The effect of multiple binding modes on empirical modeling of ligand docking to proteins

Benzimidazoles: a minor groove-binding ligand-induced stabilization of triple helix

Nonintercalating minor groove-binding ligands netropsin, Hoechst 33258, and DAPI are reported to destabilize the triplex. Ligands with different substitutions on the phenyl ring of bis- and terbenzimidazoles were evaluated for their effect on the stability of C+.GC triplex and Hoogsteen duplex. We found that newly synthesized benzimidazoles stabilize the triplex as shown by fluorescence and melting studies. Modeling studies showed that these molecules bind in the Watson-Crick minor groove of triplex, which can exert a profound impact on the properties of the host triplex. Circular dichroism-binding studies indicate 5.77 base triplets/ligand as an apparent binding site for bis- and 8.66 for terbenzimidazoles. The stabilization of triplex can be attributed to the protonation of nitrogens and amines of benzimidazoles at pH 5.2 that compensate the negative charge of phosphate backbone to reduce the repulsion between the strands resulting in the stabilization.

Consistent improvement of cross-docking results using binding site ensembles generated with elastic network normal modes

The representation of protein flexibility is still a challenge for the state-of-the-art flexible ligand docking protocols. In this article, we use a large and diverse benchmark to prove that is possible to improve consistently the cross-docking performance against a single receptor conformation, using an equilibrium ensemble of binding site conformers. The benchmark contained 28 proteins, and our method predicted the top-ranked near native ligand poses 20% more efficiently than using a single receptor. The multiple conformations were derived from the collective variable space defined by all heavy-atom elastic network normal modes, including backbone and side chains. We have found that the binding site displacements for best positioning of the ligand seem rather independent from the global collective motions of the protein. We also found that the number of binding site conformations needed to represent nonredundant flexibility was < 100. The ensemble of receptor conformations can be generated at our Web site at http://abagyan.scripps.edu/MRC.

Toward a molecular understanding of the interaction of dual specificity phosphatases with substrates: insights from structure-based modeling and high throughput screening

Dual-specificity phosphatases (DSPs) are important, but poorly understood, cell signaling enzymes that remove phosphate groups from tyrosine and serine/threonine residues on their substrate. Deregulation of DSPs has been implicated in cancer, obesity, diabetes, inflammation, and Alzheimer's disease. Due to their biological and biomedical significance, DSPs have increasingly become the subject of drug discovery high-throughput screening (HTS) and focused compound library development efforts. Progress in identifying selective and potent DSP inhibitors has, however, been restricted by the lack of sufficient structural data on inhibitor-bound DSPs. The shallow, almost flat, substrate binding sites in DSPs have been a major factor in hampering the rational design and the experimental development of active site inhibitors. Recent experimental and virtual HTS studies, as well as advances in molecular modeling, provide new insights into the potential mechanisms for substrate recognition and binding by this important class of enzymes. We present herein an overview of the progress, along with a brief description of applications to two types of DSPs: Cdc25 and MAP kinase phosphatase (MKP) family members. In particular, we focus on combined computational and experimental efforts for designing Cdc25B and MKP-1 inhibitors and understanding their mechanisms of interactions with their target proteins. These studies emphasize the utility of developing computational models and methods that meet the two major challenges currently faced in structure-based in silico design of lead compounds: the conformational flexibility of the target protein and the entropic contribution to the selection and stabilization of particular bound conformers.

A novel empirical free energy function that explains and predicts protein–protein binding affinities

A free energy function can be defined as a mathematical expression that relates macroscopic free energy changes to microscopic or molecular properties. Free energy functions can be used to explain and predict the affinity of a ligand for a protein and to score and discriminate between native and non-native binding modes. However, there is a natural tension between developing a function fast enough to solve the scoring problem but rigorous enough to explain and predict binding affinities. Here, we present a novel, physics-based free energy function that is computationally inexpensive, yet explanatory and predictive. The function results from a derivation that assumes the cost of polar desolvation can be ignored and that includes a unique and implicit treatment of interfacial water-bridged interactions. The function was parameterized on an internally consistent, high quality training set giving R2=0.97 and Q2=0.91. We used the function to blindly and successfully predict binding affinities for a diverse test set of 31 wild-type protein-protein and protein-peptide complexes (R2=0.79, rmsd=1.2 kcal mol(-1)). The function performed very well in direct comparison with a recently described knowledge-based potential and the function appears to be transferable. Our results indicate that our function is well suited for solving a wide range of protein/peptide design and discovery problems.

Characterization of a ligand-receptor binding event using receptor-dependent four-dimensional quantitative structure-activity relationship analysis

Receptor-dependent four-dimensional quantitative structure-activity relationship (RD-4D-QSAR) analysis is used to map the ligand-receptor binding event characteristic of a set of 47 glucose analogue inhibitors of glycogen phosphorylase (GPb). Specifically, the geometric and energetic binding profiles are constructed, conformational changes are determined, and conformational couplings among structural units are identified for the composite set of ligand-receptor complexes. A pruned ligand-receptor model is used to estimate ligand-receptor thermodynamics. Rather than explicitly handling the large amount of structural data generated from each of the pruned ligand-receptor models, these complexes were divided into three subregions. The subregions consist of a "functional" region, the smallest region providing definitive information about inhibitor binding, and two "allosteric" regions that surround the "functional" region and are based on distances from the center of the catalytic site. Maximum information on inhibitor binding and/or inhibitor-receptor conformational changes is extracted from each of these subregions. The key sites for inhibitor binding and conformational changes in GPb are presented as grid cell occupancy descriptors (GCODs), which can be both numerically and graphically represented. An induced conformational change in both the inhibitor and the binding site of GPb occurs in a distinct manner for each complex. The inter-relationships (correlations) between GCODs from different regions are identified and probed. Such correlations validate the ligand-receptor interactions identified from the "functional" region. A long-range network of conformational associations involving ligands and the receptor is also found by exploring correlations among the GCODs for the set of inhibitors.

Principles of docking: An overview of search algorithms and a guide to scoring functions

The docking field has come of age. The time is ripe to present the principles of docking, reviewing the current state of the field. Two reasons are largely responsible for the maturity of the computational docking area. First, the early optimism that the very presence of the "correct" native conformation within the list of predicted docked conformations signals a near solution to the docking problem, has been replaced by the stark realization of the extreme difficulty of the next scoring/ranking step. Second, in the last couple of years more realistic approaches to handling molecular flexibility in docking schemes have emerged. As in folding, these derive from concepts abstracted from statistical mechanics, namely, populations. Docking and folding are interrelated. From the purely physical standpoint, binding and folding are analogous processes, with similar underlying principles. Computationally, the tools developed for docking will be tremendously useful for folding. For large, multidomain proteins, domain docking is probably the only rational way, mimicking the hierarchical nature of protein folding. The complexity of the problem is huge. Here we divide the computational docking problem into its two separate components. As in folding, solving the docking problem involves efficient search (and matching) algorithms, which cover the relevant conformational space, and selective scoring functions, which are both efficient and effectively discriminate between native and non-native solutions. It is universally recognized that docking of drugs is immensely important. However, protein-protein docking is equally so, relating to recognition, cellular pathways, and macromolecular assemblies. Proteins function when they are bound to other molecules. Consequently, we present the review from both the computational and the biological points of view. Although large, it covers only partially the extensive body of literature, relating to small (drug) and to large protein-protein molecule docking, to rigid and to flexible. Unfortunately, when reviewing these, a major difficulty in assessing the results is the non-uniformity in the formats in which they are presented in the literature. Consequently, we further propose a way to rectify it here.

Contributions to the binding free energy of ligands to avidin and streptavidin

The free energy of binding of a ligand to a macromolecule is here formally decomposed into the (effective) energy of interaction, reorganization energy of the ligand and the macromolecule, conformational entropy change of the ligand and the macromolecule, and translational and rotational entropy loss of the ligand. Molecular dynamics simulations with implicit solvation are used to evaluate these contributions in the binding of biotin, biotin analogs, and two peptides to avidin and streptavidin. We find that the largest contribution opposing binding is the protein reorganization energy, which is calculated to be from 10 to 30 kcal/mol for the ligands considered here. The ligand reorganization energy is also significant for flexible ligands. The translational/rotational entropy is 4.5-6 kcal/mol at 1 M standard state and room temperature. The calculated binding free energies are in the correct range, but the large statistical uncertainty in the protein reorganization energy precludes precise predictions. For some complexes, the simulations show multiple binding modes, different from the one observed in the crystal structure. This finding is probably due to deficiencies in the force field but may also reflect considerable ligand flexibility.

Base flexibility in HIV-2 TAR RNA mapped by solution (15)N, (13)C NMR relaxation

Binding of the HIV tat protein to the TAR (transactivating response region) RNA element activates transcription of the HIV viral genome. The complex of TAR with argininamide serves as a model for the RNA conformation in the tat-TAR complex. The dynamics of the HIV-2 TAR-argininamide complex was investigated by measurements of the relaxation rates of protonated base carbon and nitrogen nuclei. Six auto-correlation rates as well as cross-correlation rates were measured to map the frequencies of base motion in the HIV-2 TAR-argininamide complex. These measurements reveal a broad range of dynamic heterogeneity exhibited by hexanucleotide loop, the dinucleotide bulge, and the A-form helical regions. U23 in the bulge undergoes the largest dynamic change on binding argininamide, while U25 remains flexible, reflecting the large conformational change that is triggered upon ligand binding.

Recent advances in structure-based rational drug design

Two approaches to structure-based drug design, that is, the docking of known compounds into a target protein and molecular assembly in situ, are seen to be merging technologies. The need for structural information about drug-protein complexes is now fundamental for drug discovery.