An Approach for Engineering Peptides for Competitive Inhibition of the SARS-COV-2 Spike Protein.

SARS-CoV-2 is the virus responsible for a respiratory disease called COVID-19 that devastated global public health. Since 2020, there has been an intense effort by the scientific community to develop safe and effective prophylactic and therapeutic agents against this disease. In this context, peptides have emerged as an alternative for inhibiting the causative agent. However, designing peptides that bind efficiently is still an open challenge. Here, we show an algorithm for peptide engineering. Our strategy consists of starting with a peptide whose structure is similar to the interaction region of the human ACE2 protein with the SPIKE protein, which is important for SARS-COV-2 infection. Our methodology is based on a genetic algorithm performing systematic steps of random mutation, protein-peptide docking (using the PyRosetta library) and selecting the best-optimized peptides based on the contacts made at the peptide-protein interface. We performed three case studies to evaluate the tool parameters and compared our results with proposals presented in the literature. Additionally, we performed molecular dynamics (MD) simulations (three systems, 200 ns each) to probe whether our suggested peptides could interact with the spike protein. Our results suggest that our methodology could be a good strategy for designing peptides.

A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries.

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners but often include false positives. Furthermore, they provide no information about what the binding region is (e.g., the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competitive Binding Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment and the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies of AF and AF-CBA to help users identify scenarios where the approach will be most useful. Given the method's speed and accuracy, we anticipate its broad applicability to identify binding epitope regions among potential partners, setting the stage for experimental verification.

Biophysical Insights into the Antitumoral Activity of Crotalicidin against Breast Cancer Model Membranes.

Bioactive peptides have emerged as promising therapeutic agents with antimicrobial, antifungal, antiparasitic, and, recently, antitumoral properties with a mechanism of action based on membrane destabilization and cell death, often involving a conformational change in the peptide. This biophysical study aims to provide preliminary insights into the membrane-level antitumoral mode of action of crotalicidin, a cationic host defense peptide from rattlesnake venom, toward breast cancer cell lines. The lipid composition of breast cancer cell lines was obtained after lipid extraction and quantification to prepare representative cell membrane models. Membrane-peptide interaction studies were performed using differential scanning calorimetry and Fourier-transform infrared spectroscopy. The outcome evidences the potential antitumoral activity and selectivity of crotalicidin toward breast cancer cell lines and suggests a mechanism initiated by the electrostatic interaction of the peptide with the lipid bilayer surface and posterior conformation change with membrane intercalation between the acyl chains in negatively charged lipid systems. This research provides valuable information that clears up the antitumoral mode of action of crotalicidin.

Novel Polymyxin-Inspired Peptidomimetics Targeting the SARS-CoV-2 Spike:hACE2 Interface.

Though the bulk of the COVID-19 pandemic is behind, the search for effective and safe anti-SARS-CoV-2 drugs continues to be relevant. A highly pursued approach for antiviral drug development involves targeting the viral spike (S) protein of SARS-CoV-2 to prevent its attachment to the cellular receptor ACE2. Here, we exploited the core structure of polymyxin B, a naturally occurring antibiotic, to design and synthesize unprecedented peptidomimetics (PMs), intended to target contemporarily two defined, non-overlapping regions of the S receptor-binding domain (RBD). Monomers 1, 2, and 8, and heterodimers 7 and 10 bound to the S-RBD with micromolar affinity in cell-free surface plasmon resonance assays (KD ranging from 2.31 µM to 2.78 µM for dimers and 8.56 µM to 10.12 µM for monomers). Although the PMs were not able to fully protect cell cultures from infection with authentic live SARS-CoV-2, dimer 10 exerted a minimal but detectable inhibition of SARS-CoV-2 entry in U87.ACE2+ and A549.ACE2.TMPRSS2+ cells. These results validated a previous modeling study and provided the first proof-of-feasibility of using medium-sized heterodimeric PMs for targeting the S-RBD. Thus, heterodimers 7 and 10 may serve as a lead for the development of optimized compounds, which are structurally related to polymyxin, with improved S-RBD affinity and anti-SARS-CoV-2 potential.

Harnessing Aromatic-Histidine Interactions through Synergistic Backbone Extension and Side Chain Modification.

Peptide engineering efforts have delivered drugs for diverse human diseases. Side chain alteration is among the most common approaches to designing new peptides for specific applications. The peptide backbone can be modified as well, but this strategy has received relatively little attention. Here we show that new and favorable contacts between a His side chain on a target protein and an aromatic side chain on a synthetic peptide ligand can be engineered by rational and coordinated side chain modification and backbone extension. Side chain modification alone was unsuccessful. Binding measurements, high-resolution structural studies and pharmacological outcomes all support the synergy between backbone and side chain modification in engineered ligands of the parathyroid hormone receptor-1, which is targeted by osteoporosis drugs. These results should motivate other structure-based designs featuring coordinated side chain modification and backbone extension to enhance the engagement of peptide ligands with target proteins.

Peptide-based Interaction Proteomics.

Protein-protein interactions are often mediated by short linear motifs (SLiMs) that are located in intrinsically disordered regions (IDRs) of proteins. Interactions mediated by SLiMs are notoriously difficult to study, and many functionally relevant interactions likely remain to be uncovered. Recently, pull-downs with synthetic peptides in combination with quantitative mass spectrometry emerged as a powerful screening approach to study protein-protein interactions mediated by SLiMs. Specifically, arrays of synthetic peptides immobilized on cellulose membranes provide a scalable means to identify the interaction partners of many peptides in parallel. In this minireview we briefly highlight the relevance of SLiMs for protein-protein interactions, outline existing screening technologies, discuss unique advantages of peptide-based interaction screens and provide practical suggestions for setting up such peptide-based screens.

Kinetics of the multitasking high-affinity Win binding site of WDR5 in restricted and unrestricted conditions.

Recent advances in quantitative proteomics show that WD40 proteins play a pivotal role in numerous cellular networks. Yet, they have been fairly unexplored and their physical associations with other proteins are ambiguous. A quantitative understanding of these interactions has wide-ranging significance. WD40 repeat protein 5 (WDR5) interacts with all members of human SET1/MLL methyltransferases, which regulate methylation of the histone 3 lysine 4 (H3K4). Here, using real-time binding measurements in a high-throughput setting, we identified the kinetic fingerprint of transient associations between WDR5 and 14-residue WDR5 interaction (Win) motif peptides of each SET1 protein (SET1Win). Our results reveal that the high-affinity WDR5-SET1Win interactions feature slow association kinetics. This finding is likely due to the requirement of SET1Win to insert into the narrow WDR5 cavity, also named the Win binding site. Furthermore, our explorations indicate fairly slow dissociation kinetics. This conclusion is in accordance with the primary role of WDR5 in maintaining the functional integrity of a large multisubunit complex, which regulates the histone methylation. Because the Win binding site is considered a key therapeutic target, the immediate outcomes of this study could form the basis for accelerated developments in medical biotechnology.

Biophysical Characterization of LTX-315 Anticancer Peptide Interactions with Model Membrane Platforms: Effect of Membrane Surface Charge.

LTX-315 is a clinical-stage, anticancer peptide therapeutic that disrupts cancer cell membranes. Existing mechanistic knowledge about LTX-315 has been obtained from cell-based biological assays, and there is an outstanding need to directly characterize the corresponding membrane-peptide interactions from a biophysical perspective. Herein, we investigated the membrane-disruptive properties of the LTX-315 peptide using three cell-membrane-mimicking membrane platforms on solid supports, namely the supported lipid bilayer, intact vesicle adlayer, and tethered lipid bilayer, in combination with quartz crystal microbalance-dissipation (QCM-D) and electrochemical impedance spectroscopy (EIS) measurements. The results showed that the cationic LTX-315 peptide selectively disrupted negatively charged phospholipid membranes to a greater extent than zwitterionic or positively charged phospholipid membranes, whereby electrostatic interactions were the main factor to influence peptide attachment and membrane curvature was a secondary factor. Of note, the EIS measurements showed that the LTX-315 peptide extensively and irreversibly permeabilized negatively charged, tethered lipid bilayers that contained high phosphatidylserine lipid levels representative of the outer leaflet of cancer cell membranes, while circular dichroism (CD) spectroscopy experiments indicated that the LTX-315 peptide was structureless and the corresponding membrane-disruptive interactions did not involve peptide conformational changes. Dynamic light scattering (DLS) measurements further verified that the LTX-315 peptide selectively caused irreversible disruption of negatively charged lipid vesicles. Together, our findings demonstrate that the LTX-315 peptide preferentially disrupts negatively charged phospholipid membranes in an irreversible manner, which reinforces its potential as an emerging cancer immunotherapy and offers a biophysical framework to guide future peptide engineering efforts.

De Novo Development of Mitochondria-Targeted Molecular Probes Targeting Pink1.

Mitochondria play central roles in maintaining cellular metabolic homeostasis, cell survival and cell death, and generate most of the cell's energy. Mitochondria maintain their homeostasis by dynamic (fission and fusion) and quality control mechanisms, including mitophagy, the removal of damaged mitochondria that is mediated mainly by the Pink1/Parkin pathway. Pink1 is a serine/threonine kinase which regulates mitochondrial function, hitherto many molecular mechanisms underlying Pink1 activity in mitochondrial homeostasis and cell fate remain unknown. Peptides are vital biological mediators that demonstrate remarkable potency, selectivity, and low toxicity, yet they have two major limitations, low oral bioavailability and poor stability. Herein, we rationally designed a linear peptide that targets Pink1 and, using straightforward chemistry, we developed molecular probes with drug-like properties to further characterize Pink1. Initially, we conjugated a cell-penetrating peptide and a cross-linker to map Pink1's 3D structure and its interaction sites. Next, we conjugated a fluorescent dye for cell-imaging. Finally, we developed cyclic peptides with improved stability and binding affinity. Overall, we present a facile approach to converting a non-permeable linear peptide into a research tool possessing important properties for therapeutics. This is a general approach using straightforward chemistry that can be tailored for various applications by numerous laboratories.

Insight into the Mechanism of Action and Peptide-Membrane Interactions of Aib-Rich Peptides: Multitechnique Experimental and Theoretical Analysis.

The increase in resistant bacterial strains necessitates the identification of new antimicrobial molecules. Antimicrobial peptides (AMPs) are an attractive option because of evidence that bacteria cannot easily develop resistance to AMPs. The peptaibols, a class of naturally occurring AMPs, have shown particular promise as antimicrobial drugs, but their development has been hindered by their mechanism of action not being clearly understood. To explore how peptaibols might interact with membranes, circular dichroism, vibrational circular dichroism, linear dichroism, Raman spectroscopy, Raman optical activity, neutron reflectivity and molecular dynamics simulations have been used to study a small library of peptaibol mimics, the Aib-rich peptides. All the peptides studied quickly partitioned and oriented in membranes, and we found evidence of chiral interactions between the phospholipids and membrane-embedded peptides. The protocols presented in this paper open new ground by showing how chiro-optical spectroscopies can throw light on the mechanism of action of AMPs.

Identification of Serum Biomarkers for Systemic Lupus Erythematosus Using a Library of Phage Displayed Random Peptides and Deep Sequencing.

Systemic lupus erythematosus (SLE) is one of the most serious autoimmune diseases, characterized by highly diverse clinical manifestations. A biomarker is still needed for accurate diagnostics. SLE serum autoantibodies were discovered and validated using serum samples from independent sample cohorts encompassing 306 participants divided into three groups, i.e. healthy, SLE patients, and other autoimmune-related diseases. To discover biomarkers for SLE, a phage displayed random peptide library (Ph.D. 12) and deep sequencing were applied to screen specific autoantibodies in a total of 100 serum samples from 50 SLE patients and 50 healthy controls. A statistical analysis protocol was set up for the identification of peptides as potential biomarkers. For validation, 10 peptides were analyzed using enzyme-linked immunosorbent assays (ELISA). As a result, four peptides (SLE2018Val001, SLE2018Val002, SLE2018Val006, and SLE2018Val008) were discovered with high diagnostic power to differentiate SLE patients from healthy controls. Among them, two peptides, i.e. SLE2018Val001 and SLE2018Val002, were confirmed between SLE with other autoimmune patients. The procedure we established could be easily adopted for the identification of autoantibodies as biomarkers for many other diseases.

The C-terminal extension landscape of naturally presented HLA-I ligands.

HLA-I molecules play a central role in antigen presentation. They typically bind 9- to 12-mer peptides, and their canonical binding mode involves anchor residues at the second and last positions of their ligands. To investigate potential noncanonical binding modes, we collected in-depth and accurate HLA peptidomics datasets covering 54 HLA-I alleles and developed algorithms to analyze these data. Our results reveal frequent (442 unique peptides) and statistically significant C-terminal extensions for at least eight alleles, including the common HLA-A03:01, HLA-A31:01, and HLA-A68:01. High resolution crystal structure of HLA-A68:01 with such a ligand uncovers structural changes taking place to accommodate C-terminal extensions and helps unraveling sequence and structural properties predictive of the presence of these extensions. Scanning viral proteomes with the C-terminal extension motifs identifies many putative epitopes and we demonstrate direct recognition by human CD8+ T cells of a 10-mer epitope from cytomegalovirus predicted to follow the C-terminal extension binding mode.

Zn-Enhanced Asp-Rich Antimicrobial Peptides: N-Terminal Coordination by Zn(II) and Cu(II), Which Distinguishes Cu(II) Binding to Different Peptides.

The antimicrobial activity of surfactant-associated anionic peptides (SAAPs), which are isolated from the ovine pulmonary surfactant and are selective against the ovine pathogen Mannheimia haemolytica, is strongly enhanced in the presence of Zn(II) ions. Both calorimetry and ITC measurements show that the unique Asp-only peptide SAAP3 (DDDDDDD) and its analogs SAAP2 (GDDDDDD) and SAAP6 (GADDDDD) have a similar micromolar affinity for Zn(II), which binds to the N-terminal amine and Asp carboxylates in a net entropically-driven process. All three peptides also bind Cu(II) with a net entropically-driven process but with higher affinity than they bind Zn(II) and coordination that involves the N-terminal amine and deprotonated amides as the pH increases. The parent SAAP3 binds Cu(II) with the highest affinity; however, as shown with potentiometry and absorption, CD and EPR spectroscopy, Asp residues in the first and/or second positions distinguish Cu(II) binding to SAAP3 and SAAP2 from their binding to SAAP6, decreasing the Cu(II) Lewis acidity and suppressing its square planar amide coordination by two pH units. We also show that these metal ions do not stabilize a membrane disrupting ability nor do they induce the antimicrobial activity of these peptides against a panel of human pathogens.

Occurrence of Peptide-Peptide Interactions during the Purification of Self-Assembling Peptide f1-8 from a ß-Lactoglobulin Tryptic Hydrolysate.

Self-assembling peptides have gained attention because of their nanotechnological applications. Previous work demonstrated that the self-assembling peptide f1-8 (Pf1-8) that is generated from the tryptic hydrolysis of ß-lactoglobulin can form a hydrogel after several purification steps, including membrane filtration and consecutive washes. This study evaluates the impact of each processing step on peptide profile, purity, and gelation capacity of each fraction to understand the purification process of Pf1-8 and the peptide-peptide interactions involved. We showed that peptide-peptide interactions mainly occurred through electrostatic and hydrophobic interactions, influencing the fraction compositions. Indeed, the purity of Pf1-8 did not correlate with the number of wash steps. In addition to Pf1-8, two other hydrophobic peptides were identified, peptide f15-20, and peptide f41-60. The gelation observed could be induced either through peptide-peptide interactions or through self-assembling, both being driven by non-covalent bond and more specifically hydrophobic interactions.

Peptide Regulation of Gene Expression: A Systematic Review.

Peptides are characterized by their wide range of biological activity: they regulate functions of the endocrine, nervous, and immune systems. The mechanism of such action of peptides involves their ability to regulate gene expression and protein synthesis in plants, microorganisms, insects, birds, rodents, primates, and humans. Short peptides, consisting of 2-7 amino acid residues, can penetrate into the nuclei and nucleoli of cells and interact with the nucleosome, the histone proteins, and both single- and double-stranded DNA. DNA-peptide interactions, including sequence recognition in gene promoters, are important for template-directed synthetic reactions, replication, transcription, and reparation. Peptides can regulate the status of DNA methylation, which is an epigenetic mechanism for the activation or repression of genes in both the normal condition, as well as in cases of pathology and senescence. In this context, one can assume that short peptides were evolutionarily among the first signaling molecules that regulated the reactions of template-directed syntheses. This situation enhances the prospects of developing effective and safe immunoregulatory, neuroprotective, antimicrobial, antiviral, and other drugs based on short peptides.

Domain Analysis and Motif Matcher (DAMM): A Program to Predict Selectivity Determinants in Monosiga brevicollis PDZ Domains Using Human PDZ Data.

Choanoflagellates are single-celled eukaryotes with complex signaling pathways. They are considered the closest non-metazoan ancestors to mammals and other metazoans and form multicellular-like states called rosettes. The choanoflagellate Monosiga brevicollis contains over 150 PDZ domains, an important peptide-binding domain in all three domains of life (Archaea, Bacteria, and Eukarya). Therefore, an understanding of PDZ domain signaling pathways in choanoflagellates may provide insight into the origins of multicellularity. PDZ domains recognize the C-terminus of target proteins and regulate signaling and trafficking pathways, as well as cellular adhesion. Here, we developed a computational software suite, Domain Analysis and Motif Matcher (DAMM), that analyzes peptide-binding cleft sequence identity as compared with human PDZ domains and that can be used in combination with literature searches of known human PDZ-interacting sequences to predict target specificity in choanoflagellate PDZ domains. We used this program, protein biochemistry, fluorescence polarization, and structural analyses to characterize the specificity of A9UPE9_MONBE, a M. brevicollis PDZ domain-containing protein with no homology to any metazoan protein, finding that its PDZ domain is most similar to those of the DLG family. We then identified two endogenous sequences that bind A9UPE9 PDZ with <100 µM affinity, a value commonly considered the threshold for cellular PDZ-peptide interactions. Taken together, this approach can be used to predict cellular targets of previously uncharacterized PDZ domains in choanoflagellates and other organisms. Our data contribute to investigations into choanoflagellate signaling and how it informs metazoan evolution.

Computational Investigation of Structural Interfaces of Protein Complexes with Short Linear Motifs.

Protein complexes with short linear motifs (SLiMs) are known to play important regulatory functions in eukaryotes. In this investigation, I have studied the structures deposited in PDB with SLiMs. The structures were grouped into three broad categories of protein-protein, protein-peptide, and the rest as others. Protein-peptide complexes were found to be most highly represented. The interfaces were evaluated for geometric features and conformational variables. It was observed that protein-protein and protein-peptide complexes show characteristic differences in residue pairings, which were quantified by evaluating normalized contact residue pairing frequencies. Interface residues adopt characteristic canonical residue conformations in the Ramachandran space, with a pronounced preference for positive ϕ conformations. It was observed that phosphorylated residues have an unusual propensity to adopt the positive ϕ conformations at the interface.

Integrative modeling of protein-protein interactions with pyDock for the new docking challenges.

The seventh CAPRI edition imposed new challenges to the modeling of protein-protein complexes, such as multimeric oligomerization, protein-peptide, and protein-oligosaccharide interactions. Many of the proposed targets needed the efficient integration of rigid-body docking, template-based modeling, flexible optimization, multiparametric scoring, and experimental restraints. This was especially relevant for the multimolecular assemblies proposed in the CASP12-CAPRI37 and CASP13-CAPRI46 joint rounds, which were described and evaluated elsewhere. Focusing on the purely CAPRI targets of this edition (rounds 38-45), we have participated in all 17 assessed targets (considering heteromeric and homomeric interfaces in T125 as two separate targets) both as predictors and as scorers, by using integrative modeling based on our docking and scoring approaches: pyDock, IRaPPA, and LightDock. In the protein-protein and protein-peptide targets, we have also participated with our webserver (pyDockWeb). On these 17 CAPRI targets, we submitted acceptable models (or better) within our top 10 models for 10 targets as predictors, 13 targets as scorers, and 4 targets as servers. In summary, our participation in this CAPRI edition confirmed the capabilities of pyDock for the scoring of docking models, increasingly used within the context of integrative modeling of protein interactions and multimeric assemblies.

Performance of human and server prediction in CAPRI rounds 38-45.

CAPRI challenges offer a variety of blind tests for protein-protein interaction prediction. In CAPRI Rounds 38-45, we generated a set of putative binding modes for each target with an FFT-based docking algorithm, and then scored and ranked these binding modes with a proprietary scoring function, ITScorePP. We have also developed a novel web server, Rebipp. The algorithm utilizes information retrieval to identify relevant biological information to significantly reduce the search space for a particular protein. In parallel, we have also constructed a GPU-based docking server, MDockPP, for protein-protein complex structure prediction. Here, the performance of our protocol in CAPRI rounds 38-45 is reported, which include 16 docking and scoring targets. Among them, three targets contain multiple interfaces: Targets 124, 125, and 136 have 2, 4, and 3 interfaces, respectively. In the predictor experiments, we predicted correct binding modes for nine targets, including one high-accuracy interface, six medium-accuracy binding modes, and six acceptable-accuracy binding modes. For the docking server prediction experiments, we predicted correct binding modes for eight targets, including one high-accuracy, three medium-accuracy, and five acceptable-accuracy binding modes.

PepPro: A Nonredundant Structure Data Set for Benchmarking Peptide-Protein Computational Docking.

We present a nonredundant benchmark, coined PepPro, for testing peptide-protein docking algorithms. Currently, PepPro contains 89 nonredundant experimentally determined peptide-protein complex structures, with peptide sequence lengths ranging from 5 to 30 amino acids. The benchmark covers peptides with distinct secondary structures, including helix, partial helix, a mixture of helix and ß-sheet, ß-sheet formed through binding, ß-sheet formed through self-folding, and coil. In addition, unbound proteins' structures are provided for 58 complexes and can be used for testing the ability of a docking algorithm handling the conformational changes of proteins during the binding process. PepPro should benefit the docking community for the development and improvement of peptide docking algorithms. The benchmark is available at http://zoulab.dalton.missouri.edu/PepPro_benchmark. © 2019 Wiley Periodicals, Inc.