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Biophysical Journal Aug 2006Depolymerization is, by definition, a crucial process in the reversible assembly of various biopolymers. It may also be an important factor in the pathology of sickle...
Depolymerization is, by definition, a crucial process in the reversible assembly of various biopolymers. It may also be an important factor in the pathology of sickle cell disease. If sickle hemoglobin fibers fail to depolymerize fully during passage through the lungs then they will reintroduce aggregates into the systemic circulation and eliminate or shorten the protective delay (nucleation) time for the subsequent growth of fibers. We study how depolymerization depends on the rates of end- and side-depolymerization, k(end) and k(side), which are, respectively, the rates at which fiber length is lost at each end and the rate at which new breaks appear per unit fiber length. We present both an analytic mean field theory and supporting simulations showing that the characteristic fiber depolymerization time tau= square root 1/k(end)k(side) depends on both rates, but not on the fiber length L, in a large intermediate regime 1 << k(side)L(2)/k(end) << (L/d)(2), with d the fiber diameter. We present new experimental data which confirms that both mechanisms are important and shows how the rate of side depolymerization depends strongly on the concentration of CO, acting as a proxy for oxygen. Our theory remains rather general and could be applied to the depolymerization of an entire class of linear aggregates, not just sickle hemoglobin fibers.
Topics: Carbon Monoxide; Computer Simulation; Hemoglobin, Sickle; Humans; Kinetics; Lung; Microscopy, Electron; Microscopy, Interference; Models, Statistical; Oxygen; Polymers; Time Factors
PubMed: 16714344
DOI: 10.1529/biophysj.105.075333 -
Toxins Jun 2018Cystine-stabilized peptides represent a large family of peptides characterized by high structural stability and bactericidal, fungicidal, or insecticidal properties.... (Review)
Review
Cystine-stabilized peptides represent a large family of peptides characterized by high structural stability and bactericidal, fungicidal, or insecticidal properties. Found throughout a wide range of taxa, this broad and functionally important family can be subclassified into distinct groups dependent upon their number and type of cystine bonding patters, tertiary structures, and/or their species of origin. Furthermore, the annotation of proteins related to the cystine-stabilized family are under-represented in the literature due to their difficulty of isolation and identification. As a result, there are several recent attempts to collate them into data resources and build analytic tools for their dynamic prediction. Ultimately, the identification and delivery of new members of this family will lead to their growing inclusion into the repertoire of commercial viable alternatives to antibiotics and environmentally safe insecticides. This review of the literature and current state of cystine-stabilized peptide biology is aimed to better describe peptide subfamilies, identify databases and analytics resources associated with specific cystine-stabilized peptides, and highlight their current commercial success.
Topics: Animals; Computer Simulation; Cystine; Databases, Factual; Peptides
PubMed: 29921767
DOI: 10.3390/toxins10060251 -
Glycoconjugate Journal Jan 2013The past 25 years have seen significant advances in understanding the diversity and functions of glycoprotein glycans in Drosophila melanogaster. Genetic screens have... (Review)
Review
The past 25 years have seen significant advances in understanding the diversity and functions of glycoprotein glycans in Drosophila melanogaster. Genetic screens have captured mutations that reveal important biological activities modulated by glycans, including protein folding and trafficking, as well as cell signaling, tissue morphogenesis, fertility, and viability. Many of these glycan functions have parallels in vertebrate development and disease, providing increasing opportunities to dissect pathologic mechanisms using Drosophila genetics. Advances in the sensitivity of structural analytic techniques have allowed the glycan profiles of wild-type and mutant tissues to be assessed, revealing novel glycan structures that may be functionally analogous to vertebrate glycans. This review describes a selected set of recent advances in understanding the functions of N-linked and O-linked (non-glycosaminoglycan) glycoprotein glycans in Drosophila with emphasis on their relatedness to vertebrate organisms.
Topics: Animals; Drosophila melanogaster; Glycomics; Glycoproteins; Glycosylation; Mutation; Polysaccharides; Signal Transduction
PubMed: 22936173
DOI: 10.1007/s10719-012-9442-x -
Proteomics Feb 2012Proteases play prominent roles in many physiological processes and the pathogenesis of various diseases, which makes them interesting drug targets. To fully understand... (Review)
Review
Proteases play prominent roles in many physiological processes and the pathogenesis of various diseases, which makes them interesting drug targets. To fully understand the functional role of proteases in these processes, it is necessary to characterize the target specificity of the enzymes, identify endogenous substrates and cleavage products as well as protease activators and inhibitors. The complexity of these proteolytic networks presents a considerable analytic challenge. To comprehensively characterize these systems, quantitative methods that capture the spatial and temporal distributions of the network members are needed. Recently, activity-based workflows have come to the forefront to tackle the dynamic aspects of proteolytic processing networks in vitro, ex vivo and in vivo. In this review, we will discuss how mass spectrometry-based approaches can be used to gain new insights into protease biology by determining substrate specificities, profiling the activity-states of proteases, monitoring proteolysis in vivo, measuring reaction kinetics and defining in vitro and in vivo proteolytic events. In addition, examples of future aspects of protease research that go beyond mass spectrometry-based applications are given.
Topics: Amino Acid Sequence; Humans; Kinetics; Mass Spectrometry; Peptide Hydrolases; Protease Inhibitors; Proteolysis; Proteomics; Substrate Specificity
PubMed: 22246865
DOI: 10.1002/pmic.201100399 -
Journal of the National Cancer Institute Sep 2016The subpopulation treatment effect pattern plot (STEPP) is an appealing method for assessing the clinical impact of a predictive marker on patient outcomes and...
BACKGROUND
The subpopulation treatment effect pattern plot (STEPP) is an appealing method for assessing the clinical impact of a predictive marker on patient outcomes and identifying a promising subgroup for further study. However, its original formulation lacked a decision analytic justification and applied only to a single marker.
METHODS
We derive a decision-analytic result that motivates STEPP. We discuss the incorporation of multiple predictive markers into STEPP using risk difference, cadit, and responders-only benefit functions.
RESULTS
Applying STEPP to data from a breast cancer treatment trial with multiple markers, we found that none of the three benefit functions identified a promising subgroup for further study. Applying STEPP to hypothetical data from a trial with 100 markers, we found that all three benefit functions identified promising subgroups as evidenced by the large statistically significant treatment effect in these subgroups.
CONCLUSIONS
Because the method has desirable decision-analytic properties and yields an informative plot, it is worth applying to randomized trials on the chance there is a large treatment effect in a subgroup determined by the predictive markers.
Topics: Age Factors; Antineoplastic Agents, Hormonal; Biomarkers, Tumor; Body Mass Index; Breast Neoplasms; Clinical Decision-Making; Decision Support Techniques; Disease-Free Survival; Female; Humans; Ki-67 Antigen; Letrozole; Logistic Models; Lymphatic Metastasis; Nitriles; Predictive Value of Tests; Randomized Controlled Trials as Topic; Receptors, Estrogen; Receptors, Progesterone; Tamoxifen; Triazoles; Tumor Burden
PubMed: 27193772
DOI: 10.1093/jnci/djw101 -
Cell Reports Methods Dec 2023Glycomics, the comprehensive profiling of all glycan structures in samples, is rapidly expanding to enable insights into physiology and disease mechanisms. However,...
Glycomics, the comprehensive profiling of all glycan structures in samples, is rapidly expanding to enable insights into physiology and disease mechanisms. However, glycan structure complexity and glycomics data interpretation present challenges, especially for differential expression analysis. Here, we present a framework for differential glycomics expression analysis. Our methodology encompasses specialized and domain-informed methods for data normalization and imputation, glycan motif extraction and quantification, differential expression analysis, motif enrichment analysis, time series analysis, and meta-analytic capabilities, synthesizing results across multiple studies. All methods are integrated into our open-source glycowork package, facilitating performant workflows and user-friendly access. We demonstrate these methods using dedicated simulations and glycomics datasets of N-, O-, lipid-linked, and free glycans. Differential expression tests here focus on human datasets and cancer vs. healthy tissue comparisons. Our rigorous approach allows for robust, reliable, and comprehensive differential expression analyses in glycomics, contributing to advancing glycomics research and its translation to clinical and diagnostic applications.
Topics: Humans; Glycomics; Polysaccharides
PubMed: 37992708
DOI: 10.1016/j.crmeth.2023.100652 -
Current Opinion in Structural Biology Aug 2014In this review we discuss the current advances relating to structure determination from protein microcrystals with special emphasis on the newly developed method called... (Review)
Review
In this review we discuss the current advances relating to structure determination from protein microcrystals with special emphasis on the newly developed method called MicroED. This method uses a transmission electron cryo-microscope to collect electron diffraction data from extremely small 3-dimensional (3D) crystals. MicroED has been used to solve the 3D structure of the model protein lysozyme to 2.9Å resolution. As the method further matures, MicroED promises to offer a unique and widely applicable approach to protein crystallography using nanocrystals.
Topics: Analytic Sample Preparation Methods; Cryoelectron Microscopy; Crystallography, X-Ray; Proteins
PubMed: 24709395
DOI: 10.1016/j.sbi.2014.03.004 -
PLoS Computational Biology Dec 2021There is a growing realization that multi-way chromatin contacts formed in chromosome structures are fundamental units of gene regulation. However, due to the paucity...
There is a growing realization that multi-way chromatin contacts formed in chromosome structures are fundamental units of gene regulation. However, due to the paucity and complexity of such contacts, it is challenging to detect and identify them using experiments. Based on an assumption that chromosome structures can be mapped onto a network of Gaussian polymer, here we derive analytic expressions for n-body contact probabilities (n > 2) among chromatin loci based on pairwise genomic contact frequencies available in Hi-C, and show that multi-way contact probability maps can in principle be extracted from Hi-C. The three-body (triplet) contact probabilities, calculated from our theory, are in good correlation with those from measurements including Tri-C, MC-4C and SPRITE. Maps of multi-way chromatin contacts calculated from our analytic expressions can not only complement experimental measurements, but also can offer better understanding of the related issues, such as cell-line dependent assemblies of multiple genes and enhancers to chromatin hubs, competition between long-range and short-range multi-way contacts, and condensates of multiple CTCF anchors.
Topics: Chromatin; Chromosome Mapping; DNA; Enhancer Elements, Genetic; Gene Expression Regulation; Genes; Genomics; High-Throughput Nucleotide Sequencing; Humans
PubMed: 34871311
DOI: 10.1371/journal.pcbi.1009669 -
Briefings in Bioinformatics May 2022The human major histocompatibility complex (MHC), also known as human leukocyte antigen (HLA), plays an important role in the adaptive immune system by presenting...
MOTIVATION
The human major histocompatibility complex (MHC), also known as human leukocyte antigen (HLA), plays an important role in the adaptive immune system by presenting non-self-peptides to T cell receptors. The MHC region has been shown to be associated with a variety of diseases, including autoimmune diseases, organ transplantation and tumours. However, structural analytic tools of HLA are still sparse compared to the number of identified HLA alleles, which hinders the disclosure of its pathogenic mechanism.
RESULT
To provide an integrative analysis of HLA, we first collected 1296 amino acid sequences, 256 protein data bank structures, 120 000 frequency data of HLA alleles in different populations, 73 000 publications and 39 000 disease-associated single nucleotide polymorphism sites, as well as 212 modelled HLA heterodimer structures. Then, we put forward two new strategies for building up a toolkit for transplantation and tumour immunotherapy, designing risk alignment pipeline and antigenic peptide prediction pipeline by integrating different resources and bioinformatic tools. By integrating 100 000 calculated HLA conformation difference and online tools, risk alignment pipeline provides users with the functions of structural alignment, sequence alignment, residue visualization and risk report generation of mismatched HLA molecules. For tumour antigen prediction, we first predicted 370 000 immunogenic peptides based on the affinity between peptides and MHC to generate the neoantigen catalogue for 11 common tumours. We then designed an antigenic peptide prediction pipeline to provide the functions of mutation prediction, peptide prediction, immunogenicity assessment and docking simulation. We also present a case study of hepatitis B virus mutations associated with liver cancer that demonstrates the high legitimacy of our antigenic peptide prediction process. HLA3D, including different HLA analytic tools and the prediction pipelines, is available at http://www.hla3d.cn/.
Topics: Computational Biology; HLA Antigens; Histocompatibility Antigens Class I; Humans; Immunotherapy; Neoplasms; Peptides; Protein Binding
PubMed: 35289353
DOI: 10.1093/bib/bbac076 -
Sensors (Basel, Switzerland) Aug 2023Green Chemistry is a vital and crucial instrument in achieving pollution control, and it plays an important role in helping society reach the Sustainable Development...
Green Chemistry is a vital and crucial instrument in achieving pollution control, and it plays an important role in helping society reach the Sustainable Development Goals (SDGs). NIR (near-infrared spectroscopy) has been utilized as an alternate technique for molecular identification, making the process faster and less expensive. Near-infrared diffuse reflectance spectroscopy and Machine Learning (ML) algorithms were utilized in this study to construct identification and classification models of bacteria such as , , and . Furthermore, divide these bacteria into Gram-negative and Gram-positive groups. The green and quick approach was created by combining NIR spectroscopy with a diffuse reflectance accessory. Using infrared spectral data and ML techniques such as principal component analysis (PCA), hierarchical cluster analysis (HCA) and K-Nearest Neighbor (KNN), It was feasible to accomplish the identification and classification of four bacteria and classify these bacteria into two groups: Gram-positive and Gram-negative, with 100% accuracy. We may conclude that our study has a high potential for bacterial identification and classification, as well as being consistent with global policies of sustainable development and green analytical chemistry.
Topics: Spectroscopy, Near-Infrared; Algorithms; Bacteria; Chemistry, Analytic; Escherichia coli; Machine Learning
PubMed: 37687792
DOI: 10.3390/s23177336