Structure-based substitutions for increased solubility of a designed protein

Manipulation of protein solubility is important for many aspectsof protein design and engineering. Previously, we designed aseries of consensus ankyrin repeat proteins containing one,two, three and four identical repeats (1ANK, 2ANK, 3ANK and4ANK). These proteins, particularly 4ANK, are intended for useas a universal scaffold on which specific binding sites canbe constructed. Despite being well folded and extremely stable,4ANK is soluble only under acidic conditions. Designing interactionswith naturally occurring proteins requires the designed proteinto be soluble at physiological pH. Substitution of six leucineswith arginine on exposed hydrophobic patches on the surfaceof 4ANK resulted in increased solubility over a large pH range.Study of the pH dependence of stability demonstrated that 4ANKis one of the most stable ankyrin repeat proteins known. Inaddition, analogous leucine to arginine substitutions on thesurface of 2ANK allowed the partially folded protein to assumea fully folded conformation. Our studies indicate that replacementof surface-exposed hydrophobic residues with positively chargedresidues can significantly improve protein solubility at physiologicalpH. Received June 23, 2003; revised August 22, 2003; accepted August 28, 2003.     

Design of novel FN3 domains with high stability by a consensus sequence approach

The use of consensus design to produce stable proteins has been applied to numerous structures and classes of proteins. Here, we describe the engineering of novel FN3 domains from two different proteins, namely human fibronectin and human tenascin-C, as potential alternative scaffold biotherapeutics. The resulting FN3 domains were found to be robustly expressed in Escherichia coli, soluble and highly stable, with melting temperatures of 89 and 78°C, respectively. X-ray crystallography was used to confirm that the consensus approach led to a structure consistent with the FN3 design despite having only low-sequence identity to natural FN3 domains. The ability of the Tenascin consensus domain to withstand mutations in the loop regions connecting the β-strands was investigated using alanine scanning mutagenesis demonstrating the potential for randomization in these regions. Finally, rational design was used to produce point mutations that significantly increase the stability of one of the consensus domains. Together our data suggest that consensus FN3 domains have potential utility as alternative scaffold therapeutics.     

The creation of a novel fluorescent protein by guided consensus engineering

Consensus engineering has been used to increase the stability of a number of different proteins, either by creating consensus proteins from scratch or by modifying existing proteins so that their sequences more closely match a consensus sequence. In this paper we describe the first application of consensus engineering to the ab initio creation of a novel fluorescent protein. This was based on the alignment of 31 fluorescent proteins with >62% homology to monomeric Azami green (mAG) protein, and used the sequence of mAG to guide amino acid selection at positions of ambiguity. This consensus green protein is extremely well expressed, monomeric and fluorescent with red shifted absorption and emission characteristics compared to mAG. Although slightly less stable than mAG, it is better expressed and brighter under the excitation conditions typically used in single molecule fluorescence spectroscopy or confocal microscopy. This study illustrates the power of consensus engineering to create stable proteins using the subtle information embedded in the alignment of similar proteins and shows that the benefits of this approach may extend beyond stability.     

Protein Design with Deep Learning

Computational Protein Design (CPD) has produced impressive results for engineering new proteins, resulting in a wide variety of applications. In the past few years, various efforts have aimed at replacing or improving existing design methods using Deep Learning technology to leverage the amount of publicly available protein data. Deep Learning (DL) is a very powerful tool to extract patterns from raw data, provided that data are formatted as mathematical objects and the architecture processing them is well suited to the targeted problem. In the case of protein data, specific representations are needed for both the amino acid sequence and the protein structure in order to capture respectively 1D and 3D information. As no consensus has been reached about the most suitable representations, this review describes the representations used so far, discusses their strengths and weaknesses, and details their associated DL architecture for design and related tasks.     

Design and facile production of recombinant resilin-like polypeptides: gene construction and a rapid protein purification method

Resilin is an elastic protein found in specialized regions of the cuticle of insects, which displays unique resilience and fatigue lifetime properties. As is the case with many elastomeric proteins, including elastin, gliadin and spider silks, resilin contains distinct repetitive domains that appear to confer elastic properties to the protein. Recent work within our laboratory has demonstrated that cloning and expression of exon 1 of the Drosophila melanogaster CG15920 gene, encoding a putative resilin-like protein, results in a recombinant protein that can be photochemically crosslinked to form a highly resilient, elastic biomaterial (Rec1 resilin). The current study describes a recursive cloning strategy for generating synthetic genes encoding multiple copies of consensus polypeptides, based on the repetitive domains within resilin-like genes from D. melanogaster and Anopheles gambiae. A simple non-chromatographic purification method that can be applied to these synthetic proteins and Rec1 is also reported. These methods for the design and purification of resilin-like periodic polypeptides will facilitate the future investigation of structural and functional properties of resilin, and the development of novel highly resilient biomaterials.     

RFCM-PALM: In-Silico Prediction of S-Palmitoylation Sites in the Synaptic Proteins for Male/Female Mouse Data

S-palmitoylation is a reversible covalent post-translational modification of cysteine thiol side chain by palmitic acid. S-palmitoylation plays a critical role in a variety of biological processes and is engaged in several human diseases. Therefore, identifying specific sites of this modification is crucial for understanding their functional consequences in physiology and pathology. We present a random forest (RF) classifier-based consensus strategy (RFCM-PALM) for predicting the palmitoylated cysteine sites on synaptic proteins from male/female mouse data. To design the prediction model, we have introduced a heuristic strategy for selection of the optimum set of physicochemical features from the AAIndex dataset using (a) K-Best (KB) features, (b) genetic algorithm (GA), and (c) a union (UN) of KB and GA based features. Furthermore, decisions from best-trained models of the KB, GA, and UN-based classifiers are combined by designing a three-star quality consensus strategy to further refine and enhance the scores of the individual models. The experiment is carried out on three categorized synaptic protein datasets of a male mouse, female mouse, and combined (male + female), whereas in each group, weighted data is used as training, and knock-out is used as the hold-out set for performance evaluation and comparison. RFCM-PALM shows ~80% area under curve (AUC) score in all three categories of datasets and achieve 10% average accuracy (male—15%, female—15%, and combined—7%) improvements on the hold-out set compared to the state-of-the-art approaches. To summarize, our method with efficient feature selection and novel consensus strategy shows significant performance gains in the prediction of S-palmitoylation sites in mouse datasets.     

3- Instead of 4-helix formation in a de novo designed protein in solution revealed by small-angle X-ray scattering

De novo design and chemical synthesis of proteins and their mimics are central approaches for understanding protein folding and accessing proteins with novel functions. We have previously described carbohydrates as templates for the assembly of artificial proteins, so-called carboproteins. Here, we describe the preparation and structural studies of three alpha-helical bundle carboproteins, which were assembled from three different carbohydrate templates and one amphiphilic hexadecapeptide sequence. This heptad repeat peptide sequence has been reported to lead to 4-alpha-helix formation. The low resolution solution structures of the three carboproteins were analyzed by means of small-angle X-ray scattering (SAXS) and synchrotron radiation circular dichroism (SRCD). The ab initio SAXS data analysis revealed that all three carboproteins adopted an unexpected 3+1-helix folding topology in solution, while the free peptide formed a 3-helix bundle. This finding is consistent with the calculated alpha-helicities based on the SRCD data, which are 72 and 68 % for two of the carboproteins. The choice of template did not affect the overall folding topology (that is for the 3+1 helix bundle) the template did have a noticeable impact on the solution structure. This was particularly evident when comparing 4-helix carboprotein monomers with the 2x2-helix carboprotein dimer as the latter adopted a more compact conformation. Furthermore, the clear conformational differences observed between the two 4-helix (3+1) carboproteins based on D-altropyranoside and D-galactopyranoside support the notion that folding is affected by the template, and subtle variations in template distance-geometry design may be exploited to control the solution fold. In addition, the SRCD data show that template assembly significantly increases thermostability.     

Amino acid sequence templates derived from recurrent turn motifs in proteins: critical evaluation of their predictive power

Amino acid sequence patterns suggested to characterize specificrecurrent turn conformations in proteins are tested as to theirpredictive power in a database containing 75 proteins of knownstructure. Many of these patterns are found to be associatedwith local structures that differ from the motifs originallyused to derive them. It is therefore concluded that, while theycould be useful for improving predictions made by other methods,their stand-alone predictive power is poor. The issue of derivingand validating consensus sequence patterns for use in proteinstructure prediction is raised.     

Secondary structure prediction for modelling by homology

An improved method of secondary structure prediction has beendeveloped to aid the modelling of proteins by homology. Selecteddata from four published algorithms are scaled and combinedas a weighted mean to produce consensus algorithms. Each consensusalgorithm is used to predict the secondary structure of a proteinhomologous to the target protein and of known structure. Bycomparison of the predictions to the known structure, accuracyvalues are calculated and a consensus algorithm chosen as theoptimum combination of the composite data for prediction ofthe homologous protein. This customized algorithm is then usedto predict the secondary structure of the unknown protein. Inthis manner the secondary structure prediction is initiallytuned to the required protein family before prediction of thetarget protein. The method improves statistical secondary structureprediction and can be incorporated into more comprehensive systemssuch as those involving consensus prediction from multiple sequencealignments. Thirty one proteins from five families were usedto compare the new method to that of Garnier, Osguthorpe andRobson (GOR) and sequence alignment. The improvement over GORis naturally dependent on the similarity of the homologous protein,varying from a mean of 3% to 7% with increasing alignment significancescore.     

塑料蜂窝格结构参数确定及连续挤出模具的设计

探讨了从塑料蜂窝格产品最小规格参数确定到符合该合理规格的挤出模具设计过程和思路,提供可行的工程估算公式和计算机辅助有限元分析验证的方式,在SP挤出技术支持下,推算了与模具设计相关的基础参数,框定了模具设计的虑及范围,最终提供综合设计实例,为下一步的拓展系列设计建立了简便的重复模式。     

管壳式换热器设计中几个常见问题

就管壳式换热器设计中常常遇到的几个问题进行了讨论,目的在于达成共识,确保产品设计质量。     

Using FlAsH to probe conformational changes in a large HEAT repeat protein

We have investigated the use of FlAsH, a small fluorogenic molecule that binds to tetracysteine motifs, to probe folding of the 15-HEAT repeat protein PR65A. PR65A is one of a special class of modular non-globular proteins known as tandem repeat proteins, which are composed of small structural motifs that stack to form elongated, one-dimensional architectures. We were able to introduce linear and bipartite tetracysteine motifs at several sites along the α-helical HEAT array of PR65A without disrupting the structure or stability. When the linear tetracysteine motif CCPGCC was used, FlAsH fluorescence reported globally on the folding of the protein. When the tetracysteine motif was displayed in bipartite mode through the engineering of pairs of cysteines on adjacent HEAT repeats, FlAsH fluorescence became a reporter of local conformation and of oligomerisation. Thus, by designing FlAsH-binding sites at different locations along the repeat array one can interrogate specific properties of PR65A, paving the way for structure-function analysis of this protein both in vitro and in the cell.     

Growth by Insertion: The Family of Bacterial DDxP Proteins

We have identified a variety of proteins in species of the Legionella, Aeromonas, Pseudomonas, Vibrio, Nitrosomonas, Nitrosospira, Variovorax, Halomonas, and Rhizobia genera, which feature repetitive modules of different length and composition, invariably ending at the COOH side with Asp–Asp–x–Pro (DDxP) motifs. DDxP proteins range in size from 900 to 6200 aa (amino acids), and contain 1 to 5 different module types, present in one or multiple copies. We hypothesize that DDxP proteins were modeled by the action of specific endonucleases inserting DNA segments into genes encoding DDxP motifs. Target site duplications (TSDs) formed upon repair of staggered ends generated by endonuclease cleavage would explain the DDxP motifs at repeat ends. TSDs acted eventually as targets for the insertion of more modules of the same or different types. Repeat clusters plausibly resulted from amplification of both repeat and flanking TSDs. The proposed growth shown by the insertion model is supported by the identification of homologous proteins lacking repeats in Pseudomonas and Rhizobium. The 85 DDxP repeats identified in this work vary in length, and can be sorted into short (136–215 aa) and long (243–304 aa) types. Conserved Asp–Gly–Asp–Gly–Asp motifs are located 11–19 aa from the terminal DDxP motifs in all repeats, and far upstream in most long repeats.     

The consensus concept for thermostability engineering of proteins: further proof of concept

Previously, we calculated a consensus amino acid sequence from13 homologous fungal phytases. A synthetic gene was constructedand recombinantly expressed. Surprisingly, consensus phytase-1was 15–26°C more thermostable than all parent phytasesused in its design [Lehmann et al. (2000)Protein Eng., 13, 49–57].In the present study, inclusion of six further phytase sequencesin the amino acid sequence alignment resulted in the replacementof 38 amino acid residues in either one or both of the new consensusphytases-10 and -11. Since consensus phytase-10, again, was7.4°C more thermostable than consensus phytase-1, the thermostabilityeffects of most of the 38 amino acid substitutions were testedby site-directed mutagenesis. Both stabilizing and destabilizingmutations were identified, but all affected the stability ofthe enzyme by <3°C. The combination of all stabilizingamino acid exchanges in a multiple mutant of consensus phytase-1increased the unfolding temperature from 78.0 to 88.5°C.Likewise, back-mutation of four destabilizing amino acids andintroduction of an additional stabilizing amino acid in consensusphytase-10 further increased the unfolding temperature from85.4 to 90.4°C. The thermostabilization achieved is theresult of a combination of slight improvements from multipleamino acid exchanges rather than being the effect of a singleor of just a few dominating mutations that have been introducedby chance. The present findings support the general validityof the consensus concept for thermostability engineering ofproteins.     

(Dys)function Follows Form: Nucleic Acid Structure,Repeat Expansion,and Disease Pathology in FMR1 Disorders

Fragile X-related disorders (FXDs), also known as FMR1 disorders, are examples of repeat expansion diseases (REDs), clinical conditions that arise from an increase in the number of repeats in a disease-specific microsatellite. In the case of FXDs, the repeat unit is CGG/CCG and the repeat tract is located in the 5′ UTR of the X-linked FMR1 gene. Expansion can result in neurodegeneration, ovarian dysfunction, or intellectual disability depending on the number of repeats in the expanded allele. A growing body of evidence suggests that the mutational mechanisms responsible for many REDs share several common features. It is also increasingly apparent that in some of these diseases the pathologic consequences of expansion may arise in similar ways. It has long been known that many of the disease-associated repeats form unusual DNA and RNA structures. This review will focus on what is known about these structures, the proteins with which they interact, and how they may be related to the causative mutation and disease pathology in the FMR1 disorders.     

基于分子动力学的橡胶聚合物计算机辅助设计方法

聚合物分子设计的关键步骤是得到能够满足多种性质要求的重复单元结构。作为化学产品工程中的新型发展手段，计算机辅助分子设计(CAMD)技术可以通过基团贡献法生成满足约束条件的聚合物重复单元结构，分子动力学(MD)技术则可以在微观层面上进行计算机实验模拟系统性质。建立了聚合物的CAMD-MD通用设计方法，并进行轮胎橡胶聚合物的分子设计，首先基于基团贡献法进行重复单元的设计；其次，利用层次分析法确定多性质权重排名，并基于分子动力学方法探究候选结构的性质；最后将方法应用于实际橡胶结构中，模拟得到聚能密度、密度、玻璃化转换温度和热导率性质，验证了方法的可行性。     

Emerging Connections between Nuclear Pore Complex Homeostasis and ALS

Developing effective treatments for neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) requires understanding of the underlying pathomechanisms that contribute to the motor neuron loss that defines the disease. As it causes the largest fraction of familial ALS cases, considerable effort has focused on hexanucleotide repeat expansions in the C9ORF72 gene, which encode toxic repeat RNA and dipeptide repeat (DPR) proteins. Both the repeat RNA and DPRs interact with and perturb multiple elements of the nuclear transport machinery, including shuttling nuclear transport receptors, the Ran GTPase and the nucleoporin proteins (nups) that build the nuclear pore complex (NPC). Here, we consider recent work that describes changes to the molecular composition of the NPC in C9ORF72 model and patient neurons in the context of quality control mechanisms that function at the nuclear envelope (NE). For example, changes to NPC structure may be caused by the dysregulation of a conserved NE surveillance pathway mediated by the endosomal sorting complexes required for the transport protein, CHMP7. Thus, these studies are introducing NE and NPC quality control pathways as key elements in a pathological cascade that leads to C9ORF72 ALS, opening entirely new experimental avenues and possibilities for targeted therapeutic intervention.