Protein design with fragment databases

Structure-based computational methods are popular tools for designing proteins and interactions between proteins because they provide the necessary insight and details required for rational engineering. Here, we first argue that large-scale databases of fragments contain a discrete but complete set of building blocks that can be used to design structures. We show that these structural alphabets can be saturated to provide conformational ensembles that sample the native structure space around energetic minima. Second, we show that catalogs of interaction patterns hold the key to overcome the lack of scaffolds when computationally designing protein interactions. Finally, we illustrate the power of database-driven computational protein design methods by recent successful applications and discuss what challenges remain to push this field forward.     

Prediction of protein retention in hydrophobic interaction chromatography

Hydrophobic interaction chromatography (HIC) is a powerful technique for protein separation. This review examines methodologies for predicting protein retention time in HIC involving elution with salt gradients. The methodologies discussed consider three-dimensional structure data of the protein and its surface hydrophobicity. Despite their limitations, the methods discussed are useful in designing purification processes for proteins and easing the tedious experimental work that is currently required for developing purification protocols.     

Transient pockets on XIAP-BIR2: toward the characterization of putative binding sites of small-molecule XIAP inhibitors

Protein-protein interactions are abundant in signal transduction pathways and thus of crucial importance in the regulation of apoptosis. However, designing small-molecule inhibitors for these potential drug targets is very challenging as such proteins often lack well-defined binding pockets. An example for such an interaction is the binding of the anti-apoptotic BIR2 domain of XIAP to the pro-apoptotic caspase-3 that results in the survival of damaged cells. Although small-molecule inhibitors of this interaction have been identified, their exact binding sites on XIAP are not known as its crystal structures reveal no suitable pockets. Here, we apply our previously developed protocol for identifying transient binding pockets to XIAP-BIR2. Transient pockets were identified in snapshots taken during four different molecular dynamics simulations that started from the caspase-3:BIR2 complex or from the unbound BIR2 structure and used water or methanol as solvent. Clustering of these pockets revealed that surprisingly many pockets opened in the flexible linker region that is involved in caspase-3 binding. We docked three known inhibitors into these transient pockets and so determined five putative binding sites. In addition, by docking two inactive compounds of the same series, we show that this protocol is also able to distinguish between binders and nonbinders which was not possible when docking to the crystal structures. These findings represent a first step toward the understanding of the binding of small-molecule XIAP-BIR2 inhibitors on a molecular level and further highlight the importance of considering protein flexibility when designing small-molecule protein-protein interaction inhibitors.     

In silico binding free energy predictability with π-π interaction energy-augmented scoring function: benzimidazole Raf inhibitors as a case study

The ability to estimate binding affinities of ligands precisely is of paramount importance in designing drugs. Docking programs are used primarily to predict the binding mode of ligands to receptors. However, current scoring functions as used in docking programs are not reliable enough to predict binding affinities of ligands without any further calculations. In the present study, we investigate the usefulness of adding π-π interaction energies between ring groups of residues and ligands to the scoring function for docking. It is found that such addition helps ranking ligand activities more correctly. LMP2 calculation is used to measure π-π interaction energies between ring groups. The result of this simple addition shows possibility of π-π interaction generalization in scoring functions.     

Case–Control Studies of Gene–Environment Interaction: Bayesian Design and Analysis

Summary With increasing frequency, epidemiologic studies are addressing hypotheses regarding gene‐environment interaction. In many well‐studied candidate genes and for standard dietary and behavioral epidemiologic exposures, there is often substantial prior information available that may be used to analyze current data as well as for designing a new study. In this article, first, we propose a proper full Bayesian approach for analyzing studies of gene–environment interaction. The Bayesian approach provides a natural way to incorporate uncertainties around the assumption of gene–environment independence, often used in such an analysis. We then consider Bayesian sample size determination criteria for both estimation and hypothesis testing regarding the multiplicative gene–environment interaction parameter. We illustrate our proposed methods using data from a large ongoing case–control study of colorectal cancer investigating the interaction of N‐acetyl transferase type 2 (NAT2) with smoking and red meat consumption. We use the existing data to elicit a design prior and show how to use this information in allocating cases and controls in planning a future study that investigates the same interaction parameters. The Bayesian design and analysis strategies are compared with their corresponding frequentist counterparts.     

Insights into bacterial protein glycosylation in human microbiota

The study of human microbiota is an emerging research topic. The past efforts have mainly centered on studying the composition and genomic landscape of bacterial species within the targeted communities. The interaction between bacteria and hosts is the pivotal event in the initiation and progression of infectious diseases. There is a great need to identify and characterize the molecules that mediate the bacteria-host interaction. Bacterial surface exposed proteins play an important role in the bacteria- host interaction. Numerous surface proteins are glycosylated, and the glycosylation is crucial for their function in mediating the bacterial interaction with hosts. Here we present an overview of surface glycoproteins from bacteria that inhabit three major mucosal environments across human body: oral, gut and skin. We describe the important enzymes involved in the process of protein glycosylation, and discuss how the process impacts the bacteria-host interaction. Emerging molecular details underlying glycosylation of bacterial surface proteins may lead to new opportunities for designing anti-infective small molecules, and developing novel vaccines in order to treat or prevent bacterial infection.     

Cellular protein TTRAP interacts with HIV-1 integrase to facilitate viral integration

TTRAP is a PML-NB protein that is involved in the NF-κB signaling pathway. TTRAP was recently identified by yeast two-hybrid analysis as a HIV-1 integrase (HIV-1 IN) interacting protein. This interaction was verified by co-immunoprecipitation, GST pull-down, and intracellular imaging, and deletion assays suggested that the N-terminal 180 residues of TTRAP are responsible for the interaction. In stable TTRAP knock-down cell lines, the integration of viral vectors decreased significantly compared with non-silenced cell lines. Conversely, overexpression of TTRAP by transient transfection increased the percentage of integration events. This is the first time that TTRAP has been shown to interact with HIV-1 IN and facilitate lentiviral vector integration. These findings reveal a new function of TTRAP and expand our understanding of the cellular response to HIV infection. The interaction between TTRAP and HIV-1 IN may be useful in designing new anti-viral strategies as well as for improving the efficiency of lentiviral-vector-mediated gene delivery.     

Molecular dynamics simulations and statistical coupling analysis reveal functional coevolution network of oncogenic mutations in the CDKN2A–CDK6 complex

Coevolution between proteins is crucial for understanding protein–protein interaction. Simultaneous changes allow a protein complex to maintain its overall structural–functional integrity. In this study, we combined statistical coupling analysis (SCA) and molecular dynamics simulations on the CDK6–CDKN2A protein complex to evaluate coevolution between proteins. We reconstructed an inter-protein residue coevolution network, consisting of 37 residues and 37 interactions. It shows that most of the coevolved residue pairs are spatially proximal. When the mutations happened, the stable local structures were broken up and thus the protein interaction was decreased or inhibited, with a following increased risk of melanoma. The identification of inter-protein coevolved residues in the CDK6–CDKN2A complex can be helpful for designing protein engineering experiments.     

A Proposed Framework for the Management of Water Quality in Arid-Region Lakes

For arid-region lakes, management conflicts are likely to occur between quantity and quality of water supplied: increasing quantity of water supply can lead to water quality deterioration. Such conflicts can best be resolved within an effective management program based on awareness and cooperation at all levels of water management from policy makers to experts. We propose a general framework for designing effective water resource management programs for lakes based on concrete definitions of management criteria such as water quality. The proposed system requires close interaction between policy makers, water resource managers, water suppliers and users, hydrological engineers and limnologists. The significance of mathematical modeling as a self-organizing tool of the management program is emphasized, especially with regards to designing limnological investigations directed toward lake management. We illustrate the application of this approach to water resource management in arid-region lakes (Lake Kinneret, Israel and Lake Sevan, Armenia), where artificial variability of lake morphometry due to water use is a forcing function affecting water quality.     

热激蛋白gp96免疫学功能及在主动免疫治疗肿瘤和传染病中的应用

热激蛋白gp96可特异性结合来源于肿瘤和病毒的抗原肽,与抗原呈递细胞表面CD91等受体作用进入胞内,并在内质网中将结合的抗原通过抗原呈递链呈递给MHCI类分子,激活特异性T细胞。同时,与细胞表面Toll样受体(TLR)TLR2、TLR4等相互作用,激活天然免疫。近期研究发现调节性T细胞(Treg)对gp96免疫功能有显著抑制作用,随着对影响gp96免疫功能的免疫抑制机制的深入了解,以及利用汉逊酵母表达有免疫活性的全长gp96蛋白体系的建立,gp96将在治疗肿瘤及传染性疾病中发挥更大的作用。     

The jury is out on "guilt by association" trials.

The availability of comprehensive protein-protein interaction maps will significantly enhance medical research and aid the functional characterisation of novel genes. To date, the largest scale studies of protein-protein interactions have used the yeast two hybrid method. In this review we take a closer look at the different approaches used in these studies and discuss some key considerations that should be taken into account when designing high throughput interaction mapping projects.     

A new analytical approach to optimizing the design of large-scale composting systems

This paper proposes a new approach on aiding for optimizing the design, operations, and maintenance planning of new and existing large-scale composting facilities. Numerical modeling on mass/energy transport, degradation process, and turning/shifting processes was discussed. The models are integrated with the 3D finite element method based system, which is able to solve for mass/energy distribution fields influenced by biological activities at each corresponding location and interaction with arbitrary environment. As a result, designing and planning for more cost-effective and better performance facilities without performing trail tests shall become possible.     

In vitro genetics.

Understanding the basis of specificity in an intermolecular interaction is a common if difficult task; designing a specific intermolecular interaction is much more challenging. A new technique is described that has applications to both problems, at least with regard to nucleic acids. The power of this method lies in its ability to isolate extremely rare sequences with precisely specified properties from very large pools of random sequences.     

甜味分子与G蛋白偶联受体Tas1R2/3的相互作用及激活机制

甜味分子与C家族G蛋白偶联受体(G protein-coupled receptor,GPCR)的成员之一甜味受体相互作用,从而激活受体并引起甜味觉的感知。本文简要总结了甜味受体(taste receptor 2 and 3,Tas1R2/3)的结构与功能、甜味分子与受体相互作用并激活受体的机制,并对甜味受体研究领域的发展前景进行了展望。甜味分子与受体相互作用机制的阐明对于理解甜味觉的产生与GPCR的结构与功能具有重要的意义。此外,甜味受体结构与功能的研究可为有针对性地设计新型甜味化合物提供理论基础。     

Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods

Given the importance of protein-protein interactions for nearly all biological processes, the design of protein affinity reagents for use in research, diagnosis or therapy is an important endeavor. Engineered proteins would ideally have high specificities for their intended targets, but achieving interaction specificity by design can be challenging. There are two major approaches to protein design or redesign. Most commonly, proteins and peptides are engineered using experimental library screening and/or in vitro evolution. An alternative approach involves using protein structure and computational modeling to rationally choose sequences predicted to have desirable properties. Computational design has successfully produced novel proteins with enhanced stability, desired interactions and enzymatic function. Here we review the strengths and limitations of experimental library screening and computational structure-based design, giving examples where these methods have been applied to designing protein interaction specificity. We highlight recent studies that demonstrate strategies for combining computational modeling with library screening. The computational methods provide focused libraries predicted to be enriched in sequences with the properties of interest. Such integrated approaches represent a promising way to increase the efficiency of protein design and to engineer complex functionality such as interaction specificity.