scholarly journals Investigating structure function relationships in the NOTCH family through large-scale somatic DNA sequencing studies

2020 ◽  
Author(s):  
Michael W J Hall ◽  
David Shorthouse ◽  
Philip H Jones ◽  
Benjamin A Hall
Keyword(s):  
Dna Sequencing ◽  
Structure Function ◽  
Calcium Binding ◽  
Large Scale ◽  
Driver Mutations ◽  
Missense Mutations ◽  
Mutant Selection ◽  
Ligand Interaction ◽  
Binding Interface

AbstractThe recent development of highly sensitive DNA sequencing techniques has detected large numbers of missense mutations of genes, including NOTCH1 and 2, in ageing normal tissues. Driver mutations persist and propagate in the tissue through a selective advantage over both wild-type cells and alternative mutations. This process of selection can be considered as a large scale, in vivo screen for mutations that increase clone fitness. It follows that the specific missense mutations that are observed in individual genes may offer us insights into the structure-function relationships. Here we show that the positively selected missense mutations in NOTCH1 and NOTCH2 in human oesophageal epithelium cause inactivation predominantly through protein misfolding. Once these mutations are excluded, we further find statistically significant evidence for selection at the ligand binding interface and calcium binding sites. In this, we observe stronger evidence of selection at the ligand interface on EGF12 over EGF11, suggesting that in this tissue EGF12 may play a more important role in ligand interaction. Finally, we show how a mutation hotspot in the NOTCH1 transmembrane helix arises through the intersection of both a high mutation rate and residue conservation. Together these insights offer a route to understanding the mechanism of protein function through in vivo mutant selection.

Antimicrobial resistance: its emergence and transmission

2008 ◽  
Vol 9 (2) ◽  
pp. 115-126 ◽  
Author(s):  
Patrick Boerlin ◽  
Richard J. Reid-Smith
Keyword(s):  
Gene Transfer ◽  
Antimicrobial Resistance ◽  
Horizontal Gene Transfer ◽  
Dna Sequencing ◽  
Large Scale ◽  
Mutant Selection ◽  
The Past ◽  
New Concepts ◽  
Selection Window ◽  
Integrative Conjugative Elements

AbstractNew concepts have emerged in the past few years that help us to better understand the emergence and spread of antimicrobial resistance (AMR). These include, among others, the discovery of the mutator state and the concept of mutant selection window for resistances emerging primarily through mutations in existing genes. Our understanding of horizontal gene transfer has also evolved significantly in the past few years, and important new mechanisms of AMR transfer have been discovered, including, among others, integrative conjugative elements and ISCR(insertionsequences withcommonregions) elements. Simultaneously, large-scale studies have helped us to start comprehending the immense and yet untapped reservoir of both AMR genes and mobile genetic elements present in the environment. Finally, new PCR- and DNA sequencing-based techniques are being developed that will allow us to better understand the epidemiology of classical vectors of AMR genes, such as plasmids, and to monitor them in a more global and systematic way.

scholarly journals PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Tingting Sun ◽  
Yuting Chen ◽  
Yuhao Wen ◽  
Zefeng Zhu ◽  
Minghui Li
Keyword(s):  
Machine Learning ◽  
Ligand Binding ◽  
Binding Affinity ◽  
Large Scale ◽  
Predictive Accuracy ◽  
Predictive Performance ◽  
Driver Mutations ◽  
Missense Mutations ◽  
Resistance Mutations ◽  
Benchmark Datasets

AbstractResistance to small-molecule drugs is the main cause of the failure of therapeutic drugs in clinical practice. Missense mutations altering the binding of ligands to proteins are one of the critical mechanisms that result in genetic disease and drug resistance. Computational methods have made a lot of progress for predicting binding affinity changes and identifying resistance mutations, but their prediction accuracy and speed are still not satisfied and need to be further improved. To address these issues, we introduce a structure-based machine learning method for quantitatively estimating the effects of single mutations on ligand binding affinity changes (named as PremPLI). A comprehensive comparison of the predictive performance of PremPLI with other available methods on two benchmark datasets confirms that our approach performs robustly and presents similar or even higher predictive accuracy than the approaches relying on first-principle statistical mechanics and mixed physics- and knowledge-based potentials while requires much less computational resources. PremPLI can be used for guiding the design of ligand-binding proteins, identifying and understanding disease driver mutations, and finding potential resistance mutations for different drugs. PremPLI is freely available at https://lilab.jysw.suda.edu.cn/research/PremPLI/ and allows to do large-scale mutational scanning.

scholarly journals The structure of a calsequestrin filament reveals mechanisms of familial arrhythmia

2019 ◽  
Author(s):  
Erron W. Titus ◽  
Frederick H. Deiter ◽  
Chenxu Shi ◽  
Julianne Wojciak ◽  
Melvin Scheinman ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Ventricular Tachycardia ◽  
Structure Function ◽  
Calcium Binding ◽  
Atomic Resolution ◽  
Polymorphic Ventricular Tachycardia ◽  
Dominant Disease ◽  
Resolution Structure

Mutations in the calcium-binding protein calsequestrin cause a highly lethal familial arrhythmia, catecholaminergic polymorphic ventricular tachycardia (CPVT). In vivo, calsequestrin multimerizes into filaments, but a compelling atomic-resolution structure of a calsequestrin filament is lacking. We report a crystal structure of a cardiac calsequestrin filament with supporting mutation analysis provided by anin vitrofomentation assay. We also report and characterize a novel disease-associated calsequestrin mutation, S173I, which localizes to the filament-forming interface. In addition, we show that a previously reported dominant disease mutation, K180R, maps to the same multimerization surface. Both mutations disrupt filamentation, suggesting that dominant disease arises from defects in multimer formation. A ytterbium-derivatized structure pinpoints multiple credible calcium sites at filament-forming interfaces, explaining the atomic basis of calsequestrin filamentation in the presence of calcium. This work advances our understanding of calsequestrin biochemistry and provides a unifying structure-function molecular mechanism by which dominant-acting calsequestrin mutations provoke lethal arrhythmias.

scholarly journals CHASMplus reveals the scope of somatic missense mutations driving human cancers

2018 ◽  
Author(s):  
Collin Tokheim ◽  
Rachel Karchin
Keyword(s):  
Missense Mutation ◽  
Large Scale ◽  
Computational Method ◽  
The Cancer Genome Atlas ◽  
Superior Performance ◽  
Driver Mutations ◽  
Cancer Type ◽  
Missense Mutations ◽  
Driver Genes ◽  
Cancer Types

SummaryLarge-scale cancer sequencing studies of patient cohorts have statistically implicated many genes driving cancer growth and progression, and their identification has yielded substantial translational impact. However, a remaining challenge is to increase the resolution of driver prediction from the gene level to the mutation level, because mutation-level predictions are more closely aligned with the goal of precision cancer medicine. Here we present CHASMplus, a computational method, that is uniquely capable of identifying driver missense mutations, including those specific to a cancer type, as evidenced by significantly superior performance on diverse benchmarks. Applied to 8,657 tumor samples across 32 cancer types in The Cancer Genome Atlas, CHASMplus identifies over 4,000 unique driver missense mutations in 240 genes, supporting a prominent role for rare driver mutations. We show which TCGA cancer types are likely to yield discovery of new driver missense mutations by additional sequencing, which has important implications for public policy.SignificanceMissense mutations are the most frequent mutation type in cancers and the most difficult to interpret. While many computational methods have been developed to predict whether genes are cancer drivers or whether missense mutations are generally deleterious or pathogenic, there has not previously been a method to score the oncogenic impact of a missense mutation specifically by cancer type, limiting adoption of computational missense mutation predictors in the clinic. Cancer patients are routinely sequenced with targeted panels of cancer driver genes, but such genes contain a mixture of driver and passenger missense mutations which differ by cancer type. A patient’s therapeutic response to drugs and optimal assignment to a clinical trial depends on both the specific mutation in the gene of interest and cancer type. We present a new machine learning method honed for each TCGA cancer type, and a resource for fast lookup of the cancer-specific driver propensity of every possible missense mutation in the human exome.

scholarly journals PremPLI: Predicting the Effects of Missense Mutations on Protein-Ligand Interactions

2021 ◽  
Author(s):  
Tingting Sun ◽  
Yuting Chen ◽  
Yuhao Wen ◽  
Zefeng Zhu ◽  
Minghui Li
Keyword(s):  
Ligand Binding ◽  
Binding Affinity ◽  
Large Scale ◽  
Predictive Accuracy ◽  
Predictive Performance ◽  
Driver Mutations ◽  
Missense Mutations ◽  
Resistance Mutations ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

Abstract Protein-ligand interactions trigger a multitude of signal transduction processes and resistance to small-molecule drugs is the main cause of the failure of therapeutic drugs in clinical practice. Missense mutations altering the binding of ligands to proteins are one of the critical mechanisms that result in genetic disease and drug resistance. Computational methods have made a lot of progress for predicting binding affinity changes and identifying resistance mutations, but they are still not satisfied and need to be further improved in both accuracy and speed. To address these issues, we introduced PremPLI, a structure-based machine learning method for quantitatively estimating the effects of single mutations on ligand binding affinity changes. A comprehensive comparison of the predictive performance of PremPLI with other available methods on two benchmark datasets confirms that our approach performs robustly and presents similar or even higher predictive accuracy than the approaches relying on first-principle statistical mechanics and mixed physics- and knowledge-based potentials while requires much less computational resources. PremPLI can be used for guiding the design of ligand-binding proteins, identifying and understanding disease driver mutations, and finding potential resistance mutations for different drugs. PremPLI is freely available at https://lilab.jysw.suda.edu.cn/research/PremPLI/ and allows to do large-scale mutational scanning.

scholarly journals In vivo mRNA display enables large-scale proteomics by next generation sequencing

2020 ◽  
Vol 117 (43) ◽  
pp. 26710-26718 ◽  
Author(s):  
Panos Oikonomou ◽  
Roberto Salatino ◽  
Saeed Tavazoie
Keyword(s):  
Dna Sequencing ◽  
Large Scale ◽  
Rna Binding ◽  
Functional Characterization ◽  
Mrna Display ◽  
Messenger Rnas ◽  
Next Generation ◽  
High Coverage ◽  
Cellular Context

Large-scale proteomic methods are essential for the functional characterization of proteins in their native cellular context. However, proteomics has lagged far behind genomic approaches in scalability, standardization, and cost. Here, we introduce in vivo mRNA display, a technology that converts a variety of proteomics applications into a DNA sequencing problem. In vivo-expressed proteins are coupled with their encoding messenger RNAs (mRNAs) via a high-affinity stem-loop RNA binding domain interaction, enabling high-throughput identification of proteins with high sensitivity and specificity by next generation DNA sequencing. We have generated a high-coverage in vivo mRNA display library of the Saccharomyces cerevisiae proteome and demonstrated its potential for characterizing subcellular localization and interactions of proteins expressed in their native cellular context. In vivo mRNA display libraries promise to circumvent the limitations of mass spectrometry-based proteomics and leverage the exponentially improving cost and throughput of DNA sequencing to systematically characterize native functional proteomes.

Purification of the Antihemophilic Factor by Gel Filtration on Agarose

1969 ◽  
Vol 22 (03) ◽  
pp. 577-583 ◽  
Author(s):  
M.M.P Paulssen ◽  
A.C.M.G.B Wouterlood ◽  
H.L.M.A Scheffers
Keyword(s):  
Factor Viii ◽  
Plasma Proteins ◽  
Large Scale ◽  
Gel Filtration ◽  
Large Scale Preparation ◽  
Scale Preparation ◽  
Antihemophilic Factor

SummaryFactor VIII can be isolated from plasma proteins, including fibrinogen by chromatography on agarose. The best results were obtained with Sepharose 6B. Large scale preparation is also possible when cryoprecipitate is separated by chromatography. In most fractions containing factor VIII a turbidity is observed which may be due to the presence of chylomicrons.The purified factor VIII was active in vivo as well as in vitro.

The Effect of Active Site-inhibited Factor VIIa on Tissue Factor-initiated Coagulation Using Platelets before and after Aspirin Administration

1997 ◽  
Vol 78 (04) ◽  
pp. 1202-1208 ◽  
Author(s):  
Marianne Kjalke ◽  
Julie A Oliver ◽  
Dougald M Monroe ◽  
Maureane Hoffman ◽  
Mirella Ezban ◽  
...  
Keyword(s):  
Tissue Factor ◽  
Active Site ◽  
Large Scale ◽  
Thrombin Generation ◽  
Factor Viia ◽  
Dependent Manner ◽  
Antithrombotic Agent ◽  
Before And After ◽  
Ic50 Values

SummaryActive site-inactivated factor VIIa has potential as an antithrombotic agent. The effects of D-Phe-L-Phe-L-Arg-chloromethyl ketone-treated factor VIla (FFR-FVIIa) were evaluated in a cell-based system mimicking in vivo initiation of coagulation. FFR-FVIIa inhibited platelet activation (as measured by expression of P-selectin) and subsequent large-scale thrombin generation in a dose-dependent manner with IC50 values of 1.4 ± 0.8 nM (n = 8) and 0.9 ± 0.7 nM (n = 7), respectively. Kd for factor VIIa binding to monocytes ki for FFR-FVIIa competing with factor VIIa were similar (11.4 ± 0.8 pM and 10.6 ± 1.1 pM, respectively), showing that FFR-FVIIa binds to tissue factor in the tenase complex with the same affinity as factor VIIa. Using platelets from volunteers before and after ingestion of aspirin (1.3 g), there were no significant differences in the IC50 values of FFR-FVIIa [after aspirin ingestion, the IC50 values were 1.7 ± 0.9 nM (n = 8) for P-selectin expression, p = 0.37, and 1.4 ± 1.3 nM (n = 7) for thrombin generation, p = 0.38]. This shows that aspirin treatment of platelets does not influence the inhibition of tissue factor-initiated coagulation by FFR-FVIIa, probably because thrombin activation of platelets is not entirely dependent upon expression of thromboxane A2.

Naphthoquinones and derivatives for chemotherapy: perspectives and limitations of their anti-trypanosomatids activities

2020 ◽  
Vol 26 ◽  
Author(s):  
Luíza Dantas-Pereira ◽  
Edézio F. Cunha-Junior ◽  
Valter V. Andrade-Neto ◽  
John F. Bower ◽  
Guilherme A. M. Jardim ◽  
...  
Keyword(s):  
Large Scale ◽  
Neglected Tropical Diseases ◽  
Folk Medicine ◽  
Leishmania Species ◽  
Parasitic Infections ◽  
Mechanistic Analysis ◽  
Leishmania Spp ◽  
Nanomolar Range

: Chagas disease, Sleeping sickness and Leishmaniasis, caused by trypanosomatids Trypanosoma cruzi, Trypanosoma brucei and Leishmania spp., respectively, are considered neglected tropical diseases, and they especially affect impoverished populations in the developing world. The available chemotherapies are very limited and a search for alternatives is still necessary. In folk medicine, natural naphthoquinones have been employed for the treatment of a great variety of illnesses, including parasitic infections. This review is focused on the anti-trypanosomatid activity and mechanistic analysis of naphthoquinones and derivatives. Among all the series of derivatives tested in vitro, naphthoquinone-derived 1,2,3-triazoles were very active on T. cruzi infective forms in blood bank conditions, as well as in amastigotes of Leishmania spp. naphthoquinones containing a CF3 on a phenyl amine ring inhibited T. brucei proliferation in the nanomolar range, and naphthopterocarpanquinones stood out for their activity on a range of Leishmania species. Some of these compounds showed a promising selectivity index (SI) (30 to 1900), supporting further analysis in animal models. Indeed, high toxicity to the host and inactivation by blood components are crucial obstacles to be overcome to use naphthoquinones and/or their derivatives for chemotherapy. Multidisciplinary initiatives embracing medicinal chemistry, bioinformatics, biochemistry, and molecular and cellular biology need to be encouraged to allow the optimization of these compounds. Large scale automated tests are pivotal for the efficiency of the screening step, and subsequent evaluation of both the mechanism of action in vitro and pharmacokinetics in vivo are essential for the development of a novel, specific and safe derivative, minimizing adverse effects.

Implantable neural interfaces

2018 ◽  
Author(s):  
Stefano Vassanelli
Keyword(s):  
Brain Function ◽  
Large Scale ◽  
Ionic Channels ◽  
Patch Clamp Technique ◽  
Advantages And Disadvantages ◽  
Optogenetic Stimulation ◽  
Physical Interfaces ◽  
The Brain

Establishing direct communication with the brain through physical interfaces is a fundamental strategy to investigate brain function. Starting with the patch-clamp technique in the seventies, neuroscience has moved from detailed characterization of ionic channels to the analysis of single neurons and, more recently, microcircuits in brain neuronal networks. Development of new biohybrid probes with electrodes for recording and stimulating neurons in the living animal is a natural consequence of this trend. The recent introduction of optogenetic stimulation and advanced high-resolution large-scale electrical recording approaches demonstrates this need. Brain implants for real-time neurophysiology are also opening new avenues for neuroprosthetics to restore brain function after injury or in neurological disorders. This chapter provides an overview on existing and emergent neurophysiology technologies with particular focus on those intended to interface neuronal microcircuits in vivo. Chemical, electrical, and optogenetic-based interfaces are presented, with an analysis of advantages and disadvantages of the different technical approaches.

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