Program FlexX Research Articles

Identification of hPXR Modulators via SAR-Based Virtual Screening

Purpose. Human pregnane X receptor (hPXR) has a key role in regulating metabolism of endogenous and exogenous substances. Identification of novel hPXR activators among commercial drugs aids in avoiding drug-drug interactions with future co-administered drugs. Methods. Virtual screening with Structure-Activity Relationship (SAR) models has been applied for identification of novel hPXR activators. Ligand-based modeling was conducted with Discover Studio (DS) 2.1. Bayesian classification models were generated with a training set comprising 177 compound, and were validated with a test set with 145 compounds. The activities of commonly prescribed drugs from SCUT database were predicted with one of the Bayesian models. Cell-based luciferase reporter assay was used for evaluation of chemical-mediated hPXR activation. HepG2 cells were co-transfected with PXR expression vector and CYP2B6-luciferase reporter construct. 0.1% DMSO solution was used as vehicle control while rifampicin as the positive control. The binding mode between an experimental validated hPXR modulators and hPXR were studied by docking a ligand into hPXR binding domain (PDB ID: 1NRL) with programs FlexX and SurFlex. Results. The Bayesian models showed specificity and overall prediction accuracy up to 0.92 and 0.69 for test set compounds. One Bayesian model with specificity of 0.92 was selected to screen the SCUT database and retrieved 113 hits. 17 compounds were chosen for in vitro testing. The luciferase reporter assay confirmed that seven drugs, i.e., fluticasone, nimodipine, nisoldipine, beclomethasone, finasteride, flunisolide, and megestrol were previously unidentified potent or moderate hPXR activators, with 2.7 to 18.5- fold increase in luciferase activity compared to vehicle control. Conclusion. In this study, virtual screening based on SAR models successfully identified seven novel hPXR activators among FDA approved and commonly prescribed drugs. The same approach could be used for identification of activators or inhibitors of other protein targets.

Docking and scoring with alternative side‐chain conformations

We describe a scoring and modeling procedure for docking ligands into protein models that have either modeled or flexible side-chain conformations. Our methodical contribution comprises a procedure for generating new potentials of mean force for the ROTA scoring function which we have introduced previously for optimizing side-chain conformations with the tool IRECS. The ROTA potentials are specially trained to tolerate small-scale positional errors of atoms that are characteristic of (i) side-chain conformations that are modeled using a sparse rotamer library and (ii) ligand conformations that are generated using a docking program. We generated both rigid and flexible protein models with our side-chain prediction tool IRECS and docked ligands to proteins using the scoring function ROTA and the docking programs FlexX (for rigid side chains) and FlexE (for flexible side chains). We validated our approach on the forty screening targets of the DUD database. The validation shows that the ROTA potentials are especially well suited for estimating the binding affinity of ligands to proteins. The results also show that our procedure can compensate for the performance decrease in screening that occurs when using protein models with side chains modeled with a rotamer library instead of using X-ray structures. The average runtime per ligand of our method is 168 seconds on an Opteron V20z, which is fast enough to allow virtual screening of compound libraries for drug candidates.

Identification of Novel Allosteric Regulators of Human‐Erythrocyte Pyruvate Kinase

Erythrocyte pyruvate kinase (PK) is an important glycolytic enzyme, and manipulation of its regulatory behavior by allosteric modifiers is of interest for medicinal purposes. Human-erythrocyte PK was expressed in Rosetta cells and purified on an Ni-NTA column. A search of the small-molecules database of the National Cancer Institute (NCI), using the UNITY software, led to the identification of several compounds with similar pharmacophores as fructose-1,6-bisphosphate (FBP), the natural allosteric activator of the human kinases. The compounds were subsequently docked into the FBP binding site using the programs FlexX and GOLD, and their interactions with the protein were analyzed with the energy-scoring function of HINT. Seven promising candidates, compounds 1-7, were obtained from the NCI, and subjected to kinetics analysis, which revealed both activators and inhibitors of the R-isozyme of PK (R-PK). The allosteric effectors discovered in this study could prove to be lead compounds for developing medications for the treatment of hemolytic anemia, sickle-cell anemia, hypoxia-related diseases, and other disorders arising from erythrocyte PK malfunction.

Flexible Docking of Ligands into Synthetic Receptors Using a Two-Sided Incremental Construction Algorithm

We present a new algorithm for the fast and reliable structure prediction of synthetic receptor-ligand complexes. Our method is based on the protein-ligand docking program FlexX and extends our recently introduced docking technique for synthetic receptors, which has been implemented in the program FlexR. To handle the flexibility of the relevant molecules, we apply a novel docking strategy that uses an adaptive two-sided incremental construction algorithm which incorporates the structural flexibility of both the ligand and synthetic receptor. We follow an adaptive strategy, in which one molecule is expanded by attaching its next fragment in all possible torsion angles, whereas the other (partially assembled) molecule serves as a rigid binding partner. Then the roles of the molecules are exchanged. Geometric filters are used to discard partial conformations that cannot realize a targeted interaction pattern derived in a graph-based precomputation phase. The process is repeated until the entire complex is built up. Our algorithm produces promising results on a test data set comprising 10 complexes of synthetic receptors and ligands. The method generated near-native solutions compared to crystal structures in all but one case. It is able to generate solutions within a couple of minutes and has the potential of being used as a virtual screening tool for searching for suitable guest molecules for a given synthetic receptor in large databases of guests and vice versa.

Design, synthesis and evaluation of novel uracil amino acid conjugates for the inhibition of Trypanosoma cruzi dUTPase

Potential inhibitors of the Trypanosoma cruzi dUTP nucleotidohydrolase were docked into the enzyme using the program FlexX. Compounds that docked selectively were then selected and synthesized using solid phase methodology, giving rise to a novel library of amino acid uracil acetamide compounds which were evaluated for enzyme inhibition and anti-parasitic activity.

An evaluation of automated in silico ligand docking of amino acid ligands to Family C G-protein coupled receptors

Family C G-protein coupled receptors (GPCRs) consist of the metabotropic glutamate receptors (mGluRs), the calcium-sensing receptor (CaSR), the T1R taste receptors, the GABA B receptor, the V2R pheromone receptors, and several chemosensory receptors. A common feature of Family C receptors is the presence of an amino acid binding pocket. The objective of this study was to evaluate the ability of the automatic docking program FlexX to predict the favored amino acid ligand at several Family C GPCRs. The docking process was optimized using the crystal structure of mGluR1 and the 20 amino acids were docked into homology models of the CaSR, the 5.24 chemosensory receptor, and the GPRC6A amino acid receptor. Under optimized docking conditions, glutamate was docked in the binding pocket of mGluR1 with a root mean square deviation of 1.56 angstroms from the co-crystallized glutamate structure and was ranked as the best ligand with a significantly better FlexX score compared to all other amino acids. Ligand docking to a homology model of the 5.24 receptor gave generally correct predictions of the favored amino acids, while the results obtained with models of GPRC6A and the CaSR showed that some of the favored amino acids at these receptors were correctly predicted, while a few other top scoring amino acids appeared to be false positives. We conclude that with certain caveats, FlexX can be successfully used to predict preferred ligands at Family C GPCRs.

Ligand-Induced Conformational Changes: Improved Predictions of Ligand Binding Conformations and Affinities

A computational docking strategy using multiple conformations of the target protein is discussed and evaluated. A series of low molecular weight, competitive, nonpeptide protein tyrosine phosphatase inhibitors are considered for which the x-ray crystallographic structures in complex with protein tyrosine phosphatase 1B (PTP1B) are known. To obtain a quantitative measure of the impact of conformational changes induced by the inhibitors, these were docked to the active site region of various structures of PTP1B using the docking program FlexX. Firstly, the inhibitors were docked to a PTP1B crystal structure cocrystallized with a hexapeptide. The estimated binding energies for various docking modes as well as the RMS differences between the docked compounds and the crystallographic structure were calculated. In this scenario the estimated binding energies were not predictive inasmuch as docking modes with low estimated binding energies corresponded to relatively large RMS differences when aligned with the corresponding crystal structure. Secondly, the inhibitors were docked to their parent protein structures in which they were cocrystallized. In this case, there was a good correlation between low predicted binding energy and a correct docking mode. Thirdly, to improve the predictability of the docking procedure in the general case, where only a single target protein structure is known, we evaluate an approach which takes possible protein side-chain conformational changes into account. Here, side chains exposed to the active site were considered in their allowed rotamer conformations and protein models containing all possible combinations of side-chain rotamers were generated. To evaluate which of these modeled active sites is the most likely binding site conformation for a certain inhibitor, the inhibitors were docked against all active site models. The receptor rotamer model corresponding to the lowest estimated binding energy is taken as the top candidate. Using this protocol, correct inhibitor binding modes could successfully be discriminated from proposed incorrect binding modes. Moreover, the ranking of the estimated ligand binding energies was in good agreement with experimentally observed binding affinities.

Information-based methods in the development of antiparasitic drugs.

The discovery and optimization of antiparasitic compounds has profited by information-based methods newly emerged in the modern drug development process. The generation of computer models enables the cost-efficient and fast computational screening of virtual compound libraries for biologically active molecules. Two sources of information are available: structure-based drug design utilizes information about the disease target. We describe two different computational approaches, realized as the fast, flexible docking program FlexX and as the de novo design program LUDI. Ligand-based drug design, on the other hand, requires the structures and experimental data from biologically active compounds. Parasitic targets and antiparasitic compounds studied by various information-based methods include trypanosomal trypanothione reductase, antiprotozoal bisphosphonates, and trypanosomal glycosomal glyceraldehyde-3-phosphate dehydrogenase.

Sesquiterpene lactones as inhibitors of human neutrophil elastase

Human neutrophil elastase (HNE) is a serine protease that has been implicated in the abnormal turnover of connective tissue proteins and has been described as an important pathogenic factor in several inflammatory diseases such as rheumatoid arthritis or cystic fibrosis. Here we investigated 17 sesquiterpene lactones (SLs) for their ability to inhibit human neutrophil elastase in an in vitro assay. Podachaenin was the most active compound with an IC 50 value of 7 μM. SLs do not covalently bind to the amino acids of the catalytic triad, thus differing from other elastase inhibitors with a lactone moiety. In contrast to most other biological activities of SLs HNE inhibition is not mediated by α,β-unsaturated carbonyl functions. Ligand binding calculations using the X-ray structure of HNE and the program FlexX revealed structural elements which are a prerequisite for their inhibitory activity.

Methodology and Problems of Protein‐Ligand Docking: Case Study of Dihydroorotate Dehydrogenase, Thymidine Kinase, and Phosphodiesterase 4

The docking methodology was applied to three different therapeutically interesting enzymes: human dihydroorotate dehydrogenase (DHODH), Herpes simplex virus type I thymidine kinase (HSV1 TK) and human phosphodiesterase 4 (PDE4). Programs FlexX, AutoDock and DOCK where used. The three targets represent three distinct cases. For DHODH and HSV1 TK, the binding modes of substrate and inhibitors within the active site are known, while the binding orientation of cAMP within PDE4 has been solely hypothesized. Active site of DHODH is mainly hydrophobic and the binding mode of the inhibitor brequinar was used as a template for evaluating the docking strategies. The presence of cofactors revealed to be crucial for the definition of the docking site. The HSV1 TK active site is small and polar and contains crystal water molecules and ATP. Docking of thymidine and aciclovir (ACV) within the active site was analyzed by keeping or removing water molecules. It showed the crucial role of water in predicting the binding of pyrimidines and purines. The crystal structure of PDE4 contains magnesium and zinc cations as well as catalytic water molecule but no ligand. Several docking experiments of cAMP and rolipram were performed and the results showed clear‐cut dependence between the ligand orientation and the presence of metals in the active site. All three cases show specific problems of the docking methodology, depending on the character of the active site.

Detailed analysis of scoring functions for virtual screening.

We present a comprehensive study of the performance of fast scoring functions for library docking using the program FlexX as the docking engine. Four scoring functions, among them two recently developed knowledge-based potentials, are evaluated on seven target proteins whose binding sites represent a wide range of size, form, and polarity. The results of these calculations give valuable insight into strengths and weaknesses of current scoring functions. Furthermore, it is shown that a well-chosen combination of two of the tested scoring functions leads to a new, robust scoring scheme with superior performance in virtual screening.

Chance Favors the Prepared Mind - From Serendipity to Rational Drug Design

Accidental discoveries always played an important role in science, especially in the search for new drugs. Several examples of serendipitous findings, leading to therapeutically useful drugs, are presented and discussed. Captopril, an antihypertensive Angiotensin-converting enzyme inhibitor, was the first drug that could be derived from a structural model of a protein. Dorzolamide, a Carboanhydrase inhibitor for the treatment of glaucoma, and the HIV protease inhibitors Saquinavir, Indinavir, Ritonavir, and Nelfinavir are further examples of therapeutically used drugs from structure-based design. More enzyme inhibitors, e.g. the anti-influenza drugs Zanamivir and GS 4104, are in clinical development. In the absence of a protein 3D structure, the 3D structures of certain ligands may be used for rational design. This approach is exemplified by the design of specifically acting integrin receptor antagonists. In the last years, combinatorial and computational approaches became important methods for rational drug design. SAR by NMR searches for low-affinity ligands that bind to proximal subsites of an enzyme; linkage with an appropriate tether produces nanomolar inhibitors. The de novo design program LUDI and the docking program FlexX are tools for the computer-aided design of protein ligands. Work is in progress to combine such approaches to strategies for combinatorial drug design.Dans les champs de l'obsérvation le hasard ne favorise que les ésprits préparés. Louis Pasteur (1822–1895)

CASP2 experiences with docking flexible ligands using FlexX.

We have applied our docking program FlexX to all eight CASP2 targets involving protein complexes with small ligands. Of the seven targets that were kept in the CASP2 experiment, we could solve two. We found important parts of the solution in four other examples, and were unsuccessful on the remaining example. This paper discusses all predictions in detail. Each of our prediction runs took just a few minutes of computer time on a standard workstation and could thus be demonstrated in real time at the CASP meeting. We believe that this speed is the prime strength of our program FlexX. In quality, our predictions are competitive with those produced by other predictors. The experiment showed that possible objectives of improvement of the FlexX program are to incorporate relevant aspects of receptor flexibility, deal with water molecules in the receptor pocket, allow for a postoptimization to refine favorable complexes, and improve the scoring function.

CASP2 experiences with docking flexible ligands using FLEXX

We have applied our docking program FlexX to all eight CASP2 targets involving protein complexes with small ligands. Of the seven targets that were kept in the CASP2 experiment, we could solve two. We found important parts of the solution in four other examples, and were unsuccessful on the remaining example. This paper discusses all predictions in detail. Each of our prediction runs took just a few minutes of computer time on a standard workstation and could thus be demonstrated in real time at the CASP meeting. We believe that this speed is the prime strength of our program FlexX. In quality, our predictions are competitive with those produced by other predictors. The experiment showed that possible objectives of improvement of the FlexX program are to incorporate relevant aspects of receptor flexibility, deal with water molecules in the receptor pocket, allow for a postoptimization to refine favorable complexes, and improve the scoring function.