Thiosquaramide-Based Supramolecular Polymers: Aromaticity Gain in a Switched Mode of Self-Assembly.

Despite a growing understanding of factors that drive monomer self-assembly to form supramolecular polymers, the effects of aromaticity gain have been largely ignored. Herein, we document the aromaticity gain in two different self-assembly modes of squaramide-based bolaamphiphiles. Importantly, O → S substitution in squaramide synthons resulted in supramolecular polymers with increased fiber flexibility and lower degrees of polymerization. Computations and spectroscopic experiments suggest that the oxo- and thiosquaramide bolaamphiphiles self-assemble into "head-to-tail" versus "stacked" arrangements, respectively. Computed energetic and magnetic criteria of aromaticity reveal that both modes of self-assembly increase the aromatic character of the squaramide synthons, giving rise to stronger intermolecular interactions in the resultant supramolecular polymer structures. These examples suggest that both hydrogen-bonding and stacking interactions can result in increased aromaticity upon self-assembly, highlighting its relevance in monomer design.

Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods.

Computational methods for docking small molecules to proteins are prominent in drug discovery. There are hundreds, if not thousands, of documented examples-and several pertinent cases within our research program. Fifteen years ago, our first docking-guided drug design project yielded nanomolar metalloproteinase inhibitors and illustrated the potential of structure-based drug design. Subsequent applications of docking programs to the design of integrin antagonists, BACE-1 inhibitors, and aminoglycosides binding to bacterial RNA demonstrated that available docking programs needed significant improvement. At that time, docking programs primarily considered flexible ligands and rigid proteins. We demonstrated that accounting for protein flexibility, employing displaceable water molecules, and using ligand-based pharmacophores improved the docking accuracy of existing methods-enabling the design of bioactive molecules. The success prompted the development of our own program, Fitted, implementing all of these aspects. The primary motivation has always been to respond to the needs of drug design studies; the majority of the concepts behind the evolution of Fitted are rooted in medicinal chemistry projects and collaborations. Several examples follow: (1) Searching for HDAC inhibitors led us to develop methods considering drug-zinc coordination and its effect on the pKa of surrounding residues. (2) Targeting covalent prolyl oligopeptidase (POP) inhibitors prompted an update to Fitted to identify reactive groups and form bonds with a given residue (e.g., a catalytic residue) when the geometry allows it. Fitted-the first fully automated covalent docking program-was successfully applied to the discovery of four new classes of covalent POP inhibitors. As a result, efficient stereoselective syntheses of a few screening hits were prioritized rather than synthesizing large chemical libraries-yielding nanomolar inhibitors. (3) In order to study the metabolism of POP inhibitors by cytochrome P450 enzymes (CYPs)-for toxicology studies-the program Impacts was derived from Fitted and helped us to reveal a complex metabolism with unforeseen stereocenter isomerizations. These efforts, combined with those of other docking software developers, have strengthened our understanding of the complex drug-protein binding process while providing the medicinal chemistry community with useful tools that have led to drug discoveries. In this Account, we describe our contributions over the past 15 years-within their historical context-to the design of drug candidates, including BACE-1 inhibitors, POP covalent inhibitors, G-quadruplex binders, and aminoglycosides binding to nucleic acids. We also remark the necessary developments of docking programs, specifically Fitted, that enabled structure-based design to flourish and yielded multiple fruitful, rational medicinal chemistry campaigns.

Aromatic Gain in a Supramolecular Polymer.

The synergy of aromatic gain and hydrogen bonding in a supramolecular polymer is explored. Partially aromatic bis(squaramide) bolaamphiphiles were designed to self-assemble through a combination of hydrophobic, hydrogen-bonding, and aromatic effects into stiff, high-aspect-ratio fibers. UV and IR spectroscopy show electron delocalization and geometric changes within the squaramide ring indicative of strong hydrogen bonding and aromatic gain of the monomer units. The aromatic contribution to the interaction energy was further supported computationally by nucleus-independent chemical shift (NICS) and harmonic oscillator model of aromaticity (HOMA) indices, demonstrating greater aromatic character upon polymerization: at least 30% in a pentamer. The aromatic gain-hydrogen bonding synergy results in a significant increase in thermodynamic stability and a striking difference in aggregate morphology of the bis(squaramide) bolamphiphile compared to isosteres that cannot engage in this effect.

Integrating medicinal chemistry, organic/combinatorial chemistry, and computational chemistry for the discovery of selective estrogen receptor modulators with Forecaster, a novel platform for drug discovery.

As part of a large medicinal chemistry program, we wish to develop novel selective estrogen receptor modulators (SERMs) as potential breast cancer treatments using a combination of experimental and computational approaches. However, one of the remaining difficulties nowadays is to fully integrate computational (i.e., virtual, theoretical) and medicinal (i.e., experimental, intuitive) chemistry to take advantage of the full potential of both. For this purpose, we have developed a Web-based platform, Forecaster, and a number of programs (e.g., Prepare, React, Select) with the aim of combining computational chemistry and medicinal chemistry expertise to facilitate drug discovery and development and more specifically to integrate synthesis into computer-aided drug design. In our quest for potent SERMs, this platform was used to build virtual combinatorial libraries, filter and extract a highly diverse library from the NCI database, and dock them to the estrogen receptor (ER), with all of these steps being fully automated by computational chemists for use by medicinal chemists. As a result, virtual screening of a diverse library seeded with active compounds followed by a search for analogs yielded an enrichment factor of 129, with 98% of the seeded active compounds recovered, while the screening of a designed virtual combinatorial library including known actives yielded an area under the receiver operating characteristic (AU-ROC) of 0.78. The lead optimization proved less successful, further demonstrating the challenge to simulate structure activity relationship studies.

Platinum(II) phenanthroimidazoles for targeting telomeric G-quadruplexes.

A rationally designed progression of phenanthroimidazole platinum(II) complexes were examined for their ability to target telomere-derived intramolecular G-quadruplex DNA. Through the use of circular dichroism, fluorescence displacement assays, and molecular modeling we show that these complexes template and stabilize G-quadruplexes from sequences based on the human telomeric repeat (TTAGGG)(n). The greatest stabilization was observed for the p-chlorophenyl derivative 6((G4)DC(50) =0.31 µM). We also show that the G-quadruplex binding complexes are able to inhibit telomerase activity through a modified telomerase repeat amplification protocol (TRAP-LIG assay). Preliminary cell studies show that complex 6 is preferentially cytotoxic toward cancer over normal cell lines, indicating its potential use in cancer therapy.

Quantifying interactions between G-quadruplex DNA and transition-metal complexes.

Telomerase inhibition through guanine quadruplex sequestration by small-molecule drugs is of great current interest as an anticancer strategy. G-quadruplexes (GQs) can be formed at the guanine-rich sequences found at the end of the telomere. They possess a large electron-rich pi-surface which is favorable for the binding of electron-poor small molecules. Small molecules binding to GQs can sequester the telomere ends and inhibit the enzyme telomerase, which is expressed in cancer cells and absent in normal somatic cells. Transition-metal complexes present a myriad of geometries and numerous ligand coordination environments and allow for modular syntheses for development of compound libraries to target GQs. We have demonstrated the size of the pi-surface, binding selectivity and affinity of phenanthroimidazole platinum (II) complexes [PtPIX(en)](2+)2PF (6) (-) (X = naphthyl, phenyl and en = ethylenediamine) and metallosupramolecular complexes [Pt(4,4'-bpy)(en)] (4) (8+) 8PF (6) (-) (where bpy = bipyridine) to GQs can be readily tuned and assayed through a number of biophysical techniques.

Docking ligands into flexible and solvated macromolecules. 5. Force-field-based prediction of binding affinities of ligands to proteins.

We report herein our efforts in the development of three empirical scoring functions with application in protein-ligand docking. A first scoring function was developed from 209 crystal structures of protein-ligand complexes and a second one from 946 cross-docked complexes. Tuning of the coefficients for the different terms making up these functions was performed by an iterative approach to optimize the correlations between observed activities and calculated scores. A third scoring function was developed from libraries of known actives and decoys docked to six different protein conformational ensembles. In the latter case, the tuning of the coefficients was performed so as to optimize the area under the curve of a receiver operating characteristic (ROC) for the discrimination of actives and inactives. The newly developed scoring functions were next assessed on independent sets of protein-ligand complexes for their ability to predict binding affinities and to discriminate actives from inactives. In the first validation the first function, which was trained on active compounds only, performed as well as other commonly used ones. On a high-throughput virtual screening validation on five protein conformational ensembles, the third scoring function that included data from inactive compounds performed significantly better. This validation showed that the inclusion of data from inactive compounds is critical for performance in virtual high-throughput screening applications.

Docking ligands into flexible and solvated macromolecules. 4. Are popular scoring functions accurate for this class of proteins?

In our previous report, we investigated the impact of protein flexibility and the presence of water molecules on the pose-prediction accuracy of major docking programs. To complete these investigations, we report herein a study of the impact of these two aspects on the accuracy of scoring functions. To this effect, we developed two sets of protein/ligand complexes made up of ligands cross-docked or cocrystallized with a large variety of proteins, featuring bridging water molecules and demonstrating protein flexibility. Efforts were made to reduce the correlation between the molecular weights of the selected ligands and their binding affinities, a major bias in some previously reported benchmark sets. Using these sets, 18 available scoring functions have been assessed for their accuracy to predict binding affinities and to rank-order compounds by their affinity to cocrystallized proteins. This study confirmed the good and similar accuracy of Xscore, GlideScore, DrugScore(CSD), GoldScore, PLP1, ChemScore, RankScore, and the eHiTS scoring function. Our next investigations demonstrated that most of the assessed scoring functions were much less accurate when the correct protein conformation was not provided. This study also revealed that considering the water molecules for scoring does not greatly affect the accuracy. Finally, this work sheds light on the high correlation between scoring functions and the poor increase in accuracy one can expect from consensus scoring.

A platinum supramolecular square as an effective G-quadruplex binder and telomerase inhibitor.

In this contribution, we report that a self-assembled platinum molecular square [Pt(en)(4,4'-dipyridyl)]4 can act as an efficient G-quadruplex binder and telomerase inhibitor. Molecular modeling studies show that the square arrangement of the four bipyridyl ligands, the highly electropositive nature of the overall complex, as well as hydrogen bonding interactions between the ethylenediamine ligands and phosphates of the DNA backbone all contribute to the observed strong binding affinity to the G-quadruplex. Through thermal denaturation studies with duplex and quadruplex FRET probes and enzymatic assays, we demonstrate that this platinum square strongly binds to G-quadruplexes and can act as an inhibitor of telomerase. This study thus shows the potential of supramolecular self-assembly to readily generate scaffolds of unique geometries for effective targeting of G-quadruplexes and for the ultimate development of selective antitumor therapies.

Docking ligands into flexible and solvated macromolecules. 2. Development and application of fitted 1.5 to the virtual screening of potential HCV polymerase inhibitors.

HCV NS5B polymerase is a validated target for the treatment of hepatitis C, known to be one of the most challenging enzymes for docking programs. In order to improve the low accuracy of existing docking methods observed with this challenging enzyme, we have significantly modified and updated F itted 1.0, a recently reported docking program, into F itted 1.5. This enhanced version is now applicable to the virtual screening of compound libraries and includes new features such as filters and pharmacophore- or interaction-site-oriented docking. As a first validation, F itted 1.5 was applied to the testing set previously developed for F itted 1.0 and extended to include hepatitis C virus (HCV) polymerase inhibitors. This first validation showed an increased accuracy as well as an increase in speed. It also shows that the accuracy toward HCV polymerase is better than previously observed with other programs. Next, application of F itted 1.5 to the virtual screening of the Maybridge library seeded with known HCV polymerase inhibitors revealed its ability to recover most of these actives in the top 5% of the hit list. As a third validation, further biological assays uncovered HCV polymerase inhibition for selected Maybridge compounds ranked in the top of the hit list.

Evaluation of docking programs for predicting binding of Golgi alpha-mannosidase II inhibitors: a comparison with crystallography.

Golgi alpha-mannosidase II (GMII), a zinc-dependent glycosyl hydrolase, is a promising target for drug development in anti-tumor therapies. Using X-ray crystallography, we have determined the structure of Drosophila melanogaster GMII (dGMII) complexed with three different inhibitors exhibiting IC50's ranging from 80 to 1000 microM. These structures, along with those of seven other available dGMII/inhibitor complexes, were then used as a basis for the evaluation of seven docking programs (GOLD, Glide, FlexX, AutoDock, eHiTS, LigandFit, and FITTED). We found that small inhibitors could be accurately docked by most of the software, while docking of larger compounds (i.e., those with extended aromatic cycles or long aliphatic chains) was more problematic. Overall, Glide provided the best docking results, with the most accurately predicted binding around the active site zinc atom. Further evaluation of Glide's performance revealed its ability to extract active compounds from a benchmark library of decoys.

Docking ligands into flexible and solvated macromolecules. 1. Development and validation of FITTED 1.0.

We report the development and validation of a novel suite of programs, FITTED 1.0, for the docking of flexible ligands into flexible proteins. This docking tool is unique in that it can deal with both the flexibility of macromolecules (side chains and main chains) and the presence of bridging water molecules while treating protein/ligand complexes as realistically dynamic systems. This software relies on a genetic algorithm to account for the flexibility of the two molecules as well as the location of bridging water molecules. In addition, FITTED 1.0 features a novel application of a switching function to retain or displace key water molecules from the protein-ligand complexes. Two independent modules, ProCESS and SMART, were developed to set up the proteins and the ligands prior to the docking stage. Validation of the accuracy of the software was achieved via the application of FITTED 1.0 to the docking of inhibitors of HIV-1 protease, thymidine kinase, trypsin, factor Xa, and MMP to their respective proteins.