Prediction of the structure of a receptor-protein complex using a binary docking method.

To validate procedures of rational drug design, it is important to develop computational methods that predict binding sites between a protein and a ligand molecule. Many small molecules have been tested using such programs, but examination of protein-protein and peptide-protein interactions has been sparse. We were able to test such applications once the structures of both the maltose-binding protein (MBP) and the ligand-binding domain of the aspartate receptor, which binds MBP, became available. Here we predict the binding site of MBP to its receptor using a 'binary docking' technique in which two MBP octapeptide sequences containing mutations that eliminate maltose chemotaxis are independently docked to the receptor. The peptides in the docked solutions superimpose on their original positions in the structure of MBP and allow the formation of an MBP-receptor complex. The consistency of the computational and biological results supports this approach for predicting protein-protein and peptide-protein interactions.     

Targeted disruption of the mouse transforming growth factor-beta 1 gene results in multifocal inflammatory disease.

Transforming growth factor-beta 1 (TGF-beta 1) is a multifunctional growth factor that has profound regulatory effects on many developmental and physiological processes. Disruption of the TGF-beta 1 gene by homologous recombination in murine embryonic stem cells enables mice to be generated that carry the disrupted allele. Animals homozygous for the mutated TGF-beta 1 allele show no gross developmental abnormalities, but about 20 days after birth they succumb to a wasting syndrome accompanied by a multifocal, mixed inflammatory cell response and tissue necrosis, leading to organ failure and death. TGF-beta 1-deficient mice may be valuable models for human immune and inflammatory disorders, including autoimmune diseases, transplant rejection and graft versus host reactions.     

表面活性剂对TAPP Soret带的影响

本文研究了在不同pH值下吐温—80.Tritonx—100.SLS三种表面活性剂四—(对-三甲铵苯基)卟啉Soret带的影响。     

生物序列分析

这次演讲将回顾近 1 0多年来应用某些随机模型于生物序列分析的研究工作 .这些模型本身有很长的历史 ,可追溯到 3 0多年以前 ,尽管从那时起 ,这些模型已经产生了很多新的变种 .在生物序列分析中模型的作用是归总那些涉及到在生物信息学中已知的模体 (motif)或域 (domain)的信息 ,并且提供一种工具在另一序列片段中寻找模体或域的实例 (instance) .我们将逐步介绍模体模型 ,从非常简单的 ,非随机情况开始 ,进而是更复杂的情况 ,直至近来的关于模体的剖面隐马氏模型 .第二个例子是来自利用一个或两个物种的序列数据进行基因发现 ,其中广义隐马氏模型或广义成对 (pair)隐马氏模型已被证实非常有效     

Mechanism for the learning deficits in a mouse model of neurofibromatosis type 1.

Neurofibromatosis type I (NF1) is one of the most common single-gene disorders that causes learning deficits in humans. Mice carrying a heterozygous null mutation of the Nfl gene (Nfl(+/-) show important features of the learning deficits associated with NF1 (ref. 2). Although neurofibromin has several known properties and functions, including Ras GTPase-activating protein activity, adenylyl cyclase modulation and microtubule binding, it is unclear which of these are essential for learning in mice and humans. Here we show that the learning deficits of Nf1(+/-) mice can be rescued by genetic and pharmacological manipulations that decrease Ras function. We also show that the Nf1(+/-) mice have increased GABA (gamma-amino butyric acid)-mediated inhibition and specific deficits in long-term potentiation, both of which can be reversed by decreasing Ras function. Our results indicate that the learning deficits associated with NF1 may be caused by excessive Ras activity, which leads to impairments in long-term potentiation caused by increased GABA-mediated inhibition. Our findings have implications for the development of treatments for learning deficits associated with NF1.     

复线电气化区段施工感应电对人体的危害及防护对策

感应电会对人体造成伤害。从电磁感应和静电感应原理入手，分析了产生感应电的过程，并就如何防止感应电的危害提出了防护对策，有一定实用价值。     

链条炉存在的问题及解决方法

从炉排横向配风不均、风室压火、煤层厚度阻力及锅炉燃烧等方面分析了链条锅炉存在的问题，并针对存在的问题提出了相应的解决办法。     

Microbial degradation of bitumen

Summary A blown bitumen Mexphalte R 90/40 with a high content of saturated hydrocarbons was degraded by several microorganisms to the same extent. In batch cultures ofSaccharomycopsis lipolytica, maximal biodegradation was estimated to be about 9% w/w, 3.2·10^–3 g/cm² and 3.1·10^–3 cm of degraded bitumen. The Mexphalte R 90/40 degradation rate was closely coupled to biofilm formation. The microbial activity concerned predominantly the oxidation of saturated hydrocarbons. A direct distillation bitumen 80/100 with a low content of saturated hydrocarbons and a high content of aromatic hydrocarbons and resins was more resistant to biodegradation.