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Results for “In silico modeling”

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At least 163 records · Page 9Linked to original sources

PubMed2006

The structure of an ancient conserved domain establishes a structural basis for stable histidine phosphorylation and identifies a new family of adenosine-specific kinases.

Phosphorylation of both small molecules and proteins plays a central role in many biological processes. In proteins, phosphorylation most commonly targets the oxygen atoms of Ser, Thr, and Tyr. In contrast, stably phosphorylated His residues are rarely found, due to the lability of the N-P bond, and histidine phosphorylation features most often in transient processes. Here we present the crystal structure of a protein of previously unknown function, which proves to contain a stably phosphorylated histidine residue. The protein is the product of open reading frame PAE2307, from the hyperthermophilic archaeon Pyrobaculum aerophilum, and is representative of a highly conserved protein family found in archaea and bacteria. The crystal structure of PAE2307, solved at 1.45-A resolution (R = 0.208, R(free) = 0.227), forms a remarkably tightly associated hexamer. The phosphorylated histidine at the proposed active site, pHis85, occupies a cavity that is at the interface between two subunits and contains a number of fully conserved residues. Stable phosphorylation is attributed to favorable hydrogen bonding of the phosphoryl group and a salt bridge with pHis85 that provides electronic stabilization. In silico modeling suggested that the protein may function as an adenosine kinase, a conclusion that is supported by in vitro assays of adenosine binding, using fluorescence spectroscopy, and crystallographic visualization of an adenosine complex of PAE2307 at 2.25-A resolution.

Adenosine↗

PubMed2006

Identification of novel glycogen synthase kinase-3beta substrate-interacting residues suggests a common mechanism for substrate recognition.

Substrate recognition and specificity are essential for the reliability and fidelity of protein kinase function. GSK-3 has a unique substrate specificity that requires prior phosphorylation of its substrates. However, how the enzyme selects its phosphorylated substrates is unknown. Here, we combined in silico modeling with mutagenesis and biological studies to identify GSK-3-substrate interaction sites located within its binding cleft. Protein-protein docking of GSK-3beta and the phosphorylated cAMP responsive element binding protein (pCREB) (using the available experimentally determined structures), identified Phe67, Gln89, and Asn95 of GSK-3beta as putative binding sites interacting with the CREB phosphorylation motif. Mutations of these residues to alanine impaired GSK-3beta phosphorylation of several substrates, without abrogating its autocatalytic activity. Subsequently, expression of the GSK-3beta mutants in cells resulted in decreased phosphorylation of substrates CREB, IRS-1, and beta-catenin, and prevented their suppression of glycogen synthase activity as compared with cells expressing the wild-type GSK-3beta. Our studies provide important additional understanding of how GSK-3beta recognizes its substrates: In addition to prior phosphorylation typically required in GSK-3 substrates, substrate recognition involves interactions with GSK-3beta residues: Phe67, Gln89, and Asn95, which confer a common basis for substrate binding and selectivity, yet allow for substrate diversity.

Amino Acid Sequence↗

PubMed2026

Comprehensive evaluation of AlphaFold/OpenFold prediction of experimentally unresolved proteins through novel metrics.

Predicting accurate protein structures is essential for understanding molecular mechanisms, interpreting the impact of sequence variation, and supporting translational applications ranging from drug discovery to clinical genomics. Recent advances in deep-learning-based predictors such as AlphaFold2, OpenFold, and AlphaFold3 have transformed structural biology, enabling routine in silico modeling even for challenging or previously uncharacterized proteins. However, systematic benchmarking of these tools-especially for novel targets and single amino acid variants-remains limited. Conventional global metrics often fail to capture biologically meaningful discrepancies. By evaluating multiple implementations of AlphaFold2 and OpenFold, together with ColabFold and the AlphaFold3 server, across 10 different proteins and 222 single amino acid protein variants encompassing a wide range of sizes, structures, and functions, we show that although widely used global indicators-like mean pLDDT, pTM-score, and RMSD-frequently suggest comparable performance, substantial local-level differences remain elusive. To address this gap, we introduce a comparative framework leveraging Bland-Altman agreement analysis, to evaluate per-residue Cα-confidence differences and Per-Residue profiles (PRPs), complemented by Uniform Manifold Approximation and Projection (UMAP). This approach reveals marked localized divergences, particularly within flexible or intrinsically disordered regions, where both predictor choice and single-residue substitutions trigger the largest conformational shifts. We further demonstrate that using reduced homology databases has minimal impact on predicted structural quality, offering computationally efficient alternatives. Collectively, our findings underscore the importance of integrating global and residue-specific evaluations to more accurately assess robustness, agreement, and practical usability across contemporary protein structure prediction methods.

Proteins↗

PubMed2003

Statistical evaluation of the Predictive Toxicology Challenge 2000-2001.

MOTIVATION: The development of in silico models to predict chemical carcinogenesis from molecular structure would help greatly to prevent environmentally caused cancers. The Predictive Toxicology Challenge (PTC) competition was organized to test the state-of-the-art in applying machine learning to form such predictive models. RESULTS: Fourteen machine learning groups generated 111 models. The use of Receiver Operating Characteristic (ROC) space allowed the models to be uniformly compared regardless of the error cost function. We developed a statistical method to test if a model performs significantly better than random in ROC space. Using this test as criteria five models performed better than random guessing at a significance level p of 0.05 (not corrected for multiple testing). Statistically the best predictor was the Viniti model for female mice, with p value below 0.002. The toxicologically most interesting models were Leuven2 for male mice, and Kwansei for female rats. These models performed well in the statistical analysis and they are in the middle of ROC space, i.e. distant from extreme cost assumptions. These predictive models were also independently judged by domain experts to be among the three most interesting, and are believed to include a small but significant amount of empirically learned toxicological knowledge. AVAILABILITY: PTC details and data can be found at: http://www.predictive-toxicology.org/ptc/.

Algorithms↗

PubMed2005

On the use of qualitative reasoning to simulate and identify metabolic pathways.

MOTIVATION: Perhaps the greatest challenge of modern biology is to develop accurate in silico models of cells. To do this we require computational formalisms for both simulation (how according to the model the state of the cell evolves over time) and identification (learning a model cell from observation of states). We propose the use of qualitative reasoning (QR) as a unified formalism for both tasks. The two most commonly used alternative methods of modelling biochemical pathways are ordinary differential equations (ODEs), and logical/graph-based (LG) models. RESULTS: The QR formalism we use is an abstraction of ODEs. It enables the behaviour of many ODEs, with different functional forms and parameters, to be captured in a single QR model. QR has the advantage over LG models of explicitly including dynamics. To simulate biochemical pathways we have developed 'enzyme' and 'metabolite' QR building blocks that fit together to form models. These models are finite, directly executable, easy to interpret and robust. To identify QR models we have developed heuristic chemoinformatics graph analysis and machine learning procedures. The graph analysis procedure is a series of constraints and heuristics that limit the number of ways metabolites can combine to form pathways. The machine learning procedure is generate-and-test inductive logic programming. We illustrate the use of QR for modelling and simulation using the example of glycolysis. AVAILABILITY: All data and programs used are available on request.

Algorithms↗

PubMed2005

Prediction methods and databases within chemoinformatics: emphasis on drugs and drug candidates.

MOTIVATION: To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS: We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability of chemical compounds as potential drugs, as well as for predicting their physico-chemical and ADMET properties have been proposed in recent years. These methods are discussed, and some possible future directions in this rapidly developing field are described.

Chemistry, Pharmaceutical↗

PubMed2006

BuchneraBASE: a post-genomic resource for Buchnera sp. APS.

SUMMARY: BuchneraBASE is a bioinformatic research tool for the genome of the symbiotic bacterium Buchnera sp. APS that includes an improved genome annotation, comparative information about related insect symbiont genomes and a complete mapping of metabolic reactions to an Escherichia coli in silico model. The database is designed to accommodate genome-wide post-genomic datasets that are becoming available for this organism. AVAILABILITY: BuchneraBASE is available at http://www.buchnera.org/.

Buchnera↗

PubMed2026

De novo chromatin remodelling variants in sporadic Chiari 1 malformation.

Chiari 1 malformation (CM1) is the most common congenital malformation of the human hindbrain. Although prior studies have implicated chromatin-remodeling genes in CM1, the de novo genetic architecture and underlying neurodevelopmental mechanisms remain incompletely defined. To investigate the molecular genetics of a novel familial form of CM1 linked with syringomyelia and tethered cord and determine whether rare, damaging de novo variants (DNVs) contribute to sporadic CM1 risk with gene- and pathway-level resolution, we performed whole-exome sequencing in an ultra-rare multigenerational family with CM1 and associated spinal pathology, and in the largest assembled trio-based cohort to date, comprising 1,585 proband-parent trios with sporadic, idiopathic CM1 (2017-2025). The comparison cohort included 1,798 unaffected control siblings. Clinical phenotyping was by systematic medical record review. Structural domain mapping, in silico modeling, and integration with single-cell transcriptomic data from developing human cerebellum was conducted to assess biological plausibility. A heterozygous loss-of-function variant in CHD3 segregated with CM1 and syringomyelia in a multigenerational family. In the trio-based cohort, rare protein-altering DNVs were significantly enriched across multiple chromodomain helicase DNA-binding (CHD) genes, including CHD1, CHD3, CHD4, and CHD8, exceeding gene-specific mutation expectations (protein-damaging variants: P = 1.3 × 10-9; predicted loss-of-function variants: P = 8.6 × 10-5). CHD1 contained two pathogenic DNVs (p.A999D and p.E984K). CHD4 (p.D744N, p.T1813P, and p.I1102T) and CHD8 (p.R1402X, p.R1472X, and p.R2035X) each contained three new DNVs. Variants clustered within conserved ATPase, helicase, and chromodomain regions essential for chromatin remodeling, and these patients frequently had comorbid developmental delay and related neurodevelopmental features. Single-cell transcriptomic analyses demonstrated enrichment in Purkinje cells and inhibitory neurons of midgestational cerebellum, where CHD gene products form a coherent chromatin-regulatory network. Rare, large-effect DNVs that disrupt chromatin-remodeling programs contribute to sporadic CM1, implicating genetically encoded dysregulation of cerebellar development as a central disease mechanism. Exome sequencing may complement surgical evaluation of children with sporadic CM1, particularly when accompanied by neurodevelopmental concerns, informing prognosis and family counseling.

de novo variants↗

PubMed2006

Exo-beta-D-glucosaminidase from Amycolatopsis orientalis: catalytic residues, sugar recognition specificity, kinetics, and synergism.

Catalytic residues and the mode of action of the exo-beta-D-glucosaminidase (GlcNase) from Amycolatopsis orientalis were investigated using the wild-type and mutated enzymes. Mutations were introduced into the putative catalytic residues resulting in five mutated enzymes (D469A, D469E, E541D, E541Q, and S468N/D469E) that were successfully produced. The four single mutants were devoid of enzymatic activity, indicating that Asp469 and Glu541 are essential for catalysis as predicted by sequence alignments of enzymes belonging to GH-2 family. When mono-N-acetylated chitotetraose [(GlcN)3-GlcNAc] was hydrolyzed by the enzyme, the nonreducing-end glucosamine unit was produced together with the transglycosylation products. The rate of hydrolysis of the disaccharide, 2-amino-2-deoxy-D-glucopyranosyl 2-acetamido-2-deoxy-D-glucopyranose (GlcN-GlcNAc), was slightly lower than that of (GlcN)2, suggesting that N-acetyl group of the sugar residue located at (+1) site partly interferes with the catalytic reaction. The time-course of the enzymatic hydrolysis of the completely deacetylated chitotetraose [(GlcN)4] was quantitatively determined by high-performance liquid chromatography (HPLC) and used for in silico modeling of the enzymatic hydrolysis. The modeling study provided the values of binding free energy changes of +7.0, -2.9, -1.8, -0.9, -1.0, and -0.5 kcal/mol corresponding, respectively, to subsites (-2), (-1), (+1), (+2), (+3), and (+4). When chitosan polysaccharide was hydrolyzed by a binary enzyme system consisting of A. orientalis GlcNase and Streptomyces sp. N174 endochitosanase, the highest synergy in the rate of product formation was observed at the molar ratio 2:1. Thus, GlcNase would be an efficient tool for industrial production of glucosamine monosaccharide.

Actinomycetaceae↗

PubMed1996

EcoCyc: an encyclopedia of Escherichia coli genes and metabolism.

The encyclopedia of Escherichia coli genes and metabolism (EcoCyc) is a database that combines information about the genome and the intermediary metabolism of E.coli. It describes 2034 genes, 306 enzymes encoded by these genes, 580 metabolic reactions that occur in E.coli and the organization of these reactions into 100 metabolic pathways. The EcoCyc graphical user interface allows query and exploration of the EcoCyc database using visualization tools such as genomic map browsers and automatic layouts of metabolic pathways. EcoCyc spans the space from sequence to function to allow investigation of an unusually broad range of questions. EcoCyc can be thought of as both an electronic review article, because of its copious references to the primary literature, and as an in silico model of E.coli that can be probed and analyzed through computational means.

Computer Communication Networks↗

PubMed2005

Isolation of a small molecule inhibitor of DNA base excision repair.

The base excision repair (BER) pathway is essential for the removal of DNA bases damaged by alkylation or oxidation. A key step in BER is the processing of an apurinic/apyrimidinic (AP) site intermediate by an AP endonuclease. The major AP endonuclease in human cells (APE1, also termed HAP1 and Ref-1) accounts for >95% of the total AP endonuclease activity, and is essential for the protection of cells against the toxic effects of several classes of DNA damaging agents. Moreover, APE1 overexpression has been linked to radio- and chemo-resistance in human tumors. Using a newly developed high-throughput screen, several chemical inhibitors of APE1 have been isolated. Amongst these, CRT0044876 was identified as a potent and selective APE1 inhibitor. CRT0044876 inhibits the AP endonuclease, 3'-phosphodiesterase and 3'-phosphatase activities of APE1 at low micromolar concentrations, and is a specific inhibitor of the exonuclease III family of enzymes to which APE1 belongs. At non-cytotoxic concentrations, CRT0044876 potentiates the cytotoxicity of several DNA base-targeting compounds. This enhancement of cytotoxicity is associated with an accumulation of unrepaired AP sites. In silico modeling studies suggest that CRT0044876 binds to the active site of APE1. These studies provide both a novel reagent for probing APE1 function in human cells, and a rational basis for the development of APE1-targeting drugs for antitumor therapy.

Antineoplastic Agents↗

PubMed2026

CircExor enables interpretable prediction of circRNA localization into extracellular vesicles.

Certain circular RNAs (circRNAs) are selectively enriched in extracellular vesicles (EVs), in which they contribute to intercellular communication and represent promising biomarkers, yet the sequence determinants of their sorting remain unclear. Existing computational predictors are optimized mainly for linear RNAs and rarely address circRNA localization into EVs. Here we introduce circExor, the first framework specifically designed for circRNA EV localization. We curate a dedicated benchmark data set of 2102 circRNAs and implement a variable-length end-to-end concatenation strategy together with k-mer frequency encoding to accommodate circular topology, long sequence length, and length heterogeneity. Using a tree-based classifier, circExor achieves superior performance compared with RNAlocate-v3 and ExoGRU, reaching an AUROC of 0.743 on the internal test set and an average AUROC of 0.680 on the held-out test set. SHAP-based analysis, sequence perturbation analysis, motif mapping, and cell-based experimental validation support the predicted EV tendency and identify YBX1, HNRNPK, HNRNPL, and NOVA2 as candidate RBPs potentially associated with circRNA sorting. CircExor therefore provides a predictive and interpretable framework that links in silico modeling to mechanistic hypotheses, and supports biomarker discovery and candidate prioritization for downstream studies of EV-associated circRNAs.

Journal Article↗

PubMed2004

High-throughput mutation detection underlying adaptive evolution of Escherichia coli-K12.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis of base-specific cleavage products is an efficient, highly accurate tool for the detection of single base sequence variations. We describe the first application of this comparative sequencing strategy for automated high-throughput mutation detection in microbial genomes. The method was applied to identify DNA sequence changes that occurred in Escherichia coli K-12 MG1655 during laboratory adaptive evolution to new optimal growth phenotypes. Experiments were based on a genome-scale in silico model of E. coli metabolism and growth. This model computes several phenotypic functions and predicts optimal growth rates. To identify mutations underlying a 40-d adaptive laboratory evolution on glycerol, we resequenced 4.4% of the E. coli-K12 MG1655 genome in several clones picked at the end of the evolutionary process. The 1.54-Mb screen was completed in 13.5 h. This resequencing study is the largest reported by MALDI-TOF mass spectrometry to date. Ten mutations in 40 clones and three deviations from the reference sequence were detected. Mutations were predominantly found within the glycerol kinase gene. Functional characterization of the most prominent mutation shows its metabolic impact on the process of adaptive evolution. All sequence changes were independently confirmed by genotyping and Sanger-sequencing. We demonstrate that comparative sequencing by base-specific cleavage and MALDI-TOF mass spectrometry is an automated, fast, and highly accurate alternative to capillary sequencing.

Adaptation, Biological↗

PubMed2005

A network of transcriptionally coordinated functional modules in Saccharomyces cerevisiae.

Recent computational and experimental work suggests that functional modules underlie much of cellular physiology and are a useful unit of cellular organization from the perspective of systems biology. Because interactions among modules can give rise to higher-level properties that are essential to cellular function, a complete knowledge of these interactions is necessary for future work in systems biology, including in silico modeling and metabolic engineering. Here we present a computational method for the systematic identification and analysis of functional modules whose activity is coordinated at the level of transcription. We applied this method, Search for Pairwise Interactions (SPIN), to obtain a global view of functional module connectivity in Saccharomyces cerevisiae and to provide insight into the biological mechanisms underlying this coordination. We also examined this global network at higher resolution to obtain detailed information about the interactions of particular module pairs. For instance, our results reveal possible transcriptional coordination of glycolysis and lipid metabolism by the transcription factor Gcr1p, and further suggest that glycolysis and phosphoinositide signaling may regulate each other reciprocally.

Gene Expression Profiling↗

PubMed2003

Probabilistic prediction in scale-free networks: diameter changes.

In complex systems, responses to small perturbations are too diverse to definitely predict how much they would be, and then such diverse responses can be predicted in a probabilistic way. Here we study such a problem in scale-free networks, for example, the diameter changes by the deletion of a single vertex for various in silico and real-world scale-free networks. We find that the diameter changes are indeed diverse and their distribution exhibits an algebraic decay with an exponent zeta asymptotically. Interestingly, the exponent zeta is robust as zeta approximately 2.2(1) for most scale-free networks and insensitive to the degree exponents gamma as long as 2<gamma</=3. However, there is another type with zeta approximately 1.7(1) and its examples include the Internet and its related in silico model.

Growth↗

PubMed2006

Skeleton and fractal scaling in complex networks.

We find that the fractal scaling in a class of scale-free networks originates from the underlying tree structure called a skeleton, a special type of spanning tree based on the edge betweenness centrality. The fractal skeleton has the property of the critical branching tree. The original fractal networks are viewed as a fractal skeleton dressed with local shortcuts. An in silico model with both the fractal scaling and the scale-invariance properties is also constructed. The framework of fractal networks is useful in understanding the utility and the redundancy in networked systems.

Escherichia coli↗

PubMed2006

The crystal structure of beryllofluoride Spo0F in complex with the phosphotransferase Spo0B represents a phosphotransfer pretransition state.

A number of regulatory circuits in biological systems function through the exchange of phosphoryl groups from one protein to another. Spo0F and Spo0B are components of a phosphorelay that control sporulation in the bacterium Bacillus subtilis through the exchange of a phosphoryl group. Using beryllofluoride as a mimic for phosphorylation, we trapped the interaction of the phosphorylated Spo0F with Spo0B in the crystal lattice. The transition state of phosphoryl transfer continues to be a highly debated issue, as to whether it is associative or dissociative in nature. The geometry of Spo0F binding to Spo0B favors an associative mechanism for phosphoryl transfer. In order to visualize the autophosphorylation of the histidine kinase, KinA, and the subsequent phosphoryl transfer to Spo0F, we generated in silico models representing these reaction steps.

Bacillus subtilis↗

PubMed2006

Detection of histone deacetylase inhibition by noninvasive magnetic resonance spectroscopy.

Histone deacetylase (HDAC) inhibitors are new and promising antineoplastic agents. Current methods for monitoring early response rely on invasive biopsies or indirect blood-derived markers. Our goal was to develop a magnetic resonance spectroscopy (MRS)-based method to detect HDAC inhibition. The fluorinated lysine derivative Boc-Lys-(Tfa)-OH (BLT) was investigated as a (19)F MRS molecular marker of HDAC activity together with (31)P MRS of endogenous metabolites. In silico modeling of the BLT-HDAC interaction and in vitro MRS studies of BLT cleavage by HDAC confirmed BLT as a HDAC substrate. BLT did not affect cell viability or HDAC activity in PC3 prostate cancer cells. PC3 cells were treated, in the presence of BLT, with the HDAC inhibitor p-fluoro-suberoylanilide hydroxamic acid (FSAHA) over the range of 0 to 10 micromol/L, and HDAC activity and MRS spectra were monitored. Following FSAHA treatment, HDAC activity dropped, reaching 53% of control at 10 micromol/L FSAHA. In parallel, a steady increase in intracellular BLT from 14 to 32 fmol/cell was observed. BLT levels negatively correlated with HDAC activity consistent with higher levels of uncleaved BLT in cells with inhibited HDAC. Phosphocholine, detected by (31)P MRS, increased from 7 to 16 fmol/cell following treatment with FSAHA and also negatively correlated with HDAC activity. Increased phosphocholine is probably due to heat shock protein 90 inhibition as indicated by depletion of client proteins. In summary, (19)F MRS of BLT, combined with (31)P MRS, can be used to monitor HDAC activity in cells. In principle, this could be applied in vivo to noninvasively monitor HDAC activity.

Antineoplastic Agents↗