Designing allosteric peptide ligands targeting a globular protein

Heterogeneous Synthetic Vesicles toward Artificial Cells: Engineering Structure and Composition of Membranes for Multimodal Functionalities

The desire to develop artificial cells to imitate living cells in synthetic vesicle platforms has continuously increased over the past few decades. In particular, heterogeneous synthetic vesicles made from two or more building blocks have attracted attention for artificial cell applications based on their multifunctional modules with asymmetric structures. In addition to the traditional liposomes or polymersomes, polypeptides and proteins have recently been highlighted as potential building blocks to construct artificial cells owing to their specific biological functionalities. Incorporating one or more functionally folded, globular protein into synthetic vesicles enables more cell-like functions mediated by proteins. This Review highlights the recent research about synthetic vesicles toward artificial cell models, from traditional synthetic vesicles to protein-assembled vesicles with asymmetric structures. We aim to provide fundamental and practical insights into applying knowledge on molecular self-assembly to the bottom-up construction of artificial cell platforms with heterogeneous building blocks.

Tuning the Structural Integrity and Mechanical Properties of Globular Protein Vesicles by Blending Crosslinkable and NonCrosslinkable Building Blocks

Vesicles made from functionally folded, globular proteins that perform specific biological activities, such as catalysis, sensing, or therapeutics, show potential applications as artificial cells, microbioreactors, or protein drug delivery vehicles. The mechanical properties of vesicle membranes, including the elastic modulus and hardness, play a critical role in dictating the stability and shape transformation of the vesicles under external stimuli triggers. Herein, we have developed a strategy to tune the mechanical properties and integrity of globular protein vesicle (GPV) membranes of which building molecules are recombinant fusion protein complexes: a mCherry fused with an acidic leucine zipper (mCherry-Z_E) and a basic leucine zipper fused with an elastin-like polypeptide (Z_R-ELP). To control the mechanical properties of GPVs, we introduced a nonstandard amino acid (para-azidophenylalanine (pAzF)) into the ELP domains (ELP-X), which enabled the creation of crosslinked vesicles under ultraviolet (UV) irradiation. Crosslinked GPVs made from mCherry-Z_E/Z_R-ELP-X complexes presented higher stability than noncrosslinked GPVs under hypotonic osmotic stress. The degree of swelling of GPVs increased as less crosslinking was achieved in the vesicle membranes, which resulted in the disassembly of GPVs into membraneless coacervates. Nanoindentation by atomic force microscopy (AFM) confirmed that the stiffness and Young's elastic modulus of GPVs increase as the blending molar ratio of Z_R-ELP-X to Z_R-ELP increases to make vesicles. The results obtained in this study suggest a rational design to make GPVs with tunable mechanical properties for target applications by simply varying the blending ratio of Z_R-ELP and Z_R-ELP-X in the vesicle self-assembly.

Targeting the C-Terminal Domain Small Phosphatase 1

The human C-terminal domain small phosphatase 1 (CTDSP1/SCP1) is a protein phosphatase with a conserved catalytic site of DXDXT/V. CTDSP1’s major activity has been identified as dephosphorylation of the 5th Ser residue of the tandem heptad repeat of the RNA polymerase II C-terminal domain (RNAP II CTD). It is also implicated in various pivotal biological activities, such as acting as a driving factor in repressor element 1 (RE-1)-silencing transcription factor (REST) complex, which silences the neuronal genes in non-neuronal cells, G1/S phase transition, and osteoblast differentiation. Recent findings have denoted that negative regulation of CTDSP1 results in suppression of cancer invasion in neuroglioma cells. Several researchers have focused on the development of regulating materials of CTDSP1, due to the significant roles it has in various biological activities. In this review, we focused on this emerging target and explored the biological significance, challenges, and opportunities in targeting CTDSP1 from a drug designing perspective.

Common molecular mechanism of the hepatic lesion and the cardiac parasympathetic regulation in chronic hepatitis C infection: a critical role for the muscarinic receptor type 3

BACKGROUND

The pathophysiological overlapping between Sjorgen's Syndrome (SS) and HCV, presence of anti- muscarinic receptor type 3 (M3R) antibodies in SS, the role that M3R plays in the regulation of the heart rate, has led to the assumption that cardiovagal dysfunction in HCV patients is caused by anti-M3R antibodies elicited by HCV proteins or by their direct interaction with M3R.

RESULTS

To identify HCV protein which possibly is crossreactive with M3R or which binds to this receptor, we performed the Informational Spectrum Method (ISM) analysis of the HCV proteome. This analysis revealed that NS5A protein represents the most probable interactor of M3R or that this viral protein could elicit antibodies which modulate function of this receptor. Further detailed structure/function analysis of NS5A and M3R performed by the ISM method extended with other Digital Signal processing (DSP) approaches revealed domains of these proteins which participate in their crossreactivity or in their direct interaction, representing promising diagnostic and therapeutic targets.

CONCLUSIONS

Application of the ISM with other compatible bioinformatics methods offers new perspectives for identifying diagnostic and therapeutic targets for complicated forms of HCV and other viral infections. We show how the electron-ion interaction potential (EIIP) amino-acid scale used in the ISM combined with a robust, high performance hydrophobicity scale can provide new insights for understanding protein structure/function and protein-protein interactions.

Sequence determinants of protein architecture

Delineation of the relationship between sequence and structure in proteins has proven elusive. Most studies of this problem use alignment methods and other approaches based on the characteristics of individual residues. It is demonstrated herein that the sequence-structure relationship is determined in significant part by global characteristics of sequence organization. Information encoded in complete sequences is required to distinguish proteins in different architectural groups. It is found that the statistically significant differences between sequences encoding different architectures are encoded in a surprisingly small set of low-wave-number sequence periodicities. It would therefore appear that unexpected simplicity in an appropriately defined Fourier space may be an inherent characteristic of the sequences of folded proteins.

Peptides complementary to the active loop of porin P2 from Haemophilus influenzae modulate its activity

Haemophilus influenzae type b (Hib) is one of the leading causes of invasive bacterial infection in young children. It is characterized by inflammation that is mainly mediated by cytokines and chemokines. One of the most abundant components of the Hib outer membrane is the P2 porin, which has been shown to induce the release of several inflammatory cytokines. A synthetic peptide corresponding to loop L7 of the porin activates JNK and p38 mitogen-activated protein kinase (MAPK) pathways. We report a novel use of the complementary peptide approach to design a peptide that is able to bind selectively to the protein P2, thereby reducing its activity. This work provides insights into essential molecular details of P2 that may affect the pathogenesis of Hib infections where interruption of the signaling cascade could represent an attractive therapeutic strategy.

Looking for a sequence based allostery definition: a statistical journey at different resolution scales

The aim of this work was to detect allosteric hotspots signatures characterizing protein regions acting as the 'key drivers' of global allosteric conformational change. We computationally estimated the relative strength of intra-molecular interaction in allosteric proteins between two putative allostery-susceptible sites using a co-evolution model based upon the optimization of the cross-correlation in terms of free-energy-transfer hydrophobicity scale (Tanford scale) distribution along the chain. Cross-Recurrence Quantification Analysis (Cross-RQA) applied on the sequences of allostery susceptible sites showed evidence of strong interaction amongst allosteric susceptible sites. This could be due to transient weak molecular bonds between allostery susceptible patches enabling regions far-apart to come together. Further, using a large protein dataset, by comparing allosteric protein set with a randomly generated sequence population as well as a generic protein set, we reconfirmed our earlier findings that hydrophobicity patterning (as formalized by Recurrence Quantification Analysis (RQA) descriptors) may serve as determinant of allostery and its relevance in the transmission of allosteric conformational change. We applied RQA to free-energy-transfer hydrophobicity-transformed amino acid sequences of the allostery dataset to extract allostery specific global sequence features. These free-energy-transfer hydrophobicity-based RQA markers proved to be representative of allosteric signatures and not related to the differences between randomly generated and real proteins. These free-energy-transfer hydrophobicity-based RQA markers when evaluated by pattern recognition tools could distinguish allosteric proteins with 92% accuracy.

Spectral analysis of a protein conformational switch

The existence of conformational switching in proteins, induced by single amino acid mutations, presents an important challenge to our understanding of the physics of protein folding. Sequence-local methods, commonly used to detect structural homology, are incapable of accounting for this phenomenon. We examine a set of proteins, derived from the G(A) and G(B) domains of Streptococcus protein G, which are known to show a dramatic conformational change as a result of single-residue replacement. It is shown that these sequences, which are almost identical locally, can have very different global patterns of physical properties. These differences are consistent with the observed complete change in conformation. These results suggest that sequence-local methods for identifying structural homology can be misleading. They point to the importance of global sequence analysis in understanding sequence-structure relationships.

A computational approach identifies two regions of Hepatitis C Virus E1 protein as interacting domains involved in viral fusion process

Background

The E1 protein of Hepatitis C Virus (HCV) can be dissected into two distinct hydrophobic regions: a central domain containing an hypothetical fusion peptide (FP), and a C-terminal domain (CT) comprising two segments, a pre-anchor and a trans-membrane (TM) region. In the currently accepted model of the viral fusion process, the FP and the TM regions are considered to be closely juxtaposed in the post-fusion structure and their physical interaction cannot be excluded. In the present study, we took advantage of the natural sequence variability present among HCV strains to test, by purely sequence-based computational tools, the hypothesis that in this virus the fusion process involves the physical interaction of the FP and CT regions of E1.

Results

Two computational approaches were applied. The first one is based on the co-evolution paradigm of interacting peptides and consequently on the correlation between the distance matrices generated by the sequence alignment method applied to FP and CT primary structures, respectively. In spite of the relatively low random genetic drift between genotypes, co-evolution analysis of sequences from five HCV genotypes revealed a greater correlation between the FP and CT domains than respect to a control HCV sequence from Core protein, so giving a clear, albeit still inconclusive, support to the physical interaction hypothesis.

The second approach relies upon a non-linear signal analysis method widely used in protein science called Recurrence Quantification Analysis (RQA). This method allows for a direct comparison of domains for the presence of common hydrophobicity patterns, on which the physical interaction is based upon. RQA greatly strengthened the reliability of the hypothesis by the scoring of a lot of cross-recurrences between FP and CT peptides hydrophobicity patterning largely outnumbering chance expectations and pointing to putative interaction sites. Intriguingly, mutations in the CT region of E1, reducing the fusion process in vitro, strongly reduced the amount of cross-recurrence further supporting interaction between this region and FP.

Conclusion

Our results support a fusion model for HCV in which the FP and the C-terminal region of E1 are juxtaposed and interact in the post-fusion structure. These findings have general implications for viruses, as any visualization of the post-fusion FP-TM complex has been precluded by the impossibility to obtain crystallised viral fusion proteins containing the trans-membrane region. This limitation gives to sequence based modelling efforts a crucial role in the sketching of a molecular interpretation of the fusion process. Moreover, our data also have a more general relevance for cell biology as the mechanism of intracellular fusion showed remarkable similarities with viral fusion

PROTDES: CHARMM toolbox for computational protein design

We present an open-source software able to automatically mutate any residue positions and find the best aminoacids in an arbitrary protein structure without requiring pairwise approximations. Our software, PROTDES, is based on CHARMM and it searches automatically for mutations optimizing a protein folding free energy. PROTDES allows the integration of molecular dynamics within the protein design. We have implemented an heuristic optimization algorithm that iteratively searches the best aminoacids and their conformations for an arbitrary set of positions within a structure. Our software allows CHARMM users to perform protein design calculations and to create their own procedures for protein design using their own energy functions. We show this by implementing three different energy functions based on different solvent treatments: surface area accessibility, generalized Born using molecular volume and an effective energy function. PROTDES, a tutorial, parameter sets, configuration tools and examples are freely available at http://soft.synth-bio.org/protdes.html.

Using support vector machines to distinguish enzymes: approached by incorporating wavelet transform

The enzymatic attributes of newly found protein sequences are usually determined either by biochemical analysis of eukaryotic and prokaryotic genomes or by microarray chips. These experimental methods are both time-consuming and costly. With the explosion of protein sequences registered in the databanks, it is highly desirable to develop an automated method to identify whether a given new sequence belongs to enzyme or non-enzyme. The discrete wavelet transform (DWT) and support vector machine (SVM) have been used in this study for distinguishing enzyme structures from non-enzymes. The networks have been trained and tested on two datasets of proteins with different wavelet basis functions, decomposition scales and hydrophobicity data types. Maximum accuracy has been obtained using SVM with a wavelet function of Bior2.4, a decomposition scale j=5, and Kyte-Doolittle hydrophobicity scales. The results obtained by the self-consistency test, jackknife test and independent dataset test are encouraging, which indicates that the proposed method can be employed as a useful assistant technique for distinguishing enzymes from non-enzymes.

Design, synthesis and screening of antisense peptide based combinatorial peptide libraries towards an aromatic region of SARS-CoV

A combination of high-performance affinity chromatography and antisense peptide based combinatorial peptide libraries was used to screen a potential inhibitor for SARS-CoV. An aromatic-amino acid-rich region within the transmembrane domain at the C terminal of spike (S) protein identified as a membrane-active region was chosen as the target sense peptide (SP) and immobilized as affinity ligand. Four antisense peptides were designed based on the degeneracy of genetic codes. One of them was screened as the lead peptide to construct the extended peptide libraries (EPL). The library screening was carried out at pH 5.5 so as to mimic the low-pH milieu required by virus fusion. After five cycles of screening, a dodecapeptide KKKKYRNIRRPG (DP) was identified to possess the highest binding affinity to the immobilized sense peptide. The dissociation constant of the complex between the DP and the SP was 5.64 x 10(-7) M in a physiological condition. The recognition between the DP and recombinant SARS S protein was demonstrated by ELISA assay to be in a saturable way. The competitive inhibition of the sense peptide in the competitive ELISA reveals the affinity binding between the DP and SARS S protein is specific and directed towards the target SP of the S protein. The results indicate this preferred polypeptide can be used as a lead compound of potent inhibitor of SARS-CoV. The mechanism study suggests the specific recognition between the DP and the target peptide was due to sequence-dependent and multi-modal affinity interaction.

Acoustic Wave (TSM) Biosensors: Weighing Bacteria

This chapter is focused on the development and use of acoustic wave biosensor platforms for the detection of bacteria, specifically those based on the thickness shear mode (TSM) resonator. We demonstrated the mechanical and electrical implications of bacterial positioning at the solid-liquid interface of a TSM biosensor and presented a model of the TSM with bacteria attached operating as coupled oscillators. The experiments and model provide an understanding of the nature of the signals produced by acoustic wave devices when they are used for testing bacteria. The paradox of “negative mass” could be a real threat to the interpretation of experimental results related to the detection of bacteria. The knowledge of the true nature of “negative mass” linked to the strength of bacteria attachment will contribute significantly to our understanding of the results of “weighing bacteria.” The results of this work can be used for bacterial detection and control of processes of bacterial settlement, bacterial colonization, biofilm formation, and bacterial infection in which bacterial attachment plays a role.