Computational Modeling and Experimental Evaluation of a Novel Prodrug for Targeting the Extracellular Space of Prostate Tumors

Tailoring the AIE Chromogen 2-(2-Hydroxyphenyl)benzothiazole for Use in Enzyme-Triggered Molecular Brachytherapy

A targeted strategy for treating cancer is antibody-directed enzyme prodrug therapy, where the enzyme attached to the antibody causes conversion of an inactive small-molecule prodrug into an active drug. A limitation may be the diffusion of the active drug away from the antibody target site. A related strategy with radiotherapeutics entails enzymatically promoted conversion of a soluble to insoluble radiotherapeutic agent, thereby immobilizing the latter at the target site. Such a molecular brachytherapy has been scarcely investigated. In distinct research, the advent of molecular designs for aggregation-induced emission (AIE) suggests translational use in molecular brachytherapy. Here, several 2-(2-hydroxyphenyl)benzothiazole substrates that readily aggregate in aqueous solution (and afford AIE) were elaborated in this regard. In particular, (1) the 2-(2-hydroxyphenyl) unit was derivatized to bear a pegylated phosphodiester that imparts water solubility yet undergoes enzymatic cleavage, and (2) a p-phenol unit was attached to the benzo moiety to provide a reactive site for final-step iodination (here examined with natural abundance iodide). The pegylated phosphodiester-iodinated benzothiazole undergoes conversion from aqueous-soluble to aqueous-insoluble upon treatment with a phosphatase or phosphodiesterase. The aggregation is essential to molecular brachytherapy, whereas the induced emission of AIE is not essential but provides a convenient basis for research development. Altogether, 21 compounds were synthesized (18 new, 3 known via new routes). Taken together, blending biomedical strategies of enzyme prodrug therapy with materials chemistry concerning substances that undergo AIE may comprise a step forward on the long road toward molecular brachytherapy.

Coordination environment changes of the vanadium in vanadium-dependent haloperoxidase enzymes

Vanadium-dependent haloperoxidases are a class of enzymes that catalyze oxidation reactions with halides to form halogenated organic products and water. These enzymes include chloroperoxidase and bromoperoxidase, which have very different protein sequences and sizes, but regardless the coordination environment of the active sites is surprisingly constant. In this manuscript, the comparison of the coordination chemistry of V-containing-haloperoxidases of the trigonal bipyramidal geometry was done by data mining. The catalytic cycle imposes changes in the coordination geometry of the vanadium to accommodate the peroxidovanadium(V) intermediate in an environment we describe as a distorted square pyramidal geometry. During the catalytic cycle, this intermediate converts to a trigonal bipyramidal intermediate before losing the halogen and forming a tetrahedral vanadium-protein intermediate. Importantly, the catalysis is facilitated by a proton-relay system supplied by the second sphere coordination environment and the changes in the coordination environment of the vanadium(V) making this process unique among protein catalyzed processes. The analysis of the coordination chemistry shows that the active site is very tightly regulated with only minor changes in the coordination geometry. The coordination geometry in the protein structures deviates from that found for both small molecules crystalized in the absence of protein and the reported functional small molecule model compounds. At this time there are no examples reported of a structurally similar small molecule with the geometry observed for the peroxidovanadium(V) in the active site of the vanadium-containing haloperoxidases.

DNA-binding study of anticancer drug cytarabine by spectroscopic and molecular docking techniques

The interaction of anticancer drug cytarabine with calf thymus DNA (CT-DNA) was investigated in vitro under simulated physiological conditions by multispectroscopic techniques and molecular modeling study. The fluorescence spectroscopy and UV absorption spectroscopy indicated drug interacted with CT-DNA in a groove-binding mode, while the binding constant of UV-vis and the number of binding sites were 4.0 ± 0.2 × 10⁴ L mol^-1 and 1.39, respectively. The fluorimetric studies showed that the reaction between the drugs with CT-DNA is exothermic. Circular dichroism spectroscopy was employed to measure the conformational change of DNA in the presence of cytarabine. Furthermore, the drug induces detectable changes in its viscosity for DNA interaction. The molecular modeling results illustrated that cytarabine strongly binds to groove of DNA by relative binding energy of docked structure -20.61 KJ mol^-1. This combination of multiple spectroscopic techniques and molecular modeling methods can be widely used in the investigation on the interaction of small molecular pollutants and drugs with biomacromolecules for clarifying the molecular mechanism of toxicity or side effect in vivo.

Polypharmacology in Drug Development: A Minireview of Current Technologies

Polypharmacology, the process in which a single drug is able to bind to multiple targets specifically and simultaneously, is an emerging paradigm in drug development. The potency of a given drug can be increased through the engagement of multiple targets involved in a certain disease. Polypharmacology may also help identify novel applications of existing drugs through drug repositioning. However, many problems and challenges remain in this field. Rather than covering all aspects of polypharmacology, this Minireview is focused primarily on recently reported techniques, from bioinformatics technologies to cheminformatics approaches as well as text-mining-based methods, all of which have made significant contributions to the research of polypharmacology.

A specific molecular beacon probe for the detection of human prostate cancer cells

The small-molecule, water-soluble molecular beacon probe 1 is hydrolyzed by the lysate and living cells of human prostate cancer cell lines (LNCaP), resulting in strong green fluorescence. In contrast, probe 1 does not undergo significant hydrolysis in either the lysate or living cells of human nontumorigenic prostate cells (RWPE-1). These results, corroborated by UV-Vis spectroscopy and fluorescent microscopy, reveal that probe 1 is a sensitive and specific fluorogenic and chromogenic sensor for the detection of human prostate cancer cells among nontumorigenic prostate cells and that carboxylesterase activity is a specific biomarker for human prostate cancer cells.

Computational and biological evaluation of quinazolinone prodrug for targeting pancreatic cancer

Our concept of enzyme-mediated cancer imaging and therapy aims to use radiolabeled compounds to target hydrolases over-expressed on the extracellular surface of solid tumors. A data mining approach identified extracellular sulfatase 1 (SULF1) as an enzyme expressed on the surface of pancreatic cancer cells. We designed, synthesized, and characterized 2-(2'-sulfooxyphenyl)-6-iodo-4-(3H)-quinazolinone (IQ(2-S)) as well as its radioiodinated form ((125) IQ(2-S)) as a prodrug with potential for hydrolysis by SULF1. IQ(2-S) was successfully docked in silico into three enzymes - homolog of SULF1, alkaline phosphatase, and prostatic acid phosphatase. The incubation of (125) IQ(2-S) and (125) IQ(2-P) with the three enzymes in solution confirms the docking results and enzyme selectivity for the analogs. The hydrolysis of both radioactive compounds produces the water-insoluble, fluorescent product 2-(2'-hydroxyphenyl)-6-[(125) I]iodo-4-(3H)-quinazolinone ((125) IQ(2-OH)). The in vitro incubation of (127) IQ(2-S) and (127) IQ(2-P) with pancreatic, ovarian, and prostate cancer cells expressing studied hydrolases also results in their hydrolysis and the precipitation of (127) IQ(2-OH) fluorescent crystals on the cell surface. To our knowledge, these findings are the first to report the targeting of a radioactive substrate to SULF1 and that this prodrug may be potentially useful in the imaging ((123) I/(124) I/(131) I) and radiotherapy ((131) I) of pancreatic cancer.

Human placental alkaline phosphatase-mediated hydrolysis correlates tightly with the electrostatic contribution from tail group

Human placental alkaline phosphatase has been identified as a hydrolase that is significantly overexpressed on the surface of various solid tumor cells, and is therefore a suitable prodrug design target for non-invasive cancer imaging and therapy. Structure-based prediction of enzymatic activities is essential for rational prodrug design. We have been probing the catalytic proficiency--(k(cat) /K(M) )/k(w)--of placental alkaline phosphatase toward several widely diverse substrate structures experimentally and correlating these results to in silico predictions that are based on the free energy estimates obtained from docking of each substrate structure with placental alkaline phosphatase. We have found that electrostatic contribution from the tail group is the most crucial factor to determine the catalytic efficiencies of the substrates. The electrostatic contribution and the total binding energy of the tail group are well correlated with catalytic efficiencies (R² = 0.79 and 0.89, respectively). However, hydrophobic contribution from the tail group does not correlate with the catalytic efficiencies (negative correlation, R² = 0.27). This supports the prior hypothesis stating that alkaline phosphatase-mediated differential hydrolysis of its substrates is attributable to the differential interactions with the tail group, determined by the electrostatic contributions from the non-bridging oxygen atoms. Calculation of the electrostatic potentials within the active site of human placental alkaline phosphatase also suggests that the local positive electrostatic environment may account for its capability to distinguish various substrates. Our study is likely to have immediate implications in the design of prodrugs against human placental alkaline phosphatase and other esterases overexpressed by human tumor cells.

Integrated bioinformatics analysis for cancer target identification

The exponential growth of high-throughput Omics data has provided an unprecedented opportunity for new target identification to fuel the dried-up drug discovery pipeline. However, the bioinformatics analysis of large amount and heterogeneous Omics data has posed a great deal of technical challenges for experimentalists who lack statistical skills. Moreover, due to the complexity of human diseases, it is essential to analyze the Omics data in the context of molecular networks to detect meaningful biological targets and understand disease processes. Here, we describe an integrated bioinformatics analysis strategy and provide a running example to identify suitable targets for our in-house Enzyme-Mediated Cancer Imaging and Therapy (EMCIT) technology. In addition, we go through a few key concepts in the process, including corrected false discovery rate (FDR), Gene Ontology (GO), pathway analysis, and tissue specificity. We also describe popular programs and databases which allow the convenient annotation and network analysis of Omics data. We provide a practical guideline for researchers to quickly follow the protocol described and identify those targets that are pertinent to their work.

Identification of novel inhibitors for a low molecular weight protein tyrosine phosphatase via virtual screening

The human cytoplasmic protein tyrosine phosphatase (HCPTP) has been identified as a potential target for inhibition in order to downregulate metastatic transformation in several human epithelial cancers such as breast, prostate and colon cancer. Docking with two scoring functions on both isoforms of HCPTP was employed as an initial virtual screen to identify potential inhibitors. Compounds identified as potential inhibitors via this in silico screen were subjected to kinetic analysis in order to validate their selection as improved inhibitors. Eleven compounds with IC50's of less than 100 microM were identified in a single concentration screen. Five of these compounds were determined to have an IC50 of less than 10 microM; however, all but one of these compounds inhibited via non-specific aggregation. The validated effective inhibitor, which is based on a naphthyl sulfonic acid, strongly resembles a previously synthesized rationally designed azaindole phosphonic acid. This similarity suggests subsequent inhibitor optimization based on this scaffold may generate effective inhibitors of HCPTP. The structural elements of the computationally identified inhibitors are discussed to analyze the combined use of rational design and virtual screening to reduce false negatives in the identification of multiple strong inhibitors of HCPTP.

Synthesis and preclinical evaluations of 2-(2-fluorophenyl)-6,7-methylenedioxyquinolin-4-one monosodium phosphate (CHM-1-P-Na) as a potent antitumor agent

CHM-1 [2-(2-fluorophenyl)-6,7-methylenedioxyquinolin-4-one] (1) has a unique antitumor mechanism of action. However, because 1 has relatively low hydrophilicity, it was evaluated only via ip administration, which is not clinically acceptable. In this study, we synthesized the monosodium phosphate salt (CHM-1-P-Na, 4) of 1 as a hydrophilic prodrug. Compound 4 was rapidly converted into 1 following iv and po administration and also possessed excellent antitumor activity in a SKOV-3 xenograft nude mice model. Compound 4 also had clear-cut pharmacological effects on enzymes related with tumor cells. Neither 4 nor 1 significantly affected normal biological function in a safety pharmacology profiling study. Compound 1 caused apoptotic effects in breast carcinoma cells via accumulation of cyclin B1, and importantly, the endogenous levels of the mitotic spindle checkpoint proteins BubR1 directly correlated with cellular response to microtubule disruption. With excellent antitumor activity profiles, 4 is highly promising for development as an anticancer clinical trials candidate.

The power of the web in cancer drug discovery and clinical trial design: research without a laboratory?

The discovery of effective cancer treatments is a key goal for pharmaceutical companies. However, the current costs of bringing a cancer drug to the market in the USA is now estimated at $1 billion per FDA approved drug, with many months of research at the bench and costly clinical trials. A growing number of papers highlight the use of data mining tools to determine associations between drugs, genes or protein targets, and possible mechanism of actions or therapeutic efficacy which could be harnessed to provide information that can refine or direct new clinical cancer studies and lower costs. This report reviews the paper by R.J. Epstein, which illustrates the potential of text mining using Boolean parameters in cancer drug discovery, and other studies which use alternative data mining approaches to aid cancer research.

Auger processes in the 21st century

PURPOSE

The extreme radiotoxicity of Auger electrons and their exquisite capacity to irradiate specific molecular sites has prompted scientists to extensively investigate their radiobiological effects. Their efforts have been punctuated by quadrennial international symposia that have focused on biophysical aspects of Auger processes. The latest meeting, the 6th International Symposium on Physical, Molecular, Cellular, and Medical Aspects of Auger Processes, was held 5-6 July 2007 at Harvard Medical School in Boston, Massachusetts, USA. This article provides a review of the research in this field that was published during the years 2004-2007, the period that has elapsed since the previous meeting.

CONCLUSION

The field has advanced considerably. A glimpse of the potential of this unique form of ionizing radiation to contribute to future progress in a variety of fields of study is proffered.

Target discovery from data mining approaches

Data mining of available biomedical data and information has greatly boosted target discovery in the 'omics' era. Target discovery is the key step in the biomarker and drug discovery pipeline to diagnose and fight human diseases. In biomedical science, the 'target' is a broad concept ranging from molecular entities (such as genes, proteins and miRNAs) to biological phenomena (such as molecular functions, pathways and phenotypes). Within the context of biomedical science, data mining refers to a bioinformatics approach that combines biological concepts with computer tools or statistical methods that are mainly used to discover, select and prioritize targets. In response to the huge demand of data mining for target discovery in the 'omics' era, this review explicates various data mining approaches and their applications to target discovery with emphasis on text and microarray data analysis. Two emerging data mining approaches, chemogenomic data mining and proteomic data mining, are briefly introduced. Also discussed are the limitations of various data mining approaches found in the level of database integration, the quality of data annotation, sample heterogeneity and the performance of analytical and mining tools. Tentative strategies of integrating different data sources for target discovery, such as integrated text mining with high-throughput data analysis and integrated mining with pathway databases, are introduced.

Integrative genomic data mining for discovery of potential blood-borne biomarkers for early diagnosis of cancer

Background

With the arrival of the postgenomic era, there is increasing interest in the discovery of biomarkers for the accurate diagnosis, prognosis, and early detection of cancer. Blood-borne cancer markers are favored by clinicians, because blood samples can be obtained and analyzed with relative ease. We have used a combined mining strategy based on an integrated cancer microarray platform, Oncomine, and the biomarker module of the Ingenuity Pathways Analysis (IPA) program to identify potential blood-based markers for six common human cancer types.

Methodology/Principal Findings

In the Oncomine platform, the genes overexpressed in cancer tissues relative to their corresponding normal tissues were filtered by Gene Ontology keywords, with the extracellular environment stipulated and a corrected Q value (false discovery rate) cut-off implemented. The identified genes were imported to the IPA biomarker module to separate out those genes encoding putative secreted or cell-surface proteins as blood-borne (blood/serum/plasma) cancer markers. The filtered potential indicators were ranked and prioritized according to normalized absolute Student t values. The retrieval of numerous marker genes that are already clinically useful or under active investigation confirmed the effectiveness of our mining strategy. To identify the biomarkers that are unique for each cancer type, the upregulated marker genes that are in common between each two tumor types across the six human tumors were also analyzed by the IPA biomarker comparison function.

Conclusion/Significance

The upregulated marker genes shared among the six cancer types may serve as a molecular tool to complement histopathologic examination, and the combination of the commonly upregulated and unique biomarkers may serve as differentiating markers for a specific cancer. This approach will be increasingly useful to discover diagnostic signatures as the mass of microarray data continues to grow in the ‘omics’ era.

Novel prodrugs for targeting diagnostic and therapeutic radionuclides to solid tumors

Most cancer therapeutics (chemo, radiation, antibody-based, anti-angiogenic) are at best partially and/or temporarily effective. In general, the causes for failure can be summarized as: (i) poor diffusion and/or nonuniform distribution of drug/prodrug molecules in solid tumors; (ii) high drug concentration and retention in normal tissues (leading to side effects); (iii) requirement for plasma-membrane permeability and/or internalization of drug/prodrug molecules; (iv) low uptake of drug by tumor; (v) lack of retention of drug within tumor (most have gradient-driven reversible binding); and (vi) multidrug resistance. We are developing an innovative technology that aims to surmount these problems by actively concentrating and permanently entrapping radioimaging and radiotherapeutic prodrugs specifically within solid tumors. The approach will enable noninvasive sensing (imaging) and effective therapy of solid tumors, allowing tumor detection, diagnosis, and treatment to be closely coupled (personalized medicine).

DMSO increases radioiodination yield of radiopharmaceuticals

A high-yield radioiodination method for various types of molecules is described. The approach employs DMSO as precursor solvent, a reaction ratio of 2-5 precursor molecules per iodine atom, 5-10 microg oxidant, and a 10-25 microl reaction volume. The solution is vortexed at room temperature for 1-5 min and progress of the reaction is assessed by HPLC. Radioiodinated products are obtained in > or = 95% yield and meet the requirements for radiotracer imaging, biodistribution studies, and molecular and cellular biology research.