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PubMed2004

In silico approaches for predicting ADME properties of drugs.

Combinatorial chemistry and high-throughput screening have increased the possibility of finding new lead compounds at much shorter time periods than conventional medicinal chemistry. However, too much promising drug candidates often fail because of unsatisfactory ADME properties. In silico ADME studies are expected to reduce the risk of late-stage attrition of drug development and to optimize screening and testing by looking at only the promising compounds. To this end, many in silico approaches for predicting ADME properties of compounds from their chemical structure have been developed, ranging from data-based approaches such as quantitative structure-activity relationship (QSAR), similarity searches, and 3-dimensional QSAR, to structure-based methods such as ligand-protein docking and pharmacophore modelling. In addition, several methods of integrating ADME properties to predict pharmacokinetics at the organ or body level have been studied. In this article, we briefly summarize in silico ADME approaches.

Animals↗
PubMed2002

Using in silico biology to facilitate drug development.

G protein-coupled receptor (GPCR) mediation of cardiac excitability is often overlooked in predicting the likelihood that a compound will alter repolarization. While the areas of GPCR signal transduction and electrophysiology are rich in data, experiments combining the two are difficult. In silico modelling facilitates the integration of all relevant data in both areas to explore the hypothesis that critical associations may exist between the different GPCR signalling mechanisms and cardiac excitability and repolarization. An example of this linkage is suggested by the observation that a mutation of the gene encoding HERG, the pore-forming subunit of the rapidly activating delayed rectifier K+ current (I(Kr)), leads to a form of long QT syndrome in which affected individuals are vulnerable to stress-induced arrhythmia following beta-adrenergic stimulation. Using Physiome's In Silico Cell, we constructed a model integrating the signalling mechanisms of second messengers cAMP and protein kinase A with I(Kr) in a cardiac myocyte. We analysed the model to identify the second messengers that most strongly influence I(Kr) behaviour. Our conclusions indicate that the dynamics of regulation are multifactorial, and that Physiome's approach to in silico modelling helps elucidate the subtle control mechanisms at play.

Amino Acid Motifs↗
PubMed2006

Demonstration of in silico docking at a large scale on grid infrastructure.

WISDOM stands for World-wide In Silico Docking On Malaria. First step toward enabling the in silico drug discovery pipeline on a grid infrastructure, this CPU consuming application generating large data flows was deployed successfully on EGEE, the largest grid infrastructure in the world, during the summer 2005. 46 million docking scores were computed in 6 weeks. The proposed demonstration presents the submission of in silico docking jobs at a large scale on the grid. The demonstration will use the new middleware stack gLite developed within the EGEE project.

Europe↗
PubMed1991

Shear bond strength of silicoated bonded orthodontic attachments.

The shear bond strength of bonded orthodontic attachments, coated with a silicon oxide layer to enhance adhesion, was tested and compared to that of untreated attachments. Twenty buttons for direct bonding (test group) were "silicoated" and bonded to surgically removed, unerupted human third molars, using "Right-On" adhesive. The control group consisted of 20 similar teeth to which untreated buttons were bonded. Half of the specimens in each group were then thermocycled to stress the bonds. Shear strength was tested with the use of the Instron Universal testing machine. The mean shear bond strength of the silicoated attachments was found to be higher than that of the untreated attachments. This was a highly significant finding (p less than 0.005). The bond strength after thermocycling decreased in both the test and control groups, although this decrease was only significant at the level p less than 0.01. The results obtained from this study indicate that silicoating of orthodontic attachments prior to bonding significantly increases their shear bond strength to dental enamel.

Dental Bonding↗
PubMed2026

Epigenetics and In Silico Transcriptome Analysis of Pediatric Acute Myeloid Leukemia.

Pediatric acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy that accounts for about 15%-20% of childhood leukemias. Despite therapeutic advances, relapses remain common, and survival for high-risk patients is below 60%. Unlike adult AML, pediatric AML displays distinct genetic mutations, including FLT3-ITD, NPM1, KMT2A rearrangements, and core-binding factors (CBF) fusions, as well as extensive epigenetic dysregulation. Aberrant DNA methylation, histone modifications, and altered non-coding RNA expressions disrupt hematopoietic differentiation and activate oncogenic transcriptional networks. Recent advances in silico transcriptomic analysis have transformed the study of pediatric AML by integrating gene expression and epigenetic data to identify molecular drivers and regulatory networks. Computational RNA-seq pipelines and pathway analyses have highlighted key epigenetic regulators, including DNMT3A, TET2, and HDACs, as potential therapeutic targets. Multi-omics approaches combining transcriptomic, methylomic, and chromatin accessibility data are increasingly used to define biomarkers for diagnosis, prognosis, and therapeutic response. This review provides a comprehensive overview of the molecular and epigenetic landscape of pediatric AML, emphasizing the power of in silico transcriptome analysis to uncover disease mechanisms, refine patient stratification, and guide the development of precision-based epigenetic therapies aimed at improving long-term outcomes in children with AML.

Humans↗
PubMed2026

Patterns of antimicrobial resistance genes in pathogens across One Health sectors in Ireland: an in silico approach.

As part of a rapid risk assessment, an in silico approach was used to detect antimicrobial resistance (AMR) in pathogenic isolates from humans, animals, and the environment. A total of 11,670 genomic data sets were retrieved from the NCBI Pathogen Detection system for Ireland, which represented 47 pathogenic species, including Salmonella enterica, Escherichia coli/Shigella spp., Staphylococcus aureus, Klebsiella pneumoniae, and Enterococcus faecium. Identifying the most critical pathogenic strains over time is essential, as these organisms significantly contribute to mortality, morbidity, and hospitalization. The analysis identified 799 antimicrobial resistance genes (ARGs), including their allelic diversity, 117 plasmid replicons, and 274 virulence factors. Several critical ARGs, particularly those conferring resistance to beta-lactams, aminoglycosides, quinolones, and colistin, were common across isolates originating from human, animal, and environmental sources, suggesting shared resistance profiles across One Health sectors. Klebsiella pneumoniae, E. coli/Shigella spp., S. enterica, and S. aureus were the dominant hosts of these ARGs and associated mobile genetic elements. Increasing resistance across major antibiotic classes aligned with trends reported across other European countries. This study provides a national-scale in silico comparison of AMR across pathogens and One Health sectors using publicly available genomic data. The findings help reinforce Ireland's AMR surveillance by showing which resistance genes are present and how they spread across critical pathogens in humans, animals, and the environment. These findings highlight the urgent need for improved antibiotic stewardship and integrated One Health surveillance to limit the emergence and spread of AMR.IMPORTANCEAntimicrobial resistance (AMR) is a growing threat to human, animal, and environmental health. This study used publicly available genomic data to identify antimicrobial resistance genes (ARGs) in key bacterial pathogens circulating in Ireland. By analyzing over 11,000 genomes from humans, animals, and the environment, we found that several dangerous resistance genes, including those against last-resort antibiotics, were widespread across different sources. The study highlights which bacteria and resistance genes are most critical and how they may spread between humans, animals, and the environment. These insights provide a national snapshot of AMR, supporting more effective monitoring and prevention strategies. By revealing patterns of resistance and modes of transmission, our findings underscore the importance of coordinated antibiotic stewardship and One Health approaches to slow the emergence and spread of resistant infections, protecting public health and ensuring antibiotics remain effective.

Humans↗
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↗
PubMed2006

In silico ADMET traffic lights as a tool for the prioritization of HTS hits.

The need for in silico characterization of HTS hit structures as part of a data-driven hit-selection process is demonstrated. A solution is described in the form of an in silico ADMET traffic light and PhysChem scoring system. This has been extensively validated with in-house data at Bayer, published data, and a collection of launched small-molecule oral drugs.

Drug Design↗
PubMed2007

3D in silico modeling of the human respiratory system for inhaled drug delivery and imaging analysis.

The efficacies of inhaled pharmacologic drugs could be improved if drugs could be targeted to appropriate sites within the human respiratory system. The spatial deposition patterns of particles can now be detected with a high degree of resolution using advanced techniques of imaging (e.g., SPECT). However, the effectiveness of such laboratory regimens has been limited by the inability to clearly identify airway composition within images. Therefore, we have developed a theoretical protocol to map airways within human lungs that is designed to be used in a complementary manner with laboratory investigations. The in silico model has two components: a mathematical model based on concepts of topology; and, a computer algorithm which tracks the millions of constituent lung airways. The in silico model produces 3D lung structures that are anatomically correct and can be customized to each patient. We have applied the protocol to a SPECT study where the interiors of lungs were partitioned into a series of ten nested shells. Airway composition in the respective shells provides a heretofore unavailable quantification of scintigraphy images. The protocol can be employed in a practical manner in the medical arena to aid in the interpretation of SPECT images, and to provide a platform for the design of human subject tests.

Administration, Inhalation↗
PubMed2006

In silico predictability of allergenicity: from amino acid sequence via 3-D structure to allergenicity.

In relation to the prediction of allergenicity three aspects have to be discussed: IgE immunogenicity, IgE cross-reactivity, and T-cell cross-reactivity. IgE immunogenicity depends largely on factors other than the protein itself: the context and dose and "history" of the protein by the time it reaches the immune system. It is, therefore, not fully predictable from structural information. In contrast, IgE cross-reactivity can be much more reliably assessed by in-silico homology searches in combination with in vitro IgE antibody assays. The in-silico homology search is unlikely to miss potential cross-reactivity with sequenced allergens. So far, no biologically relevant cross-reactivity at the antibody level has been demonstrated between proteins without easily demonstrable homology. T-cell cross-reactivity is much more difficult to predict than B-cell cross-reactivity. Moreover, its effects are more diverse. Yet, pre-existing cross-reactive T-cell activity is likely to influence the outcome not only of the immune response, but also of the effect phase of the allergic reaction. The question of whether any antigen can be allergenic is still a matter of debate.

Allergens↗
PubMed2003

Identification of expressed sequence tags preferentially expressed in human placentas by in silico subtraction.

OBJECTIVES: To identify expressed sequence tag (EST) clusters preferentially expressed in placentas. METHODS: The National Center for Biotechnology's online UniGene database contains 14 placenta libraries. In silico (computer-based) subtraction compared placenta libraries against the remaining libraries to identify transcripts preferentially expressed in placentas. For known genes, placental expression or their use in prenatal diagnosis was then explored online using LocusLink and PubMed. RESULTS: Placentas preferentially expressed 475 EST clusters. Of these, 18 EST clusters with no known function were expressed exclusively in placentas. Of the remaining 457 EST clusters, 90 showed preferential placental expression by >/=25 times. Of these 90, literature searches on the 45 EST clusters with known functions showed 44 linked to placental physiology or proposed as markers for prenatal diagnosis [i.e. beta-hCG, pregnancy-specific glycoproteins, human placental lactogens, pregnancy-associated plasma protein A (PAPP-A)]. Selected genes with known function in pregnancy but whose preferential placental expression fell below the factor of 25 threshold were also identified. CONCLUSION: In silico subtraction identified 44 previously studied genes involved in placental physiology as well as 63 EST clusters preferentially expressed in placental tissue, which may serve as targets for future studies seeking novel markers for prenatal diagnosis or to better understand placental genetics.

Adult↗
PubMed2005

Analysis of phosphatase and tensin homolog tumor suppressor interacting proteins by in vitro and in silico proteomics.

The phosphatase and tensin homolog (PTEN) tumor suppressor is a multifunctional protein deregulated in many types of cancer. To date, a comprehensive documentation of PTEN interacting proteins has not been performed. The goal of our study was to characterize the PTEN interactome using affinity pull-down and tandem mass spectrometry (MS/MS). Wild-type PTEN cDNA was inserted into pTRC-His2 vector to create a 6-His tagged protein, which was expressed in Escherichia coli. Lysate from a human lymphoma cell line was used in pull-down assays, utilizing affinity for nickel-agarose beads. Bound proteins were eluted with imidazole, digested and analyzed on an LCQ DecaXP ion trap mass spectrometer. The nickel affinity pull-down efficiency was evaluated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and Western blot analysis. Acquired data were searched against the NCBI nr.fasta nonredundant protein database using the SEQUEST algorithm and screened using INTERACT and ProteinProphet. All experiments were performed in duplicate with 6-His-lacZ serving as control. A total of 79 proteins were identified in the wild-type 6-His-PTEN pull-down by MS/MS. We further validated a subset of the proteins present in the PTEN interactome by performing immunoprecipitation using an anti-PTEN antibody and establishing the presence of the proteins in the immunocomplex by Western blot analysis. A search of published PTEN interactions was also performed using Online Mendelian Inheritance in Man, Human Protein Reference Database, the IntAct Project database, and PubMed. This in silico analysis confirmed 42 out of 79 (53%) of the proteins identified by MS/MS. The remaining 37 proteins represent probable PTEN interactions not previously documented in public databases or reported in the literature. These results highlight the value of combining both in vitro biochemical approaches with in silico analyses for a comprehensive study of protein-protein interactions.

Algorithms↗
PubMed2005

The role and application of in silico docking in chemical genomics research.

In silico docking techniques are being used to investigate the complementarity at the molecular level of a ligand and a protein target. As such, docking studies can be used to identify the structural features that are important for binding and for in silico screening efforts in which suitable binding partners can be identified. Here we describe a practical approach for setting up docking simulations using different docking programs. We also cover the analysis and rescoring of the obtained docking poses. Possible pitfalls in the docking studies are discussed and hints are provided to resolve commonly occurring problems.

Binding Sites↗
PubMed1986

Silico-acrylate contact lenses for extended wear.

Extended wear contact lenses (EWCL) have been successfully used for the correction of aphakia. Disadvantages of soft EWCL are lens precipitates, lens loss and failure to correct higher astigmatic errors. Silico-acrylate rigid EWCL with high oxygen transmissibility have been used in this study to correct aphakia and higher astigmatic errors. Fourteen eyes were fitted with Boston IV lenses and observed for a mean of 6.5 months. All patients tolerated the rigid EWCL well without important complications. One patient discontinued lens wear because of discomfort without obvious clinical abnormalities. Rigid silico-acrylate EWCL are a reliable alternative for soft EWCL and are in some cases to be preferred to soft EWCL.

Acrylates↗
PubMedDate not supplied

Novel sequence variants of the genes associated with the multiple endocrine neoplasia syndromes 1 and 2. analysis by an "in silico approach.".

MEN syndromes (1 and 2) are hereditary tumor syndromes inherited as autosomal dominant traits. The genes that harbor the mutations responsible for the development of these syndromes have been cloned in recent years. In the present study we applied an "in silico" approach to find previously undescribed sequence variants of the RET protooncogene and the MEN1 gene. Sequence comparisons were performed at the National Center for Biotechnology Information Database by the search tool blastn. We found several sequence alterations in both coding and non-coding sequences. The majority of polymorphisms described to date were found by our approach, in addition we observed novel sequence variants of both genes as well. These sequence variants may have both diagnostic and theoretical relevance. In silico strategies may represent new, and potentially effective ways for finding novel sequence variants.

Amino Acid Sequence↗
PubMed2006

Genome-scale in silico aided metabolic analysis and flux comparisons of Escherichia coli to improve succinate production.

In the post-genome era, it is one challenge to understand the cellular metabolism at the systematic levels. Mathematical modeling of microorganisms and subsequent computer simulation are effective tools for systems biology. In this paper, based on the genome-scale Escherichia coli stoichiometric model iJR904, through the GAMS linear programming package, the in silico maximal succinate yield was estimated to be 1.714 mol/mol glucose. When another two constraints were added, the maximal succinate yield dropped to 1.60 mol/mol glucose. Further analysis substantiated the uniqueness of the flux distribution under such constraints. After comparisons with the metabolic flux analysis (MFA) results computed from the wet experimental data of the three kinds of E. coli, three potential improvement target sites, the glucose phosphotransferase transport system, the pyruvate carboxylase, and the glyoxylate shunt, were identified and selected for the genetic modifications. All the three genetic modified strains showed increased succinate yield. The final strain TUQ19/pQZ6 had a high yield of 1.29 mol succinate/mol glucose and high productivity. The success of the above experiments proved that this in silico optimal succinate production pathway is reasonable and practical. This method may also be used as a general strategy to help enhance the yields of other favorable metabolites in E. coli.

Anaerobiosis↗
PubMed2006

Tissue expression map of a large number of expressed sequence tags and its application to in silico screening of stress response genes in common wheat.

In order to assess global changes in gene expression patterns in stress-induced tissues, we conducted large-scale analysis of expressed sequence tags (ESTs) in common wheat. Twenty-one cDNA libraries derived from stress-induced tissues, such as callus, as well as liquid cultures and abiotic stress conditions (temperature treatment, desiccation, photoperiod, moisture and ABA) were constructed. Several thousand colonies were randomly selected from each of these 21 cDNA libraries and sequenced from both the 5' and 3' ends. By computing abundantly expressed ESTs, correlated expression patterns of genes across the tissues were monitored. Furthermore, the relationships between gene expression profiles among the stress-induced tissues were inferred from the gene expression patterns. Multi-dimensional analysis of EST data is analogous to microarray experiments. As an example, genes specifically induced and/or suppressed by cold acclimation and heat-shock treatments were selected in silico. Four hundred and ninety genes showing fivefold induction or 218 genes for suppression in comparison to the control expression level were selected. These selected genes were annotated with the BLAST search. Furthermore, gene ontology was conducted for these genes with the InterPro search. Because genes regulated in response to temperature treatment were successfully selected, this method can be applied to other stress-treated tissues. Then, the method was applied to screen genes in response to abiotic stresses such as drought and ABA treatments. In silico selection of screened genes from virtual display should provide a powerful tool for functional plant genomics.

Abscisic Acid↗
PubMed2007

Validation of in silico-predicted genic SNPs in white clover (Trifolium repens L.), an outbreeding allopolyploid species.

White clover (Trifolium repens L.) is an obligate outbreeding allotetraploid forage legume. Gene-associated SNPs provide the optimum genetic system for improvement of such crop species. An EST resource obtained from multiple cDNA libraries constructed from numerous genotypes of a single cultivar has been used for in silico SNP discovery and validation. A total of 58 from 236 selected sequence clusters (24.5%) were fully validated as containing polymorphic SNPs by genotypic analysis across the parents and progeny of several two-way pseudo-testcross mapping families. The clusters include genes belonging to a broad range of predicted functional categories. Polymorphic SNP-containing ESTs have also been used for comparative genomic analysis by comparison with whole genome data from model legume species, as well as Arabidopsis thaliana. A total of 29 (50%) of the 58 clusters detected putative ortholoci with known chromosomal locations in Medicago truncatula, which is closely related to white clover within the Trifolieae tribe of the Fabaceae. This analysis provides access to translational data from model species. The efficiency of in silico SNP discovery in white clover is limited by paralogous and homoeologous gene duplication effects, which are resolved unambiguously by the transmission test. This approach will also be applicable to other agronomically important cross-pollinating allopolyploid plant species.

Arabidopsis↗