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At least 721 records · Page 40Linked to original sources
PubMed2002

DHPLC analysis as a platform for molecular diagnosis of congenital disorders of glycosylation (CDG).

Since 1997, the molecular basis of six different types of Congenital Disorders of Glycosylation with a defect in the synthesis of N-glycans (CDG-I) has been identified. To assure an efficient molecular diagnosis of the six genes involved in these types, we established a denaturing high-pressure liquid chromatography (DHPLC) screening procedure. Primers were designed and conditions were optimised for the analysis of each exon of the PMM2, MPI, ALG6, ALG3, DPM1 and MPDU1 genes. Forty previously described PMM2 mutations were tested to evaluate the method. All of them could be detected. Hence, the sensitivity of the technique is virtually 100%. Screening of 17 novel cases with a tentative, clinical diagnosis of CDG-Ia identified mutations on both alleles in 14 of them, thereby confirming the diagnosis. Six of these mutations were not previously reported (G15E, G42R, Y64C, E93A, G214S and D223N). Sequencing of the complete coding sequence of PMM2 in the remaining three patients did not reveal mutations, corroborating the good performance of the DHPLC method. A similar DHPLC approach was also applied to CDG-Ib, CDG-Ic, CDG-Id, CDG-Ie and CDG-If samples. New mutations were identified in MPI (Y129C) and ALG6 (G227E). All results were confirmed by sequencing. We conclude that the DHPLC platform is a sensitive and efficient method for the rapid analysis of disease genes with a limited number of exons.

Chromatography, High Pressure Liquid↗
PubMedDate not supplied

Survival experience in the Breast Cancer Detection Demonstration Project.

Very high survival rates have been observed in four through 11 years of follow-up in 4,240 women with a histologically confirmed diagnosis of breast cancer in the Breast Cancer Detection Demonstration Project (BCDDP). The relative five, eight, and 10-year survival rates were 88, 83, and 79 percent, respectively. Allowances were made for lead-time bias among cancers detected through screening, and the validity of the findings was supported by internal analyses, which showed that length-time bias was of little, if any, importance, and that any possible "overdiagnosis" of cancer cases was also of small relevance. In view of current interest in the value of screening women before age 50, intensive analyses were made comparing the BCDDP data for women in their 40s with women in their 50s. In terms of kinds of breast cancers found, modality of finding them, and survival rates once they have been found, the parallel results for the two groups show that screening was virtually as effective in the younger as in the older women. Some authorities are of the opinion that the benefits of mammography after age 50 are well documented, but at younger ages the evidence is still inconclusive. The findings in this study show there is no doubt of the very successful results of screening for breast cancer with mammography in younger as well as older women. In comparing relative five-year and eight-year survival rates for women with invasive breast cancers detected through screening in the BCDDP, with those for cases diagnosed in the National Cancer Institute's Surveillance, Epidemiology and End Results (NCI SEER) program from 1977 to 1982, it is seen that for individual subcategories by tumor size and nodal class, the survival rates are about the same. However, for overall invasive cancers, the five-year and eight-year survival rates were 87 and 81 percent, respectively, for the BCDDP compared with 74 and 65 percent for SEER. Thus the substantial gains in survival followed the large shift toward a high proportion of cancers being diagnosed and treated in more favorable stages through the screening accomplishments. With respect to the relative case fatality rates, the complements of the relative survival rates, the eight-year rate of 19 percent for the BCDDP versus that of 35 percent for SEER connotes 46 percent fewer women dying in the BCDDP group.

Adult↗
PubMed2002

Colon cancer: detection and prevention.

Recent data have advanced our ability to detect, survey, and manage patients with colonic neoplasia. Current studies and consensus statements increasingly support the role of colonoscopic screening over less invasive testing such as FOBT or FS for appropriately selected individuals. There are many issues, however, that remain unresolved. What is the appropriate surveillance of an individual with a single family member who had colon cancer at an early age? How should family members of suspected HNPCC kindreds be managed? There has yet to be a prospective cohort validation of the Bethesda criteria in directing clinical practice, with the endpoint of mortality reduction. Questions regarding prophylaxis with dietary supplements and medications are exciting areas that are currently under study. As newer technologies become clinically available for molecular diagnostics and screening, and virtual colonoscopy with computed tomography and magnetic resonance disseminates, there will undoubtedly be new questions to be answered regarding their ability to aid in the detection and management of colon cancer.

Chemoprevention↗
PubMed2006

Screening-based discovery and structural dissection of a novel family 18 chitinase inhibitor.

Family 18 chitinases play key roles in the life cycles of a variety of organisms ranging from bacteria to man. Very recently it has been shown that one of the mammalian chitinases is highly overexpressed in the asthmatic lung and contributes to the pathogenic process through recruitment of inflammatory cells. Although several potent natural product chitinase inhibitors have been identified, their chemotherapeutic potential or their use as cell biological tools is limited due to their size, complex chemistry, and limited availability. We describe a virtual screening-based approach to identification of a novel, purine-based, chitinase inhibitor. This inhibitor acts in the low micromolar (Ki=2.8+/-0.2 microM) range in a competitive mode. Dissection of the binding mode by x-ray crystallography reveals that the compound, which consists of two linked caffeine moieties, binds in the active site through extensive and not previously observed stacking interactions with conserved, solvent exposed tryptophans. Such exposed aromatics are also present in the structures of many other carbohydrate processing enzymes. The compound exhibits favorable chemical properties and is likely to be useful as a general scaffold for development of pan-family 18 chitinase inhibitors.

Algorithms↗
PubMed2004

Strategies for compound selection.

In-house pharmaceutical collections are no longer sufficient for sampling chemical spaces. As novel bioactive chemotypes are successfully identified by virtual and high -throughput screening, the ability to rapidly sift through large numbers of chemicals prior to acquisition or experiment is required. Strategies for compound selection include some of the following steps: 1.) database assembly ('in silico' inventory); 2a.) structural integrity verification (keep unique structures only); 2b.) limited exploration of alternative chemical representations for the uniques (stereoisomers, tautomers, ionization states); 3.) property and structural filtering (remove unwanted structures); 4.) 3D-structure generation (for virtual screening or 3D-based similarity); 5a.) clustering or statistical design for selection; 5b.) similarity-based selection (if bioactives are known); 5c.) receptor-based selection (if target binding site is known); 6.) add a random subset to the final list.

Cluster Analysis↗
PubMed2004

New approaches in identifying drugs to inactivate oncogene products.

With an information explosion on the molecular mechanism of oncogenesis, the completion of the human genome sequence project, and the advances in genomic and proteomic methods, many therapeutic targets for various cancers have been identified. It is timely that a number of new drug development techniques have been developed in this last decade. Candidate drug targets can now be efficiently validated with RNA interference and transgenic animals studies. Combinatorial chemistry provides large numbers of chemical compounds for drug lead discovery and optimization. High throughput assays and high content cell-based assays, in conjunction with sophisticated robotics, are now available for screening large numbers of compounds. Based on X-ray crystallographic structure data, drug leads can be discovered through in silico screening of virtual libraries. By applying these various drug discovery techniques, it is anticipated that more potent and specific anti-cancer agents will be discovered within the next decade.

Combinatorial Chemistry Techniques↗
PubMed2005

Druggability indices for protein targets derived from NMR-based screening data.

An analysis of heteronuclear-NMR-based screening data is used to derive relationships between the ability of small molecules to bind to a protein and various parameters that describe the protein binding site. It is found that a simple model including terms for polar and apolar surface area, surface complexity, and pocket dimensions accurately predicts the experimental screening hit rates with an R(2) of 0.72, an adjusted R(2) of 0.65, and a leave-one-out Q(2) of 0.56. Application of the model to predict the druggability of protein targets not used in the training set correctly classified 94% of the proteins for which high-affinity, noncovalent, druglike leads have been reported. In addition to understanding the pocket characteristics that contribute to high-affinity binding, the relationships that have been defined allow for quantitative comparative analyses of protein binding sites for use in target assessment and validation, virtual ligand screening, and structure-based drug design.

Algorithms↗
PubMed2002

Application of topological descriptors in QSAR and drug design: history and new trends.

Powerful methodologies for drug design and drug database screening and selection are presently available. Studies relating the structure of molecules to a property or a biological activity by means of statistical tools (QSPR and QSAR studies, respectively) are particularly relevant. An important point for this methodology is the use of good structural descriptors that are representative of the molecular features responsible for the relevant activity. Topological indices (TIs) are two-dimensional descriptors which take into account the internal atomic arrangement of compounds, and which encode in numerical form information about molecular size, shape, branching, presence of heteroatoms and multiple bonds. The usefulness of TIs in QSPR and QSAR studies has been extensively demonstrated, and they have also been used as a measure of structural similarity or diversity by their application to databases virtually generated by computer. In this article we will briefly review the history of TIs, their advantages and limitations with respect to other descriptors, and their possibilities in drug design and database selection. These applications rely on new computational techniques such as virtual combinatorial synthesis, virtual computational screening or inverse QSAR.

Algorithms↗
PubMed2007

Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking.

One approach to incorporate protein flexibility in molecular docking is the use of an ensemble consisting of multiple protein structures. Sequentially docking each ligand into a large number of protein structures is computationally too expensive to allow large-scale database screening. It is challenging to achieve a good balance between docking accuracy and computational efficiency. In this work, we have developed a fast, novel docking algorithm utilizing multiple protein structures, referred to as ensemble docking, to account for protein structural variations. The algorithm can simultaneously dock a ligand into an ensemble of protein structures and automatically select an optimal protein structure that best fits the ligand by optimizing both ligand coordinates and the conformational variable m, where m represents the m-th structure in the protein ensemble. The docking algorithm was validated on 10 protein ensembles containing 105 crystal structures and 87 ligands in terms of binding mode and energy score predictions. A success rate of 93% was obtained with the criterion of root-mean-square deviation <2.5 A if the top five orientations for each ligand were considered, comparable to that of sequential docking in which scores for individual docking are merged into one list by re-ranking, and significantly better than that of single rigid-receptor docking (75% on average). Similar trends were also observed in binding score predictions and enrichment tests of virtual database screening. The ensemble docking algorithm is computationally efficient, with a computational time comparable to that for docking a ligand into a single protein structure. In contrast, the computational time for the sequential docking method increases linearly with the number of protein structures in the ensemble. The algorithm was further evaluated using a more realistic ensemble in which the corresponding bound protein structures of inhibitors were excluded. The results show that ensemble docking successfully predicts the binding modes of the inhibitors, and discriminates the inhibitors from a set of noninhibitors with similar chemical properties. Although multiple experimental structures were used in the present work, our algorithm can be easily applied to multiple protein conformations generated by computational methods, and helps improve the efficiency of other existing multiple protein structure(MPS)-based methods to accommodate protein flexibility.

Algorithms↗
PubMed2004

Lead identification for modulators of multidrug resistance based on in silico screening with a pharmacophoric feature model.

Considerable effort has been devoted to the characterization of P-glycoprotein - drug interaction in the past. Systematic quantitative structure-activity relationship (QSAR) studies identified both predictive physicochemical parameters and pharmacophoric substructures within homologous series of compounds. Comparative molecular field analysis (CoMFA) led to distinct 3D-QSAR models for propafenone and phenothiazine analogs. Recently, several pharmacophore models have been generated for diverse sets of ligands. Starting from a training set of 15 propafenone-type MDR-modulators, we established a chemical function-based pharmacophore model. The pharmacophoric features identified by this model were (i) one hydrogen bond acceptor, (ii) one hydrophobic area, (iii) two aromatic hydrophobic areas, and (iv) one positive ionizable group. In silico screening of the Derwent World Drug Index using the model led to identification of 28 compounds. Substances retrieved by database screening are diverse in structure and include dihydropyridines, chloroquine analogs, phenothiazines, and terfenadine. On the basis of its general applicability, the presented 3DQSAR model allows in silico screening of virtual compound libraries to identify new potential lead compounds.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMed2005

The MPSim-Dock hierarchical docking algorithm: application to the eight trypsin inhibitor cocrystals.

To help improve the accuracy of protein-ligand docking as a useful tool for drug discovery, we developed MPSim-Dock, which ensures a comprehensive sampling of diverse families of ligand conformations in the binding region followed by an enrichment of the good energy scoring families so that the energy scores of the sampled conformations can be reliably used to select the best conformation of the ligand. This combines elements of DOCK4.0 with molecular dynamics (MD) methods available in the software, MPSim. We test here the efficacy of MPSim-Dock to predict the 64 protein-ligand combinations formed by starting with eight trypsin cocrystals, and crossdocking the other seven ligands to each protein conformation. We consider this as a model for how well the method would work for one given target protein structure. Using as a criterion that the structures within 2 kcal/mol of the top scoring include a conformation within a coordinate root mean square (CRMS) of 1 A of the crystal structure, we find that 100% of the 64 cases are predicted correctly. This indicates that MPSim-Dock can be used reliably to identify strongly binding ligands, making it useful for virtual ligand screening.

Algorithms↗
PubMed2006

An iterative knowledge-based scoring function to predict protein-ligand interactions: II. Validation of the scoring function.

We have developed an iterative knowledge-based scoring function (ITScore) to describe protein-ligand interactions. Here, we assess ITScore through extensive tests on native structure identification, binding affinity prediction, and virtual database screening. Specifically, ITScore was first applied to a test set of 100 protein-ligand complexes constructed by Wang et al. (J Med Chem 2003, 46, 2287), and compared with 14 other scoring functions. The results show that ITScore yielded a high success rate of 82% on identifying native-like binding modes under the criterion of rmsd < or = 2 A for each top-ranked ligand conformation. The success rate increased to 98% if the top five conformations were considered for each ligand. In the case of binding affinity prediction, ITScore also obtained a good correlation for this test set (R = 0.65). Next, ITScore was used to predict binding affinities of a second diverse test set of 77 protein-ligand complexes prepared by Muegge and Martin (J Med Chem 1999, 42, 791), and compared with four other widely used knowledge-based scoring functions. ITScore yielded a high correlation of R2 = 0.65 (or R = 0.81) in the affinity prediction. Finally, enrichment tests were performed with ITScore against four target proteins using the compound databases constructed by Jacobsson et al. (J Med Chem 2003, 46, 5781). The results were compared with those of eight other scoring functions. ITScore yielded high enrichments in all four database screening tests. ITScore can be easily combined with the existing docking programs for the use of structure-based drug design.

Acetylcholinesterase↗
PubMed2004

A minimalist approach to fragment-based ligand design using common rings and linkers: application to kinase inhibitors.

We present a novel method for stepwise scaffold assembly that integrates fragment-by-fragment ligand design approaches with high-throughput virtual library screening (COREGEN). As an extension of our earlier studies of common features present in drug molecules, we investigate the hypothesis that most pharmaceutically interesting ligands can be expressed in terms of the ring-linker frameworks that comprise them. Analysis of 119 published kinase inhibitors from at least 18 different targets illustrates that a basis set of 4 rings and 8 linkers is sufficient to describe approximately 90% of ring and linker occurrences, respectively. A similar result was derived from a larger set of approximately 40,000 kinase inhibitors from curated patents. A method for ring-linker-based assembly of scaffold libraries that uses experimental information to guide the placement of anchor fragments is validated using a set of reported kinase inhibitors of Bcr-Abl, Cdk2, and Src. In every case, the predominant structural motif of reported ligand cores is reproduced and variations are suggested. To underscore generality of this approach, a novel scaffold for a cyclooxygenase-2 (COX-2) selective ligand is proposed.

Algorithms↗
PubMed1995

Ultrarapid mutation detection by multiplex, solid-phase chemical cleavage.

The chemical cleavage of mismatches in heteroduplexes formed by probe and test DNA detects and locates any sequence change in long DNA segments (approximately 1.8 kb), and its efficiency has been well tested in the analysis of both average (e.g., coagulation factor IX) and large, complex genes (e.g., coagulation factor VIII and dystrophin). In the latter application RT/PCR products allow the examination of all essential sequences of the gene in a minimum number of reactions. We use two specific chemical reactants (hydroxylamine and osmium tetroxide) and piperidine cleavage of the above procedure to develop a very fast mutation screening method. This is based on: (1) 5' or internal fluorescent labeling to allow concurrent screening of three to four DNA fragments and (2) solid-phase chemistry to use a microtiter format and reduce the time required for the procedure, from amplification of sequence to gel loading inclusive, to one person-working-day. We test the two variations of the method, one entailing 5' labeling of probe DNA and the other uniform labeling of both probe and target DNA, by detecting 114 known hemophilia B (coagulation factor IX) mutations and by analyzing 129 new patients. Uniform labeling of both probe and target DNA prior to formation of the heteroduplexes leads to almost two-fold redundancy in the ability to detect mutations. Alternatively, the latter procedure may offer very efficient though less than 100% screening for sequence changes with only hydroxylamine. The full method with two chemical reactions (hydroxylamine and osmium tetroxide) should allow one person to screen with virtually 100% accuracy more than 300 kb of sequence in three ABI 373 gels in 1 day.

Base Sequence↗
PubMed2000

Recent developments in structure-based drug design.

Structure-based design has emerged as a new tool in medicinal chemistry. A prerequisite for this new approach is an understanding of the principles of molecular recognition in protein-ligand complexes. If the three-dimensional structure of a given protein is known, this information can be directly exploited for the retrieval and design of new ligands. Structure-based ligand design is an iterative approach. First of all, it requires the crystal structure or a model derived from the crystal structure of a closely related homolog of the target protein, preferentially complexed with a ligand. This complex unravels the binding mode and conformation of a ligand under investigation and indicates the essential aspects determining its binding affinity. It is then used to generate new ideas about ways of improving an existing ligand or of developing new alternative bonding skeletons. Computational methods supplemented by molecular graphics are applied to assist this step of hypothesis generation. The features of the protein binding pocket can be translated into queries used for virtual computer screening of large compound libraries or to design novel ligands de novo. These initial proposals must be confirmed experimentally. Subsequently they are optimized toward higher affinity and better selectivity. The latter aspect is of utmost importance in defining and controlling the pharmacological profile of a ligand. A prerequisite to tailoring selectivity by rational design is a detailed understanding of molecular parameters determining selectivity. Taking examples from current drug development programs (HIV proteinase, t-RNA transglycosylase, thymidylate synthase, thrombin and, related serine proteinases), we describe recent advances in lead discovery via computer screening, iterative design, and understanding of selectivity discrimination.

Chemistry, Pharmaceutical↗
PubMed2002

Information-based methods in the development of antiparasitic drugs.

The discovery and optimization of antiparasitic compounds has profited by information-based methods newly emerged in the modern drug development process. The generation of computer models enables the cost-efficient and fast computational screening of virtual compound libraries for biologically active molecules. Two sources of information are available: structure-based drug design utilizes information about the disease target. We describe two different computational approaches, realized as the fast, flexible docking program FlexX and as the de novo design program LUDI. Ligand-based drug design, on the other hand, requires the structures and experimental data from biologically active compounds. Parasitic targets and antiparasitic compounds studied by various information-based methods include trypanosomal trypanothione reductase, antiprotozoal bisphosphonates, and trypanosomal glycosomal glyceraldehyde-3-phosphate dehydrogenase.

Animals↗
PubMed2006

Electrostatic evaluation of isosteric analogues.

A method is presented for enumerating a large number of isosteric analogues of a ligand from a known protein-ligand complex structure and then rapidly calculating an estimate of their binding energies. This approach takes full advantage of the observed crystal structure, by reusing the atomic co-ordinates determined experimentally for one ligand, to approximate those of similar compounds that have approximately the same shape. By assuming that compounds with similar shapes adopt similar binding poses, and that entropic and protein flexibility effects are approximately constant across such an isosteric series ("the frozen ligand approximation"), it is possible to order their binding affinities relatively accurately. Additionally, the constraint that the atomic coordinates are invariant allows for a dramatic simplification in the Poisson-Boltzmann method used to calculation the electrostatic component of the binding energy. This algorithmic improvement allows for the calculation of tens of thousands of binding energies per second for drug-like molecules, enabling this technique to be used in screening large virtual libraries of isosteric analogues. Most significantly, this procedure is shown to be able to reproduce SAR effects of subtle medicinal chemistry substitutions. Finally, this paper reports the results of the proposed methodology on seven model systems; dihydrofolate reductase, Lck kinase, ribosome inactivating protein, L: -arabinose binding protein, neuraminidase, HIV-1 reverse transcriptase and COX-2.

Binding Sites↗