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PubMed2006

In silico design, synthesis, and biological evaluation of radioiodinated quinazolinone derivatives for alkaline phosphatase-mediated cancer diagnosis and therapy.

As part of the development of enzyme-mediated cancer imaging and therapy, a novel technology to entrap water-insoluble radioactive molecules within solid tumors, we show that a water-soluble, radioactive quinazolinone prodrug, ammonium 2-(2'-phosphoryloxyphenyl)-6-[125I]iodo-4-(3H)-quinazolinone (125IQ(2-P)), is hydrolyzed by alkaline phosphatase to a water-insoluble, radiolabeled drug, 2-(2'-hydroxyphenyl)-6-[125I]iodo-4-(3H)-quinazolinone (125IQ(2-OH)). Biodistribution data suggest the existence of two isoforms of the prodrug (IQ(2-P(I)) and IQ(2-P)), and this has been confirmed by their synthesis and characterization. Structural differences of the two isoforms have been examined using in silico molecular modeling techniques and docking methods to describe the interaction/binding between the isoforms and human placental alkaline phosphatase (PLAP), a tumor cell, membrane-associated, hydrolytic enzyme whose structure is known by X-ray crystallographic determination. Docking data show that IQ(2-P), but not IQ(2-P(I)), fits the active binding site of PLAP favorably and interacts with the catalytic amino acid Ser(92), which plays an important role in the hydrolytic process. The binding free energies (DeltaG(binding)) of the isoforms to PLAP predict that IQ(2-P) will be the better substrate for PLAP. The in vitro incubation of the isoforms with PLAP leads to the rapid hydrolysis of IQ(2-P) only and confirms the in silico expectations. Fluorescence microscopy shows that in vitro incubation of IQ(2-P) with mouse and human tumor cells causes the extracellular, alkaline phosphatase-mediated hydrolysis of the molecule and precipitation of fluorescent crystals of IQ(2-OH). No hydrolysis is seen in the presence of normal mouse and human cells. Furthermore, the intratumoral injection of 125IQ(2-P) into alkaline phosphatase-expressing solid human tumors grown s.c. in nude rats results in efficient hydrolysis of the compound and retention of approximately 70% of the injected radioactivity, whereas similar injection into normal tissues (e.g., muscle) does not produce any measurable hydrolysis (approximately 1%) or retention of radioactivity at the injected site. These studies support the enzyme-mediated cancer imaging and therapy technology and show the potential of such quinazolinone derivatives in the in vivo radiodetection (123I/124I) and therapy (131I) of solid tumors.

Alkaline Phosphatase↗
PubMed2004

Genome wide in silico SNP-tumor association analysis.

BACKGROUND: Carcinogenesis occurs, at least in part, due to the accumulation of mutations in critical genes that control the mechanisms of cell proliferation, differentiation and death. Publicly accessible databases contain millions of expressed sequence tag (EST) and single nucleotide polymorphism (SNP) records, which have the potential to assist in the identification of SNPs overrepresented in tumor tissue. METHODS: An in silico SNP-tumor association study was performed utilizing tissue library and SNP information available in NCBI's dbEST (release 092002) and dbSNP (build 106). RESULTS: A total of 4865 SNPs were identified which were present at higher allele frequencies in tumor compared to normal tissues. A subset of 327 (6.7%) SNPs induce amino acid changes to the protein coding sequences. This approach identified several SNPs which have been previously associated with carcinogenesis, as well as a number of SNPs that now warrant further investigation CONCLUSIONS: This novel in silico approach can assist in prioritization of genes and SNPs in the effort to elucidate the genetic mechanisms underlying the development of cancer.

Databases, Genetic↗
PubMed2004

New approaches for in silico identification of cytokine-modified beta cell gene networks.

Beta cell dysfunction and death in type 1 diabetes mellitus (T1DM) is caused by direct contact with activated macrophages and T lymphocytes and by exposure to soluble mediators secreted by these cells, such as cytokines and nitric oxide. Cytokine-induced apoptosis depends on the expression of pro- and anti-apoptotic genes that remain to be characterized. Using microarray analyses, we identified several transcription factor and "effector" gene networks regulated by interleukin-1beta and/or interferon-gamma in beta cells. This suggests that beta cell fate following exposure to cytokines is a complex and highly regulated process, depending on the duration and severity of perturbation of key gene networks. In order to draw correct conclusions from these massive amounts of data, we need to utilize novel bioinformatics and statistical tools. Thus, we are presently performing in silico analysis for the localization of binding sites for the transcription factor NF-kappaB (previously shown to be pivotal for beta cell apoptosis) in 15 temporally related gene clusters, identified by time-course microarray analysis. In silico analysis is based on a broad range of computational techniques used to detect motifs in a DNA sequence corresponding to the binding site of a transcription factor. These computer-based findings must be validated by use of positive and negative controls, and by "ChIP on chip" analysis. Moreover, new statistical approaches are required to decrease false positive findings. These novel approaches will constitute a "proof of principle" for the integrated use of bioinformatics and functional genomics in the characterization of relevant cytokine-regulated beta cell gene networks leading to beta cell apoptosis in T1DM.

Animals↗
PubMed2005

Homology-modeled ligand-binding domains of zebrafish estrogen receptors alpha, beta1, and beta2: from in silico to in vivo studies of estrogen interactions in Danio rerio as a model system.

Homology models were constructed for the ligand-binding domains of zebrafish estrogen receptors (zfERs) alpha, beta(1), and beta(2). Estradiol-binding sites are nearly identical in zfERs and their human homologs, suggesting that zebrafish will serve as a good model system for studying human ER-binding drugs. Conversely, studies of endocrine disruptor effects on zebrafish will benefit from the wealth of data available on xenoestrogen interactions with human ERs. Compounds flagged by the Interagency Coordinating Committee on the Validation of Alternative Methods for endocrine disruptor screening were docked into our zfER homology models. Ideally, these in silico docking studies would be complemented with in vivo binding studies. To this end, fluorescently tagged estradiol was docked into zfERalpha and found to bind in the same manner as in human ERalpha, with fluorescein preferentially occupying a region between helices 11 and 12. Fluorescently tagged estradiol was synthesized and was found to localize along the path of primordial germ cell migration in the developing zebrafish embryo 3 d after fertilization, consistent with previous reports of 1) a role for estradiol in sex determination, and 2) the first appearance of ERs 2 d after fertilization. These data provide a foundation for future in silico and in vivo binding studies of estrogen agonists and antagonists with zebrafish ERs.

Amino Acid Sequence↗
PubMed2005

[High throughput screening of pharmacokinetics and metabolism in drug discovery (III)--investigation on in- silico model for membrane permeability and CYP1A2 inhibition].

Pharmacokinetic and metabolic screening plays an important role in the optimization of a lead compound in drug discovery. Since those screening methods are time-consuming and labor intensive, in silico models would be effective to select compounds and guide derivatization prior to the screening. We investigated in silico models for permeability in Caco-2 cells, brain distribution and cytochrome P450 (CYP) inhibition using molecular weight, lipophilicity (clog D(7.4)), polar surface area (PSA), and number of rotatable bonds (RB). A variety of test compounds was selected from different Caco-2 assay projects. The permeability determined exhibited a good correlation with a combination of PSA and clog D(7.4) rather than with PSA alone. In the brain distribution, PSA, in addition to lipophilicity, was one of the determinant parameters, and compounds were significantly distributed to the brain in rats with the decrease in the PSA value. When this approach was adapted to CYP1A2 inhibition in the fluorometric assay, the inhibitory potential for two plane core structures was successfully predicted by utilizing number of RB, PSA, and clog D(7.4). In particular, an increase in the number of RB weakened the inhibitory potential due to a loss of the plane structures. These results suggest that the PSA and RB are key parameters to design chemical structures in terms of the improvement of both membrane permeability in the brain and gastrointestine and CYP1A2 inhibition, respectively.

Animals↗
PubMed2005

In silico modeling and simulation of bone biology: a proposal.

Contemporary, computer-based mathematical modeling techniques make it possible to represent complex biological mechanisms in a manner that permits hypothesis testing in silico. This perspective shows how such approaches might be applied to bone remodeling and therapeutic research. Currently, the dominant conceptual model applied in bone research involves the dynamic balance between the continual build-up and breakdown of bone matrix by two cell types, the osteoblasts and osteoclasts, acting together as a coordinated, remodeling unit. This conceptualization has served extraordinarily well as a focal point for understanding how mutations, chemical mediators, and mechanical force, as well as external influences (e.g., drugs, diet) affect bone structure and function. However, the need remains to better understand and predict the consequences of manipulating any single factor, or combination of factors, within the context of this complex system's multiple interacting pathways. Mathematical models are a natural extension of conceptual models, providing dynamic, quantitative descriptions of the relationships among interacting components. This formalization creates the ability to simulate the natural behavior of a system, as well as its modulation by therapeutic or dietetic interventions. A number of mathematical models have been developed to study complex bone functions, but most include only a limited set of biological components needed to address a few specific questions. However, it is possible to develop larger, multiscale models that capture the dynamic interactions of many biological components and relate them to important physiological or pathological outcomes that allow broader study. Examples of such models include entelos' physiolab platforms. These models simulate the dynamic, quantitative interactions among a biological system's biochemicals, cells, tissues, and organs and how they give rise to key physiologic and pathophysiologic outcomes. We propose that a similar predictive, dynamical, multiscale mathematical model of bone remodeling and metabolism would provide a better understanding of the mechanisms governing these phenomena as well as serve as an in silico platform for testing pharmaceutical and clinical interventions on metabolic bone disease.

Bone Diseases↗
PubMed2025

In silico identification of Leishmania GP63 protein epitopes to generate a new vaccine antigen against leishmaniasis.

BACKGROUND: The surface of Leishmania spp. presents glycoprotein 63 (GP63), a metalloprotease that acts as one of the parasite's major antigens. A vaccine against leishmaniasis has not yet been developed and stationary phase promastigotes have utmost importance in transmitting Leishmania spp. from phlebotomine sand fly to humans or reservoirs. Therefore, this study aimed to analyze GP63 protein in three different Leishmania spp. to determine new vaccine candidate antigen against leishmaniasis using sequencing data of locally detected Leishmania strains and in silico approaches. METHODOLOGY/PRINCIPAL FINDINGS: The GP63 protein sequences of the stationary phase/amastigote form of L. infantum, L. major, and L. tropica were identified and then the gene encoding GP63 protein in Leishmania positive samples (n:59) was amplified and sequenced for variation analysis. According to the results, 4, 6, 19 GP63 variants were found within L. infantum, L. major, and L. tropica isolates, respectively. The most prevalent variants within each species were selected for further analysis using in silico approaches. Accordingly, all selected GP63 proteins were antigenic and the amount of B and T cell epitopes were 23 for L. infantum, 10 for L. major, and 9 for L. tropica. The analysis of each epitope showed that all of them were non-toxic, non-allergen, and soluble but had different antigenicity values. Among these epitopes, EMEDQGSAGSAGS associated with L. major, STHDSGSTTC and AEDILTDEKRDILRK epitopes associated with L. infantum had the highest antigenicity values for B cell, MHC-I, and MHC-II epitopes, respectively. Moreover, conserved epitopes were detected among two or three Leishmania species. CONCLUSIONS/SIGNIFICANCE: This study detected many epitopes that could be used in vaccine studies and the development of serological diagnostic assays.

Antigens, Protozoan↗
PubMed2005

In silico and wet-bench identification of nuclear matrix attachment regions.

Chromatin loops are tethered at discrete regions that are approx 100-1000 bp in length. These regions of attachment serve as specific sequence landmarks, anchoring the DNA to the fibers of the chromosomal scaffold. It has been estimated that our genome contains 70,000 nuclear matrix attachment sites that serve as a dynamic nuclear organizer in both the interphase and metaphase cell. Approximately 30,000-40,000 matrix attachment regions (MARs) serve as origins of replication. MARs can also be associated with chromosomal segments densely populated with transcription factor-binding sites. This may facilitate transcription that is initiated within the region of the chromosome coincident with the surface of the nuclear matrix. Assuming an average somatic loop size of 100 kb, it is reasonable to propose that each cell utilizes 30,000 MARs to anchor each of the approx 20,000 active genic domains. This is sufficient to encompass the 30,000 functional genes in our genome that exist as members of single or multigenic families, each constituting a single chromatin domain. With the sequencing phase of various genome projects complete, in silico tools are being developed to identify the long-range control elements that modulate gene expression. This information is necessary to specifically target the time-intensive wet-bench verification and expression experiments that will provide a unified understanding of gene regulation. In this chapter we review some of the in silico strategies that are currently available and a new in vivo method based on the real-time polymerase chain reaction, to assess regions of matrix association.

Actins↗
PubMed2003

Protecting innovation in bioinformatics and in-silico biology.

Commercial success or failure of innovation in bioinformatics and in-silico biology requires the appropriate use of legal tools for protecting and exploiting intellectual property. These tools include patents, copyrights, trademarks, design rights, and limiting information in the form of 'trade secrets'. Potentially patentable components of bioinformatics programmes include lines of code, algorithms, data content, data structure and user interfaces. In both the US and the European Union, copyright protection is granted for software as a literary work, and most other major industrial countries have adopted similar rules. Nonetheless, the grant of software patents remains controversial and is being challenged in some countries. Current debate extends to aspects such as whether patents can claim not only the apparatus and methods but also the data signals and/or products, such as a CD-ROM, on which the programme is stored. The patentability of substances discovered using in-silico methods is a separate debate that is unlikely to be resolved in the near future.

Computational Biology↗
PubMed2006

In silico approaches to prediction of aqueous and DMSO solubility of drug-like compounds: trends, problems and solutions.

The solubility of drugs and drug-like compounds has been the subject of extensive studies aimed at finding a way to predict solubility from molecular structure. The aqueous solubility of a drug is an important factor that influences its absorption, distribution and elimination in the body. Poor aqueous solubility often causes a drug to appear inactive and may cause other biological problems. Compound solubility in DMSO represents another serious problem in early stages of drug discovery. An appreciation of the factors affecting a compound's DMSO solubility could help in predicting the storage conditions and appropriateness of compounds for primary bioscreening programs. In silico procedures for estimation of water and DMSO solubility represent extremely useful tools for the drug discovery practitioners. In this review, we provide a critical discussion of in silico models for the prediction of DMSO and water solubility of drug-like compounds used for virtual screening. We describe the main tendencies in the field, "booming" approaches and unsolved problems. A critical analysis of the accuracy and applicability of methods is provided.

Biological Availability↗
PubMed2003

In silico ADME prediction: data, models, facts and myths.

A critical review of a very recent work in the field of in silico ADME prediction is presented with emphasis on the work published during the period 2000-2002, and several other review articles are mentioned in order to offer a broader view of the field. We find that not much progress has been made in developing robust and predictive models, and that the lack of accurate data, together with the use of questionable modeling end-points, has greatly hindered the real progress in defining generally applicable models. Due to the largely empirical nature of QSAR/QSPR approaches, general and truly predictive models for complex phenomena, such as absorption and clearance, may still be chimeric. The development of local models for use within focused chemical series may be the most appropriate way of utilizing in silico ADME predictions, once experience and data have been gained on a given project and/or structural class.

Animals↗
PubMed2006

Development and validation of an in silico P450 profiler based on pharmacophore models.

In today's drug discovery process, the very early consideration of ADME properties is aimed at a reduction of drug candidate drop out rate in later development stages. Apart from in vitro testing, in silico methods are evaluated as complementary screening tools for compounds with unfavorable ADME attributes. Especially members of the cytochrome P450 (P450) enzyme superfamily-- e.g. P450 1A2, P450 2C9, P450 2C19, P450 2D6, and P450 3A4-- contribute to xenobiotic metabolism, and compound interaction with one of these enzymes is therefore critically evaluated. Pharmacophore models are widely used to identify common features amongst ligands for any target. In this study, both structure-based and ligand-based models for prominent drug-metabolizing members of the P450 family were generated employing the software packages LigandScout and Catalyst. Essential chemical ligand features for substrate and inhibitor activity for all five P450 enzymes investigated were determined and analyzed. Finally, a collection of 11 pharmacophores for substrates and inhibitors was evaluated as an in silico P450 profiling tool that could be used for early ADME estimation of new chemical entities.

Cytochrome P-450 Enzyme Inhibitors↗
PubMed2006

In-silico prediction and observations of nuclear matrix attachment.

The nuclear matrix is a functionally adaptive structural framework interior to the nuclear envelope. The nature and function of this nuclear organizer remains the subject of widespread discussion in the epigenetic literature. To draw this discussion together with a view to suggest a way forward we summarize the biochemical evidence for the modalities of DNA-matrix binding alongside the in-silico predictions. Concordance is exhibited at various, but not all levels. On the one hand, both the reiteration and sequence similarity of some elements of Matrix Attachment Regions suggest conservation. On the other hand, in-silico predictions suggest additional unique components. In bringing together biological and sequence evidence we conclude that binding may be hierarchical in nature, reflective of a biological role in replicating, transcribing and potentiating chromatin. Nuclear matrix binding may well be more complex than the widely accepted simple loop model.

Algorithms↗
PubMed1976

[Effectivity of intermittent treatment in patients with sputum-positive silico-tuberculosis (author's transl)].

89 patients with sputum-positive silico-tuberculosis got a fully supervised administered antituberculous treatment with intermittent regimens during the years 1969-1974. 65 of the patients had a history of former antituberculous treatment. In only 5 patients the treatment was unsuccessful. Four of the relapses were observed between the 6th and 11th month of treatment. One patient had a relapse 56 months after the onset of chemotherapy. The results indicate that only the quality of the anti-TB treatment is of importance for the course of the tuberculous component in silico-tuberculosis. The results are comparable with those of uncomplicated TB of the lungs.

Adult↗
PubMed1998

Silicoating in resin-metal bonding: restorative implications for osseointegrated implant-bone unison.

Detailed background information leading to the development of a silicoating technique is presented with its advantages and disadvantages and its role in implant dentistry. The rationale is shown for coining a new acronym "osseointegrated Implant-Bone Unison" with an interest in biomechanical considerations for a prosthodontic restorative scenario. Several clinical cases are presented that involve silicoating and composite restorations.

Composite Resins↗
PubMed2001

[In silico analysis of the restriction fragments length distribution in the human genome].

The Restriction On Computer (ROC) program (freely available at http://www.mcb.harvard.edu/gilbert/ROC) was developed and used to analyze the restriction fragment length distribution in the human genome. In contrast to other programs searching for restriction sites, ROC simultaneously analyzes several long nucleotide sequences, such as the entire genomes, and in essence simulates electrophoretic analysis of DNA restriction fragments. In addition, this program extracts and analyzes DNA repeats that account for peaks in the restriction fragment length distribution. The ROC analysis data are consistent with the experimental data obtained via in vitro restriction enzyme analysis (taxonomic printing). A difference between the in vitro and in silico results is explained by underrepresentation of tandem DNA repeats in genomic databases. The ROC analysis of individual genome fragments elucidated the nature of several DNA markers, which were earlier revealed by taxonomic printing, and showed that L1 and Alu repeats are nonrandomly distributed in various chromosomes. Another advantage is that the ROC procedure makes it possible to analyze the nonrandom character of a genomic distribution of short DNA sequences. The ROC analysis showed that a low poly(G) frequency is characteristic of the entire human genome, rather than of only coding sequences. The method was proposed for a more complex in silico analysis of the genome. For instance, it is possible to simulate DNA restriction together with blot hybridization and then to analyze the nature of markers revealed.

Base Sequence↗
PubMed2002

High-throughput and in silico techniques in drug metabolism and pharmacokinetics.

The high-throughput screening (HTS) of large proprietary compound collections and combinatorial libraries has increased the pressure on gathering pharmacokinetic and drug metabolism data as early as possible. Properties related to absorption, distribution, metabolism and excretion (ADME) can be estimated by a range of in vivo and in vitro methods, most of which are now available or under development in high(er)-throughput modus. In addition, progress has been made in in silico methods using various quantitaTive structure-activity relationship (QSAR) and molecular modeling techniques that employ a range of recently introduced descriptors tailored to e-ADME. These in silico approaches are promising filters for virtual libraries to aid synthesis as well as the selection of compounds for acquisition and screening in the early stages of drug discovery.

Absorption↗