计算机虚拟筛选技术在害虫行为调节剂研究中的应用

害虫行为调节剂是一种以嗅觉系统为靶标的绿色农药,在害虫的田间管理中发挥着重要的作用。然而,其先导化合物的发现通常依赖一系列生物测定的方法,不仅费时费力,且发现效率低。近年来,随着昆虫嗅觉功能数据的积累和结构生物学的飞速发展,以机器学习技术和分子对接为代表的2种基于计算机的药物虚拟筛选方法在害虫行为调节剂的先导化合物研究中发挥着重要的作用,极大地促进了先导化合物的发现效率,减少了筛选的盲目性。本文系统综述了2种虚拟筛选方法及其在害虫行为调节剂先导化合物研究中的应用,并对2种筛选策略在实际应用中存在的问题及应用前景进行了讨论。     

De novo design of the hydrophobic core of ubiquitin.

We have previously reported the development and evaluation of a computational program to assist in the design of hydrophobic cores of proteins. In an effort to investigate the role of core packing in protein structure, we have used this program, referred to as Repacking of Cores (ROC), to design several variants of the protein ubiquitin. Nine ubiquitin variants containing from three to eight hydrophobic core mutations were constructed, purified, and characterized in terms of their stability and their ability to adopt a uniquely folded native-like conformation. In general, designed ubiquitin variants are more stable than control variants in which the hydrophobic core was chosen randomly. However, in contrast to previous results with 434 cro, all designs are destabilized relative to the wild-type (WT) protein. This raises the possibility that beta-sheet structures have more stringent packing requirements than alpha-helical proteins. A more striking observation is that all variants, including random controls, adopt fairly well-defined conformations, regardless of their stability. This result supports conclusions from the cro studies that non-core residues contribute significantly to the conformational uniqueness of these proteins while core packing largely affects protein stability and has less impact on the nature or uniqueness of the fold. Concurrent with the above work, we used stability data on the nine ubiquitin variants to evaluate and improve the predictive ability of our core packing algorithm. Additional versions of the program were generated that differ in potential function parameters and sampling of side chain conformers. Reasonable correlations between experimental and predicted stabilities suggest the program will be useful in future studies to design variants with stabilities closer to that of the native protein. Taken together, the present study provides further clarification of the role of specific packing interactions in protein structure and stability, and demonstrates the benefit of using systematic computational methods to predict core packing arrangements for the design of proteins.     

Computational Modeling of Protein Stability: Quantitative Analysis Reveals Solutions to Pervasive Problems

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A Refined Open State of the Glycine Receptor Obtained via Molecular Dynamics Simulations

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A Comparison of Protein and mRNA Expression during Development of the Soil Dwelling Prokaryote (S. coelicolor)

In this paper, correlation analysis of protein and mRNA levels in the soil dwelling bacteria Streptomyces coelicolor (S. coelicolor M145) is presented during development of the population as it grew in liquid medium using three biological and two technical replicates, measured during exponential growth, and its entry into the stationary phase. The proteome synthesis time series are compared with the gene expression time series measured previously under identical experimental conditions. Results reveal that about one third of protein/mRNA synthesis profiles are well correlated while another third are correlated negatively. Functional analysis of the highly correlated groups is presented. Based on numerical simulation, the negative correlation between protein and mRNA is shown to be caused by the difference between the rate of translation and protein degradation.     

The AutoDock suite at 30

The AutoDock suite provides a comprehensive toolset for computational ligand docking and drug design and development. The suite builds on 30 years of methods development, including empirical free energy force fields, docking engines, methods for site prediction, and interactive tools for visualization and analysis. Specialized tools are available for challenging systems, including covalent inhibitors, peptides, compounds with macrocycles, systems where ordered hydration plays a key role, and systems with substantial receptor flexibility. All methods in the AutoDock suite are freely available for use and reuse, which has engendered the continued growth of a diverse community of primary users and third‐party developers.     

Extension of a de novo TIM barrel with a rationally designed secondary structure element

The ability to construct novel enzymes is a major aim in de novo protein design. A popular enzyme fold for design attempts is the TIM barrel. This fold is a common topology for enzymes and can harbor many diverse reactions. The recent de novo design of a four‐fold symmetric TIM barrel provides a well understood minimal scaffold for potential enzyme designs. Here we explore opportunities to extend and diversify this scaffold by adding a short de novo helix on top of the barrel. Due to the size of the protein, we developed a design pipeline based on computational ab initio folding that solves a less complex sub‐problem focused around the helix and its vicinity and adapt it to the entire protein. We provide biochemical characterization and a high‐resolution X‐ray structure for one variant and compare it to our design model. The successful extension of this robust TIM‐barrel scaffold opens opportunities to diversify it towards more pocket like arrangements and as such can be considered a building block for future design of binding or catalytic sites.     

Soft tissue structures resisting anterior instability in a computational glenohumeral joint model

The glenohumeral joint is the most dislocated joint in the body due to the lack of bony constraints and the dependence on soft tissue for stability. The roles that various structures provide to joint function are important for understanding injury treatment and orthopaedic device design purposes. The goal of this study was to develop a computational model of the glenohumeral joint whereby joint behaviour was dictated by articular contact, ligamentous constraints, muscle loading and external perturbations. The bone structure of the computational model consisted of assembled computer tomographic images of the scapula, humerus and clavicle. The soft tissue elements were composed of forces and tension-only springs that represented muscles and ligaments. Validation of this model was achieved by comparing computational predictions to the results of a cadaveric experiment in which the relative contribution of muscles and ligaments to anterior joint stability was examined. The computational model predicted an anterior subluxation force that was similar to the cadaveric experimental results in humeral external rotation. The individual structure results showed the subscapularis to be critical to stabilisation in both neutral and external rotations, the biceps stabilised the joint in neutral but not in external rotation, and the inferior glenohumeral ligament resisted anterior displacement only in external rotation. The model's predictions were similar to the conclusions of the cadaveric experiment and the literature. Knowledge gained from this type of model could assist in further understanding the contribution of soft tissue stabilisers to joint function, pre-operative planning or the design of orthopaedic implants.