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Anna Vulpetti

Publications and source records attributed to Anna Vulpetti.

13 recordsLinked to original sources

NMR-based quality control approach for the identification of false positives and false negatives in high throughput screening.

The quality of the data generated in a high throughput screening (HTS) run is fundamental for selecting bona fide inhibitors and for ensuring the capture of the full richness of inhibitors present in a chemical library. For this purpose a quality control filter based on three one dimensional (1D) proton NMR experiments is proposed. The approach called SPAM (Solubility, Purity and Aggregation of the Molecule) Filter requires the acquisition of a 1D reference spectrum, a WaterLOGSY spectrum and/or a selective longitudinal relaxation filter spectrum for the identified hits dissolved in aqueous solution and in the presence of a water soluble reference molecule. This palette of experiments permits the rapid characterization of the identity, purity, solubility and aggregation state of the active compound. This knowledge is crucial for deriving accurate IC(50) and K(1) values of the inhibitors, for identifying false negatives and for detecting promiscuous inhibitors. Only compounds that pass through the SPAM Filter can be considered as starting points for medicinal chemistry efforts directed toward lead optimization. Examples of this approach in the identification of false positives in a screening run against the enzyme thymidine phosphorylase (TP) and the rescue of a false negative in a screening run against the Ser/Thr kinase AKT1 are presented.

Algorithms↗

3-Amino-1,4,5,6-tetrahydropyrrolo[3,4-c]pyrazoles: a new class of CDK2 inhibitors.

We have recently reported about a new class of Aurora-A inhibitors based on a bicyclic tetrahydropyrrolo[3,4-c]pyrazole scaffold. Here we describe the synthesis and early expansion of CDK2/cyclin A-E inhibitors belonging to the same chemical class. Synthesis of the compounds was accomplished using a solution-phase protocol amenable to rapid parallel expansion. Compounds with nanomolar activity in the biochemical assay and able to efficiently inhibit CDK2-mediated tumor cell proliferation have been obtained.

Antineoplastic Agents↗

Structure-based drug design to the discovery of new 2-aminothiazole CDK2 inhibitors.

N-(5-Bromo-1,3-thiazol-2-yl)butanamide (compound 1) was found active (IC50=808 nM) in a high throughput screening (HTS) for CDK2 inhibitors. By exploiting crystal structures of several complexes between CDK2 and inhibitors and applying structure-based drug design (SBDD), we rapidly discovered a very potent and selective CDK2 inhibitor 4-[(5-isopropyl-1,3-thiazol-2-yl)amino] benzenesulfonamide (compound 4, IC50=20 nM). The syntheses, structure-based analog design, kinases inhibition data and X-ray crystallographic structures of CDK2/inhibitor complexes are reported.

Amino Acid Sequence↗

Virtual screening to enrich a compound collection with CDK2 inhibitors using docking, scoring, and composite scoring models.

Docking programs can generate subsets of a compound collection with an increased percentage of actives against a target (enrichment) by predicting their binding mode (pose) and affinity (score), and retrieving those with the highest scores. Using the QXP and GOLD programs, we compared the ability of six single scoring functions (PLP, Ligscore, Ludi, Jain, ChemScore, PMF) and four composite scoring models (Mean Rank: MR, Rank-by-Vote: Vt, Bayesian Statistics: BS and PLS Discriminant Analysis: DA) to separate compounds that are active against CDK2 from inactives. We determined the enrichment for the entire set of actives (IC50 < 10 microM) and for three activity subsets. In all cases, the enrichment for each subset was lower than for the entire set of actives. QXP outperformed GOLD at pose prediction, but yielded only moderately better enrichments. Five to six scoring functions yielded good enrichments with GOLD poses, while typically only two worked well with QXP poses. For each program, two scoring functions generally performed better than the others (Ligscore2 and Ludi for GOLD; QXP and Jain for QXP). Composite scoring functions yielded better results than single scoring functions. The consensus approaches MR and Vt worked best when separating micromolar inhibitors from inactives. The statistical approaches BS and DA, which require training data, performed best when distinguishing between low and high nanomolar inhibitors. The key observation that all hit rate profiles for all four activity intervals for all scoring schemes for both programs are significantly better than random, is evidence that docking can be successfully applied to enrich compound collections.

Adenosine Triphosphate↗

3-Aminopyrazole inhibitors of CDK2/cyclin A as antitumor agents. 2. Lead optimization.

Inhibitors of cyclin-dependent kinases (CDK) such as CDK2/cyclin A-E are currently undergoing clinical trials to verify their potential as new anticancer agents. In a previous article we described the lead discovery process of a 3-aminopyrazole class of CDK2/cyclin A-E inhibitors. The endpoint of this process was PNU-292137, a compound endowed with in vivo antitumor activity in a mouse tumor xenograft model. We optimized this lead compound to improve some physicochemical properties, notably solubility and plasma protein binding. This lead optimization process brought us to the discovery of (2S)-N-(5-cyclopropyl-1H-pyrazol-3-yl)-2-[4-(2-oxo-1-pyrrolidinyl)phenyl]propanamide (PHA-533533, 13), a compound with a balanced activity vs druglike profile. Compound 13 inhibited CDK2/cyclin A with a K(i) of 31 nM, counteracting tumor cell proliferation of different cell lines with an IC(50) in the submicromolar range. Solubility was improved more than 10 times over the starting lead, while plasma protein binding was decreased from 99% to 74%. With exploitation of this globally enhanced in vitro profile, 13 was more active than PNU-292137 in vivo in the A2780 xenograft model showing a tumor growth inhibition of 70%. Proof of mechanism of action was obtained in vivo by immunohistochemical analysis of tumor slices of 13-treated vs untreated animals.

Animals↗

Potent and selective Aurora inhibitors identified by the expansion of a novel scaffold for protein kinase inhibition.

Potent and selective Aurora kinase inhibitors were identified from the combinatorial expansion of the 1,4,5,6-tetrahydropyrrolo[3,4-c]pyrazole bi-cycle, a novel and versatile scaffold designed to target the ATP pocket of protein kinases. The most potent compound reported in this study had an IC(50) of 0.027 microM in the enzymatic assay for Aur-A inhibition and IC(50)s between 0.05 microM and 0.5 microM for the inhibition of proliferation of different tumor cell lines.

Adenosine Triphosphate↗

Benzodipyrazoles: a new class of potent CDK2 inhibitors.

The synthesis and the preliminary expansion of this new class of CDK2 inhibitors are presented. The synthesis was accomplished using a solution-phase protocol amenable to rapid parallel expansion and suitable to be scaled-up in view of possible lead development. Following a medicinal chemistry program aimed at improving cell permeability and selectivity, a series of compounds with nanomolar activity in the biochemical assay and able to efficiently inhibit tumor cell proliferation has been obtained.

CDC2-CDC28 Kinases↗

An analysis of the binding modes of ATP-competitive CDK2 inhibitors as revealed by X-ray structures of protein-inhibitor complexes.

CDK2 is an attractive target for the design of new therapeutic antitumor agent. Numerous CDK2 inhibitors have been discovered and their crystallographic structures either in complex with CDK2 or CDK2/Cyclin A have been published. This review aims to summarize the publicly available structural characterization of CDK2/(Cyclin A) -- ligand complexes and to highlight the similarities among the binding modes of structurally diverse inhibitors.

Adenosine Triphosphate↗

3-Aminopyrazole inhibitors of CDK2/cyclin A as antitumor agents. 1. Lead finding.

Abnormal proliferation mediated by disruption of the normal cell cycle mechanisms is a hallmark of virtually all cancer cells. Compounds targeting complexes between cyclin-dependent kinases (CDK) and cyclins, such as CDK2/cyclin A and CDK2/cyclin E, and inhibiting their kinase activity are regarded as promising antitumor agents to complement the existing therapies. From a high-throughput screening effort, we identified a new class of CDK2/cyclin A/E inhibitors. The hit-to-lead expansion of this class is described. X-ray crystallographic data of early compounds in this series, as well as in vitro testing funneled for rapidly achieving in vivo efficacy, led to a nanomolar inhibitor of CDK2/cyclin A (N-(5-cyclopropyl-1H-pyrazol-3-yl)-2-(2-naphthyl)acetamide (41), PNU-292137, IC50 = 37 nM) with in vivo antitumor activity (TGI > 50%) in a mouse xenograft model at a dose devoid of toxic effects.

Acetamides↗

Sequence and structural analysis of kinase ATP pocket residues.

Protein kinases represent one of the largest known families of enzymes. Most kinases bind ATP and most synthetic kinase inhibitors are ATP-competitive, which makes selectivity a potential problem. However, despite the high sequence similarity in the ATP binding pocket, several groups including ours have been able to develop highly potent and selective ATP-competitive inhibitors. To systematically aid the design of specific inhibitors in our protein kinase projects, we aligned all known three-dimensional structures and all known sequences of human protein kinases. We identified a set of 38 residues that make up the ATP pocket and analyzed the variability among these residues. The most variable residues in the ATP pocket are targeted to design specificity into inhibitors in our various kinase projects.

Adenosine Triphosphate↗

Novel scoring functions comprising QXP, SASA, and protein side-chain entropy terms.

Novel scoring functions that predict the affinity of a ligand for its receptor have been developed. They were built with several statistical tools (partial least squares, genetic algorithms, neural networks) and trained on a data set of 100 crystal structures of receptor-ligand complexes, with affinities spanning 10 log units. The new scoring functions contain both descriptors generated by the QXP docking program and new descriptors that were developed in-house. These new descriptors are based on solvent accessible surface areas and account for conformational entropy changes and desolvation effects of both ligand and receptor upon binding. The predictive r(2) values for a test set of 24 complexes are in the 0.712-0.741 range and RMS prediction errors in the 1.09-1.16 log K(d) range. Inclusion of the new descriptors led to significant improvements in affinity prediction, compared to scoring functions based on QXP descriptors alone. However, the QXP descriptors by themselves perform better in binding mode prediction. The performance of the linear models is comparable to that of the neural networks. The new functions perform very well, but they still need to be validated as universal tools for the prediction of binding affinity.

Algorithms↗

Assessment of docking poses: interactions-based accuracy classification (IBAC) versus crystal structure deviations.

Six docking programs (FlexX, GOLD, ICM, LigandFit, the Northwestern University version of DOCK, and QXP) were evaluated in terms of their ability to reproduce experimentally observed binding modes (poses) of small-molecule ligands to macromolecular targets. The accuracy of a pose was assessed in two ways: First, the RMS deviation of the predicted pose from the crystal structure was calculated. Second, the predicted pose was compared to the experimentally observed one regarding the presence of key interactions with the protein. The latter assessment is referred to as interactions-based accuracy classification (IBAC). In a number of cases significant discrepancies were found between IBAC and RMSD-based classifications. Despite being more subjective, the IBAC proved to be a more meaningful measure of docking accuracy in all these cases.

Crystallography, X-Ray↗

Structure-based approaches to improve selectivity: CDK2-GSK3beta binding site analysis.

An evaluation and comparison of two different approaches, GRID/CPCA and GRIND/CPCA (CPCA = consensus principal component analysis; GRIND = GRid-INdependent Descriptors), suitable for visualizing the structural differences between related proteins is presented. Ten crystal structures of CDK2/cyclin A and GSK3beta solved in-house with different inhibitors were compared with the aim of highlighting regions that could be potential sites for gaining selectivity for CDK2 versus GSK3beta. The analyses pointed out remarkable differences in the backs of the CDK2-GSK3beta ATP binding pockets that guided the optimization toward a selective benzodipyrazole CDK2 inhibitor. The gain in selectivity can be associated with the two main differences in the ATP pocket between the enzymes. Phe80 of CDK2, the so-called gatekeeper residue often exploited for the design of kinase selective ligands, is replaced by a leucine in GSK3beta, and Ala144 is replaced by a cysteine. As a consequence of these mutations, CDK2 has a less elongated and less flat buried region at the back of the ATP pocket.

Adenosine Triphosphate↗