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GEMDOCK: a generic evolutionary method for molecular docking.

We have developed an evolutionary approach for flexible ligand docking. This approval, GEMDOCK, uses a Generic Evolutionary Method for molecular DOCKing and an empirical scoring function. The former combines both discrete and continuous global search strategies with local search strategies to speed up convergence, whereas the latter results in rapid recognition of potential ligands. GEMDOCK was tested on a diverse data set of 100 protein-ligand complexes from the Protein Data Bank. In 79% of these complexes, the docked lowest energy ligand structures had root-mean-square derivations (RMSDs) below 2.0 A with respect to the corresponding crystal structures. The success rate increased to 85% if the structure water molecules were retained. We evaluated GEMDOCK on two cross-docking experiments in which each ligand of a protein ensemble was docked into each protein of the ensemble. Seventy-six percent of the docked structures had RMSDs below 2.0 A when the ligands were docked into foreign structures. We analyzed and validated GEMDOCK with respect to various search spaces and scoring functions, and found that if the scoring function was perfect, then the predicted accuracy was also essentially perfect. This study suggests that GEMDOCK is a useful tool for molecular recognition and may be used to systematically evaluate and thus improve scoring functions.

Algorithms↗

Improving CAPRI predictions: optimized desolvation for rigid-body docking.

The ICM Docking and Interface Side-Chain Optimization (ICM-DISCO) showed promising predictive results during the first CAPRI experiment by successfully finding medium- or high-accuracy models in 3 of the 7 targets. A key factor was the ability to recognize near-native rigid-body geometries in a relatively low number of alternative docking poses, together with the successful refinement of the rigid-body docking interfaces. Since then, we have focused on improving the scoring function to optimally discriminate the near-native rigid-body conformations. For that, we have defined a new desolvation descriptor for rigid-body docking, based on atomic solvation parameters (ASPs) derived from octanol-water transfer experiments. This and other new approaches have been gradually incorporated into our docking procedure during our participation on the second CAPRI experiment. Overall, we produced reasonable models for 8 of the 9 official targets. Especially encouraging were those cases in which a homology model of 1 of the subunits had to be used during the docking simulations. And not less gratifying has been the successful prediction of antibody-antigen targets in a completely automatic, unrestrained fashion. In summary, our success rate (89%) shows a consistent improvement over the previous CAPRI rounds, and suggests that a correct desolvation description is key for improved protein-protein docking predictions.

Algorithms↗

Optimal design of protein docking potentials: efficiency and limitations.

Protein-protein docking is a challenging computational problem in functional genomics, particularly when one or both proteins undergo conformational change(s) upon binding. The major challenge is to define scoring function soft enough to tolerate these changes and specific enough to distinguish between near-native and "misdocked" conformations. Using a linear programming technique, we derived protein docking potentials (PDPs) that comply with this requirement. We considered a set of 63 nonredundant complexes to this aim, and generated 400,000 putative docked complexes (decoys) based on shape complementarity criterion for each complex. The PDPs were required to yield for the native (correctly docked) structure a potential energy lower than those of all the nonnative (misdocked) structures. The energy constraints applied to all complexes led to ca. 25 million inequalities, the simultaneous solution of which yielded an optimal set of PDPs that discriminated the correctly docked (up to 4.0 A root-mean-square deviation from known complex structure) structure among the 85 top-ranking (0.02%) decoys in 59/63 examined bound-bound cases. The high performance of the potentials was further verified in jackknife tests and by ranking putative docked conformation submitted to CAPRI. In addition to their utility in identifying correctly folded complexes, the PDPs reveal biologically meaningful features that distinguish docking potentials from folding potentials.

Antigens↗

PIPER: an FFT-based protein docking program with pairwise potentials.

The Fast Fourier Transform (FFT) correlation approach to protein-protein docking can evaluate the energies of billions of docked conformations on a grid if the energy is described in the form of a correlation function. Here, this restriction is removed, and the approach is efficiently used with pairwise interaction potentials that substantially improve the docking results. The basic idea is approximating the interaction matrix by its eigenvectors corresponding to the few dominant eigenvalues, resulting in an energy expression written as the sum of a few correlation functions, and solving the problem by repeated FFT calculations. In addition to describing how the method is implemented, we present a novel class of structure-based pairwise intermolecular potentials. The DARS (Decoys As the Reference State) potentials are extracted from structures of protein-protein complexes and use large sets of docked conformations as decoys to derive atom pair distributions in the reference state. The current version of the DARS potential works well for enzyme-inhibitor complexes. With the new FFT-based program, DARS provides much better docking results than the earlier approaches, in many cases generating 50% more near-native docked conformations. Although the potential is far from optimal for antibody-antigen pairs, the results are still slightly better than those given by an earlier FFT method. The docking program PIPER is freely available for noncommercial applications.

Antibodies↗

Predicting molecular interactions and inducible complementarity: fragment docking of Fab-peptide complexes.

Antibody-antigen interactions are representative of a broad class of receptor-ligand interactions involving both specificity and potential inducible complementarity. To test possible mechanisms of antigen-antibody recognition and specificity computationally, we have used a Metropolis Monte Carlo algorithm to dock fragments of the epitope Glu-Val-Val-Pro-His-Lys-Lys to the X-ray structures of both the free and the complexed Fab of the antibody B13I2 (raised against the C-helix of myohemerythrin). The fragments Pro-His and Val-Pro-His, which contain residues experimentally identified as important for binding, docked correctly to both structures, but all tetrapeptide and larger fragments docked correctly only to the complexed Fab, even when torsional flexibility was added to the ligand. However, only tetrapeptide and larger fragments showed significantly more favorable energies when docked to the complexed Fab coordinates than when docked to either the free Fab or a non-specific site remote from the combining site. Comparison of the free and complexed B13I2 structures revealed that atoms within 5 A of Val-Pro-His showed little movement upon peptide binding, but atoms within 5 A of the other four epitope residues showed greater movements. These results computationally distinguished recognition and binding processes with practical implications for drug design strategies. Overall, this new fragment docking approach establishes distinct roles for the "lock-and-key" (recognition) and the "handshake" (binding) paradigms in antibody-antigen interaction, suggests an incremental approach to incorporating flexibility in computational docking, and identifies critical regions within receptor binding sites for ligand recognition.

Algorithms↗

Modelling protein docking using shape complementarity, electrostatics and biochemical information.

A protein docking study was performed for two classes of biomolecular complexes: six enzyme/inhibitor and four antibody/antigen. Biomolecular complexes for which crystal structures of both the complexed and uncomplexed proteins are available were used for eight of the ten test systems. Our docking experiments consist of a global search of translational and rotational space followed by refinement of the best predictions. Potential complexes are scored on the basis of shape complementarity and favourable electrostatic interactions using Fourier correlation theory. Since proteins undergo conformational changes upon binding, the scoring function must be sufficiently soft to dock unbound structures successfully. Some degree of surface overlap is tolerated to account for side-chain flexibility. Similarly for electrostatics, the interaction of the dispersed point charges of one protein with the Coulombic field of the other is measured rather than precise atomic interactions. We tested our docking protocol using the native rather than the complexed forms of the proteins to address the more scientifically interesting problem of predictive docking. In all but one of our test cases, correctly docked geometries (interface Calpha RMS deviation </=2 A from the experimental structure) are found during a global search of translational and rotational space in a list that was always less than 250 complexes and often less than 30. Varying degrees of biochemical information are still necessary to remove most of the incorrectly docked complexes.

Algorithms↗

A shape- and chemistry-based docking method and its use in the design of HIV-1 protease inhibitors.

The program DOCK [1,2] has been used successfully to identify molecules which will bind to a specified receptor [3]. The original method ranks molecules based on their shape complementarity to the receptor site and relies on the chemist to bring the appropriate electrostatic or hydrogen bond properties into the molecular skeletons obtained in the search. This is useful when screening a small database of compounds, where it is not likely that molecules with both the correct shape and electrostatic properties will be found. As large databases are more likely to have redundant molecular shapes with a variety of functionality (e.g., members of a congeneric series), it would be useful to have a method which identifies molecules with both the correct shape and functionality. To this end we have modified the DOCK 1.0 method to target user-specified atom types to selected positions in the receptor site. The target sites can be chosen based on structural evidence, calculation or inspection. Targeted-DOCK improves the ability of the DOCK method to find the crystallographically determined binding mode of a ligand. Additionally, targeted-DOCK searches a database of small molecules at 100-1000 times the rate of DOCK 1.0, allowing more molecules to be screened and more sophisticated scoring schemes to be employed. Targeted-DOCK has been used successfully in the design of a novel non-peptide inhibitor of HIV-1 protease.

Binding Sites↗

ProPose: a docking engine based on a fully configurable protein-ligand interaction model.

Virtual high-throughput screening of molecular databases and in particular high-throughput protein-ligand docking are both common methodologies that identify and enrich hits in the early stages of the drug design process. Current protein-ligand docking algorithms often implement a program-specific model for protein-ligand interaction geometries. However, in order to create a platform for arbitrary queries in molecular databases, a new program is desirable that allows more manual control of the modeling of molecular interactions. For that reason, ProPose, an advanced incremental construction docking engine, is presented here that implements a fast and fully configurable molecular interaction and scoring model. This program uses user-defined, discrete, pharmacophore-like representations of molecular interactions that are transformed on-the-fly into a continuous potential energy surface, allowing for the incorporation of target specific interaction mechanisms into docking protocols in a straightforward manner. A torsion angle library, based on semi-empirical quantum chemistry calculations, is used to provide minimum energy torsion angles for the incremental construction algorithm. Docking results of a diverse set of protein-ligand complexes from the Protein Data Bank demonstrate the feasibility of this new approach. As a result, the seamless integration of pharmacophore-like interaction types into the docking and scoring scheme implemented in ProPose opens new opportunities for efficient, receptor-specific screening protocols. [figure: see text]. ProPose--a fully configurable protein-ligand docking program--transforms pharmacophores into a smooth potential energy surface.

Binding Sites↗

New insights about HERG blockade obtained from protein modeling, potential energy mapping, and docking studies.

We created a homology model of the homo-tetrameric pore domain of HERG using the crystal structure of the bacterial potassium channel, KvAP, as a template. We docked a set of known blockers with well-characterized effects on channel function into the lumen of the pore between the selectivity filter and extracellular entrance using a novel docking and refinement procedure incorporating Glide and Prime. Key aromatic groups of the blockers are predicted to form multiple simultaneous ring stacking and hydrophobic interactions among the eight aromatic residues lining the pore. Furthermore, each blocker can achieve these interactions via multiple docking configurations. To further interpret the docking results, we mapped hydrophobic and hydrophilic potentials within the lumen of each refined docked complex. Hydrophilic iso-potential contours define a 'propeller-shaped' volume at the selectivity filter entrance. Hydrophobic contours define a hollow 'crown-shaped' volume located above the 'propeller', whose hydrophobic 'rim' extends along the pore axis between Tyr652 and Phe656. Blockers adopt conformations/binding orientations that closely mimic the shapes and properties of these contours. Blocker basic groups are localized in the hydrophilic 'propeller', forming electrostatic interactions with Ser624 rather than a generally accepted pi-cation interaction with Tyr652. Terfenadine, cisapride, sertindole, ibutilide, and clofilium adopt similar docked poses, in which their N-substituents bridge radially across the hollow interior of the 'crown' (analogous to the hub and spokes of a wheel), and project aromatic/hydrophobic portions into the hydrophobic 'rim'. MK-499 docks with its longitudinal axis parallel to the axis of the pore and 'crown', and its hydrophobic groups buried within the hydrophobic 'rim'.

Conserved Sequence↗

The receptor docking segment and S-adenosyl-L-homocysteine bind independently to the methyltransferase of bacterial chemotaxis.

To mediate adaptation to stimuli, the methyltransferase (CheR) catalyzes methyl group transfer from S-adenosyl-L-methionine (SAM) to glutamyl residues in the transmembrane receptors of the bacterial chemosensory signaling pathway. The interaction between receptors and CheR occurs at two sites: a methylation site-active site interaction, and a 'docking' site interaction that is separated both from the methylation sites and the CheR active site. It is not certain if the docking site interaction functions merely to localize the transferase in close proximity to the methylation sites, or if it also increases CheR catalytic activity. Isothermal titration calorimetry experiments are conducted to test for allosteric interactions between the docking and active sites on CheR, which are expected to be present if docking activates CheR. The binding parameters (DeltaG, DeltaH, DeltaS) of a substrate analog of SAM, S-adenosyl-L-homocysteine (SAH), are measured both in the absence and presence of saturating concentrations of a pentapeptide (NWETF) that defines the docking receptor docking segment. SAH binding is unaffected by the presence of saturating NWETF, providing evidence that an allosteric activation of CheR does not take place upon docking, and thus supports the idea that the CheR-NWETF interaction merely functions to localize CheR near the sites of methylation.

Binding Sites↗

Docking experiments in the flexible non-nucleoside inhibitor binding pocket of HIV-1 reverse transcriptase.

Docking experiments were undertaken using a number of published crystal structures of HIV-1 reverse transcriptase complexes with various non-nucleoside inhibitors. The docking method was validated by successfully docking each ligand, in the conformation found in the crystal structure of the complex with the enzyme, back into its binding pocket in the right orientation and position. Each ligand was then subjected to conformational searching and a database of unique low-energy conformations of all ligands established. Docking this database into each of the reverse transcriptase binding pockets showed that all inhibitors could be fitted into each different pocket, without alteration of the pocket geometry. This contradicts findings from earlier docking investigations and implies that the conformation of the binding pocket in each different complex is conserved sufficiently to allow particular uniform ligand binding modes. The inhibitor conformations selected by this docking process are mostly the same as the one the ligand adopts in its own pocket and the selected conformations and orientations exhibit an impressive degree of similarity in the arrangement of their steric and electronic features. A correlation has also been observed between inhibitor flexibility and tightness of fit into the pockets with the more flexible inhibitors achieving a tighter fit and thus fewer favourable orientations upon docking.

Binding Sites↗

Single-coordinate-driving method for molecular docking: application to modeling of guest inclusion in cyclodextrin.

An extension of the computer program CICADA has been developed that allows us to use the single-coordinate-driving (SCD) method for flexible molecular docking. The docking procedure is composed of three independent space rotations, three independent translations, and the torsions selected by the user. One of the coordinates is driven; the other coordinates are relaxed. This procedure follows low-energy wells on the potential energy surface of the entire system. The program allows us to dock more than one ligand molecule to the receptor. We ran two test examples, docking N,N-dimethylformamide into alpha-cyclodextrin and R-phenoxypropionic acid into beta-cyclodextrin. The test examples showed that the SCD approach is able to overcome high-energy barriers and to cover the entire box within which the search is performed. The limitations of molecular dynamics docking in comparison with our approach also are discussed. The philosophy of the newly developed approach is not only to find the best dock for the receptor-ligand(s) system, but also to describe all the important binding modes and provide a good starting point for studying the dynamics within the cavity during the docking process.

Carbohydrate Conformation↗

Docking studies of matrix metalloproteinase inhibitors: zinc parameter optimization to improve the binding free energy prediction.

Docking of metalloproteinase inhibitors remains a challenge due to the zinc multiple coordination geometries and the lack of appropriate force field parameters to model the metal/ligand interactions. In this study, we explore the docking accuracy and scoring reliability for the docking of matrix metalloproteinase (MMP) inhibitors using AutoDock 3.0. Potential problems associated with zinc ion were investigated by docking 16 matrix metalloproteinase ligands to their crystal structures. A good coordination between the zinc binding group (ZBG) and the zinc was shown to be a prerequisite for the ligand to fit the binding site. A simplex optimization of zinc parameters, including zinc radius, well depth, and zinc charges, was performed utilizing the 14 MMP complexes with good docking. The use of optimized zinc parameters (zinc radius: 0.87 A; well depth: 0.35 kcal/mol; and zinc charges: +0.95 e) shows improvement in both docking accuracy at the zinc binding site and the prediction of binding free energies. Although further improvement in the docking procedure, particularly the scoring function is needed, optimization of zinc parameters provides an efficient way to improve the performance of AutoDock as a drug discovery tool.

Binding Sites↗

Enhanced virtual screening by combined use of two docking methods: getting the most on a limited budget.

Flexible ligand docking is a routine part of a modern structure-based lead discovery process. As of today, there are quite a number of commercial docking programs that can be used to screen large databases (hundreds of thousands to millions of compounds). However, limiting factors such as the number of commercial software licenses needed to perform docking simultaneously on multiple processors ("software cost") and the relatively long time required per molecule to get good results ("quality-to-speed") should be taken into account when planning a large docking run. How can we optimize the efficiency of selecting lead candidates by docking, in respect to the quality of the results, search speed, and software cost? We present a combination of two methods, our "fast-free-approximate" in-house docking program and the "slow-costly-accurate" ICM-Dock, as an example of one solution to the problem. Our proposed protocol is illustrated by a series of virtual screening experiments aimed at identifying active compounds in the MDL Drug Data Report database. In more than half of the 20 cases examined, at least several actives per protein target were identified in approximately 24 hours per target.

Algorithms↗

Molecular docking and high-throughput screening for novel inhibitors of protein tyrosine phosphatase-1B.

High-throughput screening (HTS) of compound libraries is used to discover novel leads for drug development. When a structure is available for the target, computer-based screening using molecular docking may also be considered. The two techniques have rarely been used together on the same target. The opportunity to do so presented itself in a project to discover novel inhibitors for the enzyme protein tyrosine phosphatase-1B (PTP1B), a tyrosine phosphatase that has been implicated as a key target for type II diabetes. A corporate library of approximately 400 000 compounds was screened using high-throughput experimental techniques for compounds that inhibited PTP1B. Concurrently, molecular docking was used to screen approximately 235 000 commercially available compounds against the X-ray crystallographic structure of PTP1B, and 365 high-scoring molecules were tested as inhibitors of the enzyme. Of approximately 400 000 molecules tested in the high-throughput experimental assay, 85 (0.021%) inhibited the enzyme with IC50 values less than 100 microM; the most active had an IC50 value of 4.2 microM. Of the 365 molecules suggested by molecular docking, 127 (34.8%) inhibited PTP1B with IC50 values less than 100 microM; the most active of these had an IC50 of 1.7 microM. Structure-based docking therefore enriched the hit rate by 1700-fold over random screening. The hits from both the high-throughput and docking screens were dissimilar from phosphotyrosine, the canonical substrate group for PTP1B; the two hit lists were also very different from each other. Surprisingly, the docking hits were judged to be more druglike than the HTS hits. The diversity of both hit lists and their dissimilarity from each other suggest that docking and HTS may be complementary techniques for lead discovery.

Benzene Derivatives↗

Information decay in molecular docking screens against holo, apo, and modeled conformations of enzymes.

Molecular docking uses the three-dimensional structure of a receptor to screen a small molecule database for potential ligands. The dependence of docking screens on the conformation of the binding site remains an open question. To evaluate the information loss that occurs as the active site conformation becomes less defined, a small molecule database was docked against the holo (ligand bound), apo, and homology modeled structures of 10 different enzyme binding sites. The holo and apo representations were crystallographic structures taken from the Protein Data Bank (PDB), and the homology-modeled structures were taken from the publicly available resource ModBase. The database docked was the MDL Drug Data Report (MDDR), a functionally annotated database of 95000 small molecules that contained at least 35 ligands for each of the 10 systems. In all sites, at least 99% of the molecules in the MDDR were treated as nonbinding decoys. For each system, the holo, apo, and modeled structures were used to screen the MDDR, and the ability of each structure to enrich the known ligands for that system over random selection was evaluated. The best overall enrichment was produced by the holo structure in seven systems, the apo structure in two systems, and the modeled structure in one system. These results suggest that the performance of the docking calculation is affected by the particular representation of the receptor used in the screen, and that the holo structure is the one most likely to yield the best discrimination between known ligands and decoy molecules, but important exceptions to this rule also emerge from this study. Although each of the holo, apo, and modeled conformations led to enrichment of known ligands in all systems, the enrichment did not always rise to a level judged to be sufficient to justify the effort of a docking screen. Using a 20-fold enrichment of known ligands over random selection as a rough guideline for what might be enough to justify a docking screen, the holo conformation of the enzyme met this criterion in eight of 10 sites, whereas the apo conformation met this criterion in only two sites and the modeled conformation in three.

Animals↗

Prediction of HIV-1 integrase/viral DNA interactions in the catalytic domain by fast molecular docking.

This study details the separate analyses of binding specificity of HIV-1 integrase (IN) and viral B-DNA forms through ligand-receptor docking studies by means of a fast molecular docking method. The application of solvated electrostatics with the University of Houston Brownian Dynamics Program (UHBD) and configurational sampling by the Daughter of Turnip (DOT) docking program resulted in the computation of energies of more than 113 billion configurations for each ligand-receptor docking study, a procedure considered computationally intractable a few years ago. A specific binding pattern of viral DNA to the IN catalytic domain region has been predicted as a result of these calculations. In a representative docked configuration, we observe the 3'-hydroxyl of the conserved deoxyadenosine to be close to one of the two divalent metal ions that are necessary for catalysis. A superimposition of our energy-minimized docked complex on representative structures from a molecular dynamics (MD) simulation of a crystallographically resolved IN/inhibitor complex revealed an overlap of viral DNA with the inhibitor, indicating that the bound inhibitor might operate by blocking substrate binding. The DOT docking calculation also identified a second, adjacent DNA-binding site, which we believe is the nonspecific host DNA binding site. The binding pattern predicted by DOT complements previous electrostatics, MD simulation, photo-cross-linking, and mutagenesis studies and also provides a further refinement of the IN/viral DNA binding interaction as a basis for new structure-based design efforts.

Catalytic Domain↗

SDOCKER: a method utilizing existing X-ray structures to improve docking accuracy.

This paper introduces a new strategy for structure-based drug design that combines high-quality docking with data from existing ligand-protein cocrystal X-ray structures. The main goal of SDOCKER, a new algorithm that implements this strategy, is docking accuracy improvement. In this new paradigm, simulated annealing molecular dynamics is used for conformational sampling and optimization and an additional similarity force is applied on the basis of the positions of ligands from X-ray data that focus the sampling on relevant regions of the active site. Because the structural information from both the ligand and protein active site is included, this approach is more effective in finding the optimal conformation for a ligand-protein complex than the classical docking or similarity overlays. Interestingly, it was found that a 3D similarity-only approach gives comparable docking accuracy to the regular force field approach used in classical docking, given the final structures are minimized in the presence of the protein. The combination of both, as implemented in SDOCKER, is shown here to be more accurate. A significant improvement in docking accuracy has been observed for three different test systems. Specifically an improvement of 10%, 17.5%, and 10% is seen for 37 HIV-1 protease, 32 thrombin, and 23 CDK2 ligands, respectively, compared to docking using the force field alone. In addition, SDOCKER's accuracy performance dependence on the similarity template is discussed. The strategy of utilizing existing ligand X-ray information should prove effective in light of the multitude of structures available from structural genomics approaches.

Algorithms↗