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PubMed2000

Quasi-orthogonal basis sets of molecular graph descriptors as a chemical diversity measure

In the pharmaceutical industry, the virtual screening of combinatorial libraries is used to rationally select compounds for biological testing from databases of hundreds of thousands of compounds. In addition to structural descriptors, such as fingerprints and pharmacophores, the application of relatively simple structural descriptors traditionally used in quantitative structure-activity studies offers speed and efficiency for rapidly measuring the molecular diversity of such collections. We explore new topological indices computed from the molecular graph as potential structural descriptors for the characterization of molecular diversity. A database of 2000 compounds randomly selected from the National Cancer Institute AIDS database was used to measure the intercorrelation of the descriptors. The initial collection of 240 structural descriptors was reduced to several quasi-orthogonal sets of up to 9 descriptors, using different thresholds for the maximum intercorrelation coefficient.

Journal Article↗
PubMed2004

NMR-based characterization of phenothiazines as a RNA binding scaffold.

Phenothiazines were identified by virtual screening as promising ligands for HIV-1 TAR RNA and A-site ribosomal RNA, and binding in each case was verified experimentally. Consequently, since phenothiazines generally possess high bioavailability and low toxicity, we used several NMR techniques to explore the binding characteristics of acetopromazine with a total of five different RNA constructs: four as potential drug targets plus one control RNA construct. Acetopromazine was able to bind to various internal bulges and terminal loops containing both purines and pyrimidines, but no binding could be detected with double-stranded RNA or tetraloops. Dissociation constants determined via NMR varied from 0.27 to >3 mM. Analysis of differential saturation transfer difference (STD) NMR effects of acetopromazine suggests that the phenothiazine moiety has the closest contact to the binding sites of TAR and A-site RNA while the flexible N,N-dimethylpropylamino side chain contributes less to binding. NMR studies on A-site ribosomal RNA binding by six commercially available phenothiazines, while too few to establish a true structure-activity relationship, revealed a distinct dependence on aromatic ring and side chain substituents. Substituted phenothiazines have low molecular weight, are not highly charged, and have an inherent affinity for irregular tertiary RNA folds, suggesting that they can serve as a novel scaffold for constructing RNA-binding ligands.

Binding Sites↗
PubMed2002

Structure-based design and characterization of novel platforms for ricin and shiga toxin inhibition.

Ribosome inhibiting proteins, RIPs, are a widespread family of toxic enzymes. Ricin is a plant toxin used as a poison and biological warfare agent; shiga toxin is a homologue expressed by pathogenic strains of E. coli. There is interest in creating effective antidote inhibitors to this class of enzymes. RIPs act by binding and hydrolyzing a specific adenine base from rRNA. Previous virtual screens revealed that pterins could bind in the specificity pocket of ricin and inhibit the enzyme. In this paper we explore a range of compounds that could serve as better platforms for inhibitor design. This establishes the importance of key hydrogen bond donors and acceptors for active-site complementarity. 8-Methyl-9-oxoguanine is a soluble compound that has the best inhibitory properties of any platform tested. The X-ray structure of this complex revealed that the inhibitor binds in an unexpected way that provides insight for future design. Several inhibitors of ricin were also shown to be inhibitors of shiga toxin, suggesting this program has the potential to develop effective antidotes to an important form of food poisoning.

Binding Sites↗
PubMed2002

Molecular dynamics and free energy analyses of cathepsin D-inhibitor interactions: insight into structure-based ligand design.

In this study, we compare the calculated and experimental binding free energies for a combinatorial library of inhibitors of cathepsin D (CatD), an aspartyl protease. Using a molecular dynamics (MD)-based, continuum solvent method (MM-PBSA), we are able to reproduce the experimental binding affinity for a set of seven inhibitors with an average error of ca. 1 kcal/mol and a correlation coefficient of 0.98. By comparing the dynamical conformations of the inhibitors complexed with CatD with the initial conformations generated by CombiBuild (University of California, San Francisco, CA, 1995), we have found that the docking conformation observed in an X-ray structure of one peptide inhibitor bound to CatD (Proc. Natl. Acad. Sci. U.S.A. 1993, 90, 6796-6800) is in good agreement with our MD simulation. However, the DOCK scoring function, based on intermolecular van der Waals and electrostatics, using a distance-dependent dielectric constant (J. Comput. Chem. 1992, 13, 505-524), poorly reproduces the trend of experimental binding affinity for these inhibitors. Finally, the use of PROFEC (J. Comput.-Aided Mol. Des. 1998, 12, 215-227) analysis allowed us to identify two possible substitutions to improve the binding of one of the better inhibitors to CatD. This study offers hope that current methods of estimating the free energy of binding are accurate enough to be used in a multistep virtual screening protocol.

Algorithms↗
PubMed2001

Novel lead generation through hypothetical pharmacophore three-dimensional database searching: discovery of isoflavonoids as nonsteroidal inhibitors of rat 5 alpha-reductase.

A hypothetical pharmacophore of 5 alpha-reductase inhibitors was generated and served as a template in virtual screening. When the pharmacophore was used, eight isoflavone derivatives were characterized as novel potential nonsteroidal inhibitors of rat 5 alpha-reductase. This investigation has demonstrated a practical approach toward the development of lead compounds through a hypothetic pharmacophore via three-dimensional database searching.

3-Oxo-5-alpha-Steroid 4-Dehydrogenase↗
PubMed2003

Synthesis and biological evaluation of non-peptidic cyclophilin ligands.

Peptidylprolyl isomerase cyclophilins play critical roles in a variety of biological processes. Recent findings that cyclophilins are present at high levels in the CNS and that cyclosporin A may possess neuroprotective/neurotrophic effects have prompted us to search for nonimmunosuppressant small molecule cyclophilin ligands. To this end, we report the lead identification through "virtual screening" and the synthesis of our first series of non-peptidic cyclophilin ligands, along with the preliminary biological results.

Animals↗
PubMed2003

Non-peptide angiotensin II receptor antagonists: chemical feature based pharmacophore identification.

Chemical feature based pharmacophore models were elaborated for angiotensin II receptor subtype 1 (AT(1)) antagonists using both a quantitative and a qualitative approach (Catalyst HypoGen and HipHop algorithms, respectively). The training sets for quantitative model generation consisted of 25 selective AT(1) antagonists exhibiting IC(50) values ranging from 1.3 nM to 150 microM. Additionally, a qualitative pharmacophore hypothesis was derived from multiconformational structure models of the two highly active AT(1) antagonists 4u (IC(50) = 0.2 nM) and 3k (IC(50) = 0.7 nM). In the case of the quantitative model, the best pharmacophore hypothesis consisted of a five-features model (Hypo1: seven points, one hydrophobic aromatic, one hydrophobic aliphatic, a hydrogen bond acceptor, a negative ionizable function, and an aromatic plane function). The best qualitative model consisted of seven features (Hypo2: 11 points, two aromatic rings, two hydrogen bond acceptors, a negative ionizable function, and two hydrophobic functions). The obtained pharmacophore models were validated on a wide set of test molecules. They were shown to be able to identify a range of highly potent AT(1) antagonists, among those a number of recently launched drugs and some candidates presently undergoing clinical tests and/or development phases. The results of our study provide confidence for the utility of the selected chemical feature based pharmacophore models to retrieve structurally diverse compounds with desired biological activity by virtual screening.

Acrylates↗
PubMed2003

Generation of predictive pharmacophore models for CCR5 antagonists: study with piperidine- and piperazine-based compounds as a new class of HIV-1 entry inhibitors.

Predictive pharmacophore models were developed for a large series of piperidine- and piperazine-based CCR5 antagonists as anti-HIV-1 agents reported by Schering-Plough Research Institute in recent years. The pharmacophore models were generated using a training set consisting of 25 carefully selected antagonists based on well documented criteria. The activity spread, expressed in K(i), of training set molecules was from 0.1 to 1300 nM. The most predictive pharmacophore model (hypothesis 1), consisting of five features, namely, two hydrogen bond acceptors and three hydrophobic, had a correlation (r) of 0.920 and a root mean square of 0.879, and the cost difference between null cost and fixed cost was 44.46 bits. The model was cross-validated by randomizing the data using the CatScramble technique. The results confirmed that the pharmacophore models generated from the test set were not due to chance correlation. The best model (hypothesis 1) was validated using test set molecules (total of 78) and performed well in classifying active and inactive molecules correctly. The model was further validated by mapping onto it a diverse set of six CCR5 antagonists identified by five different pharmaceutical companies. The best model correctly predicted these compounds as being highly active. These multiple validation approaches provide confidence in the utility of the predictive pharmacophore model developed in this study as a 3D query tool in virtual screening to retrieve new chemical entities as potent CCR5 antagonists. The model can also be used in predicting biological activities of compounds prior to undertaking their costly synthesis.

Algorithms↗
PubMed2004

Evaluation of docking performance: comparative data on docking algorithms.

Docking molecules into their respective 3D macromolecular targets is a widely used method for lead optimization. However, the best known docking algorithms often fail to position the ligand in an orientation close to the experimental binding mode. It was reported recently that consensus scoring enhances the hit rates in a virtual screening experiment. This methodology focused on the top-ranked pose, with the underlying assumption that the orientation/conformation of the docked compound is the most accurate. In an effort to eliminate the scoring function bias, and assess the ability of the docking algorithms to provide solutions similar to the crystallographic modes, we investigated the most known docking programs and evaluated all of the resultant poses. We present the results of an extensive computational study in which five docking programs (FlexX, DOCK, GOLD, LigandFit, Glide) were investigated against 14 protein families (69 targets). Our findings show that some algorithms perform consistently better than others, and a correspondence between the nature of the active site and the best docking algorithm can be found.

Algorithms↗
PubMed2003

Discovery of a potent and selective protein kinase CK2 inhibitor by high-throughput docking.

To assess the potential of protein kinase CK2 as a target for developing new antitumor agents, we have undertaken a search for inhibitors of this enzyme. As part of this effort, we report here the discovery of the potent and selective CK2 inhibitor (5-oxo-5,6-dihydroindolo[1,2-a]quinazolin-7-yl)acetic acid. We identified this inhibitor of a novel structural type by high-throughput docking of our corporate compound collection in the ATP binding site of a homology model of human CK2, using an appropriate protocol. The synthesis of the inhibitor as well as that of related analogues whose CK2 inhibitory activities give support to the binding mode proposed by the docking program is described. The results obtained suggest that virtual screening of a 3D database by molecular docking is a useful approach for lead finding provided that adapted postdocking filtering and reranking procedures are applied to the primary hit list.

Acetates↗
PubMed2004

2-Anilino-4-(thiazol-5-yl)pyrimidine CDK inhibitors: synthesis, SAR analysis, X-ray crystallography, and biological activity.

Following the identification through virtual screening of 4-(2,4-dimethyl-thiazol-5-yl)pyrimidin-2-ylamines as moderately potent inhibitors of cyclin-dependent kinase-2 (CDK2), a CDK inhibitor analogue program was initiated. The first aims were to optimize potency and to evaluate the cellular mode of action of lead candidate molecules. Here the synthetic chemistry, the structure-guided design approach, and the structure-activity relationships (SARs) that led to the discovery of 2-anilino-4-(thiazol-5-yl)pyrimidine ATP-antagonistic CDK2 inhibitors, many with very low nM K(i)s against CDK2, are reported. Furthermore, X-ray crystal structures of four representative analogues from our chemical series in complex with CDK2 are presented, and these structures are used to rationalize the observed biochemical SARs. Finally results are reported that show, using the most potent CDK2 inhibitor compound from the current series, that the observed antiproliferative and proapoptotic effects are consistent with cellular CDK2 and CDK9 inhibition.

Aniline Compounds↗
PubMed2004

Three-dimensional quantitative structure-activity relationship analysis of a set of Plasmodium falciparum dihydrofolate reductase inhibitors using a pharmacophore generation approach.

A 3D pharmacophore model able to quantitatively predict inhibition constants was derived for a series of inhibitors of Plasmodium falciparum dihydrofolate reductase (PfDHFR), a validated target for antimalarial therapy. The data set included 52 inhibitors, with 23 of these comprising the training set and 29 an external test set. The activity range, expressed as Ki, of the training set molecules was from 0.3 to 11 300 nM. The 3D pharmacophore, generated with the HypoGen module of Catalyst 4.7, consisted of two hydrogen bond donors, one positive ionizable feature, one hydrophobic aliphatic feature, and one hydrophobic aromatic feature and provided a 3D-QSAR model with a correlation coefficient of 0.954. Importantly, the type and spatial location of the chemical features encoded in the pharmacophore were in full agreement with the key binding interactions of PfDHFR inhibitors as previously established by molecular modeling and crystallography of enzyme-inhibitor complexes. The model was validated using several techniques, namely, Fisher's randomization test using CatScramble, leave-one-out test to ensure that the QSAR model is not strictly dependent on one particular compound of the training set, and activity prediction in an external test set of compounds. In addition, the pharmacophore was able to correctly classify as active and inactive the dihydrofolate reductase and aldose reductase inhibitors extracted from the MDDR database, respectively. This test was performed in order to challenge the predictive ability of the pharmacophore with two classes of inhibitors that target very different binding sites. Molecular diversity of the data sets was finally estimated by means of the Tanimoto approach. The results obtained provide confidence for the utility of the pharmacophore in the virtual screening of libraries and databases of compounds to discover novel PfDHFR inhibitors.

Aldehyde Reductase↗
PubMed2005

Unveiling the full potential of flexible receptor docking using multiple crystallographic structures.

One of the current challenges in docking studies is the inclusion of receptor flexibility. This is crucial because the binding sites of many therapeutic targets sample a wide range of conformational states, which has major consequences on molecular recognition. In this paper, we make use of very large sets of X-ray structures of cyclin dependent kinase 2 (CDK2) and heat shock protein 90 (HSP90) to assess the performance of flexible receptor docking in binding-mode prediction and virtual screening experiments. Flexible receptor docking performs much better than rigid receptor docking in the former application. Regarding the latter, we observe a significant improvement in the prediction of binding affinities, but owing to an increase in the number of false positives, this is not translated into better hit rates. A simple scoring scheme to correct this limitation is presented. More importantly, pitfalls inherent to flexible receptor docking have been identified and guidelines are presented to avoid them.

Adenosine Triphosphate↗
PubMed2005

Validation and use of the MM-PBSA approach for drug discovery.

The MM-PBSA approach has become a popular method for calculating binding affinities of biomolecular complexes. Published application examples focus on small test sets and few proteins and, hence, are of limited relevance in assessing the general validity of this method. To further characterize MM-PBSA, we report on a more extensive study involving a large number of ligands and eight different proteins. Our results show that applying the MM-PBSA energy function to a single, relaxed complex structure is an adequate and sometimes more accurate approach than the standard free energy averaging over molecular dynamics snapshots. The use of MM-PBSA on a single structure is shown to be valuable (a) as a postdocking filter in further enriching virtual screening results, (b) as a helpful tool to prioritize de novo design solutions, and (c) for distinguishing between good and weak binders (DeltapIC(50) > or = 2-3), but rarely to reproduce smaller free energy differences.

Binding Sites↗
PubMed2004

"Lead hopping". Validation of topomer similarity as a superior predictor of similar biological activities.

Two extensive studies quantifying the ability of topomer shape similarity to forecast a variety of biological similarities are described. In a prospective trial of "lead hopping", using topomer similarity for virtual screening and queries from the patent literature, biological assays of 308 selected compounds (representing 0.03% of those available, per assay type) yielded 11 successful "lead hops" in the 13 assays attempted. The hit rate averaged over all assays was 39% ("activity"defined as inhibition > or =20% at 10 microM), significantly greater than an unexpectedly high negative control hit rate of 15%. The average "Tanimoto 2D fingerprint similarity" between query and "lead hop" structures (0.36) was little more than the Tanimoto similarity between random drug-like structures. Topomer shape and Tanimoto 2D fingerprint similarities were also compared retrospectively, in their tendencies to concentrate together potential and actual drugs reported to belong to the same "activity class", for twenty classes. Among the most similar 3% of structures (corresponding to "> or =0.85 Tanimoto" for these structures), an average of 62% of the topomer similar selection possessed a near neighbor belonging to the same activity class, roughly a one-third superiority over the "Tanimoto > or = 0.85" selection containing 48% actives in avoiding false positives. Conversely, the least similar 75% of structures contained 0.3% actives for topomer similarity vs 1.0% actives for Tanimoto 2D fingerprint similarity, a 3-fold superiority for topomers in avoiding false negatives.

Computing Methodologies↗
PubMed2004

An in silico approach to discovering novel inhibitors of human sirtuin type 2.

Type 2 human sirtuin (SIRT2) is a NAD(+)-dependent cytoplasmic protein that is colocalized with HDAC6 on microtubules. SIRT2 has been shown to deacetylate alpha-tubulin and to control mitotic exit in the cell cycle. To date, some small molecular inhibitors of SIRT2 have been identified; however, more inhibitors are still needed to improve the understanding of SIRT2 biological function and to discover its possible therapeutic indications. In this paper, an in silico identification procedure is described for discovering novel SIRT2 inhibitors. Molecular modeling and virtual screening were utilized to find potential compounds, which were then subjected to experimental tests for their SIRT2 inhibitory activity. Five of the 15 compounds tested in vitro showed inhibitory activity toward SIRT2, yielding a hit ratio of 33% in a micromolar level and thus demonstrating the usefulness of this procedure in finding new bioactive compounds. Two of the five compounds yielded in vitro IC(50) values of 56.7 and 74.3 microM, and these can be considered as novel inhibitors of SIRT2. On the basis of our results, a phenol moiety on the active compound is suggested to be important for SIRT2 inhibitory activity. This phenol group, together with a hydrophobic moiety and hydrogen-bonding features, is suggested to form an active SIRT2 pharmacophore.

Anthraquinones↗
PubMed2006

Evaluation of 3-carboxy-4(1H)-quinolones as inhibitors of human protein kinase CK2.

Due to the emerging role of protein kinase CK2 as a molecule that participates not only in the development of some cancers but also in viral infections and inflammatory failures, small organic inhibitors of CK2, besides application in scientific research, may have therapeutic significance. In this paper, we present a new class of CK2 inhibitors-3-carboxy-4(1H)-quinolones. This class of inhibitors has been selected via receptor-based virtual screening of the Otava compound library. It was revealed that the most active compounds, 5,6,8-trichloro-4-oxo-1,4-dihydroquinoline-3-carboxylic acid (7) (IC(50) = 0.3 microM) and 4-oxo-1,4-dihydrobenzo[h]quinoline-3-carboxylic acid (9) (IC(50) = 1 microM), are ATP competitive (K(i) values are 0.06 and 0.28 microM, respectively). Evaluation of the inhibitors on seven protein kinases shows considerable selectivity toward CK2. According to theoretical calculations and experimental data, a structural model describing the key features of 3-carboxy-4(1H)-quinolones responsible for tight binding to CK2 active site has been developed.

Adenosine Triphosphate↗
PubMed2005

Improving binding mode predictions by docking into protein-specifically adapted potential fields.

The development of a protein-specifically adapted objective function for docking is described. Structural and energetic information about known protein-ligand complexes is exploited to tailor knowledge-based potentials using a "reverse", protein-based CoMFA-type (=AFMoC) approach. That way, effects due to protein flexibility and information about multiple solvation schemes can be implicitly incorporated. Compared to the application of AFMoC for binding affinity predictions, a Shannon entropy based column filtering of the descriptor matrix and the capping of adapted repulsive potentials within the binding site have turned out to be crucial for the success of this method. The new developed approach (AFMoC(obj)) was validated on a data set of 66 HIV-1 protease inhibitors, for which experimental structural information was available. Convincingly, for ligands with up to 20 rotatable bonds, in more than 75% of all cases a binding mode below 2 A rmsd has been identified on the first scoring rank when AFMoC(obj)-based potentials were used as the objective function in AutoDock. With respect to nonadapted DrugScore or AutoDock fields, the binding mode prediction accuracy was significantly improved by 14%. Noteworthy, very similar results were obtained for training and test set compounds, demonstrating the strength and robustness of this method. Implications of our findings for binding affinity predictions and its usage in virtual screening are further discussed.

Binding Sites↗