Rule-based modeling and simulations of the inner kinetochore structure

Background

Combinatorial complexity is a central problem when modeling biochemical reaction networks, since the association of a few components can give rise to a large variation of protein complexes. Available classical modeling approaches are often insufficient for the analysis of very large and complex networks in detail. Recently, we developed a new rule-based modeling approach that facilitates the analysis of spatial and combinatorially complex problems. Here, we explore for the first time how this approach can be applied to a specific biological system, the human kinetochore, which is a multi-protein complex involving over 100 proteins.

Results

Applying our freely available SRSim software to a large data set on kinetochore proteins in human cells, we construct a spatial rule-based simulation model of the human inner kinetochore. The model generates an estimation of the probability distribution of the inner kinetochore 3D architecture and we show how to analyze this distribution using information theory. In our model, the formation of a bridge between CenpA and an H3 containing nucleosome only occurs efficiently for higher protein concentration realized during S-phase but may be not in G1. Above a certain nucleosome distance the protein bridge barely formed pointing towards the importance of chromatin structure for kinetochore complex formation. We define a metric for the distance between structures that allow us to identify structural clusters. Using this modeling technique, we explore different hypothetical chromatin layouts.

Conclusions

Applying a rule-based network analysis to the spatial kinetochore complex geometry allowed us to integrate experimental data on kinetochore proteins, suggesting a 3D model of the human inner kinetochore architecture that is governed by a combinatorial algebraic reaction network. This reaction network can serve as bridge between multiple scales of modeling. Our approach can be applied to other systems beyond kinetochores.     

ComplexBrowser: A Tool for Identification and Quantification of Protein Complexes in Large-scale Proteomics Datasets

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Highlights

• •Automated analysis of protein complexes in proteomic experiments.
• •Quantitative measurement of the coordinated changes in protein complex components.
• •Interactive visualizations for exploratory analysis of proteomic results.

     

DIAlignR Provides Precise Retention Time Alignment Across Distant Runs in DIA and Targeted Proteomics

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Highlights

• •Retention time shift can lead to inversion of elution order of peptides.
• •Global alignment methods are suboptimal for alignment of distant runs.
• •DIAlignR employs hybrid (global + local) RT alignment approach.
• •DIAlignR can align swapped peaks accurately across distant runs.

     

MyROOT: a method and software for the semiautomatic measurement of primary root length in Arabidopsis seedlings

Root analysis is essential for both academic and agricultural research. Despite the great advances in root phenotyping and imaging, calculating root length is still performed manually and involves considerable amounts of labor and time. To overcome these limitations, we developed MyROOT, a software for the semiautomatic quantification of root growth of seedlings growing directly on agar plates. Our method automatically determines the scale from the image of the plate, and subsequently measures the root length of the individual plants. To this aim, MyROOT combines a bottom‐up root tracking approach with a hypocotyl detection algorithm. At the same time as providing accurate root measurements, MyROOT also significantly minimizes the user intervention required during the process. Using Arabidopsis, we tested MyROOT with seedlings from different growth stages and experimental conditions. When comparing the data obtained from this software with that of manual root measurements, we found a high correlation between both methods (R² = 0.997). When compared with previous developed software with similar features (BRAT and EZ‐Rhizo), MyROOT offered an improved accuracy for root length measurements. Therefore, MyROOT will be of great use to the plant science community by permitting high‐throughput root length measurements while saving both labor and time.     

大鼠尿激酶SYBR Green I real time RT-PCR引物的设计

设计用于SYBR Green I法实时定量逆转录多聚酶链反应(QRT-PCR)检测大鼠尿激酶型纤溶酶原激活因子(uPA)mRNA的引物。从基因库获取靶基因及相关序列,充分收集争分析相关生物信息学数据,应用Oligo 6.22设计出一对长度为21bp的引物,其GG含量为52.4%;上下游引物3’最稳定二聚体和及发夹结构的能量分别为-1.5、-0.40 kcal/mol和-3.5、-O.90 kcal/mol,引物间最稳定二聚体为-3.1 kcal/mol。5’端和中间△G值较高,高于3’端△G;引发效率分别455和403。实验证明,该引物能够高效、特异地实现对靶序列的检测,适用于SYBR Green I法实时定量检测(uPA)mRNA。     

3D-QSAR assisted identification of FABP4 inhibitors: An effective scaffold hopping analysis/QSAR evaluation

Following on the recent publication of pharmacologically relevant effects, small molecule inhibitors of adipocyte fatty-acid binding protein 4 (FABP4) have attracted high interest. FABP4 is mainly expressed in macrophages and adipose tissue, where it regulates fatty acid storage and lipolysis, being also an important mediator of inflammation. In this regard, FABP4 recently demonstrated an interesting molecular target for the treatment of type 2 diabetes, other metabolic diseases and some type of cancers. In the past years, hundreds of effective FABP4 inhibitors have been synthesized. In this paper, a quantitative structure-activity relationship (QSAR) model has been produced, in order to predict the bioactivity of FABP4 inhibitors. The methodology has been combined with a scaffold-hopping approach, allowing to identify three new molecules that act as effective inhibitors of this protein. These molecules, synthesized and tested for their FABP4 inhibitor activity, showed IC₅₀ values between 3.70 and 5.59 μM, with a high level of agreement with the predicted values.     

A software tool for organ-specific second cancer risk assessment from exposure to therapeutic doses

The aim of this study was the development of a software tool (SCRcalc) for the automatic estimation of the patient- and organ-specific cancer risk due to radiotherapy. SCRcalc was developed using the Python 3.8.7 programming language. It incorporates equations and parameters of mechanistic models for the calculation of the organ equivalent dose (OED), the excess absolute risk (EA R) and the lifetime attributable risk (LA R) of carcinogenesis for various organs due to radiotherapy. Data from differential dose-volume histograms, as defined by a treatment planning system, could be automatically inserted into the program. Eighteen different cancer risk estimates for various organs were performed of patients subjected to radiation therapy with conventional and modulated techniques. These software estimates were compared with manual calculations. SCRcalc was developed as a standalone executable program without any dependencies. It enables direct estimations of the OED and LAR for various organs at risk. An important aspect of the software is that it does not require pre-processing of the DVH data. No differences were found between the SCRcalc results and those derived from manual calculations. The newly developed software offers the possibility to medical physicists and radiation oncologists to directly estimate the probability of radiotherapy-induced secondary malignancies for various organs at risk.     

ImShot: An Open-Source Software for Probabilistic Identification of Proteins In Situ and Visualization of Proteomics Data

Imaging mass spectrometry (IMS) has developed into a powerful tool allowing label-free detection of numerous biomolecules in situ. In contrast to shotgun proteomics, proteins/peptides can be detected directly from biological tissues and correlated to its morphology leading to a gain of crucial clinical information. However, direct identification of the detected molecules is currently challenging for MALDI–IMS, thereby compelling researchers to use complementary techniques and resource intensive experimental setups. Despite these strategies, sufficient information could not be extracted because of lack of an optimum data combination strategy/software. Here, we introduce a new open-source software ImShot that aims at identifying peptides obtained in MALDI–IMS. This is achieved by combining information from IMS and shotgun proteomics (LC–MS) measurements of serial sections of the same tissue. The software takes advantage of a two-group comparison to determine the search space of IMS masses after deisotoping the corresponding spectra. Ambiguity in annotations of IMS peptides is eliminated by introduction of a novel scoring system that identifies the most likely parent protein of a detected peptide in the corresponding IMS dataset. Thanks to its modular structure, the software can also handle LC–MS data separately and display interactive enrichment plots and enriched Gene Ontology terms or cellular pathways. The software has been built as a desktop application with a conveniently designed graphic user interface to provide users with a seamless experience in data analysis. ImShot can run on all the three major desktop operating systems and is freely available under Massachusetts Institute of Technology license.     

ProSight Annotator: Complete control and customization of protein entries in UniProt XML files

The effectiveness of any proteomics database search depends on the theoretical candidate information contained in the protein database. Unfortunately, candidate entries from protein databases such as UniProt rarely contain all the post-translational modifications (PTMs), disulfide bonds, or endogenous cleavages of interest to researchers. These omissions can limit discovery of novel and biologically important proteoforms. Conversely, searching for a specific proteoform becomes a computationally difficult task for heavily modified proteins. Both situations require updates to the database through user-annotated entries. Unfortunately, manually creating properly formatted UniProt Extensible Markup Language (XML) files is tedious and prone to errors. ProSight Annotator solves these issues by providing a graphical interface for adding user-defined features to UniProt-formatted XML files for better informed proteoform searches. It can be downloaded from http://prosightannotator.northwestern.edu .