New insights from molecular dynamic simulation studies of the multiple binding modes of a ligand with G-quadruplex DNA

G-quadruplexes are higher-order DNA and RNA structures formed from guanine-rich sequences. These structures have recently emerged as a new class of potential molecular targets for anticancer drugs. An understanding of the three-dimensional interactions between small molecular ligands and their G-quadruplex targets in solution is crucial for rational drug design and the effective optimization of G-quadruplex ligands. Thus far, rational ligand design has been focused mainly on the G-quartet platform. It should be noted that small molecules can also bind to loop nucleotides, as observed in crystallography studies. Hence, it would be interesting to elucidate the mechanism underlying how ligands in distinct binding modes influence the flexibility of G-quadruplex. In the present study, based on a crystal structure analysis, the models of a tetra-substituted naphthalene diimide ligand bound to a telomeric G-quadruplex with different modes were built and simulated with a molecular dynamics simulation method. Based on a series of computational analyses, the structures, dynamics, and interactions of ligand-quadruplex complexes were studied. Our results suggest that the binding of the ligand to the loop is viable in aqueous solutions but dependent on the particular arrangement of the loop. The binding of the ligand to the loop enhances the flexibility of the G-quadruplex, while the binding of the ligand simultaneously to both the quartet and the loop diminishes its flexibility. These results add to our understanding of the effect of a ligand with different binding modes on G-quadruplex flexibility. Such an understanding will aid in the rational design of more selective and effective G-quadruplex binding ligands.     

Rapid protein-ligand costructures using chemical shift perturbations

Structure-based drug discovery requires the iterative determination of protein-ligand costructures in order to improve the binding affinity and selectivity of potential drug candidates. In general, X-ray and NMR structure determination methods are time consuming and are typically the limiting factor in the drug discovery process. The application of molecular docking simulations to filter and evaluate drug candidates has become a common method to improve the throughput and efficiency of structure-based drug design. Unfortunately, molecular docking methods suffer from common problems that include ambiguous ligand conformers or failure to predict the correct docked structure. A rapid approach to determine accurate protein-ligand costructures is described based on NMR chemical shift perturbation (CSP) data routinely obtained using 2D 1H-15N HSQC spectra in high-throughput ligand affinity screens. The CSP data is used to both guide and filter AutoDock calculations using our AutoDockFilter program. This method is demonstrated for 19 distinct protein-ligand complexes where the docked conformers exhibited an average rmsd of 1.17 +/- 0.74 A relative to the original X-ray structures for the protein-ligand complexes.     

Binding to an RNA aptamer changes the charge distribution and conformation of malachite green

RNA plays a central role in many biological processes and is therefore an important target for drug development. In recent years an increasing wealth of structural and functional information about RNA-ligand complexes has been obtained using in vitro selected RNAs (aptamers). However, all those studies focused on structure and changes of the nucleic acid and mostly considered the ligand as a rigid target. To develop a detailed picture of ligand structure and dynamics in RNA-small molecule complexes, the malachite green binding aptamer was studied. Isotopically labeled ligand in complex with RNA was analyzed by NMR spectroscopy in solution. The surprisingly asymmetric changes in the (13)C chemical shift of the ligand methyl groups indicate that the dye undergoes changes in its conformation and charge distribution upon binding. The role of the RNA electrostatic field in this interaction was explored using ab initio calculations of the ligand structure and charge distribution. The results indicate that the uneven charge distribution in the RNA binding pocket provides a major contribution to the driving force of the ligand structural changes. The observation that not only the RNA adapts to the ligand, in what is called adaptive binding, but that the ligand itself also undergoes conformational changes ("induced fit") is crucial for the rational design of RNA ligands and for understanding the properties of RNA-ligand complexes.     

Rhodium(I) and iridium(I) complexes of pyrazolyl-N-heterocyclic carbene ligands

Several Rh(I) and Ir(I) complexes containing an N-heterocyclic carbene-pyrazolyl chelate ligand have been synthesised. Determination of the single-crystal X-ray structure of the Ir(I) complex showed a novel binding mode with the iridium centre coordinated to two ligands via two carbene donors in preference to one ligand forming the entropically favoured chelate. The hydrogenation activity of several of these complexes was investigated along with that of previously synthesised Rh(I) and Ir(I) complexes containing an analogous phosphine-pyrazolyl chelate.     

SOS-NMR: a saturation transfer NMR-based method for determining the structures of protein-ligand complexes

An NMR-based alternative to traditional X-ray crystallography and NMR methods for structure-based drug design is described that enables the structure determination of ligands complexed to virtually any biomolecular target regardless of size, composition, or oligomeric state. The method utilizes saturation transfer difference (STD) NMR spectroscopy performed on a ligand complexed to a series of target samples that have been deuterated everywhere except for specific amino acid types. In this way, the amino acid composition of the ligand-binding site can be defined, and, given the three-dimensional structure of the protein target, the three-dimensional structure of the protein-ligand complex can be determined. Unlike earlier NMR methods for solving the structures of protein-ligand complexes, no protein resonance assignments are necessary. Thus, the approach has broad potential applications--especially in cases where X-ray crystallography and traditional NMR methods have failed to produce structural data. The method is called SOS-NMR for structural information using Overhauser effects and selective labeling and is validated on two protein-ligand complexes: FKBP complexed to 2-(3'-pyridyl)-benzimidazole and MurA complexed to uridine diphosphate N-acetylglucosamine.     

Self-recognition based on atropoisomerism with new chiral bidentate ligands and copper(I)

A new family of atropoisomeric bidentate ligands that have a dissymmetric benzimidazole-pyridine binding site has been synthesized. Aromatic rings, that is, naphthyl, tolyl and cumyl, were introduced in order to fine tune the complexation properties of the ligands. The tetrahedral copper(I) complexes L2Cu were prepared and the structure of the complex with the naphthyl-substituted ligand was established by X-ray diffraction. The behavior of the L2Cu complexes in solution was studied by 1H NMR spectroscopy. With the most crowded cumyl-derived ligand, ligand self-recognition based on chirality occured: 95% of the complex was present in solution as a racemate RRdelta/SSlambda, the heterochiral RSdelta/SRlambda isomers represented only 5 % of the mixture, and the RRlambda/SSdelta isomers were not detected. Owing to lower steric repulsions within the other L2Cu complexes (i.e., with the naphthyl- and tolyl-based ligands) the homorecognition is less pronounced, as diastereomeric excesses of 6 and 26% were measured, respectively.     

Standard free energy of releasing a localized water molecule from the binding pockets of proteins: double-decoupling method

Localized water molecules in the binding pockets of proteins play an important role in noncovalent association of proteins and small drug compounds. At times, the dominant contribution to the binding free energy comes from the release of localized water molecules in the binding pockets of biomolecules. Therefore, to quantify the energetic importance of these water molecules for drug design purposes, we have used the double-decoupling approach to calculate the standard free energy of tying up a water molecule in the binding pockets of two protein complexes. The double-decoupling approach is based on the underlying principle of statistical thermodynamics. We have calculated the standard free energies of tying up the water molecule in the binding pockets of these complexes to be favorable. These water molecules stabilize the protein-drug complexes by interacting with the ligands and binding pockets. Our results offer ideas that could be used in optimizing protein-drug interactions, by designing ligands that are capable of targeting localized water molecules in protein binding sites. The resulting free energy of ligand binding could benefit from the potential free energy gain accompanying the release of these water molecules. Furthermore, we have examined the theoretical background of the double-decoupling method and its connection to the molecular dynamics thermodynamic integration techniques.     

Using model complexes to augment and advance metalloproteinase inhibitor design

The tetrahedral zinc complex [(Tp(Ph,Me))ZnOH] (Tp(Ph,Me) = hydrotris(3,5-phenylmethylpyrazolyl)borate) was combined with 2-thenylmercaptan, ethyl 4,4,4-trifluoroacetoacetate, salicylic acid, salicylamide, thiosalicylic acid, thiosalicylamide, methyl salicylate, methyl thiosalicyliate, and 2-hydroxyacetophenone to form the corresponding [(Tp(Ph,Me))Zn(ZBG)] complexes (ZBG = zinc-binding group). X-ray crystal structures of these complexes were obtained to determine the mode of binding for each ZBG, several of which had been previously studied with SAR by NMR (structure-activity relationship by nuclear magnetic resonance) as potential ligands for use in matrix metalloproteinase inhibitors. The [(Tp(Ph,Me))Zn(ZBG)] complexes show that hydrogen bonding and donor atom acidity have a pronounced effect on the mode of binding for this series of ligands. The results of these studies give valuable insight into how ligand protonation state and intramolecular hydrogen bonds can influence the coordination mode of metal-binding proteinase inhibitors. The findings here suggest that model-based approaches can be used to augment drug discovery methods applied to metalloproteins and can aid second-generation drug design.     

Stereochemical influence of the ligand on the structure of manganese complexes: implications for catalytic epoxidations

Manganese complexes of the ligand HphoxCOOR (R=H or Me) have been synthesized and characterized by X-ray analysis, ESI-MS, ligand-field spectroscopy, electrochemistry, and paramagnetic 1H NMR. The ligands, chirally pure or racemic, influence the structures of the complexes formed. Manganese(III) complexes of the ligand HphoxCOOMe are square-pyramidal or octahedral with two ligands bound in a trans fashion in the solid state. The racemic ligand (RS-HphoxCOOMe) as well as the enantiopure ligand (R-HphoxCOOMe) forms manganese complexes with similar solid-state structures. Ligand-exchange reactions occur in solution giving rise to meso complexes as confirmed by ESI-MS and deuteration studies. The manganese(III) complex of R-HphoxCOOH is octahedral, with two dianionic ligands bound in a fac-cct fashion in a tridentate manner. The manganese(III) complex of RS-HphoxCOOH is also octahedral with two dianionic ligands now bound in a trans fashion in a didentate manner and with two water molecules occupying axial sites. The paramagnetic 1H NMR spectra of the complexes have been interpreted on the basis of the relaxation times with the help of the inversion-recovery pulse technique. The binding of imidazole with the metal center depends on the chirality of the ligands in the metal complexes of HphoxCOOMe. Imidazole coordination was found to occur with the metal complex that contains two ligands with the same chirality (R and R) (R-1), while no imidazole coordination was found upon reaction with the metal complex that contains two ligands with opposite chirality (R and S) (RS-1). Epoxidation reactions of various alkenes with H2O2 as the oxidant reveal that the complexes give turnover numbers in the range of 10-35, the epoxide being the major product. The catalytic activity depends on the additives used, and a clear base effect is observed. The turnover numbers have been found to be higher in the complexes where no binding of N-Meim is observed. The latter fact unambiguously shows that imidazole binding is not a prerequisite for higher turnover numbers, in contrast to the Mn-Schiff base catalysts.     

Iridium(III) Sensitisers and Energy Upconversion: The Influence of Ligand Structure upon TTA-UC Performance

Six substituted ligands based upon 2-(naphthalen-1-yl)quinoline-4-carboxylate and 2-(naphthalen-2-yl)quinoline-4-carboxylate have been synthesised in two steps from a range of commercially available isatin derivatives. These species are shown to be effective cyclometallating ligands for Ir^III, yielding complexes of the form [Ir(C^N)₂(bipy)]PF₆ (where C^N=cyclometallating ligand; bipy=2,2′-bipyridine). X-ray crystallographic studies on three examples demonstrate that the complexes adopt a distorted octahedral geometry wherein a cis-C,C and trans-N,N coordination mode is observed. Intraligand torsional distortions are evident in all cases. The Ir^III complexes display photoluminescence in the red part of the visible region (668–693 nm), which is modestly tuneable through the ligand structure. The triplet lifetimes of the complexes are clearly influenced by the precise structure of the ligand in each case. Supporting computational (DFT) studies suggest that the differences in observed triplet lifetime are likely due to differing admixtures of ligand-centred versus MLCT character instilled by the facets of the ligand structure. Triplet–triplet annihilation upconversion (TTA-UC) measurements demonstrate that the complexes based upon the 1-naphthyl derived ligands are viable photosensitisers with upconversion quantum efficiencies of 1.6–6.7 %.     

Development of biologically active compounds by combining 3D QSAR and structure-based design methods

One of the major challenges in computational approaches to drug design is the accurate prediction of the binding affinity of novel biomolecules. In the present study an automated procedure which combines docking and 3D-QSAR methods was applied to several drug targets. The developed receptor-based 3D-QSAR methodology was tested on several sets of ligands for which the three-dimensional structure of the target protein has been solved – namely estrogen receptor, acetylcholine esterase and protein-tyrosine-phosphatase 1B. The molecular alignments of the studied ligands were determined using the docking program AutoDock and were compared with the X-ray structures of the corresponding protein-ligand complexes. The automatically generated protein-based ligand alignment obtained was subsequently taken as basis for a comparative field analysis applying the GRID/GOLPE approach. Using GRID interaction fields and applying variable selection procedures, highly predictive models were obtained. It is expected that concepts from receptor-based 3D QSAR will be valuable tools for the analysis of high-throughput screening as well as virtual screening data     

Nanodiscs for INPHARMA NMR Characterization of GPCRs: Ligand Binding to the Human A2A Adenosine Receptor

G-protein-coupled-receptors (GPCRs) are of fundamental importance for signal transduction through cell membranes. This makes them important drug targets, but structure-based drug design (SBDD) is still hampered by the limitations for structure determination of unmodified GPCRs. We show that the interligand NOEs for pharmacophore mapping (INPHARMA) method can provide valuable information on ligand poses inside the binding site of the unmodified human A_2A adenosine receptor reconstituted in nanodiscs. By comparing experimental INPHARMA spectra with back-calculated spectra based on ligand poses obtained from molecular dynamics simulations, a complex structure for A_2AR with the low-affinity ligand 3-pyrrolidin-1-ylquinoxalin-2-amine was determined based on the X-ray structure of ligand ZM-241,358 in complex with a modified A_2AR.     

What Can We Learn from Molecular Recognition in Protein–Ligand Complexes for the Design of New Drugs?

The understanding of noncovalent interactions in protein–ligand complexes is essential in modern biochemistry and should contribute toward the discovery of new drugs. In the present review, we summarize recent work aimed at a better understanding of the physical nature of molecular recognition in protein–ligand complexes and also at the development and application of new computational tools that exploit our current knowledge on structural and energetic aspects of protein–ligand interactions in the design of novel ligands. These approaches are based on the exponentially growing amount of information about the geometry of protein structures and the properties of small organic molecules exposed to a structured molecular environment. The various contributions that determine the binding affinity of ligands toward a particular receptor are discussed. Their putative binding site conformations are analyzed, and some predictions are attempted. The similarity of ligands is examined with respect to their recognition properties. This information is used to understand and propose binding modes. In addition, an overview of the existing methods for the design and selection of novel protein ligands is given.     

The role of human in the loop: lessons from D3R challenge 4

The rapid development of new machine learning techniques led to significant progress in the area of computer-aided drug design. However, despite the enormous predictive power of new methods, they lack explainability and are often used as black boxes. The most important decisions in drug discovery are still made by human experts who rely on intuitions and simplified representation of the field. We used D3R Grand Challenge 4 to model contributions of human experts during the prediction of the structure of protein–ligand complexes, and prediction of binding affinities for series of ligands in the context of absence or abundance of experimental data. We demonstrated that human decisions have a series of biases: a tendency to focus on easily identifiable protein–ligand interactions such as hydrogen bonds, and neglect for a more distributed and complex electrostatic interactions and solvation effects. While these biases still allow human experts to compete with blind algorithms in some areas, the underutilization of the information leads to significantly worse performance in data-rich tasks such as binding affinity prediction.     

Use of MCSS to design small targeted libraries: application to picornavirus ligands.

Computational methods were used to design structure-based combinatorial libraries of antipicornaviral capsid-binding ligands. The multiple copy simultaneous search (MCSS) program was employed to calculate functionality maps for many diverse functional groups for both the poliovirus and rhinovirus capsid structures in the region of the known drug binding pocket. Based on the results of the MCSS calculations, small combinatorial libraries consisting of 10s or 100s of three-monomer compounds were designed and synthesized. Ligand binding was demonstrated by a noncell-based mass spectrometric assay, a functional immuno-precipitation assay, and crystallographic analysis of the complexes of the virus with two of the candidate ligands. The P1/Mahoney poliovirus strain was used in the experimental studies. A comparison showed that the MCSS calculations had correctly identified the observed binding site for all three monomer units in one ligand and for two out of three in the other ligand. The correct central monomer position in the second ligand was reproduced in calculations in which the several key residues lining the pocket were allowed to move. This study validates the computational methodology. It also illustrates that subtle changes in protein structure can lead to differences in docking results and points to the importance of including target flexibility, as well as ligand flexibility, in the design process.     

De novo ligand design with explicit water molecules: an application to bacterial neuraminidase

Most computer-aided drug design methods ignore the presence of crystallographically-determined water molecules in the binding site of a target protein. In this paper, our de novo ligand design methods are applied to the X-ray crystal structure of bacterial neuraminidase in the presence of some selected water molecules. We have found that, for this particular protein, the complete removal of all bound water molecules leads to difficulties in generating any potential ligands if the unsatisfied hydrogen-bonding sitepoints left by removing these water molecules are to be satisfied by a ligand. As more of the crystallographically determined water molecules are allowed in the binding site, it becomes much easier to generate ligands in larger numbers and with wider chemical diversity. This example shows that, in some cases, bound water molecules can be more accessible for hydrogen bonding to an incoming ligand than the actual protein binding sitepoints associated with them. From the point of view of de novo ligand design, water molecules can thus act as versatile amphiprotic hydrogen-bonding sitepoints and reduce the conformational constraints of a particular binding site.     

Direct calculation of the binding free energies of FKBP ligands

Direct calculations of the absolute free energies of binding for eight ligands to FKBP protein were performed using the Fujitsu BioServer massively parallel computer. Using the latest version of the general assisted model building with energy refinement (AMBER) force field for ligand model parameters and the Bennett acceptance ratio for computing free-energy differences, we obtained an excellent linear fit between the calculated and experimental binding free energies. The rms error from a linear fit is 0.4 kcal/mol for eight ligand complexes. In comparison with a previous study of the binding energies of these same eight ligand complexes, these results suggest that the use of improved model parameters can lead to more predictive binding estimates, and that these estimates can be obtained with significantly less computer time than previously thought. These findings make such direct methods more attractive for use in rational drug design.     

MCDOCK: A Monte Carlo simulation approach to the molecular docking problem

Prediction of the binding mode of a ligand (a drug molecule) to its macromolecular receptor, or molecular docking, is an important problem in rational drug design. We have developed a new docking method in which a non-conventional Monte Carlo (MC) simulation technique is employed. A computer program, MCDOCK, was developed to carry out the molecular docking operation automatically. The current version of the MCDOCK program (version 1.0) allows for the full flexibility of ligands in the docking calculations. The scoring function used in MCDOCK is the sum of the interaction energy between the ligand and its receptor, and the conformational energy of the ligand. To validate the MCDOCK method, 19 small ligands, the binding modes of which had been determined experimentally using X-ray diffraction, were docked into their receptor binding sites. To produce statistically significant results, 20 MCDOCK runs were performed for each protein–ligand complex. It was found that a significant percentage of these MCDOCK runs converge to the experimentally observed binding mode. The root-mean-square (rms) of all non-hydrogen atoms of the ligand between the predicted and experimental binding modes ranges from 0.25 to 1.84 Å for these 19 cases. The computational time for each run on an SGI Indigo2/R10000 varies from less than 1 min to 15 min, depending upon the size and the flexibility of the ligands. Thus MCDOCK may be used to predict the precise binding mode of ligands in lead optimization and to discover novel lead compounds through structure-based database searching.     

Discovery of small molecule inhibitors of ubiquitin-like poxvirus proteinase I7L using homology modeling and covalent docking approaches

Essential for viral replication and highly conserved among poxviridae, the vaccinia virus I7L ubiquitin-like proteinase (ULP) is an attractive target for development of smallpox antiviral drugs. At the same time, the I7L proteinase exemplifies several interesting challenges from the rational drug design perspective. In the absence of a published I7L X-ray structure, we have built a detailed 3D model of the I7L ligand binding site (S2-S2' pocket) based on exceptionally high structural conservation of this site in proteases of the ULP family. The accuracy and limitations of this model were assessed through comparative analysis of available X-ray structures of ULPs, as well as energy based conformational modeling. The 3D model of the I7L ligand binding site was used to perform covalent docking and VLS of a comprehensive library of about 230,000 available ketone and aldehyde compounds. Out of 456 predicted ligands, 97 inhibitors of I7L proteinase activity were confirmed in biochemical assays ( approximately 20% overall hit rate). These experimental results both validate our I7L ligand binding model and provide initial leads for rational optimization of poxvirus I7L proteinase inhibitors. Thus, fragments predicted to bind in the prime portion of the active site can be combined with fragments on non-prime side to yield compounds with improved activity and specificity.