Synthesis of Epitope-Targeting Antibody Based on Native Protein–Protein Interactions for Ftsz Filamentation Suppressor

Abstract Phage display and biopanning is a powerful tool for generating binding molecules for a specific target. However, the selection process based on binding affinity provides no assurance for the antibody’s affinity to the target epitope. In this study, we propose a molecular-evolution approach guided by native protein–protein interactions to generate epitope-targeting antibodies. The binding-site sequence in a native protein was grafted into a complementarity-determining region (CDR) in the antibody, and a nonrelated CDR loop (in the grafted antibody) was randomized by phage display techniques. In this construction of antibodies by integrating graft and evolution technology (CAnIGET method), suitable grafting of the functional sequence weakly functionalized the antibody, and the molecular-evolution approach enhanced the binding function to inhibit the native protein–protein interactions. Antibody fragments with an affinity for filamenting temperature-sensitive mutant Z (FtsZ) were constructed and completely inhibited the polymerization of FtsZ. Consequently, the expression of these fragments drastically decreased the cell division rate. We demonstrate the potential of the CAnIGET method with the use of native protein–protein interactions for steady epitope-specific evolutionary engineering.

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Structure-Based Stabilization of Non-native Protein–Protein Interactions of Coronavirus Nucleocapsid Proteins in Antiviral Drug Design

Journal of Medicinal Chemistry ◽

10.1021/acs.jmedchem.9b01913 ◽

2020 ◽

Vol 63 (6) ◽

pp. 3131-3141 ◽

Cited By ~ 22

Author(s):

Shan-Meng Lin ◽

Shih-Chao Lin ◽

Jia-Ning Hsu ◽

Chung-ke Chang ◽

Ching-Ming Chien ◽

...

Keyword(s):

Drug Design ◽

Protein Interactions ◽

Antiviral Drug ◽

Native Protein ◽

Protein Protein Interactions ◽

Nucleocapsid Proteins

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Engineering cell signaling modulators from native protein–protein interactions

Current Opinion in Structural Biology ◽

10.1016/j.sbi.2016.11.002 ◽

2017 ◽

Vol 45 ◽

pp. 25-35 ◽

Cited By ~ 8

Author(s):

Wei Zhang ◽

Moshe Ben-David ◽

Sachdev S Sidhu

Keyword(s):

Cell Signaling ◽

Protein Interactions ◽

Native Protein ◽

Protein Protein Interactions

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Use of periplasmic target protein capture for phage display engineering of tight-binding protein–protein interactions

Protein Engineering Design and Selection ◽

10.1093/protein/gzr043 ◽

2011 ◽

Vol 24 (11) ◽

pp. 819-828 ◽

Cited By ~ 2

Author(s):

Bartlomiej G. Fryszczyn ◽

Nicholas G. Brown ◽

Wanzhi Huang ◽

Miriam A. Balderas ◽

Timothy Palzkill

Keyword(s):

Phage Display ◽

Protein Interactions ◽

Binding Protein ◽

Tight Binding ◽

Target Protein ◽

Protein Protein Interactions ◽

Protein Capture

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A phage display system designed to detect and study protein-protein interactions

Molecular Microbiology ◽

10.1111/j.1365-2958.2007.06077.x ◽

2008 ◽

Vol 67 (4) ◽

pp. 719-728 ◽

Cited By ~ 6

Author(s):

Catherine L. Bair ◽

Amos Oppenheim ◽

Andrei Trostel ◽

Gali Prag ◽

Sankar Adhya

Keyword(s):

Phage Display ◽

Protein Interactions ◽

Display System ◽

Protein Protein Interactions

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Struct2Graph: A graph attention network for structure based predictions of protein-protein interactions

10.1101/2020.09.17.301200 ◽

2020 ◽

Author(s):

Mayank Baranwal ◽

Abram Magner ◽

Jacob Saldinger ◽

Emine S. Turali-Emre ◽

Shivani Kozarekar ◽

...

Keyword(s):

Protein Interactions ◽

Intracellular Signaling ◽

Metabolic Regulation ◽

Selection Process ◽

3D Structure ◽

Structural Data ◽

Sequence Information ◽

Protein Protein Interactions ◽

Attention Network ◽

Interaction Sites

AbstractDevelopment of new methods for analysis of protein-protein interactions (PPIs) at molecular and nanometer scales gives insights into intracellular signaling pathways and will improve understanding of protein functions, as well as other nanoscale structures of biological and abiological origins. Recent advances in computational tools, particularly the ones involving modern deep learning algorithms, have been shown to complement experimental approaches for describing and rationalizing PPIs. However, most of the existing works on PPI predictions use protein-sequence information, and thus have difficulties in accounting for the three-dimensional organization of the protein chains. In this study, we address this problem and describe a PPI analysis method based on a graph attention network, named Struct2Graph, for identifying PPIs directly from the structural data of folded protein globules. Our method is capable of predicting the PPI with an accuracy of 98.89% on the balanced set consisting of an equal number of positive and negative pairs. On the unbalanced set with the ratio of 1:10 between positive and negative pairs, Struct2Graph achieves a five-fold cross validation average accuracy of 99.42%. Moreover, unsupervised prediction of the interaction sites by Struct2Graph for phenol-soluble modulins are found to be in concordance with the previously reported binding sites for this family.Author summaryPPIs are the central part of signal transduction, metabolic regulation, environmental sensing, and cellular organization. Despite their success, most strategies to decode PPIs use sequence based approaches do not generalize to broader classes of chemical compounds of similar scale as proteins that are equally capable of forming complexes with proteins that are not based on amino acids, and thus lack of an equivalent sequence-based representation. Here, we address the problem of prediction of PPIs using a first of its kind, 3D structure based graph attention network (available at https://github.com/baranwa2/Struct2Graph). Despite its excellent prediction performance, the novel mutual attention mechanism provides insights into likely interaction sites through its knowledge selection process in a completely unsupervised manner.

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Green, orange, red, and far-red optogenetic tools derived from cyanobacteriochromes

10.1101/769422 ◽

2019 ◽

Author(s):

Jaewan Jang ◽

Sherin McDonald ◽

Maruti Uppalapati ◽

G. Andrew Woolley

Keyword(s):

Phage Display ◽

Protein Interactions ◽

Red Light ◽

Protein Protein Interactions ◽

Target State ◽

Binding Partners ◽

Absorbing State

AbstractExisting optogenetic tools for controlling protein-protein interactions are available in a limited number of wavelengths thereby limiting opportunities for multiplexing. The cyanobacteriochrome (CBCR) family of photoreceptors responds to an extraordinary range of colors, but light-dependent binding partners for CBCR domains are not currently known. We used a phage-display based approach to develop small (~50-residue) monomeric binders selective for the green absorbing state (Pg), or for the red absorbing state (Pr) of the CBCR Am1_c0023g2 with a phycocyanobilin chromophore and also for the far-red absorbing state (Pfr) of Am1_c0023g2 with a biliverdin chromophore. These bind in a 1:1 mole ratio with KDs for the target state from 0.2 to 2 μM and selectivities from 10 to 500-fold. We demonstrate green, orange, red, and far-red light-dependent control of protein-protein interactions in vitro and also in vivo where these multicolor optogenetic tools are used to control transcription in yeast.

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Modified Potential Functions Result in Enhanced Predictions of a Protein Complex by All-Atom MD Simulations, Confirming a Step-wise Association Process for Native PPIs

10.1101/241810 ◽

2018 ◽

Cited By ~ 1

Author(s):

Zhen-lu Li ◽

Matthias Buck

Keyword(s):

Electrostatic Interaction ◽

Protein Interactions ◽

Protein Complex ◽

Complex Structure ◽

Md Simulations ◽

Potential Functions ◽

Amino Acid Side Chain ◽

Native Protein ◽

Protein Protein Interactions ◽

Steering Mechanism

ABSTRACTNative protein-protein interactions (PPIs) are the cornerstone for understanding the structure, dynamics and mechanisms of function of protein complexes. In this study, we investigate the association of the SAM domains of the EphA2 receptor and SHIP2 enzyme by performing a combined total of 48 μs all-atom molecular dynamics (MD) simulations. While the native SAM heterodimer is only predicted at a low rate of 6.7% with the original CHARMM36 force field, the yield is increased to 16.7% and to 18.3% by scaling the vdW solute-solvent interactions (better fitting the solvation free energy of amino acid side chain analogues) and by an increase of vdW radius of guanidinium interactions, and thus a dramatic reduction of electrostatic interaction between Arg and Glu/Asn in CHARMM36m, respectively. These modifications effectively improve the overly sticky association of proteins, such as ubiquitin, using the original potential function. By analyzing the 25 native SAM complexes formed in the simulations, we find that their formation involves a pre-orientation guided by electrostatic interaction, consistent with an electrostatic steering mechanism. The complex could then transform to the native protein interaction surfaces directly from a well pre-orientated position (Δinterface-RMSD < 5Å). In other cases, modest (< 90°) orientational and/or translational adjustments are needed (5 Å <Δi-RMSD <10 Å) to the native complex. Although the tendency for non-native complexes to dissociate has nearly doubled with the modified potential functions, a re-association to the correct complex structure is still rare. Instead a most non-native complexes are undergoing configurational changes/surface searching, which do not lead to native structures on a timescale of 250 ns. These observations provide a rich picture on mechanisms of protein-protein complex formation, and suggest that computational predictions of native complex protein-protein interactions could be improved further.

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