2, p38-α, TIE2, and ABL1, and included both pose-prediction and affinity-ranking components. GC3 was structured much like the prior challenges GC2015 and GC2. First, Stage 1 tested pose prediction and affinity ranking methods; then all available crystal structures were released, and Stage 2 tested only affinity rankings, now in the context of the available structures. Unique to GC3 was the addition of a Stage 1b self-docking subchallenge, in which the protein coordinates from all of the cocrystal structures used in the cross-docking challenge were released, and participants were asked to predict the pose of CatS ligands using these newly released structures. We provide an overview of the outcomes and discuss insights into trends and best-practices.

RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, rcsb.org), the US data center for the global PDB archive, serves thousands of Data Depositors in the Americas and Oceania and makes 3D macromolecular structure data available at no charge and without usage restrictions to more than 1 million rcsb.org Users worldwide and 600 000 pdb101.rcsb.org education-focused Users around the globe. PDB Data Depositors include structural biologists using macromolecular crystallography, nuclear magnetic resonance spectroscopy and 3D electron microscopy. PDB Data Consumers include researchers, educators and students studying Fundamental Biology, Biomedicine, Biotechnology and Energy. Recent reorganization of RCSB PDB activities into four integrated, interdependent services is described in detail, together with tools and resources added over the past 2 years to RCSB PDB web portals in support of a 'Structural View of Biology.'

Outlier analyses of the Protein Data Bank archive using a probability-density-ranking approach.

Outlier analyses are central to scientific data assessments. Conventional outlier identification methods do not work effectively for Protein Data Bank (PDB) data, which are characterized by heavy skewness and the presence of bounds and/or long tails. We have developed a data-driven nonparametric method to identify outliers in PDB data based on kernel probability density estimation. Unlike conventional outlier analyses based on location and scale, Probability Density Ranking can be used for robust assessments of distance from other observations. Analyzing PDB data from the vantage points of probability and frequency enables proper outlier identification, which is important for quality control during deposition-validation-biocuration of new three-dimensional structure data. Ranking of Probability Density also permits use of Most Probable Range as a robust measure of data dispersion that is more compact than Interquartile Range. The Probability-Density-Ranking approach can be employed to analyze outliers and data-spread on any large data set with continuous distribution.

Worldwide Protein Data Bank biocuration supporting open access to high-quality 3D structural biology data.

Database URL: https://www.wwpdb.org/.

D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.

The Drug Design Data Resource (D3R) ran Grand Challenge 2 (GC2) from September 2016 through February 2017. This challenge was based on a dataset of structures and affinities for the nuclear receptor farnesoid X receptor (FXR), contributed by F. Hoffmann-La Roche. The dataset contained 102 IC50 values, spanning six orders of magnitude, and 36 high-resolution co-crystal structures with representatives of four major ligand classes. Strong global participation was evident, with 49 participants submitting 262 prediction submission packages in total. Procedurally, GC2 mimicked Grand Challenge 2015 (GC2015), with a Stage 1 subchallenge testing ligand pose prediction methods and ranking and scoring methods, and a Stage 2 subchallenge testing only ligand ranking and scoring methods after the release of all blinded co-crystal structures. Two smaller curated sets of 18 and 15 ligands were developed to test alchemical free energy methods. This overview summarizes all aspects of GC2, including the dataset details, challenge procedures, and participant results. We also consider implications for progress in the field, while highlighting methodological areas that merit continued development. Similar to GC2015, the outcome of GC2 underscores the pressing need for methods development in pose prediction, particularly for ligand scaffolds not currently represented in the Protein Data Bank ( http://www.pdb.org ), and in affinity ranking and scoring of bound ligands.

Validation of Structures in the Protein Data Bank.

The Worldwide PDB recently launched a deposition, biocuration, and validation tool: OneDep. At various stages of OneDep data processing, validation reports for three-dimensional structures of biological macromolecules are produced. These reports are based on recommendations of expert task forces representing crystallography, nuclear magnetic resonance, and cryoelectron microscopy communities. The reports provide useful metrics with which depositors can evaluate the quality of the experimental data, the structural model, and the fit between them. The validation module is also available as a stand-alone web server and as a programmatically accessible web service. A growing number of journals require the official wwPDB validation reports (produced at biocuration) to accompany manuscripts describing macromolecular structures. Upon public release of the structure, the validation report becomes part of the public PDB archive. Geometric quality scores for proteins in the PDB archive have improved over the past decade.

OneDep: Unified wwPDB System for Deposition, Biocuration, and Validation of Macromolecular Structures in the PDB Archive.

OneDep, a unified system for deposition, biocuration, and validation of experimentally determined structures of biological macromolecules to the PDB archive, has been developed as a global collaboration by the worldwide PDB (wwPDB) partners. This new system was designed to ensure that the wwPDB could meet the evolving archiving requirements of the scientific community over the coming decades. OneDep unifies deposition, biocuration, and validation pipelines across all wwPDB, EMDB, and BMRB deposition sites with improved focus on data quality and completeness in these archives, while supporting growth in the number of depositions and increases in their average size and complexity. In this paper, we describe the design, functional operation, and supporting infrastructure of the OneDep system, and provide initial performance assessments.

Multivariate Analyses of Quality Metrics for Crystal Structures in the PDB Archive.

Following deployment of an augmented validation system by the Worldwide Protein Data Bank (wwPDB) partnership, the quality of crystal structures entering the PDB has improved. Of significance are improvements in quality measures now prominently displayed in the wwPDB validation report. Comparisons of PDB depositions made before and after introduction of the new reporting system show improvements in quality measures relating to pairwise atom-atom clashes, side-chain torsion angle rotamers, and local agreement between the atomic coordinate structure model and experimental electron density data. These improvements are largely independent of resolution limit and sample molecular weight. No significant improvement in the quality of associated ligands was observed. Principal component analysis revealed that structure quality could be summarized with three measures (Rfree, real-space R factor Z score, and a combined molecular geometry quality metric), which can in turn be reduced to a single overall quality metric readily interpretable by all PDB archive users.

D3R grand challenge 2015: Evaluation of protein-ligand pose and affinity predictions.

The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016. Two targets served as the framework to test community docking and scoring methods: (1) HSP90, donated by AbbVie and the Community Structure Activity Resource (CSAR), and (2) MAP4K4, donated by Genentech. The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand-protein poses. An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy. Unlike previous blinded Challenges, we did not provide cognate receptors or receptors prepared with hydrogens and likewise did not require a specified crystal structure to be used for pose or affinity prediction in Stage 1. Given the freedom to select from over 200 crystal structures of HSP90 in the PDB, participants employed workflows that tested not only core docking and scoring technologies, but also methods for addressing water-mediated ligand-protein interactions, binding pocket flexibility, and the optimal selection of protein structures for use in docking calculations. Nearly 40 participating groups submitted over 350 prediction sets for Grand Challenge 2015. This overview describes the datasets and the organization of the challenge components, summarizes the results across all submitted predictions, and considers broad conclusions that may be drawn from this collaborative community endeavor.

DCC: a Swiss army knife for structure factor analysis and validation.

Since 2008, X-ray structure depositions to the Protein Data Bank archive (PDB) have required submission of experimental data in the form of structure factor files. RCSB PDB has developed the program DCC to allow worldwide PDB (wwPDB; http://wwpdb.org) biocurators, using a single command-line program, to invoke a number of third-party software packages to compare the model file with the experimental data. DCC functionality includes structure factor validation, electron-density map generation and slicing, local electron-density analysis, and residual B factor analysis. DCC outputs a summary containing various crystallographic statistics in PDBx/mmCIF format for use in automatic data processing and archiving pipelines.

Trendspotting in the Protein Data Bank.

The Protein Data Bank (PDB) was established in 1971 as a repository for the three dimensional structures of biological macromolecules. Since then, more than 85000 biological macromolecule structures have been determined and made available in the PDB archive. Through analysis of the corpus of data, it is possible to identify trends that can be used to inform us abou the future of structural biology and to plan the best ways to improve the management of the ever-growing amount of PDB data.

Outcome of the first electron microscopy validation task force meeting.

This Meeting Review describes the proceedings and conclusions from the inaugural meeting of the Electron Microscopy Validation Task Force organized by the Unified Data Resource for 3DEM (http://www.emdatabank.org) and held at Rutgers University in New Brunswick, NJ on September 28 and 29, 2010. At the workshop, a group of scientists involved in collecting electron microscopy data, using the data to determine three-dimensional electron microscopy (3DEM) density maps, and building molecular models into the maps explored how to assess maps, models, and other data that are deposited into the Electron Microscopy Data Bank and Protein Data Bank public data archives. The specific recommendations resulting from the workshop aim to increase the impact of 3DEM in biology and medicine.

Exploring the impact of polyproline II (PII) conformational bias on the binding of peptides to the SEM-5 SH3 domain.

The left-handed polyproline II helical structure (P(II)) is observed to be a dominant conformation in the disordered states of protein and small polypeptide chains, even when no prolines are present in the sequence. Recently, in work by Ferreon and Hilser, the energetics associated with Ala and Gly substitutions at a surface exposed proline site were determined calorimetrically by measuring the binding energetics of Sos peptide variants to the C-terminal Src Homology 3 domain of SEM-5. The results were interpreted as a significant conformational bias toward the bound conformation (i.e., P(II)), even when the ligand is unbound. That study was not able to determine, however, whether the conformational bias of the peptides could be explained in terms other than that of a P(II) preference. Here, we test, using a computer algorithm based on the hard sphere collision (HSC) model, the notion of whether a bias in the unbound states of the peptide ligands is specific for the P(II) conformation, or if a bias to any other region of (phi, psi) space can also result in the same observed binding energetics. The results of these computer simulations indicate that, of the regions of (phi, psi) modeled for bias in the small peptides, only the bias to the P(II) conformation, and at rates of bias similar to the experimentally observed rates, quantitatively reproduced the experimental binding energetics.

Remediation of the protein data bank archive.

The Worldwide Protein Data Bank (wwPDB; wwpdb.org) is the international collaboration that manages the deposition, processing and distribution of the PDB archive. The online PDB archive at ftp://ftp.wwpdb.org is the repository for the coordinates and related information for more than 47 000 structures, including proteins, nucleic acids and large macromolecular complexes that have been determined using X-ray crystallography, NMR and electron microscopy techniques. The members of the wwPDB-RCSB PDB (USA), MSD-EBI (Europe), PDBj (Japan) and BMRB (USA)-have remediated this archive to address inconsistencies that have been introduced over the years. The scope and methods used in this project are presented.

Automated and accurate deposition of structures solved by X-ray diffraction to the Protein Data Bank.

The RCSB Protein Data Bank (PDB) has a number of options for deposition of structural data and has developed software tools to facilitate the process. In addition to ADIT and the PDB Validation Suite, a new software application, pdb_extract, has been designed to promote automatic data deposition of structures solved by X-ray diffraction. The pdb_extract software can extract information about data reduction, phasing, molecular replacement, density modification and refinement from the output files produced by many X-ray crystallographic applications. The options, procedures and tools for accurate and automated PDB data deposition are described here.

Tools for the automatic identification and classification of RNA base pairs.

Three programs have been developed to aid in the classification and visualization of RNA structure. BPViewer provides a web interface for displaying three-dimensional (3D) coordinates of individual base pairs or base pair collections. A web server, RNAview, automatically identifies and classifies the types of base pairs that are formed in nucleic acid structures by various combinations of the three edges, Watson-Crick, Hoogsteen and the Sugar edge. RNAView produces two-dimensional (2D) diagrams of secondary and tertiary structure in either Postscript, VRML or RNAML formats. The application RNAMLview can be used to rearrange various parts of the RNAView 2D diagram to generate a standard representation (like the cloverleaf structure of tRNAs) or any layout desired by the user. A 2D diagram can be rapidly reformatted using RNAMLview since all the parts of RNA (like helices and single strands) are dynamically linked while moving the selected parts. With the base pair annotation and the 2D graphic display, RNA motifs are rapidly identified and classified. A survey has been carried out for 41 unique structures selected from the NDB database. The statistics for the occurrence of each edge and of each of the 12 bp families are given for the combinations of the four bases: A, G, U and C. The program also allows for visualization of the base pair interactions by using a symbolic convention previously proposed for base pairs. The web servers for BPViewer and RNAview are available at http://ndbserver.rutgers.edu/services/. The application RNAMLview can also be downloaded from this site. The 2D diagrams produced by RNAview are available for RNA structures in the Nucleic Acid Database (NDB) at http://ndbserver.rutgers.edu/atlas/.

The Protein Data Bank and structural genomics.

The Protein Data Bank (PDB; http://www.pdb.org/) continues to be actively involved in various aspects of the informatics of structural genomics projects--developing and maintaining the Target Registration Database (TargetDB), organizing data dictionaries that will define the specification for the exchange and deposition of data with the structural genomics centers and creating software tools to capture data from standard structure determination applications.

Structural basis of transcription activation: the CAP-alpha CTD-DNA complex.

The Escherichia coli catabolite activator protein (CAP) activates transcription at P(lac), P(gal), and other promoters through interactions with the RNA polymerase alpha subunit carboxyl-terminal domain (alphaCTD). We determined the crystal structure of the CAP-alphaCTD-DNA complex at a resolution of 3.1 angstroms. CAP makes direct protein-protein interactions with alphaCTD, and alphaCTD makes direct protein-DNA interactions with the DNA segment adjacent to the DNA site for CAP. There are no large-scale conformational changes in CAP and alphaCTD, and the interface between CAP and alphaCTD is small. These findings are consistent with the proposal that activation involves a simple "recruitment" mechanism.