DOCK 6: Impact of new features and current docking performance.

This manuscript presents the latest algorithmic and methodological developments to the structure-based design program DOCK 6.7 focused on an updated internal energy function, new anchor selection control, enhanced minimization options, a footprint similarity scoring function, a symmetry-corrected root-mean-square deviation algorithm, a database filter, and docking forensic tools. An important strategy during development involved use of three orthogonal metrics for assessment and validation: pose reproduction over a large database of 1043 protein-ligand complexes (SB2012 test set), cross-docking to 24 drug-target protein families, and database enrichment using large active and decoy datasets (Directory of Useful Decoys [DUD]-E test set) for five important proteins including HIV protease and IGF-1R. Relative to earlier versions, a key outcome of the work is a significant increase in pose reproduction success in going from DOCK 4.0.2 (51.4%) → 5.4 (65.2%) → 6.7 (73.3%) as a result of significant decreases in failure arising from both sampling 24.1% → 13.6% → 9.1% and scoring 24.4% → 21.1% → 17.5%. Companion cross-docking and enrichment studies with the new version highlight other strengths and remaining areas for improvement, especially for systems containing metal ions. The source code for DOCK 6.7 is available for download and free for academic users at http://dock.compbio.ucsf.edu/.

Darwinian docking.

The Darwinian model of evolution is an optimization strategy that can be adapted to docking. It differs from the common use of genetic algorithms, primarily in its acceptance of diverse solutions over finding "global" optima. A related problem is selecting compounds using multiple criteria. I discuss these ideas and present the outlines of a protocol for selecting "hits" and "leads" in drug discovery.

DOCK 6: combining techniques to model RNA-small molecule complexes.

With an increasing interest in RNA therapeutics and for targeting RNA to treat disease, there is a need for the tools used in protein-based drug design, particularly DOCKing algorithms, to be extended or adapted for nucleic acids. Here, we have compiled a test set of RNA-ligand complexes to validate the ability of the DOCK suite of programs to successfully recreate experimentally determined binding poses. With the optimized parameters and a minimal scoring function, 70% of the test set with less than seven rotatable ligand bonds and 26% of the test set with less than 13 rotatable bonds can be successfully recreated within 2 A heavy-atom RMSD. When DOCKed conformations are rescored with the implicit solvent models AMBER generalized Born with solvent-accessible surface area (GB/SA) and Poisson-Boltzmann with solvent-accessible surface area (PB/SA) in combination with explicit water molecules and sodium counterions, the success rate increases to 80% with PB/SA for less than seven rotatable bonds and 58% with AMBER GB/SA and 47% with PB/SA for less than 13 rotatable bonds. These results indicate that DOCK can indeed be useful for structure-based drug design aimed at RNA. Our studies also suggest that RNA-directed ligands often differ from typical protein-ligand complexes in their electrostatic properties, but these differences can be accommodated through the choice of potential function. In addition, in the course of the study, we explore a variety of newly added DOCK functions, demonstrating the ease with which new functions can be added to address new scientific questions.

Computational investigation of kinetics of cross-linking reactions in proteins: importance in structure prediction.

The determination of protein structure using distance constraints is a new and promising field of study. One implementation involves attaching residues of a protein using a cross-linking agent, followed by protease digestion, analysis of the resulting peptides by mass spectroscopy, and finally sequence threading to detect the protein folds. In the present work, we carry out computational modeling of the kinetics of cross-linking reactions in proteins using the master equation approach. The rate constants of the cross-linking reactions are estimated using the pKas and the solvent-accessible surface areas of the residues involved. This model is tested with fibroblast growth factor (FGF) and cytochrome C. It is consistent with the initial experimental rate data for individual lysine residues for cytochrome C. Our model captures all observed cross-links for FGF and almost 90% of the observed cross-links for cytochrome C, although it also predicts cross-links that were not observed experimentally (false positives). However, the analysis of the false positive results is complicated by the fact that experimental detection of cross-links can be difficult and may depend on specific experimental conditions such as pH, ionic strength. Receiver operator characteristic plots showed that our model does a good job in predicting the observed cross-links. Molecular dynamics simulations showed that for cytochrome C, in general, the two lysines come closer for the observed cross-links as compared to the false positive ones. For FGF, no such clear pattern exists. The kinetic model and MD simulation can be used to study proposed cross-linking protocols.

The collaboratory for MS3D: a new cyberinfrastructure for the structural elucidation of biological macromolecules and their assemblies using mass spectrometry-based approaches.

Modern biomedical research is evolving with the rapid growth of diverse data types, biophysical characterization methods, computational tools and extensive collaboration among researchers spanning various communities and having complementary backgrounds and expertise. Collaborating researchers are increasingly dependent on shared data and tools made available by other investigators with common interests, thus forming communities that transcend the traditional boundaries of the single research laboratory or institution. Barriers, however, remain to the formation of these virtual communities, usually due to the steep learning curve associated with becoming familiar with new tools, or with the difficulties associated with transferring data between tools. Recognizing the need for shared reference data and analysis tools, we are developing an integrated knowledge environment that supports productive interactions among researchers. Here we report on our current collaborative environment, which focuses on bringing together structural biologists working in the area of mass spectrometric based methods for the analysis of tertiary and quaternary macromolecular structures (MS3D) called the Collaboratory for MS3D (C-MS3D). C-MS3D is a Web-portal designed to provide collaborators with a shared work environment that integrates data storage and management with data analysis tools. Files are stored and archived along with pertinent meta data in such a way as to allow file handling to be tracked (data provenance) and data files to be searched using keywords and modification dates. While at this time the portal is designed around a specific application, the shared work environment is a general approach to building collaborative work groups. The goal of this is to not only provide a common data sharing and archiving system, but also to assist in the building of new collaborations and to spur the development of new tools and technologies.

Partial acetylation of lysine residues improves intraprotein cross-linking.

Intramolecular cross-linking coupled with mass spectrometric identification of cross-linked amino acids is a rapid method for elucidating low-resolution protein tertiary structures or fold families. However, previous cross-linking studies on model proteins, such as cytochrome c and ribonuclease A, identified a limited number of peptide cross-links that are biased toward only a few of the potentially reactive lysine residues. Here, we report an approach to improve the diversity of intramolecular protein cross-linking starting with a systematic quantitation of the reactivity of lysine residues of a model protein, bovine cytochrome c. Relative lysine reactivities among the 18 lysine residues of cytochrome c were determined by the ratio of d0 and acetyl-d3 groups at each lysine after partial acetylation with sulfosuccinimidyl acetate followed by denaturation and quantitative acetylation of remaining unmodified lysines with acetic-d6 anhydride. These lysine reactivities were then compared with theoretically derived pKa and relative solvent accessibility surface values. To ascertain if partial N-acetylation of the most reactive lysine residues prior to cross-linking can redirect and increase the observable Lys-Lys cross-links, partially acetylated bovine cytochrome c was cross-linked with the amine-specific, bis-functional reagent, bis(sulfosuccinimidyl)suberate. After proteolysis and mass spectrometry analysis, partial acetylation was shown to significantly increase the number of observable peptides containing Lys-Lys cross-links, shifting the pattern from the most reactive lysine residues to less reactive ones. More importantly, these additional cross-linked peptides contained novel Lys-Lys cross-link information not seen in the non-acetylated protein and provided additional distance constraints that were consistent with the crystal structure and facilitated the identification of the proper protein fold.

Rational design of a nonpeptide general chemical scaffold for reversible inhibition of PDZ domain interactions.

Novel small molecules were designed to specifically target the ligand-binding pocket of a PDZ domain. Iterative molecular docking and modeling allowed the design of an indole scaffold 10a as a reversible inhibitor of ligand binding. The 10a scaffold inhibited the interaction between MAGI-3 and PTEN and showed cellular activities that are consistent with the inhibition of NHERF-1 function.

Development and validation of a modular, extensible docking program: DOCK 5.

We report on the development and validation of a new version of DOCK. The algorithm has been rewritten in a modular format, which allows for easy implementation of new scoring functions, sampling methods and analysis tools. We validated the sampling algorithm with a test set of 114 protein-ligand complexes. Using an optimized parameter set, we are able to reproduce the crystal ligand pose to within 2 A of the crystal structure for 79% of the test cases using our rigid ligand docking algorithm with an average run time of 1 min per complex and for 72% of the test cases using our flexible ligand docking algorithm with an average run time of 5 min per complex. Finally, we perform an analysis of the docking failures in the test set and determine that the sampling algorithm is generally sufficient for the binding pose prediction problem for up to 7 rotatable bonds; i.e. 99% of the rigid ligand docking cases and 95% of the flexible ligand docking cases are sampled successfully. We point out that success rates could be improved through more advanced modeling of the receptor prior to docking and through improvement of the force field parameters, particularly for structures containing metal-based cofactors.

Proteomimetic libraries: design, synthesis, and evaluation of p53-MDM2 interaction inhibitors.

The p53-MDM2 interaction regulates p53-mediated cellular responses to DNA damage, and MDM2 is overexpressed in 7% of all cancers. Structure-based computational design was applied to this system to design libraries centered on a scaffold that projects side chain functionalities with distance and angular relationships equivalent to those seen in the MDM2 interacting motif of p53. A library of 173 such compounds was synthesized using solution phase parallel chemistry. The in vitro competitive ability of the compounds to block p53 peptide binding to MDM2 was determined using a fluorescence polarization competition assay. The most active compound bound with K(d) = 12 microM, and its binding was characterized by (15)N-(1)H HSQC NMR.

Estimation of Absolute Free Energies of Hydration Using Continuum Methods: Accuracy of Partial Charge Models and Optimization of Nonpolar Contributions.

Absolute free energies of hydration (ΔGhyd) for more than 500 neutral and charged compounds have been computed, using Poisson-Boltzmann (PB) and Generalized Born (GB) continuum methods plus a solvent-accessible surface area (SA) term, to evaluate the accuracy of eight simple point-charge models used in molecular modeling. The goal is to develop improved procedures and protocols for protein-ligand binding calculations and virtual screening (docking). The best overall PBSA and GBSA results, in comparison with experimental ΔGhyd values for small molecules, were obtained using MSK, RESP, or ChelpG charges obtained from ab initio calculations using 6-31G* wave functions. Correlations using semiempirical (AM1BCC, AM1CM2, and PM3CM2) or empirical (Gasteiger-Marsili and MMFF94) methods yielded mixed results, particularly for charged compounds. For neutral compounds, the AM1BCC method yielded the best agreement with experimental results. In all cases, the PBSA and GBSA results are highly correlated (overall r(2) = 0.94), which highlights the fact that various partial charge models influence the final results much more than which continuum method is used to compute hydration free energies. Overall improved agreement with experimental results was demonstrated using atom-based constants in place of a single surface area term. Sets of optimized SA constants, suitable for use with a given charge model, were derived by fitting to the difference in experimental free energies and polar continuum results. The use of optimized atom-based SA constants for the computation of ΔGhyd can fine-tune already reasonable agreement with experimental results, ameliorate gross deficiencies in any particular charge model, account for nonoptimal radii, or correct for systematic errors.

Apolipoprotein (apo) E4 enhances amyloid beta peptide production in cultured neuronal cells: apoE structure as a potential therapeutic target.

Apolipoprotein (apo) E4 is a major risk factor for Alzheimer's disease, and many studies have suggested that apoE has isoform-specific effects on the deposition or clearance of amyloid beta (Abeta) peptides. We examined the effects of apoE isoforms on the processing of amyloid precursor protein (APP) and on Abeta production in rat neuroblastoma B103 cells stably transfected with human wild-type APP695 (B103-APP). Lipid-poor apoE4 increased Abeta production in B103-APP cells to a greater extent than lipid-poor apoE3 (60% vs. 30%) due to more pronounced stimulation of APP recycling by apoE4 than apoE3. The difference in Abeta production was abolished by preincubating the cells with the receptor-associated protein (25 nM), which blocks the low-density lipoprotein receptor-related protein (LRP) pathway, or by reducing LRP expression by small interference RNA. The differences were also attenuated by replacing Arg-61 with threonine in apoE4 or pretreating apoE4 with small molecules, both of which abolish apoE4 intramolecular domain interaction. Thus, apoE4 appears to modulate APP processing and Abeta production through both the LRP pathway and domain interaction. These findings provide insights into why apoE4 is associated with increased risk for Alzheimer's disease and may represent a potential target for drug development.

An information theoretic approach to macromolecular modeling: I. Sequence alignments.

We are interested in applying the principles of information theory to structural biology calculations. In this article, we explore the information content of an important computational procedure: sequence alignment. Using a reference state developed from exhaustive sequences, we measure alignment statistics and evaluate gap penalties based on first-principle considerations and gap distributions. We show that there are different gap penalties for different alphabet sizes and that the gap penalties can depend on the length of the sequences being aligned. In a companion article, we examine the information content of molecular force fields.

An information theoretic approach to macromolecular modeling: II. Force fields.

In this article, we explore the information content of molecular force-field calculations. We make use of exhaustive lattice models of molecular conformations and reduced alphabet sequences to determine the relative resolving power of pairwise interaction-based force fields. We find that sequence-specific interactions that operate over longer distances offer greater amounts of information than nearest-neighbor or non-sequence-specific interactions. In a companion article in this issue, we explored the information content of sequence alignment procedures and the calculation of gap penalties. Both articles have implications for protein and nucleic-acid computations.

Evaluating the high-throughput screening computations.

The judges evaluated the submissions for the McMaster University High-Throughput Data-Mining and Docking Competition based on 3 criteria: identification of active compounds, percent enrichment, and overview of the competition. Using these metrics, 4 of the participating groups found meaningful enrichment, and 3 groups made perceptive comments about the general nature of the competition.

Hierarchical database screenings for HIV-1 reverse transcriptase using a pharmacophore model, rigid docking, solvation docking, and MM-PB/SA.

In this work, an efficient strategy was presented to search drug leads for human immunodeficiency virus type 1 reverse transcriptase (HIV-1 RT) using hierarchical database screenings, which included a pharmacophore model, multiple-conformation rigid docking, solvation docking, and molecular mechanics-Poisson-Boltzmann/surface area (MM-PB/SA) sequentially. Encouraging results were achieved in searching a refined available chemical directory (ACD) database: the enrichment factor after the first three filters was estimated to be 25-fold; the hit rate for all the four filters was predicted to be 41% in a control test using 37 known HIV-1 non-nucleoside reverse transcriptase inhibitors; 10 out of 30 promising solvation-docking hits had MM-PB/SA binding free energies better than -6.8 kcal/mol and the best one, HIT15, had -17.0 kcal/mol. In conclusion, the hierarchical multiple-filter database searching strategy is an attractive strategy in drug lead exploration.

SitePrint: three-dimensional pharmacophore descriptors derived from protein binding sites for family based active site analysis, classification, and drug design.

Integrating biological and chemical information is one key task in drug discovery, and one approach to attaining this goal is via three-dimensional pharmacophore descriptors derived from protein binding sites. The SitePrint program generates, aligns, scores, and classifies three-dimensional pharmacophore descriptors, active site grids, and ligand surfaces. The descriptors are formed from molecular fragments that have been docked, minimized, filtered, and clustered in protein active sites. The descriptors have geometric coordinates derived from the fragment positions, and they capture the shape, electrostatics, locations, and angles of entry into pockets of the recognition sites: they also provide a direct link to databases of organic molecules. The descriptors have been shown to be robust with respect to small changes in protein structure observed when multiple compounds are cocrystallized in a protein. Five aligned thrombin cocrystals with an average core alpha-carbon RMSD of 0.7 A gave three-dimensional pharmacophore descriptors with an average RMSD of 1.1 A. On a larger test set, alignment and scoring of the descriptors using clique-based alignment, and a best first search strategy with an adapted forward-looking Ullmann heuristic was able to select the global minimum three-dimensional alignment in twenty-nine out of thirty cases in less than one CPU second on a workstation. A protein family based analysis was then performed to demonstrate the usefulness of the method in producing a correlation of active site pharmacophore descriptors to protein function. Each protein in a test set of thirty was assigned membership to a family based on computed active site similarity to the following families: kinases, nuclear receptors, the aspartyl, cysteine, serine, and metallo proteases. This method of classifying proteins is complementary to approaches based on sequence or fold homology. The values within protein families for correctly assigning membership of a protein to a family ranged from 25% to 80%.

Photochemically knocking out glutamate receptors in vivo.

AMPA (alpha-amino-3-hydroxy-5-methyl-4-isooxazole) receptors, a major subtype of ionotropic glutamate receptors (iGluRs), mediate the majority of the fast communication between neurons, and the activity-dependent trafficking of AMPA receptors at synapses plays a role in mammalian learning and memory. Here we describe the design, synthesis, and evaluation of a photoreactive AMPA receptor antagonist that provides a means of "knocking out" AMPA receptors present on the surface of cells. The antagonist, 6-azido-7-nitro-1,4-dihydroquinoxaline-2,3-dione (ANQX), was designed by introducing a photoreactive azido group onto a quinoxalinedione inhibitor scaffold. Computational docking of ANQX to the AMPA receptor ligand-binding core predicted efficient binding to AMPA receptors. Glutamate-evoked currents were reversibly blocked at micromolar ANQX concentrations prior to photolysis and irreversibly blocked following photolysis. ANQX provides a means of directly evaluating the trafficking of native AMPA receptors with unparalleled spatiotemporal resolution.

Distributions in protein conformation space: implications for structure prediction and entropy.

By considering how polymer structures are distributed in conformation space, we show that it is possible to quantify the difficulty of structural prediction and to provide a measure of progress for prediction calculations. The critical issue is the probability that a conformation is found within a specified distance of another conformer. We address this question by constructing a cumulative distribution function (CDF) for the average probability from observations about its limiting behavior at small displacements and numerical simulations of polyalanine chains. We can use the CDF to estimate the likelihood that a structure prediction is better than random chance. For example, the chance of randomly predicting the native backbone structure of a 150-amino-acid protein to low resolution, say within 6 A, is 10(-14). A high-resolution structural prediction, say to 2 A, is immensely more difficult (10(-57)). With additional assumptions, the CDF yields the conformational entropy of protein folding from native-state coordinate variance. Or, using values of the conformational entropy change on folding, we can estimate the native state's conformational span. For example, for a 150-mer protein, equilibrium alpha-carbon displacements in the native ensemble would be 0.3-0.5 A based on T Delta S of 1.42 kcal/(mol residue).

Computer-assisted design of selective imidazole inhibitors for cytochrome p450 enzymes.

A modified version of the DOCK program has been used to predict inhibitors for cytochrome P450cam and its L244A mutant. A library of azole compounds was designed in silico and screened for binding to wild-type P450cam. Lead compounds were synthesized and found to inhibit wild-type P450cam. To test our approach to designing ligands that discriminate between closely related sites, the azole library was DOCKed into both the active sites of wild-type P450cam and its L244A mutant. The L244A active site is predicted to be slightly larger than that of wild-type P450cam. Ligands predicted to have a high affinity for the mutant alone were synthesized and assayed with the recombinant enzymes. All of the compounds showed inhibition of the L244A enzyme (IC(50) = 6-40 microM), and the compounds that were predicted to be too large to bind to the wild-type showed poor inhibition (IC(50) > or = 1 mM). The binding mode was shown to be similar to that predicted by our modified version of DOCK by spectroscopic analysis. A discrepancy between the IC(50) values and spectroscopic K(s) values indicates that the spectroscopic binding constants do not accurately estimate inhibitory activity. This study, the first report of computer-assisted ligand (drug) design for P450 enzymes in which the coordination bond between imidazole and the heme is explicitly considered in structural modeling, opens a promising design avenue because azole compounds are widely used as P450 enzyme inhibitors and drugs.

Inhibition of Mycobacterium tuberculosis AhpD, an element of the peroxiredoxin defense against oxidative stress.

The resistance of Mycobacterium tuberculosis to isoniazid (INH) is largely linked to suppression of a catalase-peroxidase enzyme (KatG) that activates INH. In the absence of KatG, antioxidant protection is provided by enhanced expression of the peroxiredoxin AhpC, which is itself reduced by AhpD, a protein with low alkylhydroperoxidase activity of its own. Inhibition of AhpD might therefore impair the antioxidant protection afforded by AhpC and make KatG-negative strains more sensitive to oxidative stress. We report here that the 3(E),17-dioxime of testosterone is a potent competitive AhpD inhibitor, with a K(i) of 50 +/- 2 nM. The inhibitor is stereospecific, in that the 3(E) but not 3(Z) isomer is active. Computational studies provide support for a proposed AhpD substrate binding site. However, the inhibitor does not completely suppress the in vitro activity of AhpC/AhpD, because a low titer of AhpD suffices to maintain AhpC activity. This finding, and the low solubility of the inhibitor, explains its inability to suppress the growth of INH-resistant M. tuberculosis in infected mouse lungs.