抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

AACR Centennial Conference: Translational Cancer Medicine-- Nov 4-8, 2007; Singapore

PL02-05 

All cancers are due to abnormalities in DNA. The availability of the human genome sequence has led to the proposal that resequencing of cancer genomes will reveal the full complement of somatic mutations and hence all the cancer genes. To explore the nature of the information that will be derived from cancer genome sequencing we have sequenced the coding exons of the family of 518 protein kinases, ~1.3Mb DNA per cancer sample, in 210 cancers of diverse histological types. Despite the screen being directed toward the coding regions of a gene family that has previously been strongly implicated in oncogenesis, the results indicate that the majority of somatic mutations detected are “passengers”. There is considerable variation in the number and pattern of these mutations between individual cancers, indicating substantial diversity of processes of molecular evolution between cancers. The imprints of exogenous mutagenic exposures, mutagenic treatment regimes and DNA repair defects can all be seen in the distinctive mutational signatures of individual cancers. This systematic mutation screen and others have previously yielded a number of cancer genes that are frequently mutated in one or more cancer types and which are now anticancer drug targets (for example BRAF , PIK3CA , and EGFR ). However, detailed analyses of the data from our screen additionally suggest that there exist a large number of additional “driver” mutations which are distributed across a substantial number of genes. It therefore appears that cells may be able to utilise mutations in a large repertoire of potential cancer genes to acquire the neoplastic phenotype. However, many of these genes are employed only infrequently. These findings may have implications for future anticancer drug development.

Patterns of Somatic Mutation in Human Cancer Genomes

/pdf/metal-organic-frameworks-and-self-assembled-supramolecular-2xs948xxr9.pdf

Metal–Organic Frameworks and Self-Assembled Supramolecular Coordination Complexes: Comparing and Contrasting the Design, Synthesis, and Functionality of Metal–Organic Materials

Inositol hexakisphosphate kinases (IP6Ks) are emerging as relevant pharmacological targets because a multitude of disease-related phenotypes has been associated with their function. While the development of potent IP6K inhibitors is gaining momentum, a pharmacological tool to distinguish the mammalian isozymes is still lacking. Here, we implemented an analog-sensitive approach for IP6Ks and performed a high-throughput screen to identify suitable lead compounds. The most promising hit, FMP-201300, exhibited high potency and selectivity towards the unique valine gatekeeper mutants of IP6K1 and IP6K2, compared to the respective wild-type kinases. Biochemical validation experiments revealed an allosteric mechanism of action that was corroborated by HDX-MS measurements. The latter analysis suggested that displacement of the αC helix, caused by the gatekeeper mutation, facilitates the binding of FMP-201300 to an allosteric pocket adjacent to the ATP binding site. FMP-201300 therefore serves as a valuable springboard for the further development of compounds that can selectively target the three mammalian IP6Ks; either as analog-sensitive kinase inhibitors or as an allosteric lead compound for the wild-type kinases.

An unconventional gatekeeper mutation sensitizes inositol hexakisphosphate kinases to an allosteric inhibitor

The detection and annotation of posttranslationally modified proteins in complex samples has benefited greatly from the ability to chemically synthesize and characterize model compounds harboring the modification of interest. To explore the signaling role of protein pyrophosphorylation, a recently discovered modification mediated by the inositol pyrophosphate messengers, our group has developed a robust method to incorporate pyrophosphate residues into peptide sequences. We highlight several examples from the literature that inspired our chemical approach and discuss future applications of our orthogonal pyrophosphorylation strategy.

Synthetic Pyrophosphorylation Methods and Their Use in Chemical Biology

Protein phosphorylation is one of the most ubiquitous post‐translational modifications, regulating numerous essential processes in cells. Accordingly, the large‐scale annotation of phosphorylation sites continues to provide central insight into the regulation of signaling networks. The global analysis of the phosphoproteome typically relies on mass spectrometry analysis of phosphopeptides, with an enrichment step necessary due to the sub‐stoichiometric nature of phosphorylation. Several affinity‐based methods and chemical modification strategies have been developed to date, but the choice of enrichment method can have a considerable impact on the results. Here, we show that a biotinylated, photo‐cleavable phosphorimidazolide reagent permits the immobilization and subsequent cleavage of phosphopeptides. The method is capable of the capture and release of phosphopeptides of varying characteristics, and this mild and selective strategy expands the current repertoire for phosphopeptide chemical modification with the potential to enrich and identify new phosphorylation sites in the future.

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/cbic.202200407

Chemoselective Labeling and Immobilization of Phosphopeptides with Phosphorimidazolide Reagents

Inositol pyrophosphates (PP-InsPs); are a functionally diverse family of eukaryotic molecules that deploy a highly-specialized array of phosphate groups as a combinatorial cell-signaling code. One reductive strategy to derive a molecular-level understanding of the many actions of PP-InsPs is to individually characterize the proteins that bind them. Here, we describe an alternate approach that seeks a single, collective rationalization for PP-InsP binding to an entire group of proteins, i.e., the multiple nucleolar proteins previously reported to bind 5-InsP7 (5-diphospho-inositol-1,2,3,4,6-pentakisphosphate). Quantitative confocal imaging of the outer nucleolar granular region revealed its expansion when cellular 5-InsP7 levels were elevated by either (a) reducing the 5-InsP7 metabolism by a CRISPR-based knockout (KO) of either NUDT3 or PPIP5Ks; or (b), the heterologous expression of wild-type inositol hexakisphosphate kinase, i.e., IP6K2; separate expression of a kinase-dead IP6K2 mutant did not affect granular volume. Conversely, the nucleolar granular region in PPIP5K KO cells shrank back to the wild-type volume upon attenuating 5-InsP7 synthesis using either a pan-IP6K inhibitor or the siRNA-induced knockdown of IP6K1+IP6K2. Significantly, the inner fibrillar volume of the nucleolus was unaffected by 5-InsP7. We posit that 5-InsP7 acts as an ‘electrostatic glue’ that binds together positively charged surfaces on separate proteins, overcoming mutual protein–protein electrostatic repulsion the latter phenomenon is a known requirement for the assembly of a non-membranous biomolecular condensate.

/pdf/nucleolar-architecture-is-modulated-by-a-small-molecule-the-2fyc0th3.pdf

Nucleolar Architecture Is Modulated by a Small Molecule, the Inositol Pyrophosphate 5-InsP7

Inositol pyrophosphates (IPPs) comprise a specific class of signaling molecules that regulate central biological processes in eukaryotes. The conserved Vip1/PPIP5K family controls intracellular IP8 levels, the highest phosphorylated form of IPPs present in yeasts, as it has both inositol kinase and pyrophosphatase activities. Previous studies have shown that the fission yeast S. pombe Vip1/PPIP5K family member Asp1 impacts chromosome transmission fidelity via modulation of spindle function. We now demonstrate that an IP8 analogue is targeted by endogenous Asp1 and that cellular IP8 is subject to cell cycle control. Mitotic entry requires Asp1 kinase function and IP8 levels are increased at the G2/M transition. In addition, the kinetochore, the conductor of chromosome segregation assembled on chromosomes is modulated by IP8. Members of the yeast CCAN kinetochore-subcomplex such as Mal2/CENP-O localize to the kinetochore depending on the intracellular IP8-level: higher than wild-type IP8 levels reduces Mal2 kinetochore targeting, while a reduction in IP8 has the opposite effect. As our perturbations of the inositol polyphosphate and IPP pathways demonstrate that kinetochore architecture depends solely on IP8 and not on other IPPs, we conclude that chromosome transmission fidelity is controlled by IP8 via an interplay between entry into mitosis, kinetochore architecture and spindle dynamics.

/pdf/inositol-pyrophosphate-controlled-kinetochore-architecture-2m1nemft.pdf

Dorothea Fiedler

Papers

An unconventional gatekeeper mutation sensitizes inositol hexakisphosphate kinases to an allosteric inhibitor

Synthetic Pyrophosphorylation Methods and Their Use in Chemical Biology

Chemoselective Labeling and Immobilization of Phosphopeptides with Phosphorimidazolide Reagents

Nucleolar Architecture Is Modulated by a Small Molecule, the Inositol Pyrophosphate 5-InsP7

Inositol Pyrophosphate-Controlled Kinetochore Architecture and Mitotic Entry in S. pombe