Ian W. Davis

PHENIX: a comprehensive Python-based system for macromolecular structure solution

The PHENIX software for macromolecular structure determination is described.

MolProbity: all-atom contacts and structure validation for proteins and nucleic acids

MolProbity is a general-purpose web server offering quality validation for 3D structures of proteins, nucleic acids and complexes. It provides detailed all-atom contact analysis of any steric problems within the molecules as well as updated dihedral-angle diagnostics, and it can calculate and display the H-bond and van der Waals contacts in the interfaces between components. An integral step in the process is the addition and full optimization of all hydrogen atoms, both polar and nonpolar. New analysis functions have been added for RNA, for interfaces, and for NMR ensembles. Additionally, both the web site and major component programs have been rewritten to improve speed, convenience, clarity and integration with other resources. MolProbity results are reported in multiple forms: as overall numeric scores, as lists or charts of local problems, as downloadable PDB and graphics files, and most notably as informative, manipulable 3D kinemage graphics shown online in the KiNG viewer. This service is available free to all users at http://molprobity.biochem.duke.edu.

Structure validation by Cα geometry: ϕ,ψ and Cβ deviation

Geometrical validation around the Cα is described, with a new Cβ measure and updated Ramachandran plot. Deviation of the observed Cβ atom from ideal position provides a single measure encapsulating the major structure‐validation information contained in bond angle distortions. Cβ deviation is sensitive to incompatibilities between sidechain and backbone caused by misfit conformations or inappropriate refinement restraints. A new ϕ,ψ plot using density‐dependent smoothing for 81,234 non‐Gly, non‐Pro, and non‐prePro residues with B < 30 from 500 high‐resolution proteins shows sharp boundaries at critical edges and clear delineation between large empty areas and regions that are allowed but disfavored. One such region is the γ‐turn conformation near +75°,−60°, counted as forbidden by common structure‐validation programs; however, it occurs in well‐ordered parts of good structures, it is overrepresented near functional sites, and strain is partly compensated by the γ‐turn H‐bond. Favored and allowed ϕ,ψ regions are also defined for Pro, pre‐Pro, and Gly (important because Gly ϕ,ψ angles are more permissive but less accurately determined). Details of these accurate empirical distributions are poorly predicted by previous theoretical calculations, including a region left of α‐helix, which rates as favorable in energy yet rarely occurs. A proposed factor explaining this discrepancy is that crowding of the two‐peptide NHs permits donating only a single H‐bond. New calculations by Hu et al. [Proteins 2002 (this issue)] for Ala and Gly dipeptides, using mixed quantum mechanics and molecular mechanics, fit our nonrepetitive data in excellent detail. To run our geometrical evaluations on a user‐uploaded file, see MOLPROBITY (http://kinemage.biochem.duke.edu) or RAMPAGE (http://www‐cryst.bioc.cam.ac.uk/rampage). Proteins 2003;50:437–450.

Structure validation by Calpha geometry: phi,psi and Cbeta deviation.

Geometrical validation around the Cα is described, with a new Cβ measure and updated Ramachandran plot. Deviation of the observed Cβ atom from ideal position provides a single measure encapsulating the major structure‐validation information contained in bond angle distortions. Cβ deviation is sensitive to incompatibilities between sidechain and backbone caused by misfit conformations or inappropriate refinement restraints. A new ϕ,ψ plot using density‐dependent smoothing for 81,234 non‐Gly, non‐Pro, and non‐prePro residues with B < 30 from 500 high‐resolution proteins shows sharp boundaries at critical edges and clear delineation between large empty areas and regions that are allowed but disfavored. One such region is the γ‐turn conformation near +75°,−60°, counted as forbidden by common structure‐validation programs; however, it occurs in well‐ordered parts of good structures, it is overrepresented near functional sites, and strain is partly compensated by the γ‐turn H‐bond. Favored and allowed ϕ,ψ regions are also defined for Pro, pre‐Pro, and Gly (important because Gly ϕ,ψ angles are more permissive but less accurately determined). Details of these accurate empirical distributions are poorly predicted by previous theoretical calculations, including a region left of α‐helix, which rates as favorable in energy yet rarely occurs. A proposed factor explaining this discrepancy is that crowding of the two‐peptide NHs permits donating only a single H‐bond. New calculations by Hu et al. [Proteins 2002 (this issue)] for Ala and Gly dipeptides, using mixed quantum mechanics and molecular mechanics, fit our nonrepetitive data in excellent detail. To run our geometrical evaluations on a user‐uploaded file, see MOLPROBITY (http://kinemage.biochem.duke.edu) or RAMPAGE (http://www‐cryst.bioc.cam.ac.uk/rampage). Proteins 2003;50:437–450.

Rosetta3: An Object-Oriented Software Suite for the Simulation and Design of Macromolecules

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

MOLPROBITY: structure validation and all-atom contact analysis for nucleic acids and their complexes.

MolProbity is a general-purpose web service offering quality validation for three-dimensional (3D) structures of proteins, nucleic acids and complexes. It provides detailed all-atom contact analysis of any steric problems within the molecules and can calculate and display the H-bond and van der Waals contacts in the interfaces between components. An integral step in the process is the addition and full optimization of all hydrogen atoms, both polar and nonpolar. The results are reported in multiple forms: as overall numeric scores, as lists, as downloadable PDB and graphics files, and most notably as informative, manipulable 3D kinemage graphics shown on-line in the KiNG viewer. This service is available free to all users at http://kinemage.biochem.duke.edu.

Structure validation by Cα geometry: φ,ψ and Cβ deviation

Geometrical validation around the Cα is described, with a new Cβ measure and updated Ramachandran plot. Deviation of the observed Cβ atom from ideal position provides a single measure encapsulating the major structure‐validation information contained in bond angle distortions. Cβ deviation is sensitive to incompatibilities between sidechain and backbone caused by misfit conformations or inappropriate refinement restraints. A new ϕ,ψ plot using density‐dependent smoothing for 81,234 non‐Gly, non‐Pro, and non‐prePro residues with B < 30 from 500 high‐resolution proteins shows sharp boundaries at critical edges and clear delineation between large empty areas and regions that are allowed but disfavored. One such region is the γ‐turn conformation near +75°,−60°, counted as forbidden by common structure‐validation programs; however, it occurs in well‐ordered parts of good structures, it is overrepresented near functional sites, and strain is partly compensated by the γ‐turn H‐bond. Favored and allowed ϕ,ψ regions are also defined for Pro, pre‐Pro, and Gly (important because Gly ϕ,ψ angles are more permissive but less accurately determined). Details of these accurate empirical distributions are poorly predicted by previous theoretical calculations, including a region left of α‐helix, which rates as favorable in energy yet rarely occurs. A proposed factor explaining this discrepancy is that crowding of the two‐peptide NHs permits donating only a single H‐bond. New calculations by Hu et al. [Proteins 2002 (this issue)] for Ala and Gly dipeptides, using mixed quantum mechanics and molecular mechanics, fit our nonrepetitive data in excellent detail. To run our geometrical evaluations on a user‐uploaded file, see MOLPROBITY (http://kinemage.biochem.duke.edu) or RAMPAGE (http://www‐cryst.bioc.cam.ac.uk/rampage). Proteins 2003;50:437–450.

RosettaLigand docking with full ligand and receptor flexibility.

Computational docking of small-molecule ligands into protein receptors is an important tool for modern drug discovery. Although conformational adjustments are frequently observed between the free and ligand-bound states, the conformational flexibility of the protein is typically ignored in protein-small molecule docking programs. We previously described the program RosettaLigand, which leverages the Rosetta energy function and side-chain repacking algorithm to account for flexibility of all side chains in the binding site. Here we present extensions to RosettaLigand that incorporate full ligand flexibility as well as receptor backbone flexibility. Including receptor backbone flexibility is found to produce more correct docked complexes and to lower the average RMSD of the best-scoring docked poses relative to the rigid-backbone results. On a challenging set of retrospective and prospective cross-docking tests, we find that the top-scoring ligand pose is correctly positioned within 2 A RMSD for 64% (54/85) of cases overall.

KING (Kinemage, Next Generation): A versatile interactive molecular and scientific visualization program

Proper visualization of scientific data is important for understanding spatial relationships. Particularly in the field of structural biology, where researchers seek to gain an understanding of the structure and function of biological macromolecules, it is important to have access to visualization programs which are fast, flexible, and customizable. We present KiNG, a Java program for visualizing scientific data, with a focus on macromolecular visualization. KiNG uses the kinemage graphics format, which is tuned for macromolecular structures, but is also ideal for many other kinds of spatially embedded information. KiNG is written in cross‐platform, open‐source Java code, and can be extended by end users through simple or elaborate “plug‐in” modules. Here, we present three such applications of KiNG to problems in structural biology (protein backbone rebuilding), bioinformatics of high‐dimensional data (e.g., protein sidechain chi angles), and classroom education (molecular illustration). KiNG is a mature platform for rapidly creating and capitalizing on scientific visualizations. As a research tool, it is invaluable as a test bed for new methods of visualizing scientific data and information. It is also a powerful presentation tool, whether for structure browsing, teaching, direct 3D display on the web, or as a method for creating pictures and videos for publications. KiNG is freely available for download at http://kinemage.biochem.duke.edu.

Scientific benchmarks for guiding macromolecular energy function improvement

Accurate energy functions are critical to macromolecular modeling and design. We describe new tools for identifying inaccuracies in energy functions and guiding their improvement, and illustrate the application of these tools to the improvement of the Rosetta energy function. The feature analysis tool identifies discrepancies between structures deposited in the PDB and low-energy structures generated by Rosetta; these likely arise from inaccuracies in the energy function. The optE tool optimizes the weights on the different components of the energy function by maximizing the recapitulation of a wide range of experimental observations. We use the tools to examine three proposed modifications to the Rosetta energy function: improving the unfolded state energy model (reference energies), using bicubic spline interpolation to generate knowledge-based torisonal potentials, and incorporating the recently developed Dunbrack 2010 rotamer library (Shapovalov & Dunbrack, 2011).