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

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

Potent and selective small-molecule inhibitors are valuable tools to elucidate the functions of protein kinases within complex signaling networks. Incorporation of a photoswitchable moiety into the inhibitor scaffold offers the opportunity to steer inhibitor potency with temporal precision, while the challenge of selective inhibition can often be addressed by employing a chemical genetic approach, termed the analog-sensitive method. Here, we combine the perks of these two approaches and report photoswitchable azopyrazoles to target calcium-dependent protein kinase 1 (CDPK1) from Toxoplasma gondii, a kinase naturally susceptible to analog-sensitive kinase inhibitors due to its glycine gatekeeper residue. The most promising azopyrazoles display favorable photochemical properties, thermal stability, and a substantial difference in IC50 values between both photostationary states. Consequently, the CDPK1 kinase reaction can be controlled dynamically and reversibly by applying light of different wavelengths. Inhibition of CDPK1 by the azopyrazoles drastically relies on the nature of the gatekeeper residue as a successive increase in gatekeeper size causes a concurrent loss of inhibitory activity. Furthermore, two photoswitchable inhibitors exhibit activity against T. gondii and Cryptosporidium parvum infection in a cell culture model, making them a promising addition to the toolbox for dissecting the role of CDPK1 in the infectious cycle with high temporal control. Overall, this work merges the benefits of the analog-sensitive approach and photopharmacology without compromising inhibitory potency and thus holds great promise for application to other protein kinases in the future.

Photoswitchable Inhibitors to Optically Control Specific Kinase Activity.

Inositol poly- and pyrophosphates (InsPs and PP-InsPs) are central eukaryotic messengers. These very highly phosphorylated molecules can exist in two distinct conformations, a canonical one with five phosphoryl groups in equatorial positions, and a “flipped” conformation with five axial substituents. Using 13C-labeled InsPs/PP-InsPs, the behavior of these molecules was investigated by 2D-NMR under solution conditions reminiscent of a cytosolic environment. Remarkably, the most highly phosphorylated messenger 1,5(PP)2-InsP4 (also termed InsP8) readily adopts both conformations at physiological conditions. Environmental factors—such as pH, metal cation composition, and temperature—strongly influence the conformational equilibrium. Thermodynamic data revealed that the transition of InsP8 from the equatorial to the axial conformation is, in fact, an exothermic process. The speciation of InsPs and PP-InsPs also affects their interaction with protein binding partners; addition of Mg2+ decreased the binding constant Kd of InsP8 to an SPX protein domain. The results illustrate that PP-InsP speciation reacts very sensitively to solution conditions, suggesting it might act as an environment-responsive molecular switch.

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One Scaffold, Two Conformations: The Ring-Flip of the Messenger InsP8 Occurs under Cytosolic Conditions

Reversible protein phosphorylation is a central signaling mechanism in eukaryotic cells. While the identification of canonical phosphorylation sites using mass-spectrometry (MS) based proteomics has become routine, annotation of non-canonical phosphorylation has remained a challenge. Here, we report a tailored pyrophosphoproteomics workflow to detect and reliably assign protein pyrophosphorylation in two human cell lines, providing the first direct evidence of endogenous protein pyrophosphorylation. Detection of protein pyrophosphorylation was reproducible, specific and consistent with previous biochemical evidence relating the installation of the modification to inositol pyrophosphates (PP-InsPs). We manually validated 148 pyrophosphosites across 71 human proteins, the most heavily pyrophosphorylated of which were the nucleolar proteins NOLC1 and TCOF1. A predictive workflow based on the MS data set was established to recognize putative pyrophosphorylation sequences, and UBF1, a nucleolar protein incompatible with the proteomics method, was biochemically shown to undergo pyrophosphorylation. When the biosynthesis of PP-InsPs was perturbed in a model cell line, proteins expressed in this background exhibited lower levels of pyrophosphorylation. Disruption of PP-InsP biosynthesis also significantly reduced rDNA transcription, potentially by lowering pyrophosphorylation on regulatory proteins NOLC1, TCOF1, and UBF1. Overall, protein pyrophosphorylation emerges as an archetype of non-canonical phosphorylation, and should be considered in future phosphoproteomic analyses.

Dorothea Fiedler

Papers

Photoswitchable Inhibitors to Optically Control Specific Kinase Activity.

One Scaffold, Two Conformations: The Ring-Flip of the Messenger InsP8 Occurs under Cytosolic Conditions

Pyrophosphoproteomics: extensive protein pyrophosphorylation revealed in human cell lines