Antimicrobial peptide capsids of de novo design.
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ABSTRACT:
SUBMITTER: De Santis E
PROVIDER: S-EPMC5741663 | biostudies-literature | 2017 Dec
REPOSITORIES: biostudies-literature
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Project description:Poor penetration of antitumor drugs into the extravascular tumor tissue is often a major factor limiting the efficacy of cancer treatments. Our group has recently described a strategy to enhance tumor penetration of chemotherapeutic drugs through use of iRGD peptide (CRGDK/RGPDC). This peptide comprises two sequence motifs: RGD, which binds to ?v?3/5 integrins on tumor endothelia and tumor cells, and a cryptic CendR motif (R/KXXR/K-OH). Once integrin binding has brought iRGD to the tumor, the peptide is proteolytically cleaved to expose the cryptic CendR motif. The truncated peptide loses affinity for its primary receptor and binds to neuropilin-1, activating a tissue penetration pathway that delivers the peptide along with attached or co-administered payload into the tumor mass. Here, we describe the design of a new tumor-penetrating peptide based on the current knowledge of homing sequences and internalizing receptors. The tumor-homing motif in the new peptide is the NGR sequence, which binds to endothelial CD13. The NGR sequence was placed in the context of a CendR motif (RNGR), and this sequence was embedded in the iRGD framework. The resulting peptide (CRNGRGPDC, iNGR) homed to tumor vessels and penetrated into tumor tissue more effectively than the standard NGR peptide. iNGR induced greater tumor penetration of coupled nanoparticles and co-administered compounds than NGR. Doxorubicin given together with iNGR was significantly more efficacious than the drug alone. These results show that a tumor-specific, tissue-penetrating peptide can be constructed from known sequence elements. This principle may be useful in designing tissue-penetrating peptides for other diseases.
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Project description:BACKGROUND:Drug design against proteins to cure various diseases has been studied for several years. Numerous design techniques were discovered for small organic molecules for specific protein targets. The specificity, toxicity and selectivity of small molecules are hard problems to solve. The use of peptide drugs enables a partial solution to the toxicity problem. There has been a wide interest in peptide design, but the design techniques of a specific and selective peptide inhibitor against a protein target have not yet been established. METHODOLOGY/PRINCIPAL FINDINGS:A novel de novo peptide design approach is developed to block activities of disease related protein targets. No prior training, based on known peptides, is necessary. The method sequentially generates the peptide by docking its residues pair by pair along a chosen path on a protein. The binding site on the protein is determined via the coarse grained Gaussian Network Model. A binding path is determined. The best fitting peptide is constructed by generating all possible peptide pairs at each point along the path and determining the binding energies between these pairs and the specific location on the protein using AutoDock. The Markov based partition function for all possible choices of the peptides along the path is generated by a matrix multiplication scheme. The best fitting peptide for the given surface is obtained by a Hidden Markov model using Viterbi decoding. The suitability of the conformations of the peptides that result upon binding on the surface are included in the algorithm by considering the intrinsic Ramachandran potentials. CONCLUSIONS/SIGNIFICANCE:The model is tested on known protein-peptide inhibitor complexes. The present algorithm predicts peptides that have better binding energies than those of the existing ones. Finally, a heptapeptide is designed for a protein that has excellent binding affinity according to AutoDock results.
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Project description:This work describes the de-novo design of peptides that inhibit a broad range of plant pathogens. Four structurally different groups of peptides were developed that differ in size and position of their charged and hydrophobic clusters and were assayed for their ability to inhibit bacterial growth and fungal spore germination. Several peptides are highly active at concentrations between 0,1 and 1 µg/ml against plant pathogenic bacteria, such as Pseudomonas syringae, Pectobacterium carotovorum, and Xanthomonas vesicatoria. Importantly, no hemolytic activity could be detected for these peptides at concentrations up to 200 µg/ml. Moreover, the peptides are also active after spraying on the plant surface demonstrating a possible way of application. In sum, our designed peptides represent new antimicrobial agents and with the increasing demand for antimicrobial compounds for production of "healthy" food, these peptides might serve as templates for novel antibacterial and antifungal agents.
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Project description:Antimicrobial peptides (AMPs) are the frontline innate defense system evolutionarily preserved in insects to combat invading pathogens. These AMPs could serve as an alternative to classical antibiotics to overcome the burden of treating multidrug resistant bacteria. Psacotheasin, a knottin type AMP was isolated from Psacothea hilaris and shown to exhibit antimicrobial activity, especially against fungi through apoptosis mediated cell death. In this study, we aimed to identify novel probable AMPs from Psacothea hilaris, the yellow spotted longicorn beetle. The beetle was immunized with the two bacterial strains (E. coli and S. aureus), and the yeast strain C. albicans. After immunization, total RNA was isolated and sequenced in Illumina platform. Then, beetle transcriptome was de novo assembled and searched for putative AMPs with the known physiochemical features of the AMPs. A selection of AMP candidates were synthesized and tested for antimicrobial activity. Four peptides showed stronger activity against E. coli than the control AMP, melittin while one peptide showed similar activity against S. aureus. Moreover, four peptides and two peptides showed antifungal activity stronger than and similar to melittin, respectively. Collectively one peptide showed both antibacterial and antifungal activity superior to melittin; thus, it provides a potent antimicrobial peptide. All the peptides showed no hemolysis in all the tested concentrations. These results suggest that in silico mining of insects' transcriptome could be a promising tool to obtain and optimize novel AMPs for human needs.
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Project description:Histones are small proteins critical to the efficient packaging of DNA in the nucleus. DNA–protein complexes, known as nucleosomes, are formed when the DNA winds itself around the surface of the histones. The methylation of histone residues by enhancer of zeste homolog 2 (EZH2) maintains gene repression over successive cell generations. Overexpression of EZH2 can silence important tumor suppressor genes leading to increased invasiveness of many types of cancers. This makes the inhibition of EZH2 an important target in the development of cancer therapeutics. We employed a three-stage computational de novo peptide design method to design inhibitory peptides of EZH2. The method consists of a sequence selection stage and two validation stages for fold specificity and approximate binding affinity. The sequence selection stage consists of an integer linear optimization model that was solved to produce a rank-ordered list of amino acid sequences with increased stability in the bound peptide-EZH2 structure. These sequences were validated through the calculation of the fold specificity and approximate binding affinity of the designed peptides. Here we report the discovery of novel EZH2 inhibitory peptides using the de novo peptide design method. The computationally discovered peptides were experimentally validated in vitro using dose titrations and mechanism of action enzymatic assays. The peptide with the highest in vitro response, SQ037, was validated in nucleo using quantitative mass spectrometry-based proteomics. This peptide had an IC50 of 13.5 mM, demonstrated greater potency as an inhibitor when compared to the native and K27A mutant control peptides, and demonstrated competitive inhibition versus the peptide substrate. Additionally, this peptide demonstrated high specificity to the EZH2 target in comparison to other histone methyltransferases. The validated peptides are the first computationally designed peptides that directly inhibit EZH2. These inhibitors should prove useful for further chromatin biology investigations.
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Project description:Histones are small proteins critical to the efficient packaging of DNA in the nucleus. DNA-protein complexes, known as nucleosomes, are formed when the DNA winds itself around the surface of the histones. The methylation of histone residues by enhancer of zeste homolog 2 (EZH2) maintains gene repression over successive cell generations. Overexpression of EZH2 can silence important tumor suppressor genes leading to increased invasiveness of many types of cancers. This makes the inhibition of EZH2 an important target in the development of cancer therapeutics. We employed a three-stage computational de novo peptide design method to design inhibitory peptides of EZH2. The method consists of a sequence selection stage and two validation stages for fold specificity and approximate binding affinity. The sequence selection stage consists of an integer linear optimization model that was solved to produce a rank-ordered list of amino acid sequences with increased stability in the bound peptide-EZH2 structure. These sequences were validated through the calculation of the fold specificity and approximate binding affinity of the designed peptides. Here we report the discovery of novel EZH2 inhibitory peptides using the de novo peptide design method. The computationally discovered peptides were experimentally validated in vitro using dose titrations and mechanism of action enzymatic assays. The peptide with the highest in vitro response, SQ037, was validated in nucleo using quantitative mass spectrometry-based proteomics. This peptide had an IC50 of 13.5 [Formula: see text]M, demonstrated greater potency as an inhibitor when compared to the native and K27A mutant control peptides, and demonstrated competitive inhibition versus the peptide substrate. Additionally, this peptide demonstrated high specificity to the EZH2 target in comparison to other histone methyltransferases. The validated peptides are the first computationally designed peptides that directly inhibit EZH2. These inhibitors should prove useful for further chromatin biology investigations.
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Project description:The emergence of drug-resistant bacteria has compromised the use of many conventional antibiotics, leading to heightened interest in a variety of antimicrobial peptides. Although these peptides have attractive potential as antibiotics, their size, stability, tissue distribution, and toxicity have hampered attempts to harness these capabilities. To address such issues, we have developed small (molecular mass <1,000 Da) arylamide foldamers that mimic antimicrobial peptides. Hydrogen-bonded restraints in the arylamide template rigidify the conformation via hydrogen bond formation and increase activity toward Staphylococcus aureus and Escherichia coli. The designed foldamers are highly active against S. aureus in an animal model. These results demonstrate the application of foldamer templates as therapeutics.
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Project description:Antibody drugs play a critical role in infectious diseases, cancer, autoimmune diseases, and inflammation. However, experimental methods for the generation of therapeutic antibodies such as using immunized mice or directed evolution remain time consuming and cannot target a specific antigen epitope. Here, we describe the application of a computational framework called OptMAVEn combined with molecular dynamics to de novo design antibodies. Our reference system is antibody 2D10, a single-chain antibody (scFv) that recognizes the dodecapeptide DVFYPYPYASGS, a peptide mimic of mannose-containing carbohydrates. Five de novo designed scFvs sharing less than 75% sequence similarity to all existing natural antibody sequences were generated using OptMAVEn and their binding to the dodecapeptide was experimentally characterized by biolayer interferometry and isothermal titration calorimetry. Among them, three scFvs show binding affinity to the dodecapeptide at the nM level. Critically, these de novo designed scFvs exhibit considerably diverse modeled binding modes with the dodecapeptide. The results demonstrate the potential of OptMAVEn for the de novo design of thermally and conformationally stable antibodies with high binding affinity to antigens and encourage the targeting of other antigen targets in the future. Biotechnol. Bioeng. 2017;114: 1331-1342. © 2017 Wiley Periodicals, Inc.
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Project description:Computational antibody engineering efforts to date have focused on improving binding affinities or biophysical characteristics. De novo design of antibodies binding specific epitopes could greatly accelerate discovery of therapeutics as compared to conventional immunization or synthetic library selection strategies. Here, we employed de novo complementarity determining region (CDR) design to engineer targeted antibody-antigen interactions using previously described in silico methods. CDRs predicted to bind the minimal FLAG peptide (Asp-Tyr-Lys-Asp) were grafted onto a single-chain variable fragment (scFv) acceptor framework. Fifty scFvs comprised of designed heavy and light or just heavy chain CDRs were synthesized and screened for peptide binding by phage ELISA. Roughly half of the designs resulted in detectable scFv expression. Four antibodies, designed entirely in silico, bound the minimal FLAG sequence with high specificity and sensitivity. When reformatted as soluble antigen-binding fragments (Fab), these clones expressed well, were predominantly monomeric and retained peptide specificity. In both formats, the antibodies bind the peptide only when present at the amino-terminus of a carrier protein and even conservative peptide amino acid substitutions resulted in a complete loss of binding. These results support in silico CDR design of antibody specificity as an emerging antibody engineering strategy.
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Project description:Antimicrobial peptides (AMPs) have been identified as a potentially new class of antibiotics to combat bacterial resistance to conventional drugs. The design of de novo AMPs with high therapeutic indexes, low cost of synthesis, high resistance to proteases and high bioavailability remains a challenge. Such design requires computational modeling of antimicrobial properties. Currently, most computational methods cannot accurately calculate antimicrobial potency against particular strains of bacterial pathogens. We developed a tool for AMP prediction (Special Prediction (SP) tool) and made it available on our Web site (https://dbaasp.org/prediction). Based on this tool, a simple algorithm for the design of de novo AMPs (DSP) was created. We used DSP to design short peptides with high therapeutic indexes against gram-negative bacteria. The predicted peptides have been synthesized and tested in vitro against a panel of gram-negative bacteria, including drug resistant ones. Predicted activity against Escherichia coli ATCC 25922 was experimentally confirmed for 14 out of 15 peptides. Further improvements for designed peptides included the synthesis of D-enantiomers, which are traditionally used to increase resistance against proteases. One synthetic D-peptide (SP15D) possesses one of the lowest values of minimum inhibitory concentration (MIC) among all DBAASP database short peptides at the time of the submission of this article, while being highly stable against proteases and having a high therapeutic index. The mode of anti-bacterial action, assessed by fluorescence microscopy, shows that SP15D acts similarly to cell penetrating peptides. SP15D can be considered a promising candidate for the development of peptide antibiotics. We plan further exploratory studies with the SP tool, aiming at finding peptides which are active against other pathogenic organisms.
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