基于集成模型的蛋白变构位点预测方法

变构是调节蛋白质功能的重要机制,对许多生物过程至关重要。变构调节剂比正构剂具有更高的特异性和更低的毒副作用,这使得变构药物设计比正构药物设计有更多的优势。变构位点的发现是变构药物设计的前提,目前实验上获得的变构位点多是偶然所得,因此亟待发展有效的理论方法来预测蛋白质变构位点。本工作提出了一种集成的机器学习方法AllosEC用于预测蛋白质变构口袋,该方法除了考虑口袋的理化性质外,还加入了口袋的二级结构信息、深度指数(DPX)和突出指数(CX)特征。另外,为了克服正负样本极度不平衡的问题,本工作使用欠采样方法来平衡训练数据集。在独立测试集上,AllosEC在多个评价指标上优于现有的其他方法,SEN、SPE、PRE和MCC分别为0.708、0.915、0.405和0.486。这样,本工作提供了性能良好的蛋白质变构位点预测方法AllosEC。Allostery is an important mechanism for regulating protein functions, which is essential for many biological processes. Compared with orthosteric regulators, allosteric regulators have higher specificity and lower toxicities, which makes allosteric drug design have more advantages than orthosteric drug design. The discovery of allosteric sites is a prerequisite for allosteric drug design. Currently, experimentally obtained allosteric sites are mostly obtained by chance, and therefore there is an urgent need to develop effective theoretical methods to predict protein allosteric sites. Here, we present an ensemble machine learning method AllosEC for protein allosteric pocket prediction, where besides the pockets’ physicochemical properties, their secondary structure information, depth indexes (DPXes) and protrusion indexes (CXes) are considered. In order to overcome the problem of extreme imbalance between positive and negative samples, this work uses an under sampling method to balance the training dataset. AllosEC outperforms other existing methods in multiple evaluation metrics on the independent test set, with SEN, SPE, PRE and MCC of 0.708, 0.915, 0.405 and 0.486, respectively. Thus, this work provides a good method AllosEC for protein allosteric site prediction.

高等植物捕光天线蛋白的NPQ调控机制及其优化

非光化学猝灭(non-photochemical quenching,NPQ)是植物应对强光和过量光的一种光保护状态。NPQ状态和捕光状态之间的切换与光辐照强度涨落的动态匹配是提高光合效率的一种新途径,阐明NPQ发生的分子机制对于通过基因工程优化NPQ过程从而提高农作物产量具有重要意义。NPQ主要发生在主要捕光天线蛋白LHCII(major light-harvesting complex II)上,它们在捕光状态与NPQ状态间的切换速率主要受PsbS蛋白(photosystem II subunit S)以及叶黄素循环的调控。本文简要介绍LHCII在温度、酸度诱导下在捕光状态和NPQ状态间可逆切换的变构调控机制,以及叶黄素循环和PsbS的调控作用,以期为提高光合效率和农业产出提供理论基础和新思路。

Effect of Two Herbicides on the Growth of Early Seedlings of Rye(Secale cereale)

[Objective]The aim was to study the effect of herbicide on the growth of early seedlings of rye（Secale cereale）.[Method]Effect of two kinds of herbicide（Atrazine and APM）on seedling growth of rye was investigated at the physiological,biochemical and cellular level.[Result]The Atrazin significantly decreased the contents of chlorophyll a,b and soluble proteins.Rye seeds were treated with 0.01-1 mg/L Atrazine for 16 h,the contents of chlorophyll a and b decreased from 1.26（a）,0.49（b）mg/g FW（control）to 1.15（a）,0.46（b）mg/g FW（0.1 mg/L）and 0.81（a）,0.33（b）mg/g FW（1.0 mg/L）.The content of soluble protein decreased with the increasing concentration of Atrazin.Atrazin had no significant influence on the cell division and chromosome structure variation.The contents of chlorophyll a,b and soluble proteins had no significantly change under the treatment of APM,but the number of chromosome structure variation such as chromosome bridge,multipolar division cells,lagging chromosome and unequal division cells increased significantly.[Conclusion]The critical concentration of Atrazine was 0.1-1.0 mg/L and 4 mg/L of APM in rye.

PHASE TRANSITION IN SEQUENCE UNIQUE RECONSTRUCTION

In this paper, sequence unique reconstruction refers to the property that a sequence is uniquely reconstructable from all its K-tuples. We propose and study the phase transition behavior of the probability P（K） of unique reconstruction with regard to tuple size K in random sequences （iid model）. Based on Monte Carlo experiments, artificial proteins generated from lid model exhibit a phase transition when P（K） abruptly jumps from a low value phase （e.g. 〈 0.1） to a high value phase （e.g. 〉 0.9）. With a generalization to any alphabet, we prove that for a random sequence of length L, as L is large enough, P（K） undergoes a sharp phase transition when p ≤ 0.1015 where p = P （two random letters match）. Besides, formulas are derived to estimate the transition points, which may be of practical use in sequencing DNA by hybridization. Concluded from our study, most proteins do not deviate greatly from random sequences in the sense of sequence unique reconstruction, while there are some ＂stubborn＂ proteins which only become uniquely reconstructable at a very large K and probably have biological implications.

The dynamical contact order:Protein folding rate parameters based on quantum conformational transitions

Protein folding is regarded as a quantum transition between the torsion states of a polypeptide chain.According to the quantum theory of conformational dynamics,we propose the dynamical contact order(DCO) defined as a characteristic of the contact described by the moment of inertia and the torsion potential energy of the polypeptide chain between contact residues.Conse-quently,the protein folding rate can be quantitatively studied from the point of view of dynamics.By comparing theoretical calculations and experimental data on the folding rate of 80 proteins,we successfully validate the view that protein folding is a quantum conformational transition.We conclude that(i) a correlation between the protein folding rate and the contact inertial moment exists;(ii) multi-state protein folding can be regarded as a quantum conformational transition similar to that of two-state proteins but with an intermediate delay.We have estimated the order of magnitude of the time delay;(iii) folding can be classified into two types,exergonic and endergonic.Most of the two-state proteins with higher folding rate are exergonic and most of the multi-state proteins with low folding rate are endergonic.The folding speed limit is determined by exergonic folding.