分子对接技术在色谱配基筛选中的应用与优化

分子对接技术是药物虚拟筛选的重要手段,将它应用到固定化配基与蛋白质相互作用的研究中需要改进.以目标蛋白质整体为研究对象,采用不同大小的滚球分子计算生成不同的蛋白质表面,分析在不同表面上的对接结果与配基吸附容量间的相关性.结果表明固定化配基与蛋白质相互作用主要发生在蛋白质表面上,并在以滚球分子半径5.0 A计算生成的蛋白质表面上的对接结果更能反映固定化配基与蛋白质的真实作用.     

PostDock: A novel visualization tool for the analysis of molecular docking

“PostDock”, a new visualization tool for the analysis and comparison of molecular docking results is described. It processes a docking results database and displays an interactive pseudo-3D snapshot of multiple ligand docking poses such that their docking energies and docking poses are visually encoded for rapid assessment. The docking energies are represented by a transparency scale whereas the docking poses are encoded by a color scale. The applications of PostDock for ligand–protein docking and for a novel molecular design approach termed “reverse-docking” are presented.     

Antileishmanial phytochemical phenolics: Molecular docking to potential protein targets

A molecular docking analysis has been carried out to examine potential Leishmania protein targets of antiprotozoal plant-derived polyphenolic compounds. A total of 352 phenolic phytochemicals, including 10 aurones, six cannabinoids, 34 chalcones, 20 chromenes, 52 coumarins, 92 flavonoids, 41 isoflavonoids, 52 lignans, 25 quinones, eight stilbenoids, nine xanthones, and three miscellaneous phenolic compounds, were used in the virtual screening study using 24 Leishmania enzymes (52 different protein structures from the Protein Data Bank). Noteworthy protein targets were Leishmania dihydroorotate dehydrogenase, N-myristoyl transferase, phosphodiesterase B1, pteridine reductase, methionyl-tRNA synthetase, tyrosyl-tRNA synthetase, uridine diphosphate-glucose pyrophosphorylase, nicotinamidase, and glycerol-3-phosphate dehydrogenase. Based on in-silico analysis of antiparasitic polyphenolics in this study, two aurones, one chalcone, five coumarins, six flavonoids, one isoflavonoid, three lignans, and one stilbenoid, can be considered to be promising drug leads worthy of further investigation.     

A method for including protein flexibility in protein-ligand docking: improving tools for database mining and virtual screening

Second-generation methods for docking ligands into their biological receptors, such as FLOG, provide for flexibility of the ligand but not of the receptor. Molecular dynamics based methods, such as free energy perturbation, account for flexibility, solvent effects, etc., but are very time consuming. We combined the use of statistical analysis of conformational samples from short-run protein molecular dynamics with grid-based docking protocols and demonstrated improved performance in two test cases. Our statistical analysis explores the importance of the average strength of a potential interaction with the biological target and optionally applies a weighting depending on the variability in the strength of the interaction seen during dynamics simulation. Using these methods, we improved the num-top-ranked 10% of a database of drug-like molecules, in searches based on the three-dimensional structure of the protein. These methods are able to match the ability of manual docking to assess likely inactivity on steric grounds and indeed to rank order ligands from a homologous series of cyclooxygenase-2 inhibitors with good correlation to their true activity. Furthermore, these methods reduce the need for human intervention in setting up molecular docking experiments.     

Single-coordinate-driving method for molecular docking: application to modeling of guest inclusion in cyclodextrin

An extension of the computer program CICADA has been developed that allows us to use the single-coordinate-driving (SCD) method for flexible molecular docking. The docking procedure is composed of three independent space rotations, three independent translations, and the torsions selected by the user. One of the coordinates is driven; the other coordinates are relaxed. This procedure follows low-energy wells on the potential energy surface of the entire system. The program allows us to dock more than one ligand molecule to the receptor. We ran two test examples, docking N,N-dimethylformamide into alpha-cyclodextrin and R-phenoxypropionic acid into beta-cyclodextrin. The test examples showed that the SCD approach is able to overcome high-energy barriers and to cover the entire box within which the search is performed. The limitations of molecular dynamics docking in comparison with our approach also are discussed. The philosophy of the newly developed approach is not only to find the best dock for the receptor-ligand(s) system, but also to describe all the important binding modes and provide a good starting point for studying the dynamics within the cavity during the docking process.     

Local active noise control using a novel method of designing quiet zones

This paper is concerned with sound minimization in space for local active control in pure tone diffuse fields. Theoretical studies have been performed to develop a new method of designing larger zones of quiet than are obtained with conventional systems. The principle of this new method is to maximize the area of the 10 dB quiet zones. This is in contrast to the conventional design methods, where the acoustic pressure or the acoustic pressure and particle velocity are set to zero at given cancellation points, or the acoustic pressure is minimized over an area using 2-norm and ∞-norm strategies. It is shown that larger zones of quiet are obtained using this new method. The preliminary experiment has also been carried out to validate the simulation results. The main contributions of the paper are that a novel method of designing active systems to generate larger zones of quiet is proposed and the performance of the active systems is analyzed through computer simulations and experiments.     

Recognition of docking sites on a protein using β-shape based on Voronoi diagram of atoms

A protein consists of atoms. Given a protein, the automatic recognition of depressed regions on the surface of the protein, often called docking sites or pockets, is important for the analysis of interaction between a protein and a ligand and facilitates fast development of new drugs.Presented in this paper is a geometric approach for the detection of docking sites using β-shape which is based on the Voronoi diagram for atoms in Euclidean distance metric. We first propose a geometric construct called a β-shape which represents the proximity among atoms on the surface of a protein. Then, using the β-shape, which takes the size differences among different atoms into account, we present an algorithm to extract the pockets for the possible docking site on the surface of a protein.     

VRDD: applying virtual reality visualization to protein docking and design

We have developed an interactive docking program called VRDD. It offers various modes of displaying molecules in an immersive, three-dimensional virtual reality (VR) environment. It allows a user to interactively perform molecular docking aided by automatic docking and side chain conformational search. Binding free energies are computed in real time, and the program enables the user to explore only clash-free orientations of a ligand. VRDD also supplies visual and auditory feedback during docking and side chain search, indicating the levels of atomic overlap and interaction energy. The stunning VR graphics immerse users in the scene and can maximally stimulate their design intuition. We have tested VRDD on three cases with increasing complexity: a nine-residue-long peptide bound to a major histocompatibility complex (MHC) molecule, barstar bound to barnase, and an antibody bound to a hemagglutinin. Without prior knowledge, combinations of hand-docking and automatic refinement led to accurate complex structures for the first two complexes. The third case, for which all automatic docking algorithms failed to identify the correct complex in a previous blind test, also failed for VRDD. Our results show that the combination of VR docking and automatic docking can make unique contributions to molecular modeling.     

新型抗流感病毒药物——三羟基甲氧基黄酮分子对接的研究

运用柔性分子对接程序Affinity,深入研究了5,7,4'-三羟基-8-甲氧基黄酮(MF)与N1、N9亚型神经氨酸酶之间的结合方式并阐明其作用机制.结果表明MF与N1亚型神经氨酸酶之间有一种作用模式,其结合能为-70.26 kcal·mol-1,而与N9亚型之间存两种竞争性的结合模式,最大结合能为-83.51 kcal·mol-1.进一步分析发现MF与这两种亚型神经氨酸酶相互作用的作用力类型、氢键作用及关键作用的氨基酸残基等有着明显的区别.现行药物奥斯米韦作用模式单一,MF则可以与各种亚型甚至变异的神经氨酸酶发生很好地相互作用.因此,MF是一种极具应用前景的新型抗流感病毒药物.结合前人的研究成果,本研究提出了以MF为底物的流感药物修饰方向.     

一种新型控制方法—自抗扰控制技术及其工程应用综述

自抗扰控制（active disturbance rejection control,ADRC）是韩京清研究员于1998年正式提出的一种不依赖被控对象模型的新型实用技术,具有很好的工程应用前景。为了便于理论分析与工程实际应用的推广实现,高志强教授在ADRC的基础上提出易于参数整定的线性自抗扰控制（LADRC）,极大地推动了自抗扰控制理论发展与实际应用。本文简要介绍了自抗扰控制的基本思想及线性自抗扰控制的基本原理,较为系统地阐述了自抗扰控制理论的研究进展,就自抗扰控制在实际工程领域中的应用进行了分类总结,最后给出需要进一步深入研究的方向。     

Molecular modeling, docking and ADMET studies applied to the design of a novel hybrid for treatment of Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia in adults, which is characterized by senile plaquets and cholinergic deficit as the disease progresses. Improvement of cholinergic neurotransmission is the basis of some drugs currently used in the treatment of AD. It is achieved by acetylcholinesterase (AChE) inhibition, the enzyme responsible for acetylcholine hydrolysis. Molecular modeling techniques were of utmost importance to design a new pharmaceutical against Alzheimer's disease, with potential inhibitory activity over AChE, since the inhibition of human plasma butyrylcholinesterase (BChE) may cause side effects. Some of the drugs currently used in the treatment of AD are capable of increasing the cholinergic transmission through the AChE inhibition. In this work we proposed molecular hybrids of tacrine with donepezil (fusion of these structures), in order to suggest new proposals of AChE inhibitors for future treatment of AD. We have analyzed all the structures by docking, density functional studies and drug like properties.     

A simple method to calculate the accessible volume of protein-bound ligands: application for ligand selectivity

We here present a method for estimating the accessible volume surrounding each atom of a ligand when bound to a receptor. The accessible volumes are calculated as the volume of a sphere with fixed radius, centered on each ligand atom, not simultaneously occupied by the volume of the receptor. The method is capable of describing the packing of the ligand in the binding pocket. Moreover, where structural models of several receptors in complex with the same ligand are available, a comparative study discriminating on accessible volumes can be performed. For these cases, a relatively large accessible volume in a particular receptor might indicate that this receptor has a unique cavity that might be exploited to develop a selective ligand analog. The ligand atoms showing variation in surrounding volume accessibility when bound to different receptors constitute attractive anchor points where one might want to attach substituents that modify the selectivity of the ligand. We have applied the described method to two different enzyme-ligand systems that bind tetrahydrobiopterin, i.e. the aromatic amino acid hydroxylases and nitric oxygen synthases. Our results yield new insights into the specificity of cofactor binding to these protein families.     

SOMAP: a novel interactive approach to multiple protein sequences alignment

A novel interactive method for generating multiple protein sequence alignments is described. The program has no internal limit to the number or length of sequences it can handle and is designed for use with DEC VAX processors running the VMS operating system. The approach used is essentially one of manual sequence manipulation, aided by built-in symbolic displays of identities and similarities, and strict and 'fuzzy' (ambiguous) pattern-matching facilities. Additional flexibility is provided by means of an interface to a publicly available automatic alignment system and to a comprehensive sequence analysis package.     

Correction to a novel framework for rapid diagnosis of COVID-19 on computed tomography scans

Pattern Analysis and Applications - A correction to this paper has been published: https://doi.org/10.1007/s10044-021-00969-x     

A novel dynamic genetic algorithm-based method for vehicle scheduling in cross docking systems with frequent unloading operation

An important factor for efficiently managing the supply chain is to efficiently control the physical flow of the supply chain. For this purpose, many companies try to use efficient methods to increase customer satisfaction and reduce costs. Cross docking is a good method to reduce the warehouse space requirements, inventory management costs, and turnaround times for customer orders. This paper proposes a novel dynamic genetic algorithm-based method for scheduling vehicles in cross docking systems such that the total operation time is minimized. In this paper, it is assumed that a temporary storage is placed at the shipping dock and inbound vehicles are allowed to repeatedly enter and leave the dock to unload their products. In the proposed method of this paper two different kinds of chromosome for inbound and outbound trucks are proposed. In addition, some algorithms are proposed including initialization, operational time calculation, crossover and mutation for inbound and outbound trucks, independently. Moreover a dynamic approach is proposed for performing crossover and mutation operation in genetic algorithm. In order to evaluate the performance of the proposed algorithm of this paper, various examples are provided and analyzed. The computational results reveal that the proposed algorithm of this paper performs better than two well-known works of literature in providing solutions with shorter operation time.     

Antifaces: a novel, fast method for image detection

This paper offers a novel detection method, which works well even in the case of a complicated image collection. It can also be applied to detect 3D objects under different views. The detection problem is solved by sequentially applying very simple filters (or detectors), which are designed to yield small results on the multitemplate (hence antifaces), and large results on “random” natural images. This is achieved by making use of a simple probabilistic assumption on the distribution of natural images, which is borne out well in practice. Only images which passed the threshold test imposed by the first detector are examined by the second detector, etc. The detectors are designed to act independently so that their false alarms are uncorrelated; this results in a false alarm rate which decreases exponentially in the number of detectors. The algorithm's performance compares favorably to the well-known eigenface and support vector machine based algorithms, but is substantially faster     

SMFCC:一种新的语音信号特征提取方法

针对说话人识别系统中存在的有效语音特征提取以及噪声影响的问题,提出了一种新的语音特征提取方法——基于S变换的美尔倒谱系数(SMFCC)。该方法是在传统美尔倒谱系数(MFCC)的基础上利用S变换的二维时频多分辨率特性,以及奇异值分解(SVD)方法的二维时频矩阵有效去噪性,并结合相关统计分析方法最终获得语音特征。采用TIMIT语音数据库,将所提的特征和现有特征进行对比实验。SMFCC特征的等错误率(EER)和最小检测代价(MinDCF)均小于线性预测倒谱系数(LPCC)、MFCC及其结合方法LMFCC,比MFCC的EER和MinDCF08分别下降了3.6%与17.9%。实验结果表明所提方法能够有效去除语音信号中的噪声,提升局部分辨率。     

Inverse docking method for new proteins targets identification: A parallel approach

Molecular docking is a widely used computational technique that allows studying structure-based interactions complexes between biological objects at the molecular scale. The purpose of the current work is to develop a set of tools that allows performing inverse docking, i.e., to test at a large scale a chemical ligand on a large dataset of proteins, which has several applications on the field of drug research. We developed different strategies to parallelize/distribute the docking procedure, as a way to efficiently exploit the computational performance of multi-core and multi-machine (cluster) environments. The experiments conducted to compare these different strategies encourage the search for decomposing strategies since it improves the execution of inverse docking.     

高维共鸣识别——蛋白质比较的新方法

在提出的符号序列的高维数字表达以及高维傅里叶变换概念的基础上,提出了蛋白质比较的新方法——高维共鸣识别。将两种蛋白质对应的氨基酸序列转化为向量序列,分别计算它们对应的向量序列的离散傅里叶变换。据此,定义两个蛋白质序列所对应的交叉谱函数,考查交叉谱函数的信噪比,判断两种蛋白质序列的相似性或差异性。计算结果显示它是蛋白质比对的又一个有效方法,是Cosic一维共鸣识别的拓展。