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PubMed2006

Receptor-ligand binding sites and virtual screening.

Within the pharmaceutical industry, the ultimate source of continuing profitability is the unremitting process of drug discovery. To be profitable, drugs must be marketable: legally novel, safe and relatively free of side effects, efficacious, and ideally inexpensive to produce. While drug discovery was once typified by a haphazard and empirical process, it is now increasingly driven by both knowledge of the receptor-mediated basis of disease and how drug molecules interact with receptors and the wider physiome. Medicinal chemistry postulates that to understand a congeneric ligand series, or set thereof, is to understand the nature and requirements of a ligand binding site. Likewise, structural molecular biology posits that to understand a binding site is to understand the nature of ligands bound therein. Reality sits somewhere between these extremes, yet subsumes them both. Complementary to rules of ligand design, arising through decades of medicinal chemistry, structural biology and computational chemistry are able to elucidate the nature of binding site-ligand interactions, facilitating, at both pragmatic and conceptual levels, the drug discovery process.

Binding Sites↗
PubMed2006

Discovery of potential sorbitol dehydrogenase inhibitors from virtual screening.

Sorbitol dehydrogenase (SDH) is the second enzyme in the polyol pathway of glucose metabolism and is a possible target for the treatment of the complications of diabetes. In this study the molecular modelling program DOCK was used to analyse 249,071 compounds from the National Cancer Institute Database and predict those with high affinity for SDH. From a total of 21 tested the 7 compounds including flavin adenine dinucleotide disodium hydrate, (+)-Amethopterin, 3-hydroxy-2-napthoic(2-hydroxybenzylidene) hydrazide, folic acid, N-2,4-dinitrophenyl-L-cysteic acid, Vanillin azine and 1H-indole-2,3-dione,5-bromo-6-nitro-1-(2,3,4-tri-O-acetyl-alpha-L-arabinopyranosyl)-(9Cl), were shown to inhibit SDH and displayed IC50 values of 0.192 microM, 1.1 microM, 1.2 microM, 4.5 microM, 5.3 microM, 7 microM and 28 microM, respectively. These compounds may aid the design of pharmaceutical agents for the treatment of diabetes complications.

Database Management Systems↗
PubMedDate not supplied

Identification of a novel steroid derivative, NSC12983, as a paclitaxel-like tubulin assembly promoter by 3-D virtual screening.

By flexibly docking 9593 compounds of the NCI-3D database against the refined structure of beta-tubulin using DOCK 4.0, a long-forgotten synthetic steroid derivative, NSC12983, has been identified as a microtubule-stabilizing agent. The 32 top scorers includes NSC12983 and the three added references: paclitaxel, docetaxel and IDN5109. That is, 12.5% of the 0.33% top scorers are active. In addition, NSC12983 is active on Mycobacterium tuberculosis in vitro and in vivo, which might be due to its ability to promote the assembly of essential cell division protein.

Antineoplastic Agents, Phytogenic↗
PubMedDate not supplied

Consideration of molecular weight during compound selection in virtual target-based database screening.

Virtual database screening allows for millions of chemical compounds to be computationally selected based on structural complimentary to known inhibitors or to a target binding site on a biological macromolecule. Compound selection in virtual database screening when targeting a biological macromolecule is typically based on the interaction energy between the chemical compound and the target macromolecule. In the present study it is shown that this approach is biased toward the selection of high molecular weight compounds due to the contribution of the compound size to the energy score. To account for molecular weight during energy based screening, we propose normalization strategies based on the total number of heavy atoms in the chemical compounds being screened. This approach is computationally efficient and produces molecular weight distributions of selected compounds that can be selected to be (1) lower than that of the original database used in the virtual screening, which may be desirable for selection of leadlike compounds or (2) similar to that of the original database, which may be desirable for the selection of drug-like compounds. By eliminating the bias in target-based database screening toward higher molecular weight compounds it is anticipated that the proposed procedure will enhance the success rate of computer-aided drug design.

Computer-Aided Design↗
PubMedDate not supplied

An automated method for exploring targeted substructural diversity within sets of chemical structures.

Practicing medicinal chemists tend to treat a lead compound as an assemblage of its substructural parts. By iteratively confining their synthetic efforts in a localized fashion, they are able to systematically investigate how minor changes in certain portions of the molecule effect the properties of interest in the logical expectation that the observed beneficial changes will be cumulative. One disadvantage to this approach arises when large amounts of structure data begin to accumulate which is often the case in recent times due to such developments as high-throughput screening, virtual screening, and combinatorial chemistry. How then does one interactively mine this diverse data consistent with the desired substructural template, so those desirable structural features can be discovered and interpreted, especially when they may not occur in the most active compounds due to structural deficiencies in other portions of the molecule? In this paper, we present an algorithm to automate this process that has historically been performed in an ad-hoc and manual fashion. Using the proposed method, significantly larger numbers of compounds can be analyzed in this fashion, potentially discovering useful structural feature combinations that would not have otherwise been detected due to the sheer scale of modern structural and biological data collections.

Algorithms↗
PubMed2006

Virtual ligand screening: strategies, perspectives and limitations.

In contrast to high-throughput screening, in virtual ligand screening (VS), compounds are selected using computer programs to predict their binding to a target receptor. A key prerequisite is knowledge about the spatial and energetic criteria responsible for protein-ligand binding. The concepts and prerequisites to perform VS are summarized here, and explanations are sought for the enduring limitations of the technology. Target selection, analysis and preparation are discussed, as well as considerations about the compilation of candidate ligand libraries. The tools and strategies of a VS campaign, and the accuracy of scoring and ranking of the results, are also considered.

Binding Sites↗
PubMed2005

A low-molecular-weight compound discovered through virtual database screening inhibits Stat3 function in breast cancer cells.

This study focused on the screening of small-molecule inhibitors that target signal transducers and activators of transcription 3 (Stat3) in human breast carcinoma. The constitutive activation of Stat3 is frequently detected in human breast cancer cell lines as well as clinical breast cancer specimens and may play an important role in the oncogenesis of breast carcinoma. Activated Stat3 may participate in oncogenesis by stimulating cell proliferation, promoting tumor angiogenesis, and resisting apoptosis. Because a variety of human cancers are associated with constitutively active Stat3, Stat3 represents an attractive target for cancer therapy. In this study, of the nearly 429,000 compounds screened by virtual database screening, chemical samples of top 100 compounds identified as candidate small-molecule inhibitors of Stat3 were evaluated by using Stat3-dependent luciferase reporter as well as other cell-based assays. Through serial functional evaluation based on our established cell-based assays, one compound, termed STA-21, was identified as the best match for our selection criteria. Further investigation demonstrated that STA-21 inhibits Stat3 DNA binding activity, Stat3 dimerization, and Stat3-dependent luciferase activity. Moreover, STA-21 reduces the survival of breast carcinoma cells with constitutive Stat3 signaling but has minimal effect on the cells in which constitutive Stat3 signaling is absent. Together, these results demonstrate that STA-21 inhibits breast cancer cells that express constitutively active Stat3.

Breast Neoplasms↗
PubMed2005

Virtual colonoscopy: issues related to primary screening.

Virtual colonoscopy (VC) is a minimally invasive CT examination that has continued to rapidly evolve and improve as a diagnostic screening tool. Current state-of-the-art VC technique has already been shown to be highly effective for screening at the University of Wisconsin. Although more widespread implementation of VC screening faces multiple challenges and barriers, these are all greatly overshadowed by the immediate need for increased patient compliance in effective colorectal screening programs. Given the wide availability of CT and the favorable safety profile compared with optical colonoscopy, VC holds significant potential for addressing a very important yet preventable public health concern. This paper will briefly address some of the major issues related to the general application of VC for colorectal screening, such as diagnostic performance, development of an acceptable screening algorithm, and several technique-related issues.

Algorithms↗
PubMed2004

Colorectal neoplasia screening with virtual colonoscopy: when, at what cost, and with what national impact?

BACKGROUND & AIMS: When optimized, virtual colonoscopy may be highly sensitive for colorectal neoplasia. We evaluated the effectiveness and cost-effectiveness of virtual colonoscopy screening (VC) vs. colonoscopy screening (COLO) and the potential impact at the national level. METHODS: Using a Markov model, we estimated the clinical and economic consequences of VC and COLO from ages 50 to 80 years. Using census data, we made projections to the national level. RESULTS: In the best case considered (95%, 94%, and 87% sensitivity for colorectal cancer [CRC], polyps > or =10 mm, and polyps <10 mm), VC was nearly as effective as COLO. However, if test costs were equal, total cost per person was 15% greater for VC than COLO, making COLO dominant. When test cost for VC was < or =60% of test cost for COLO, the small benefit of COLO vs. VC cost >200,000 US dollars/incremental life-year. The greater the likelihood of being referred for colonoscopy after VC, the greater the advantage of COLO. With 75% screening adherence in the United States, VC and COLO could decrease CRC incidence by 46%-54%, with COLO requiring 6.9 million colonoscopies/yr, and VC, 3.2 million colonoscopies/yr, plus 5.4 million virtual colonoscopies/yr with VC. CONCLUSIONS: Even if screening test sensitivities were similar, COLO is likely to be preferred over VC unless virtual colonoscopy costs significantly less than colonoscopy. VC may be most appropriate in persons unlikely to need colonoscopy, such as those at low CRC risk. If VC were substituted for COLO, the demand on resources would shift from endoscopic to radiologic services, but would not diminish.

Aged↗
PubMedDate not supplied

Virtual colonoscopy: a new approach for colorectal cancer screening.

Virtual endoscopy is the processing of computerized tomography image data to create a virtual environment of the human body to allow diagnosis of disease processes. This new technique allows the observer the opportunity to interact with an image that is artificially generated by the computer. Virtual colonoscopy provides a method for processing data that can display computer images of the colon in a more anatomic life-like format to facilitate image interpretation and improve diagnostic accuracy. The clinical application of virtual endoscopic techniques is also being used with other procedures such as bronchoscopy, gastroscopy, cystoscopy, sinus imaging, virtual angioscopy, and cerebral ventriculography. Current screening recommendations for colorectal cancer are discussed in this article along with methods, advantages, challenges, and future opportunities for virtual colonoscopy.

Colonography, Computed Tomographic↗
PubMed2001

Virtual colonoscopy: a new tool for colorectal cancer screening.

Virtual colonoscopy or computed-tomography colonography is a promising new method for colorectal cancer screening. Helical computed tomography is used to generate high-resolution, two-dimensional axial images of the abdomen and pelvis. Three-dimensional images of the colon simulating those obtained with conventional colonoscopy can be reconstructed from the data obtained. Favorable attributes of virtual colonoscopy include its safety, high patient acceptance, and ability to provide a full structural evaluation of the entire colon. Multiple studies of virtual colonoscopy have been published in the literature in the past year regarding technique, image display, image reconstruction, clinical trial results, and feasibility as a screening tool. This manuscript will review the various studies in each of these areas.

Journal Article↗
PubMed2006

Discovery of a nanomolar inhibitor of the human murine double minute 2 (MDM2)-p53 interaction through an integrated, virtual database screening strategy.

An integrated, virtual database screening strategy has led to 7-[anilino(phenyl)methyl]-2-methyl-8-quinolinol (4, NSC 66811) as a novel inhibitor of the murine double minute 2 (MDM2)-p53 interaction. This quinolinol binds to MDM2 with a Ki of 120 nM and activates p53 in cancer cells with a mechanism of action consistent with targeting the MDM2-p53 interaction. It mimics three p53 residues critical in the binding to MDM2 and represents a promising new class of non-peptide inhibitors of the MDM2-p53 interaction.

Aniline Compounds↗
PubMed2006

Towards an automated virtual slide screening: theoretical considerations and practical experiences of automated tissue-based virtual diagnosis to be implemented in the Internet.

AIMS: To develop and implement an automated virtual slide screening system that distinguishes normal histological findings and several tissue--based crude (texture-based) diagnoses. THEORETICAL CONSIDERATIONS: Virtual slide technology has to handle and transfer images of GB Bytes in size. The performance of tissue based diagnosis can be separated into a) a sampling procedure to allocate the slide area containing the most significant diagnostic information, and b) the evaluation of the diagnosis obtained from the information present in the selected area. Nyquist's theorem that is broadly applied in acoustics, can also serve for quality assurance in image information analysis, especially to preset the accuracy of sampling. Texture-based diagnosis can be performed with recursive formulas that do not require a detailed segmentation procedure. The obtained results will then be transferred into a "self-learning" discrimination system that adjusts itself to changes of image parameters such as brightness, shading, or contrast. METHODS: Non-overlapping compartments of the original virtual slide (image) will be chosen at random and according to Nyquist's theorem (predefined error-rate). The compartments will be standardized by local filter operations, and are subject for texture analysis. The texture analysis is performed on the basis of a recursive formula that computes the median gray value and the local noise distribution. The computations will be performed at different magnifications that are adjusted to the most frequently used objectives (*2, *4.5, *10, *20, *40). The obtained data are statistically analyzed in a hierarchical sequence, and in relation to the clinical significance of the diagnosis. RESULTS: The system has been tested with a total of 896 lung cancer cases that include the diagnoses groups: cohort (1) normal lung--cancer; cancer subdivided: cohort (2) small cell lung cancer--non small cell lung cancer; non small cell lung cancer subdivided: cohort (3) squamous cell carcinoma--adenocarcinoma--large cell carcinoma. The system can classify all diagnoses of the cohorts (1) and (2) correctly in 100%, those of cohort (3) in more than 95%. The percentage of the selected area can be limited to only 10% of the original image without any increased error rate. CONCLUSION: The developed system is a fast and reliable procedure to fulfill all requirements for an automated "pre-screening" of virtual slides in lung pathology.

Journal Article↗
PubMed2003

Leveraging structural approaches: applications of NMR-based screening and X-ray crystallography for inhibitor design.

In the last several years, NMR strategies in drug discovery have evolved from a primarily structural focus to a set of technologies that are non-structural in nature but that have a much greater impact on the identification and optimization of real drug leads. NMR-based screening methods, such as the SHAPES strategy, help rapidly identify good starting points for drug design in a relatively high throughput implementation. The SHAPES method uses simple NMR techniques to detect binding of a limited, but diverse library of low molecular weight, soluble compounds to a potential drug target. SHAPES library compounds are derived largely from molecular frameworks most commonly found in known therapeutic agents. The NMR experiments used in these protocols are based on the well-known NMR techniques, and may be applied to targets with no limitation on molecular weight and no requirement for isotope labeling. Following screening, SHAPES hits may be used to guide virtual screening, synthesis of combinatorial libraries, and bias the first compounds that undergo high throughput screening. Integration of the SHAPES strategy with iterative X-ray crystallographic structure determination can be very useful in deriving an initial structural pharmacophore model and achieving significant in vitro potency in a short time frame. Here, examples are provided of how the combination of NMR SHAPES screening, virtual screening, molecular modeling and X-ray crystallography has led to novel drug scaffolds in several drug discovery programs: JNK3 MAP kinase and the fatty acid binding protein, aP2.

Binding Sites↗