Development and characterization of a new inhibitor of heme oxygenase activity for cancer treatment.

Heme oxygenase-1 (HO-1, HMOX1) degrades pro-oxidant heme into carbon monoxide (CO), ferrous ions (Fe2+) and biliverdin. The enzyme exerts multiple cytoprotective functions associated with the promotion of angiogenesis and counteraction of the detrimental effects of cellular stress which are crucial for the survival of both normal and tumor cells. Accordingly, in many tumor types, high expression of HO-1 correlates with poor prognosis and resistance to treatment, i.e. chemotherapy, suggesting inhibition of HO-1 as a possible antitumor approach. At the same time, the lack of selective and well-profiled inhibitors of HO-1 determines the unmet need for new modulators of this enzyme, with the potential to be used in either adjuvant therapy or as the stand-alone targeted therapeutics. In the current study, we provided novel inhibitors of HO-1 and validated the effect of pharmacological inhibition of HO activity by the imidazole-based inhibitor (SLV-11199) in human pancreatic (PANC-1) and prostate (DU-145) cancer cell lines. We demonstrated potent inhibition of HO activity in vitro and showed associated anticancer effectiveness of SLV-11199. Treatment with the tested compound led to decreased cancer cell viability and clonogenic potential. It has also sensitized the cancer cells to chemotherapy. In PANC-1 cells, diminished HO activity resulted in down-regulation of pro-angiogenic factors like IL-8. Mechanistic investigations revealed that the treatment with SLV-11199 decreased cell migration and inhibited MMP-1 and MMP-9 expression. Moreover, it affected mesenchymal phenotype by regulating key modulators of the epithelial to mesenchymal transition (EMT) signalling axis. Finally, F-actin cytoskeleton and focal contacts were destabilized by the reported compound. Overall, the current study suggests a possible relevance of the tested novel inhibitor of HO activity as a potential anticancer compound. To support such utility, further investigation is still needed, especially in in vivo conditions.

Molecular Determinants for Unphosphorylated STAT3 Dimerization Determined by Integrative Modeling.

Signal transducer and activator of transcription factors (STATs) are proteins that can translocate into the nucleus, bind DNA, and activate gene transcription. STAT proteins play a crucial role in cell proliferation, apoptosis, and differentiation. The prevalent view is that STAT proteins are able to form dimers and bind DNA only upon phosphorylation of specific tyrosine residues in the transactivation domain. However, this paradigm has been questioned recently by the observation of dimers of unphosphorylated STATs (USTATs) by X-ray, Förster resonance energy transfer, and site-directed mutagenesis. A more complex picture of the dimerization process and of the role of the dimers is, thus, emerging. Here we present an integrated modeling study of STAT3, a member of the STAT family of utmost importance in cancer development and therapy, in which we combine available experimental data with several computational methodologies such as homology modeling, protein-protein docking, and molecular dynamics to build reliable atomistic models of USTAT3 dimers. The models generated with the integrative approach presented here were then validated by performing computational alanine scanning for all the residues in the protein-protein interface. These results confirmed the experimental observation of the importance of some of these residues (in particular Leu78 and Asp19) in the USTAT3 dimerization process. Given the growing importance of USTAT3 dimers in several cellular pathways, our models provide an important tool for studying the effects of pathological mutations at the molecular and/or atomistic level, and in the rational design of new inhibitors of dimerization.

Molecular Dynamics of Biomolecules through Direct Analysis of Dipolar Couplings.

Residual dipolar couplings (RDCs) are important probes in structural biology, but their analysis is often complicated by the determination of an alignment tensor or its associated assumptions. We here apply the maximum entropy principle to derive a tensor-free formalism which allows for direct, dynamic analysis of RDCs and holds the classic tensor formalism as a special case. Specifically, the framework enables us to robustly analyze data regardless of whether a clear separation of internal and overall dynamics is possible. Such a separation is often difficult in the core subjects of current structural biology, which include multidomain and intrinsically disordered proteins as well as nucleic acids. We demonstrate the method is tractable and self-consistent and generalizes to data sets comprised of observations from multiple different alignment conditions.

Flaviviral protease inhibitors identified by fragment-based library docking into a structure generated by molecular dynamics.

Fragment-based docking was used to select a conformation for virtual screening from a molecular dynamics trajectory of the West Nile virus nonstructural 3 protease. This conformation was chosen from an ensemble of 100 molecular dynamics snapshots because it optimally accommodates benzene, the most common ring in known drugs, and two positively charged fragments (methylguanidinium and 2-phenylimidazoline). The latter fragments were used as probes because of the large number of hydrogen bond acceptors in the substrate binding site of the protease. Upon high-throughput docking of a diversity set of 18,694 molecules and pose filtering, only five compounds were chosen for experimental validation, and two of them are active in the low micromolar range in an enzymatic assay and a tryptophan fluorescence quenching assay. Evidence for specific binding to the protease active site is provided by nuclear magnetic resonance spectroscopy. The two inhibitors have different scaffolds (diphenylurea and diphenyl ester) and are promising lead candidates because they have a molecular weight of about 300 Da.

NMR study of complexes between low molecular mass inhibitors and the West Nile virus NS2B-NS3 protease.

The two-component NS2B-NS3 protease of West Nile virus is essential for its replication and presents an attractive target for drug development. Here, we describe protocols for the high-yield expression of stable isotope-labelled samples in vivo and in vitro. We also describe the use of NMR spectroscopy to determine the binding mode of new low molecular mass inhibitors of the West Nile virus NS2B-NS3 protease which were discovered using high-throughput in vitro screening. Binding to the substrate-binding sites S1 and S3 is confirmed by intermolecular NOEs and comparison with the binding mode of a previously identified low molecular mass inhibitor. Our results show that all these inhibitors act by occupying the substrate-binding site of the protease rather than by an allosteric mechanism. In addition, the NS2B polypeptide chain was found to be positioned near the substrate-binding site, as observed previously in crystal structures of the protease in complex with peptide inhibitors or bovine pancreatic trypsin inhibitor. This indicates that the new low molecular mass compounds, although inhibiting the protease, also promote the proteolytically active conformation of NS2B, which is very different from the crystal structure of the protein without inhibitor.

Activation of the West Nile virus NS3 protease: molecular dynamics evidence for a conformational selection mechanism.

The flaviviral nonstructural 3 protease (NS3pro) is essential for virus replication and is therefore a pharmaceutically relevant target to fight Dengue and West Nile virus (WNV). NS3pro is a chymotrypsin-like serine protease which requires a polypeptide cofactor (NS2B) for activation. Recent X-ray crystallography studies have led to the suggestion that the substrate binds to the two-component NS2B-NS3pro enzyme by an induced-fit mechanism. Here, multiple explicit water molecular dynamics simulations of the WNV NS2B-NS3pro enzyme show that the active conformation of the NS2B cofactor (in which its beta-loop is part of the substrate binding site) is stable over a 50-ns time scale even in the absence of the inhibitor. The partial and reversible opening of the NSB2 beta-loop and its correlated motion with an adjacent NS3pro loop, both observed in the simulations started from the active conformation, are likely to facilitate substrate binding and product release. Moreover, in five of eight simulations without inhibitor (started from two X-ray structures both with improperly formed oxyanion hole) the Thr132-Gly133 peptide bond flips spontaneously thereby promoting the formation of the catalytically competent oxyanion hole, which then stays stable until the end of the runs. The simulation results provide evidence at atomic level of detail that the substrate binds to the NS2B-NS3pro enzyme by conformational selection, rather than induced-fit mechanism.

Discovery of a non-peptidic inhibitor of west nile virus NS3 protease by high-throughput docking.

BACKGROUND: The non-structural 3 protease (NS3pro) is an essential flaviviral enzyme and therefore one of the most promising targets for drug development against West Nile virus (WNV) and dengue infections. METHODOLOGY: In this work, a small-molecule inhibitor of the WNV NS3pro has been identified by automatic fragment-based docking of about 12000 compounds and testing by nuclear magnetic resonance (NMR) spectroscopy of only 22 molecules. Specific binding of the inhibitor into the active site of NS3pro and its binding mode are confirmed by 15N-HSQC NMR spectra. The inhibitory activity is further validated by an enzymatic assay and a tryptophan fluorescence quenching assay. CONCLUSION: The inhibitor [4-(carbamimidoylsulfanylmethyl)-2,5-dimethylphenyl]-methylsulfanylmethanimidamide has a good ratio of binding affinity versus molecular weight (ligand efficiency of 0.33 kcal/mol per non-hydrogen atom), and thus has good potential as lead compound for further development to combat West Nile virus infections.

Protein structure prediction: combining de novo modeling with sparse experimental data.

Routine structure prediction of new folds is still a challenging task for computational biology. The challenge is not only in the proper determination of overall fold but also in building models of acceptable resolution, useful for modeling the drug interactions and protein-protein complexes. In this work we propose and test a comprehensive approach to protein structure modeling supported by sparse, and relatively easy to obtain, experimental data. We focus on chemical shift-based restraints from NMR, although other sparse restraints could be easily included. In particular, we demonstrate that combining the typical NMR software with artificial intelligence-based prediction of secondary structure enhances significantly the accuracy of the restraints for molecular modeling. The computational procedure is based on the reduced representation approach implemented in the CABS modeling software, which proved to be a versatile tool for protein structure prediction during the CASP (CASP stands for critical assessment of techniques for protein structure prediction) experiments (see http://predictioncenter/CASP6/org). The method is successfully tested on a small set of representative globular proteins of different size and topology, including the two CASP6 targets, for which the required NMR data already exist. The method is implemented in a semi-automated pipeline applicable to a large scale structural annotation of genomic data. Here, we limit the computations to relatively small set. This enabled, without a loss of generality, a detailed discussion of various factors determining accuracy of the proposed approach to the protein structure prediction.

Protein modeling with reduced representation: statistical potentials and protein folding mechanism.

A high resolution reduced model of proteins is used in Monte Carlo dynamics studies of the folding mechanism of a small globular protein, the B1 immunoglobulin-binding domain of streptococcal protein G. It is shown that in order to reproduce the physics of the folding transition, the united atom based model requires a set of knowledge-based potentials mimicking the short-range conformational propensities and protein-like chain stiffness, a model of directional and cooperative hydrogen bonds, and properly designed knowledge-based potentials of the long-range interactions between the side groups. The folding of the model protein is cooperative and very fast. In a single trajectory, a number of folding/unfolding cycles were observed. Typically, the folding process is initiated by assembly of a native-like structure of the C-terminal hairpin. In the next stage the rest of the four-ribbon beta-sheet folds. The slowest step of this pathway is the assembly of the central helix on the scaffold of the beta-sheet.