Stochastic roadmap simulation for the study of ligand-protein interactions

Understanding the dynamics of ligand-protein interactions is indispensable in the design of novel therapeutic agents. In this paper, we establish the use of Stochastic Roadmap Simulation (SRS) for the study of ligand-protein interactions through two studies. In our first study, we measure the effects of mutations on the catalytic site of a protein, a process called computational mutagenesis. In our second study, we focus on distinguishing the catalytic site from other putative binding sites. SRS compactly represents many Monte Carlo (MC) simulation paths in a compact graph structure, or roadmap. Furthermore, SRS allows us to analyze all the paths in this roadmap simultaneously. In our application of SRS to the domain of ligand-protein interactions, we consider a new parameter called escape time, the expected number of MC simulation steps required for the ligand to escape from the 'funnel of attraction' of the binding site, as a metric for analyzing such interactions. Although computing escape times would probably be infeasible with MC simulation, these computations can be performed very efficiently with SRS. Our results for six mutant complexes for the first study and seven ligand-protein complexes for the second study, are very promising: In particular, the first results agree well with the biological interpretation of the mutations, while the second results show that escape time is a good metric to distinguish the catalytic site for five out of seven complexes.     

Predicting structural effects in HIV-1 protease mutant complexes with flexible ligand docking and protein side-chain optimization

We present a computational approach for predicting structures of ligand-protein complexes and analyzing binding energy landscapes that combines Monte Carlo simulated annealing technique to determine the ligand bound conformation with the dead-end elimination algorithm for side-chain optimization of the protein active site residues. Flexible ligand docking and optimization of mobile protein side-chains have been performed to predict structural effects in the V32I/I47V/V82I HIV-1 protease mutant bound with the SB203386 ligand and in the V82A HIV-1 protease mutant bound with the A77003 ligand. The computational structure predictions are consistent with the crystal structures of these ligand-protein complexes. The emerging relationships between ligand docking and side-chain optimization of the active site residues are rationalized based on the analysis of the ligand-protein binding energy landscape. Proteins 33:295–310, 1998. © 1998 Wiley-Liss, Inc.     

Interaction of ochratoxin A with human serum albumin. Binding sites localized by competitive interactions with the native protein and its recombinant fragments

Competitive interactions of ochratoxin A (OTA) and several other acidic compounds were utilized to gain insight into the localization of binding sites and the nature of binding interactions between anionic species and human serum albumin (HSA). Depolarization of OTA fluorescence in the presence of a competing anion was used to quantify ligand-protein interactions. The results obtained were rationalized in terms of OTA displacement from its major binding site. Based on their ability to displace OTA, two distinct groups of the anionic ligands were revealed. The first group contained structurally diverse compounds that shared a common binding site in subdomain IIA (Sudlow Site I). The second group consisted of three non-steroidal anti-inflammatory drugs, which showed much lower affinity to Site I than the OTA dianion. The major site for these drugs was located in domain III. Fluorescence spectroscopy measurements of OTA, warfarin (WAR) and naproxen (NAP) complexes with recombinant proteins corresponding to the domains of HSA (D1-D3) revealed binding to all domains but with different affinities. The binding constants for OTA and WAR decreased in the series D2z.Gt;D3>D1. In contrast, NAP showed the most favorable interaction with D3 and comparable affinities to the two remaining domains. The OTA binding constant for D2, 7.9 x 10(5) M(-1), was smaller than the largest constant for HSA by a factor of approximately 7. The binding constant for OTA with D3, 1.1 x 10(5) M(-1), was very close to that of the secondary binding site for HSA.     

Determinants of cytochrome P450 2C8 substrate binding: structures of complexes with montelukast, troglitazone, felodipine, and 9-cis-retinoic acid

Although a crystal structure and a pharmacophore model are available for cytochrome P450 2C8, the role of protein flexibility and specific ligand-protein interactions that govern substrate binding are poorly understood. X-ray crystal structures of P450 2C8 complexed with montelukast (2.8 A), troglitazone (2.7 A), felodipine (2.3 A), and 9-cis-retinoic acid (2.6 A) were determined to examine ligand-protein interactions for these chemically diverse compounds. Montelukast is a relatively large anionic inhibitor that exhibits a tripartite structure and complements the size and shape of the active-site cavity. The inhibitor troglitazone occupies the upper portion of the active-site cavity, leaving a substantial part of the cavity unoccupied. The smaller neutral felodipine molecule is sequestered with its dichlorophenyl group positioned close to the heme iron, and water molecules fill the distal portion of the cavity. The structure of the 9-cis-retinoic acid complex reveals that two substrate molecules bind simultaneously in the active site of P450 2C8. A second molecule of 9-cis-retinoic acid is located above the proximal molecule and can restrain the position of the latter for more efficient oxygenation. Solution binding studies do not discriminate between cooperative and noncooperative models for multiple substrate binding. The complexes with structurally distinct ligands further demonstrate the conformational adaptability of active site-constituting residues, especially Arg-241, that can reorient in the active-site cavity to stabilize a negatively charged functional group and define two spatially distinct binding sites for anionic moieties of substrates.     

Ligand--protein interactions in the glutamate receptor

Fourier transform infrared spectroscopy was used to investigate ligand-protein interactions in the ligand-binding domain of the GluR4 glutamate receptor subunit. Glutamate binding induces more extensive secondary structural changes in the ligand-binding domain than does kainate binding. Glutamate also alters the hydrogen bonding strength of the single free cysteine side chain in the domain, while kainate does not. On the other hand, the interaction of a binding site arginine residue with kainate appears to be stronger than that with glutamate. These results identify chemical and structural differences that may explain the different functional characteristics of the two agonists acting on ionotropic glutamate receptors. In doing so, they complement and extend recent crystallographic structures of the ligand-binding domain.     

Conserved positions for ribose recognition: importance of water bridging interactions among ATP,ADP and FAD-protein complexes

Analysis of the spatial arrangement of protein and water atoms that form polar interactions with ribose has been performed for a structurally non-redundant dataset of ATP, ADP and FAD-protein complexes. The 26 ligand-protein structures were separated into two groups corresponding to the most populated furanose ring conformations (N and S-domains). Four conserved positions were found for S-domain protein-ligand complexes and five for N-domain complexes. Multiple protein folds and secondary structural elements were represented at a single conserved position. The following novel points were revealed: (i) Two complementary positions sometimes combine to describe a putative atomic spatial location for a specific conserved binding spot. (ii) More than one third of the interactions scored were water-mediated. Thus, conserved spatial positions rich in water atoms are a significant feature of ribose-protein complexes.     

Efficient docking of peptides to proteins without prior knowledge of the binding site

Reliability in docking of ligand molecules to proteins or other targets is an important challenge for molecular modeling. Applications of the docking technique include not only prediction of the binding mode of novel drugs, but also other problems like the study of protein-protein interactions. Here we present a study on the reliability of the results obtained with the popular AutoDock program. We have performed systematical studies to test the ability of AutoDock to reproduce eight different protein/ligand complexes for which the structure was known, without prior knowledge of the binding site. More specifically, we look at factors influencing the accuracy of the final structure, such as the number of torsional degrees of freedom in the ligand. We conclude that the Autodock program package is able to select the correct complexes based on the energy without prior knowledge of the binding site. We named this application blind docking, as the docking algorithm is not able to "see" the binding site but can still find it. The success of blind docking represents an important finding in the era of structural genomics.     

Complexity and simplicity of ligand-macromolecule interactions: the energy landscape perspective

The energy landscape approach has contributed to recent progress in understanding the complexity and simplicity of ligand-macromolecule interactions. Significant advances in computational structure prediction of ligand-protein complexes have been made using approaches that include the effects of protein flexibility and incorporate a hierarchy of energy functions. The results suggest that the complexity of structure prediction in molecular recognition may be determined by low-resolution properties of the underlying binding energy landscapes and by the nature of the energy funnels near the native structures of the complexes.     

Understanding the relative affinity and specificity of the substrate binding site of protein kinase B for substrate-mimetic inhibitors

Designing selective inhibitor of protein kinase B (PKB/Akt) is an area of intense research to develop potential anticancer drugs. As a general point of strategy, the peptide substrate-binding site only responds to a highly specific sequence of amino acids. Targeting the substrate-mimetic inhibitors to the peptide substrate-binding site has the potential for better selectivity. It is therefore of great interest to understand the peptide substrate binding mode of PKB, as well as its specificity and affinity for different substrate-mimetic inhibitors. In the present study, we used molecular dynamic simulations to better understand the interactions of the PKB substrate-binding site with the substrate-mimetic inhibitors. Our computational models successfully mirrored PKB’s selectivity for the substrate-mimetic inhibitors. Furthermore, the key residues interacting with the substrate-mimetic inhibitor were discussed by analysing the different interaction modes of these inhibitors, with different inhibitory potencies, binding to PKB and by comparing the different binding free energy contributions of corresponding residues around the binding pocket. The pharmacophoric requirements were then also summarised for the substrate-mimetic inhibitor binding to PKB. It is expected that this work will provide useful chemical or biochemical informatics for the design of novel and potent substrate-mimetic inhibitors of PKB.     

X-ray and molecular modelling in fragment-based design of three small quinoline scaffolds for HIV integrase inhibitors

Crystal structures of three small molecular scaffolds based on quinoline, 2-methylquinoline-5,8-dione, 5-hydroxy-quinaldine-6-carboxylic acid and 8-hydroxy-quinaldine-7-carboxylic acid, were characterised. 5-Hydroxy-quinaldine-6-carboxylic acid was co-crystallized with cobalt(II) chloride to form a model of divalent metal cation-ligand interactions for potential HIV integrase inhibitors. Molecular docking into active site of HIV IN was also performed on 1WKN PDB file. Selected ligand-protein interactions have been found specific for active compounds. Studied structures can be used as scaffolds in fragment-based design of new potent drugs.     

Comparative docking studies of CYP1b1 and its PCG-associated mutant forms

Molecular docking has been used to compare and contrast the binding modes of oestradiol with the wild-type and some disease-associated mutant forms of the human CYP1b1 protein. The receptor structures used for docking were derived from molecular dynamics simulations of homology-modelled structures. Earlier studies involving molecular dynamics and principal component analysis indicated that mutations could have a disruptive effect on function, by destabilizing the native properties of the functionally important regions, especially those of the haem-binding and substrate-binding regions, which constitute the site of catalytic activity of the enzyme. In order to gain more insights into the possible differences in substrate-binding and catalysis between the wild-type and mutant proteins, molecular docking studies were carried out. Mutants showed altered protein-ligand interactions compared with the wild-type as a consequence of changes in the geometry of the substrate-binding region and in the position of haem relative to the active site. An important difference in ligand-protein interactions between the wild-type and mutants is the presence of stacking interaction with phenyl residues in the wild-type, which is either completely absent or considerably weaker in mutants. The present study revealed essential differences in the interactions between ligand and protein in wild-type and disease mutants, and helped in understanding the deleterious nature of disease mutations at the level of molecular function.     

SuperStar: comparison of CSD and PDB-based interaction fields as a basis for the prediction of protein-ligand interactions.

SuperStar is an empirical method for identifying interaction sites in proteins, based entirely on the experimental information about non-bonded interactions, present in the IsoStar database. The interaction information in IsoStar is contained in scatterplots, which show the distribution of a chosen probe around structure fragments. SuperStar breaks a template molecule (e.g. a protein binding site) into structural fragments which correspond to those in the scatterplots. The scatterplots are then superimposed on the corresponding parts of the template and converted into a composite propensity map.The original version of SuperStar was based entirely on scatterplots from the CSD. Here, scatterplots based on protein-ligand interactions are implemented in SuperStar, and validated on a test set of 122 X-ray structures of protein-ligand complexes. In this validation, propensity maps are compared with the experimentally observed positions of ligand atoms of comparable types. Although non-bonded interaction geometries in small molecule structures are similar to those found in protein-ligand complexes, their relative frequencies of occurrence are different. Polar interactions are more common in the first class of structures, while interactions between hydrophobic groups are more common in protein crystals. In general, PDB and CSD-based SuperStar maps appear equally successful in the prediction of protein-ligand interactions. PDB-based maps are more suitable to identify hydrophobic pockets, and inherently take into account the experimental uncertainties of protein atomic positions. If the protonation state of a histidine, aspartate or glutamate protein side-chain is known, specific CSD-based maps for that protonation state are preferred over PDB-based maps which represent an ensemble of protonation states.     

fingeRNAt—A novel tool for high-throughput analysis of nucleic acid-ligand interactions

Computational methods play a pivotal role in drug discovery and are widely applied in virtual screening, structure optimization, and compound activity profiling. Over the last decades, almost all the attention in medicinal chemistry has been directed to protein-ligand binding, and computational tools have been created with this target in mind. With novel discoveries of functional RNAs and their possible applications, RNAs have gained considerable attention as potential drug targets. However, the availability of bioinformatics tools for nucleic acids is limited. Here, we introduce fingeRNAt—a software tool for detecting non-covalent interactions formed in complexes of nucleic acids with ligands. The program detects nine types of interactions: (i) hydrogen and (ii) halogen bonds, (iii) cation-anion, (iv) pi-cation, (v) pi-anion, (vi) pi-stacking, (vii) inorganic ion-mediated, (viii) water-mediated, and (ix) lipophilic interactions. However, the scope of detected interactions can be easily expanded using a simple plugin system. In addition, detected interactions can be visualized using the associated PyMOL plugin, which facilitates the analysis of medium-throughput molecular complexes. Interactions are also encoded and stored as a bioinformatics-friendly Structural Interaction Fingerprint (SIFt)—a binary string where the respective bit in the fingerprint is set to 1 if a particular interaction is present and to 0 otherwise. This output format, in turn, enables high-throughput analysis of interaction data using data analysis techniques. We present applications of fingeRNAt-generated interaction fingerprints for visual and computational analysis of RNA-ligand complexes, including analysis of interactions formed in experimentally determined RNA-small molecule ligand complexes deposited in the Protein Data Bank. We propose interaction fingerprint-based similarity as an alternative measure to RMSD to recapitulate complexes with similar interactions but different folding. We present an application of interaction fingerprints for the clustering of molecular complexes. This approach can be used to group ligands that form similar binding networks and thus have similar biological properties. The fingeRNAt software is freely available at https://github.com/n-szulc/fingeRNAt.     

Analysis of mutations in fibroblast growth factor (FGF) and a pathogenic mutation in FGF receptor (FGFR) provides direct evidence for the symmetric two-end model for FGFR dimerization

Two competing models for fibroblast growth factor (FGF) receptor (FGFR) dimerization have recently emerged based on ternary FGF-FGFR-heparin crystal structures. In the symmetric two-end model, heparin promotes dimerization of two FGF-FGFR complexes by stabilizing bivalent interactions of the ligand and receptor through primary and secondary sites and by stabilizing direct receptor-receptor contacts. In the asymmetric model, there are no protein-protein contacts between the two FGF-FGFR complexes, which are bridged solely by heparin. To identify the correct mode of FGFR dimerization, we abolished interactions at the secondary ligand-receptor interaction site, which are observed only in the symmetric two-end model, using site-directed mutagenesis. Cellular studies and real-time binding assays, as well as matrix-assisted laser desorption ionization-time of flight analysis, demonstrate that loss of secondary ligand-receptor interactions results in diminished FGFR activation due to decreased dimerization without affecting FGF-FGFR binding. Additionally, structural and biochemical analysis of an activating FGFR2 mutation resulting in Pfeiffer syndrome confirms the physiological significance of receptor-receptor contacts in the symmetric two-end model and provides a novel mechanism for FGFR gain of function in human skeletal disorders. Taken together, the data validate the symmetric two-end model of FGFR dimerization and argue against the asymmetric model of FGFR dimerization.     

Electron spin resonance study of human alpha 1-acid glycoprotein interaction with a spin labelled steroid.

The interaction of human alpha 1-acid glycoprotein (AAG) with a corticosteroid was studied using nitroxide labeled deoxycorticosterone and electron spin resonance (ESR) spectroscopy. The ESR spectra of the spin labeled steroid in the presence of AAG could be used to characterize the ligand-protein interaction at equilibrium without the need of a separation between bound and free species. An association constant Ka of 6.10(5) M-1 at 20 degrees C and a binding capacity of one site per mole protein were found. ESR spectra recorded at equilibrium at various temperatures allowed the calculation of enthalpy and entropy variations for the steroid-protein interaction; these thermodynamic parameters exhibited a rapid change above 45 degrees C which may be related to a protein conformational modification above this temperature, as detected by circular dichroism study. The ESR spectra width could be used to define a polar character for the spin label environment in the steroid binding site of AAG and to calculate an apparent rotational correlation time of 2.8 x 10(-8) sec for the steroid-protein complex in aqueous solution at 20 degrees C. It can be concluded that spin labeling and ESR methodology is of value in the study of steroid-protein interactions of biological significance above all because it can provide direct physico-chemical information concerning the local environment of the ligand in its binding site at equilibrium.     

Protein-binding properties of a designed steroidal lactam compound

Introducing amide bonds into a steroid nucleus or its side chain may reduce the acute toxicity and enhance the pharmaceutical activity. In this work, a designed steroidal amide compound, named 3β-hydroxy-17-aza-d-homo-5-androsten-17-one (HAAO), was synthesized and identified. The interactions between HAAO and human serum albumin (HSA) were studied by multiple spectroscopic methods and molecular modeling procedures. It was found that HAAO locates in Sudlow’s site I in subdomain IIA of HSA molecules, relying on hydrogen bonds and van der Waals power to form HAAO–HSA complexes at ground state. The number of binding sites, binding constants, enthalpy change (ΔH^θ), Gibbs free energy change (ΔG^θ) and entropy change (ΔS^θ) were calculated at different temperatures based on fluorescence quenching theory and classical thermodynamic equation. The percentages content of the HSA’s secondary structures in presence of HAAO were detected by circular dichroism (CD) spectra and compared with those in no presence of HAAO. In addition, the experimental results of both binding site and conformational change were further confirmed by molecular modeling investigation, in which more details of the binding were visually unfolded. The information provided by the study may be useful for designing novel chemotherapeutic drugs and be helpful both in the early stages of drug discovery and in clinical practice.