Experimental and computational mapping of the binding surface of a crystalline protein

Multiple Solvent Crystal Structures (MSCS) is a crystallographic technique to identify energetically favorable positions and orientations of small organic molecules on the surface of proteins. We determined the high-resolution crystal structures of thermolysin (TLN), generated from crystals soaked in 50--70% acetone, 50--80% acetonitrile and 50 mM phenol. The structures of the protein in the aqueous-organic mixtures are essentially the same as the native enzyme and a number of solvent interaction sites were identified. The distribution of probe molecules shows clusters in the main specificity pocket of the active site and a buried subsite. Within the active site, we compared the experimentally determined solvent positions with predictions from two computational functional group mapping techniques, GRID and Multiple Copy Simultaneous Search (MCSS). The experimentally determined small molecule positions are consistent with the structures of known protein--ligand complexes of TLN.     

Identification of substrate binding sites in enzymes by computational solvent mapping

Enzyme structures determined in organic solvents show that most organic molecules cluster in the active site, delineating the binding pocket. We have developed algorithms to perform solvent mapping computationally, rather than experimentally, by placing molecular probes (small molecules or functional groups) on a protein surface, and finding the regions with the most favorable binding free energy. The method then finds the consensus site that binds the highest number of different probes. The probe-protein interactions at this site are compared to the intermolecular interactions seen in the known complexes of the enzyme with various ligands (substrate analogs, products, and inhibitors). We have mapped thermolysin, for which experimental mapping results are also available, and six further enzymes that have no experimental mapping data, but whose binding sites are well characterized. With the exception of haloalkane dehalogenase, which binds very small substrates in a narrow channel, the consensus site found by the mapping is always a major subsite of the substrate-binding site. Furthermore, the probes at this location form hydrogen bonds and non-bonded interactions with the same residues that interact with the specific ligands of the enzyme. Thus, once the structure of an enzyme is known, computational solvent mapping can provide detailed and reliable information on its substrate-binding site. Calculations on ligand-bound and apo structures of enzymes show that the mapping results are not very sensitive to moderate variations in the protein coordinates.     

Automated generation of MCSS-derived pharmacophoric DOCK site points for searching multiconformation databases

All docking methods employ some sort of heuristic to orient the ligand molecules into the binding site of the target structure. An automated method, MCSS2SPTS, for generating chemically labeled site points for docking is presented. MCSS2SPTS employs the program Multiple Copy Simultaneous Search (MCSS) to determine target-based theoretical pharmacophores. More specifically, chemically labeled site points are automatically extracted from selected low-energy functional-group minima and clustered together. These pharmacophoric site points can then be directly matched to the pharmacophoric features of database molecules with the use of either DOCK or PhDOCK to place the small molecules into the binding site. Several examples of the ability of MCSS2SPTS to reproduce the three-dimensional pharmacophoric features of ligands from known ligand-protein complex structures are discussed. In addition, a site-point set calculated for one human immunodeficiency virus 1 (HIV1) protease structure is used with PhDOCK to dock a set of HIV1 protease ligands; the docked poses are compared to the corresponding complex structures of the ligands. Finally, the use of an MCSS2SPTS-derived site-point set for acyl carrier protein synthase is compared to the use of atomic positions from a bound ligand as site points for a large-scale DOCK search. In general, MCSS2SPTS-generated site points focus the search on the more relevant areas and thereby allow for more effective sampling of the target site.     

Similarity-driven flexible ligand docking

A similarity-driven approach to flexible ligand docking is presented. Given a reference ligand or a pharmacophore positioned in the protein active site, the method allows inclusion of a similarity term during docking. Two different algorithms have been implemented, namely, a similarity-penalized docking (SP-DOCK) and a similarity-guided docking (SG-DOCK). The basic idea is to maximally exploit the structural information about the ligand binding mode present in cases where ligand-bound protein structures are available, information that is usually ignored in standard docking procedures. SP-DOCK and SG-DOCK have been derived as modified versions of the program DOCK 4.0, where the similarity program MIMIC acts as a module for the calculation of similarity indices that correct docking energy scores at certain steps of the calculation. SP-DOCK applies similarity corrections to the set of ligand orientations at the end of the ligand incremental construction process, penalizing the docking energy and, thus, having only an effect on the relative ordering of the final solutions. SG-DOCK applies similarity corrections throughout the entire ligand incremental construction process, thus affecting not only the relative ordering of solutions but also actively guiding the ligand docking. The performance of SP-DOCK and SG-DOCK for binding mode assessment and molecular database screening is discussed. When applied to a set of 32 thrombin ligands for which crystal structures are available, SG-DOCK improves the average RMSD by ca. 1 A when compared with DOCK. When those 32 thrombin ligands are included into a set of 1,000 diverse molecules from the ACD, DIV, and WDI databases, SP-DOCK significantly improves the retrieval of thrombin ligands within the first 10% of each of the three databases with respect to DOCK, with minimal additional computational cost. In all cases, comparison of SP-DOCK and SG-DOCK results with those obtained by DOCK and MIMIC is performed.     

Geometric and chemical patterns of interaction in protein--ligand complexes and their application in docking

We present a new method for representing the binding site of a protein receptor that allows the use of the DOCK approach to screen large ensembles of receptor conformations for ligand binding. The site points are constructed from templates of what we called "attached points" (ATPTS). Each template (one for each type of amino acid) is composed of a set of representative points that are attached to side-chain and backbone atoms through internal coordinates, carry chemical information about their parent atoms and are intended to cover positions that might be occupied by ligand atoms when complexed to the protein. This method is completely automatic and proved to be extremely fast. With the aim of obtaining an experimental basis for this approach, the Protein Data Bank was searched for proteins in complex with small molecules, to study the geometry of the interactions between the different types of protein residues and the different types of ligand atoms. As a result, well-defined patterns of interaction were obtained for most amino acids. These patterns were then used for constructing a set of templates of attached points, which constitute the core of the ATPTS approach. The quality of the ATPTS representation was demonstrated by using this method, in combination with the DOCK matching and orientation algorithms, to generate correct ligand orientations for >1000 protein--ligand complexes.     

Computation of electrostatic complements to proteins: a case of charge stabilized binding.

Recent evidence suggests that the net effect of electrostatics is generally to destabilize protein binding due to large desolvation penalties. A novel method for computing ligand-charge distributions that optimize the tradeoff between ligand desolvation penalty and favorable interactions with a binding site has been applied to a model for barnase. The result is a ligand-charge distribution with a favorable electrostatic contribution to binding due, in part, to ligand point charges whose direct interaction with the binding site is unfavorable, but which make strong intra-molecular interactions that are uncloaked on binding and thus act to lessen the ligand desolvation penalty.     

Effects of initial settings on computational protein–ligand docking accuracies for several docking programs

In this study, the influences of initial settings, i.e. initial conformations, configurations and docking parameters, on docking results were investigated. The conformations used in the study were generated by the CAMDAS program. After the conformational search calculations, five structures were selected from the conformer groups according to their conformation energies and root mean square deviations against crystal structures; for example, the lowest energy conformer, as well as the closest and farthest conformers to the crystal structure, was retrieved. Several docking parameter settings were used (default, high speed, generating 50 poses). In this study, docking calculations were conducted using the GOLD, eHiTS, AutoDock, AutoDock vina, FRED and DOCK programs. The success rates of GOLD, eHiTS and FRED were better than those of AutoDock, AutoDock vina and DOCK. The docking results using the farthest conformations were worse than those obtained using other conformations, indicating that some conformation search for the ligand molecule should be performed before the docking calculations.     

Binding Hot Spots and Amantadine Orientation in the Influenza A Virus M2 Proton Channel

Structures of truncated versions of the influenza A virus M2 proton channel have been determined recently by x-ray crystallography in the open conformation of the channel, and by NMR in the closed state. The structures differ in the position of the bound inhibitors. The x-ray structure shows a single amantadine molecule in the middle of the channel, whereas in the NMR structure four drug molecules bind at the channel's outer surface. To study this controversy we applied computational solvent mapping, a technique developed for the identification of the most druggable binding hot spots of proteins. The method moves molecular probes—small organic molecules containing various functional groups—around the protein surface, finds favorable positions using empirical free energy functions, clusters the conformations, and ranks the clusters on the basis of the average free energy. The results of the mapping show that in both structures the primary hot spot is an internal cavity overlapping the amantadine binding site seen in the x-ray structure. However, both structures also have weaker hot spots at the exterior locations that bind rimantadine in the NMR structure, although these sites are partially due to the favorable interactions with the interfacial region of the lipid bilayer. As confirmed by docking calculations, the open channel binds amantadine at the more favorable internal site, in good agreement with the x-ray structure. In contrast, the NMR structure is based on a peptide/micelle construct that is able to accommodate the small molecular probes used for the mapping, but has a too narrow pore for the rimantadine to access the internal hot spot, and hence the drug can bind only at the exterior sites.     

Incorporating replacement free energy of binding‐site waters in molecular docking

Binding‐site water molecules play a crucial role in protein‐ligand recognition, either being displaced upon ligand binding or forming water bridges to stabilize the complex. However, rigorously treating explicit binding‐site waters is challenging in molecular docking, which requires to fully sample ensembles of waters and to consider the free energy cost of replacing waters. Here, we describe a method to incorporate structural and energetic properties of binding‐site waters into molecular docking. We first developed a solvent property analysis (SPA) program to compute the replacement free energies of binding‐site water molecules by post‐processing molecular dynamics trajectories obtained from ligand‐free protein structure simulation in explicit water. Next, we implemented a distance‐dependent scoring term into DOCK scoring function to take account of the water replacement free energy cost upon ligand binding. We assessed this approach in protein targets containing important binding‐site waters, and we demonstrated that our approach is reliable in reproducing the crystal binding geometries of protein‐ligand‐water complexes, as well as moderately improving the ligand docking enrichment performance. In addition, SPA program (free available to academic users upon request) may be applied in identifying hot‐spot binding‐site residues and structure‐based lead optimization. Proteins 2014; 82:1765–1776. © 2014 Wiley Periodicals, Inc.     

Flexible ligand docking using evolutionary algorithms: investigating the effects of variation operators and local search hybrids

The docking of ligands to proteins can be formulated as a computational problem where the task is to find the most favorable energetic conformation among the large space of possible protein-ligand complexes. Stochastic search methods such as evolutionary algorithms (EAs) can be used to sample large search spaces effectively and is one of the commonly used methods for flexible ligand docking. During the last decade, several EAs using different variation operators have been introduced, such as the ones provided with the AutoDock program. In this paper we evaluate the performance of different EA settings such as choice of variation operators, population size, and usage of local search. The comparison is performed on a suite of six docking problems previously used to evaluate the performance of search algorithms provided with the AutoDock program package. The results from our investigation confirm that the choice of variation operators has an impact on the search-capabilities of EAs. The introduced DockEA using the best settings found obtained the overall best docking solutions compared to the Lamarckian GA (LGA) provided with AutoDock. Furthermore, the DockEA proved to be more robust than the LGA (in terms of reproducing the results in several runs) on the more difficult problems with a high number of flexible torsion angles.     

Molecular dynamics simulations of the adipocyte lipid binding protein reveal a novel entry site for the ligand

The adipocyte lipid binding protein (ALBP) binds fatty acids (FA) in a cavity that is inaccessible from the bulk. Therefore, the penetration of the FA necessitates conformational changes whose nature is still unknown. It was suggested that the lipid first enters through a "portal region" which consists of the alphaII helix and the adjacent tight turns. The initial event in the ligand binding must be the interaction of the lipid with the protein surface. To analyze this interaction, we have carried out three molecular dynamics simulations of the apo-ALBP, with a palmitate ion initially located at different positions near the protein surface. The simulation indicated that the ligand could adsorb to the protein in more than one location. Yet, in one case, the ligand managed to penetrate the protein by entering a newly formed cavity some 10 A deep. The entry site is located near the N-terminus, at the junction between the loops connecting the beta-strands. Further progression of the penetration seems to be arrested by the need for desolvation of the COOH end of the headgroup. Evolutionary analysis showed that amino acids in this entry site are well conserved. On the basis of these observations, we suggest that the ligand may enter the protein from a site other than the portal region. Furthermore, the rate-limiting step is proposed to be the desolvation of the FA polar headgroup.     

Contributions of water transfer energy to protein‐ligand association and dissociation barriers: Watermap analysis of a series of p38α MAP kinase inhibitors

In our previous work, we proposed that desolvation and resolvation of the binding sites of proteins can serve as the slowest steps during ligand association and dissociation, respectively, and tested this hypothesis on two protein‐ligand systems with known binding kinetics behavior. In the present work, we test this hypothesis on another kinetically‐determined protein‐ligand system—that of p38α and eight Type II BIRB 796 inhibitor analogs. The k_on values among the inhibitor analogs are narrowly distributed (10⁴ ≤ k_on ≤ 10⁵ M^?1 s^?1), suggesting a common rate‐determining step, whereas the k_off values are widely distributed (10^?1 ≤ k_off ≤ 10^?6 s^?1), suggesting a spectrum of rate‐determining steps. We calculated the solvation properties of the DFG‐out protein conformation using an explicit solvent molecular dynamics simulation and thermodynamic analysis method implemented in WaterMap to predict the enthalpic and entropic costs of water transfer to and from bulk solvent incurred upon association and dissociation of each inhibitor. The results suggest that the rate‐determining step for association consists of the transfer of a common set of enthalpically favorable solvating water molecules from the binding site to bulk solvent. The rate‐determining step for inhibitor dissociation consists of the transfer of water from bulk solvent to specific binding site positions that are unfavorably solvated in the apo protein, and evacuated during ligand association. Different sets of unfavorable solvation are evacuated by each ligand, and the observed dissociation barriers are qualitatively consistent with the calculated solvation free energies of those sets.     

pH dependence of copper geometry, reduction potential, and nitrite affinity in nitrite reductase

Many properties of copper-containing nitrite reductase are pH-dependent, such as gene expression, enzyme activity, and substrate affinity. Here we use x-ray diffraction to investigate the structural basis for the pH dependence of activity and nitrite affinity by examining the type 2 copper site and its immediate surroundings in nitrite reductase from Rhodobacter sphaeroides 2.4.3. At active pH the geometry of the substrate-free oxidized type 2 copper site shows a near perfect tetrahedral geometry as defined by the positions of its ligands. At higher pH values the most favorable copper site geometry is altered toward a more distorted tetrahedral geometry whereby the solvent ligand adopts a position opposite to that of the His-131 ligand. This pH-dependent variation in type 2 copper site geometry is discussed in light of recent computational results. When co-crystallized with substrate, nitrite is seen to bind in a bidentate fashion with its two oxygen atoms ligating the type 2 copper, overlapping with the positions occupied by the solvent ligand in the high and low pH structures. Fourier transformation infrared spectroscopy is used to assign the pH dependence of the binding of nitrite to the active site, and EPR spectroscopy is used to characterize the pH dependence of the reduction potential of the type 2 copper site. Taken together, these spectroscopic and structural observations help to explain the pH dependence of nitrite reductase, highlighting the subtle relationship between copper site geometry, nitrite affinity, and enzyme activity.     

The effect of different electrostatic potentials on docking accuracy: a case study using DOCK5.4

As a commonly used structure-based approach for virtual screening, molecular design and lead optimization, molecular docking can search the preferred orientation and conformation of a ligand for its optimal binding to a receptor or enzyme active site. In doing so, selecting an appropriate method to calculate the electrostatic potentials is critical. In the current report, nine different semi-empirical and empirical methods, including AM1, AM1-BCC, Del-Re, MMFF, Gasteiger, Hückel, Gasteiger-Hückel, Pullman and formal charges were investigated for their performance on the prediction of docking poses using the DOCK5.4 program. The results demonstrated that the AM1-BCC charges had the highest success rate.     

Inhibitors of kinesin activity from structure-based computer screening

Kinesin motor proteins use ATP hydrolysis for transport along microtubules in the cell. We sought to identify small organic ligands to inhibit kinesin's activity. Candidate molecules were identified by computational docking of commercially available compounds using the computer program DOCK. Compounds were docked at either of two sites, and a selection was tested for inhibition of microtubule-stimulated ATPase activity. Twenty-two submillimolar inhibitors were identified. Several inhibitors appeared to be competitive for microtubule binding and not for ATP binding, and three compounds showed 50% inhibition down to single-digit micromolar levels. Most inhibitors grouped into four distinct classes (fluoresceins, phenolphthaleins, anthraquinones, and naphthylene sulfonates). We measured the binding of one inhibitor, rose bengal lactone (RBL), to kinesin (dissociation constant 2.5 microM) by its increase in steady-state fluorescence anisotropy. The RBL binding site on kinesin was localized by fluorescent resonance energy transfer (FRET) using a donor fluorophore (coumarin) covalently attached at unique, surface-exposed cysteine residues engineered at positions 28, 149, 103, 220, or 330. RBL was found to bind in its original docked site: the pocket cradled by loop 8 and beta-strand 5 in kinesin's three-dimensional structure. These results confirm this region's role in microtubule binding and identify this pocket as a novel binding site for kinesin inhibition.     

Computational solvent mapping reveals the importance of local conformational changes for broad substrate specificity in mammalian cytochromes P450

Computational solvent mapping moves small organic molecules as probes around a protein surface, finds favorable binding positions, clusters the conformations, and ranks the clusters on the basis of their average free energy. Prior mapping studies of enzymes, crystallized in either substrate-free or substrate-bound form, have shown that the largest number of solvent probe clusters invariably overlaps in the active site. We have applied this method to five cytochromes P450. As expected, the mapping of two bacterial P450s, P450 cam (CYP101) and P450 BM-3 (CYP102), identified the substrate-binding sites in both ligand-bound and ligand-free P450 structures. However, the mapping finds the active site only in the ligand-bound structures of the three mammalian P450s, 2C5, 2C9, and 2B4. Thus, despite the large cavities seen in the unbound structures of these enzymes, the features required for binding small molecules are formed only in the process of substrate binding. The ability of adjusting their binding sites to substrates that differ in size, shape, and polarity is likely to be responsible for the broad substrate specificity of these mammalian P450s. Similar behavior was seen at "hot spots" of protein-protein interfaces that can also bind small molecules in grooves created by induced fit. In addition, the binding of S-warfarin to P450 2C9 creates a high-affinity site for a second ligand, which may help to explain the prevalence of drug-drug interactions involving this and other mammalian P450s.     

Solvation energy density occlusion approximation for evaluation of desolvation penalties in biomolecular interactions

In calculations involving many displacements of an interacting pair of biomolecules, such as brownian dynamics, the docking of a substrate/ligand to an enzyme/receptor, or the screening of a large number of ligands as prospective inhibitors for a particular receptor site, there is a need for rapid evaluation of the desolvation penalties of the interacting pair. Although continuum electrostatic treatments with distinct dielectric constants for solute and solvent provide an account of the electrostatics of solvation and desolvation, it is necessary to re-solve the Poisson equation, at considerable computational cost, for each displacement of the interacting pair. We present a new method that uses a formulation of continuum electrostatic solvation in terms of the solvation energy density and approximates desolvation in terms of the occlusion of this density. We call it the SEDO approximation. It avoids the need to re-solve the Poisson equation, as desolvation is now estimated by an integral over the occluded volume. Test calculations are presented for some simple model systems and for some real systems that have previously been studied using the Poisson equation approach: MHC class I protein-peptide complexes and a congeneric series of human immunodeficiency virus type 1 (HIV-1) protease--ligand complexes. For most of the systems considered, the trends and magnitudes of the desolvation component of interaction energies obtained using the SEDO approximation are in reasonable correlation with those obtained by re-solving the Poisson equation. In most cases, the error introduced by the SEDO approximation is much less than that of the often-used test-charge approximation for the charge-charge components of intermolecular interactions. Proteins 2001;43:12-27.     

Prediction of Protein-Protein Interaction Sites Using Electrostatic Desolvation Profiles

Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces.     

Aspartate aminotransferase: Investigation of the active sites

An investigation of the crystal structure of cytosolic pigheart aspartate aminotransferase (AAT, E.C.2.6.1.1) was carried out to determine the structural requirements for ligand recognition by the active site. Structural differences were observed between the two active sites of the AAT dimer. The natural ligand, l-aspartate, was docked into both active sites using various methods. However, due to structural differences, the ligand was able to form all the necessary interactions for initial binding in only one of the active sites. The program GRID (P. J. Goodford. J. Med. Chem. 1985, 28, 849-857) was used to predict favorable binding sites for the functional groups of the aspartate ligand. These binding sites corresponded to the position of the docked aspartate ligand, indicating that substrate recognition takes place before any major conformational changes occur within the enzyme.