1
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Bergman M, Xiao X, Hall CK. In Silico Design and Analysis of Plastic-Binding Peptides. J Phys Chem B 2023; 127:8370-8381. [PMID: 37735840 PMCID: PMC10591858 DOI: 10.1021/acs.jpcb.3c04319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/23/2023]
Abstract
Peptides that bind to inorganic materials can be used to functionalize surfaces, control crystallization, or assist in interfacial self-assembly. In the past, inorganic-binding peptides have been found predominantly through peptide library screening. While this method has successfully identified peptides that bind to a variety of materials, an alternative design approach that can intelligently search for peptides and provide physical insight for peptide affinity would be desirable. In this work, we develop a computational, physics-based approach to design inorganic-binding peptides, focusing on peptides that bind to the common plastics polyethylene, polypropylene, polystyrene, and poly(ethylene terephthalate). The PepBD algorithm, a Monte Carlo method that samples peptide sequence and conformational space, was modified to include simulated annealing, relax hydration constraints, and an ensemble of conformations to initiate design. These modifications led to the discovery of peptides with significantly better scores compared to those obtained using the original PepBD. PepBD scores were found to improve with increasing van der Waals interactions, although strengthening the intermolecular van der Waals interactions comes at the cost of introducing unfavorable electrostatic interactions. The best designs are enriched in amino acids with bulky side chains and possess hydrophobic and hydrophilic patches whose location depends on the adsorbed conformation. Future work will evaluate the top peptide designs in molecular dynamics simulations and experiment, enabling their application in microplastic pollution remediation and plastic-based biosensors.
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Affiliation(s)
- Michael Bergman
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, 27606, USA
| | - Xingqing Xiao
- Department of Chemistry, School of Science, Hainan University, Longhua District, Haikou, Hainan, 571101, China
| | - Carol K. Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, 27606, USA
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2
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Sarma S, Catella CM, San Pedro ET, Xiao X, Durmusoglu D, Menegatti S, Crook N, Magness ST, Hall CK. Design of 8-mer peptides that block Clostridioides difficile toxin A in intestinal cells. Commun Biol 2023; 6:878. [PMID: 37634026 PMCID: PMC10460389 DOI: 10.1038/s42003-023-05242-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 08/14/2023] [Indexed: 08/28/2023] Open
Abstract
Infections by Clostridioides difficile, a bacterium that targets the large intestine (colon), impact a large number of people worldwide. Bacterial colonization is mediated by two exotoxins: toxins A and B. Short peptides that can be delivered to the gut and inhibit the biocatalytic activity of these toxins represent a promising therapeutic strategy to prevent and treat C. diff. infection. We describe an approach that combines a Peptide Binding Design (PepBD) algorithm, molecular-level simulations, a rapid screening assay to evaluate peptide:toxin binding, a primary human cell-based assay, and surface plasmon resonance (SPR) measurements to develop peptide inhibitors that block Toxin A in colon epithelial cells. One peptide, SA1, is found to block TcdA toxicity in primary-derived human colon (large intestinal) epithelial cells. SA1 binds TcdA with a KD of 56.1 ± 29.8 nM as measured by surface plasmon resonance (SPR).
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Affiliation(s)
- Sudeep Sarma
- Department of Chemical Engineering, North Carolina State University, Raleigh, NC, 27695-7905, USA
| | - Carly M Catella
- Department of Chemical Engineering, North Carolina State University, Raleigh, NC, 27695-7905, USA
| | - Ellyce T San Pedro
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
| | - Xingqing Xiao
- Department of Chemical Engineering, North Carolina State University, Raleigh, NC, 27695-7905, USA
| | - Deniz Durmusoglu
- Department of Chemical Engineering, North Carolina State University, Raleigh, NC, 27695-7905, USA
| | - Stefano Menegatti
- Department of Chemical Engineering, North Carolina State University, Raleigh, NC, 27695-7905, USA
- Biomanufacturing Training and Education Center (BTEC), North Carolina State University, Raleigh, NC, 27695, USA
| | - Nathan Crook
- Department of Chemical Engineering, North Carolina State University, Raleigh, NC, 27695-7905, USA
| | - Scott T Magness
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
| | - Carol K Hall
- Department of Chemical Engineering, North Carolina State University, Raleigh, NC, 27695-7905, USA.
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3
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Sarma S, Catella CM, Pedro ETS, Xiao X, Durmusoglu D, Menegatti S, Crook N, Magness ST, Hall CK. Design of 8-mer Peptides that Block Clostridioides difficile Toxin A in Intestinal Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.10.523493. [PMID: 36711911 PMCID: PMC9882058 DOI: 10.1101/2023.01.10.523493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Clostridioides difficile ( C. diff .) is a bacterium that causes severe diarrhea and inflammation of the colon. The pathogenicity of C. diff . infection is derived from two major toxins, toxins A (TcdA) and B (TcdB). Peptide inhibitors that can be delivered to the gut to inactivate these toxins are an attractive therapeutic strategy. In this work, we present a new approach that combines a pep tide b inding d esign algorithm (PepBD), molecular-level simulations, rapid screening of candidate peptides for toxin binding, a primary human cell-based assay, and surface plasmon resonance (SPR) measurements to develop peptide inhibitors that block the glucosyltransferase activity of TcdA by targeting its glucosyltransferase domain (GTD). Using PepBD and explicit-solvent molecular dynamics simulations, we identified seven candidate peptides, SA1-SA7. These peptides were selected for specific TcdA GTD binding through a custom solid-phase peptide screening system, which eliminated the weaker inhibitors SA5-SA7. The efficacies of SA1-SA4 were then tested using a trans-epithelial electrical resistance (TEER) assay on monolayers of the human gut epithelial culture model. One peptide, SA1, was found to block TcdA toxicity in primary-derived human jejunum (small intestinal) and colon (large intestinal) epithelial cells. SA1 bound TcdA with a K D of 56.1 ± 29.8 nM as measured by surface plasmon resonance (SPR). Significance Statement Infections by Clostridioides difficile , a bacterium that targets the large intestine (colon), impact a significant number of people worldwide. Bacterial colonization is mediated by two exotoxins: toxins A and B. Short peptides that can inhibit the biocatalytic activity of these toxins represent a promising strategy to prevent and treat C. diff . infection. We describe an approach that combines a Peptide B inding D esign (PepBD) algorithm, molecular-level simulations, a rapid screening assay to evaluate peptide:toxin binding, a primary human cell-based assay, and surface plasmon resonance (SPR) measurements to develop peptide inhibitors that block Toxin A in small intestinal and colon epithelial cells. Importantly, our designed peptide, SA1, bound toxin A with nanomolar affinity and blocked toxicity in colon cells.
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Affiliation(s)
- Sudeep Sarma
- Department of Chemical Engineering, North Carolina State University, Raleigh NC 27695-7905, USA
| | - Carly M. Catella
- Department of Chemical Engineering, North Carolina State University, Raleigh NC 27695-7905, USA
| | - Ellyce T. San Pedro
- Department of Medicine, University of North Carolina at Chapel Hill, NC 27514, United States
| | - Xingqing Xiao
- Department of Chemical Engineering, North Carolina State University, Raleigh NC 27695-7905, USA
| | - Deniz Durmusoglu
- Department of Chemical Engineering, North Carolina State University, Raleigh NC 27695-7905, USA
| | - Stefano Menegatti
- Department of Chemical Engineering, North Carolina State University, Raleigh NC 27695-7905, USA
- Biomanufacturing Training and Education Center (BTEC), North Carolina State University, Raleigh, NC 27695, United States
| | - Nathan Crook
- Department of Chemical Engineering, North Carolina State University, Raleigh NC 27695-7905, USA
| | - Scott T. Magness
- Department of Medicine, University of North Carolina at Chapel Hill, NC 27514, United States
| | - Carol K. Hall
- Department of Chemical Engineering, North Carolina State University, Raleigh NC 27695-7905, USA
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4
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Xiao X, Robang AS, Sarma S, Le JV, Helmicki ME, Lambert MJ, Guerrero-Ferreira R, Arboleda-Echavarria J, Paravastu AK, Hall CK. Sequence patterns and signatures: Computational and experimental discovery of amyloid-forming peptides. PNAS NEXUS 2022; 1:pgac263. [PMID: 36712347 PMCID: PMC9802472 DOI: 10.1093/pnasnexus/pgac263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 11/22/2022] [Indexed: 11/27/2022]
Abstract
Screening amino acid sequence space via experiments to discover peptides that self-assemble into amyloid fibrils is challenging. We have developed a computational peptide assembly design (PepAD) algorithm that enables the discovery of amyloid-forming peptides. Discontinuous molecular dynamics (DMD) simulation with the PRIME20 force field combined with the FoldAmyloid tool is used to examine the fibrilization kinetics of PepAD-generated peptides. PepAD screening of ∼10,000 7-mer peptides resulted in twelve top-scoring peptides with two distinct hydration properties. Our studies revealed that eight of the twelve in silico discovered peptides spontaneously form amyloid fibrils in the DMD simulations and that all eight have at least five residues that the FoldAmyloid tool classifies as being aggregation-prone. Based on these observations, we re-examined the PepAD-generated peptides in the sequence pool returned by PepAD and extracted five sequence patterns as well as associated sequence signatures for the 7-mer amyloid-forming peptides. Experimental results from Fourier transform infrared spectroscopy (FTIR), thioflavin T (ThT) fluorescence, circular dichroism (CD), and transmission electron microscopy (TEM) indicate that all the peptides predicted to assemble in silico assemble into antiparallel β-sheet nanofibers in a concentration-dependent manner. This is the first attempt to use a computational approach to search for amyloid-forming peptides based on customized settings. Our efforts facilitate the identification of β-sheet-based self-assembling peptides, and contribute insights towards answering a fundamental scientific question: "What does it take, sequence-wise, for a peptide to self-assemble?".
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Affiliation(s)
| | | | | | - Justin V Le
- Department of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Michael E Helmicki
- Department of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Matthew J Lambert
- Department of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Ricardo Guerrero-Ferreira
- Robert P. Apkarian Integrated Electron Microscopy Core, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Johana Arboleda-Echavarria
- Robert P. Apkarian Integrated Electron Microscopy Core, Emory University School of Medicine, Atlanta, GA 30322, USA
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5
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Sarma S, Herrera SM, Xiao X, Hudalla GA, Hall CK. Computational Design and Experimental Validation of ACE2-Derived Peptides as SARS-CoV-2 Receptor Binding Domain Inhibitors. J Phys Chem B 2022; 126:8129-8139. [PMID: 36219223 PMCID: PMC9578369 DOI: 10.1021/acs.jpcb.2c03918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 09/28/2022] [Indexed: 01/05/2023]
Abstract
The COVID-19 pandemic has caused significant social and economic disruption across the globe. Cellular entry of SARS-CoV-2 into the human body is mediated via binding of the Receptor Binding Domain (RBD) on the viral Spike protein (SARS-CoV-2 RBD) to Angiotensin-Converting Enzyme 2 (ACE2) expressed on host cells. Molecules that can disrupt ACE2:RBD interactions are attractive therapeutic candidates to prevent virus entry into human cells. A computational strategy that combines our Peptide Binding Design (PepBD) algorithm with atomistic molecular dynamics simulations was used to design new inhibitory peptide candidates via sequence iteration starting with a 23-mer peptide, referred to as SBP1. SBP1 is derived from a region of the ACE2 Peptidase Domain α1 helix that binds to the SARS-CoV-2 RBD of the initial Wuhan-Hu-1 strain. Three peptides demonstrated a solution-phase RBD-binding dissociation constant in the micromolar range during tryptophan fluorescence quenching experiments, one peptide did not bind, and one was insoluble at micromolar concentrations. However, in competitive ELISA assays, none of these peptides could outcompete ACE2 binding to SARS-CoV-2-RBD up to concentrations of 50 μM, similar to the parent SBP1 peptide which also failed to outcompete ACE2:RBD binding. Molecular dynamics simulations suggest that P4 would have a good binding affinity for the RBD domain of Beta-B.1.351, Gamma-P.1, Kappa-B.1.617.1, Delta-B.1.617.2, and Omicron-B.1.1.529 variants, but not the Alpha variant. Consistent with this, P4 bound Kappa-B.1.617.1 and Delta-B.1.617.2 RBD with micromolar affinity in tryptophan fluorescence quenching experiments. Collectively, these data show that while relatively short unstructured peptides can bind to SARS-CoV-2 RBD with moderate affinity, they are incapable of outcompeting the strong interactions between RBD and ACE2.
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Affiliation(s)
- Sudeep Sarma
- Department
of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina27695-7905, United States
| | - Stephanie M. Herrera
- J.
Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, 1275 Center Drive, Biomedical Sciences J293, P.O Box 116131, Gainesville, Florida32611, United States
| | - Xingqing Xiao
- Department
of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina27695-7905, United States
| | - Gregory A. Hudalla
- J.
Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, 1275 Center Drive, Biomedical Sciences J293, P.O Box 116131, Gainesville, Florida32611, United States
| | - Carol K. Hall
- Department
of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina27695-7905, United States
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6
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De novo Discovery of Peptide-based Affinity Ligands for the Fab Fragment of Human Immunoglobulin G. J Chromatogr A 2022; 1669:462941. [DOI: 10.1016/j.chroma.2022.462941] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 03/04/2022] [Accepted: 03/05/2022] [Indexed: 12/16/2022]
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7
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Xiao X, Sarma S, Menegatti S, Crook N, Magness ST, Hall CK. In Silico Identification and Experimental Validation of Peptide-Based Inhibitors Targeting Clostridium difficile Toxin A. ACS Chem Biol 2022; 17:118-128. [PMID: 34965093 DOI: 10.1021/acschembio.1c00743] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Clostridium difficile infection is mediated by two major exotoxins: toxins A (TcdA) and B (TcdB). Inhibiting the biocatalytic activities of these toxins with targeted peptide-based drugs can reduce the risk of C. difficile infection. In this work, we used a computational strategy that integrates a peptide binding design (PepBD) algorithm and explicit-solvent atomistic molecular dynamics simulation to determine promising toxin A-targeting peptides that can recognize and bind to the catalytic site of the TcdA glucosyltransferase domain (GTD). Our simulation results revealed that two out of three in silico discovered peptides, viz. the neutralizing peptides A (NPA) and B (NPB), exhibit lower binding free energies when bound to the TcdA GTD than the phage-display discovered peptide, viz. the reference peptide (RP). These peptides may serve as potential inhibitors against C. difficile infection. The efficacy of the peptides RP, NPA, and NPB to neutralize the cytopathic effects of TcdA was tested in vitro in human jejunum cells. Both phage-display peptide RP and in silico peptide NPA were found to exhibit strong toxin-neutralizing properties, thereby preventing the TcdA toxicity. However, the in silico peptide NPB demonstrates a relatively low efficacy against TcdA.
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Affiliation(s)
- Xingqing Xiao
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Sudeep Sarma
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Stefano Menegatti
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
- Biomanufacturing Training and Education Center (BTEC), North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Nathan Crook
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Scott T Magness
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514, United States
| | - Carol K Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
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8
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Xiao X, Wang Y, Seroski DT, Wong KM, Liu R, Paravastu AK, Hudalla GA, Hall CK. De novo design of peptides that coassemble into β sheet-based nanofibrils. SCIENCE ADVANCES 2021; 7:eabf7668. [PMID: 34516924 PMCID: PMC8442925 DOI: 10.1126/sciadv.abf7668] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Peptides’ hierarchical coassembly into nanostructures enables controllable fabrication of multicomponent biomaterials. In this work, we describe a computational and experimental approach to design pairs of charge-complementary peptides that selectively coassemble into β-sheet nanofibers when mixed together but remain unassembled when isolated separately. The key advance is a peptide coassembly design (PepCAD) algorithm that searches for pairs of coassembling peptides. Six peptide pairs are identified from a pool of ~106 candidates via the PepCAD algorithm and then subjected to DMD/PRIME20 simulations to examine their co-/self-association kinetics. The five pairs that spontaneously aggregate in kinetic simulations selectively coassemble in biophysical experiments, with four forming β-sheet nanofibers and one forming a stable nonfibrillar aggregate. Solid-state NMR, which is applied to characterize the coassembling pairs, suggests that the in silico peptides exhibit a higher degree of structural order than the previously reported CATCH(+/−) peptides.
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Affiliation(s)
- Xingqing Xiao
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695-7905, USA
| | - Yiming Wang
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695-7905, USA
| | - Dillon T. Seroski
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Kong M. Wong
- Department of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Renjie Liu
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Anant K. Paravastu
- Department of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Gregory A. Hudalla
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Carol K. Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695-7905, USA
- Corresponding author.
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9
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Novel peptide ligands for antibody purification provide superior clearance of host cell protein impurities. J Chromatogr A 2020; 1625:461237. [DOI: 10.1016/j.chroma.2020.461237] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 05/10/2020] [Accepted: 05/12/2020] [Indexed: 11/19/2022]
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10
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Gonzalez-Rivera JC, Orr AA, Engels SM, Jakubowski JM, Sherman MW, O'Connor KN, Matteson T, Woodcock BC, Contreras LM, Tamamis P. Computational evolution of an RNA-binding protein towards enhanced oxidized-RNA binding. Comput Struct Biotechnol J 2020; 18:137-152. [PMID: 31988703 PMCID: PMC6965710 DOI: 10.1016/j.csbj.2019.12.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2019] [Revised: 12/06/2019] [Accepted: 12/06/2019] [Indexed: 12/02/2022] Open
Abstract
The oxidation of RNA has been implicated in the development of many diseases. Among the four ribonucleotides, guanosine is the most susceptible to oxidation, resulting in the formation of 8-oxo-7,8-dihydroguanosine (8-oxoG). Despite the limited knowledge about how cells regulate the detrimental effects of oxidized RNA, cellular factors involved in its regulation have begun to be identified. One of these factors is polynucleotide phosphorylase (PNPase), a multifunctional enzyme implicated in RNA turnover. In the present study, we have examined the interaction of PNPase with 8-oxoG in atomic detail to provide insights into the mechanism of 8-oxoG discrimination. We hypothesized that PNPase subunits cooperate to form a binding site using the dynamic SFF loop within the central channel of the PNPase homotrimer. We evolved this site using a novel approach that initially screened mutants from a library of beneficial mutations and assessed their interactions using multi-nanosecond Molecular Dynamics simulations. We found that evolving this single site resulted in a fold change increase in 8-oxoG affinity between 1.2 and 1.5 and/or selectivity between 1.5 and 1.9. In addition to the improvement in 8-oxoG binding, complementation of K12 Δpnp with plasmids expressing mutant PNPases caused increased cell tolerance to H2O2. This observation provides a clear link between molecular discrimination of RNA oxidation and cell survival. Moreover, this study provides a framework for the manipulation of modified-RNA protein readers, which has potential application in synthetic biology and epitranscriptomics.
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Affiliation(s)
- Juan C. Gonzalez-Rivera
- McKetta Department of Chemical Engineering, The University of Texas, 200 E. Dean Keeton Street Stop C0400, Austin, TX 78712, United States
| | - Asuka A. Orr
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, 3122 TAMU Room 200, College Station, TX 77843, United States
| | - Sean M. Engels
- McKetta Department of Chemical Engineering, The University of Texas, 200 E. Dean Keeton Street Stop C0400, Austin, TX 78712, United States
| | - Joseph M. Jakubowski
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, 3122 TAMU Room 200, College Station, TX 77843, United States
| | - Mark W. Sherman
- Institute of Cellular and Molecular Biology, The University of Texas at Austin, 100 E 24th Street, Stop A5000, Austin, TX 78712, United States
| | - Katherine N. O'Connor
- McKetta Department of Chemical Engineering, The University of Texas, 200 E. Dean Keeton Street Stop C0400, Austin, TX 78712, United States
| | - Tomas Matteson
- Institute of Cellular and Molecular Biology, The University of Texas at Austin, 100 E 24th Street, Stop A5000, Austin, TX 78712, United States
| | - Brendan C. Woodcock
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, 3122 TAMU Room 200, College Station, TX 77843, United States
| | - Lydia M. Contreras
- McKetta Department of Chemical Engineering, The University of Texas, 200 E. Dean Keeton Street Stop C0400, Austin, TX 78712, United States
- Institute of Cellular and Molecular Biology, The University of Texas at Austin, 100 E 24th Street, Stop A5000, Austin, TX 78712, United States
- Corresponding authors at: McKetta Department of Chemical Engineering, The University of Texas, 200 E. Dean Keeton Street Stop C0400, Austin, TX 78712, United States (L.M. Contreras).
| | - Phanourios Tamamis
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, 3122 TAMU Room 200, College Station, TX 77843, United States
- Corresponding authors at: McKetta Department of Chemical Engineering, The University of Texas, 200 E. Dean Keeton Street Stop C0400, Austin, TX 78712, United States (L.M. Contreras).
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11
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Xiao X, Kuang Z, Burke BJ, Chushak Y, Farmer BL, Mirau PA, Naik RR, Hall CK. In Silico Discovery and Validation of Neuropeptide-Y-Binding Peptides for Sensors. J Phys Chem B 2019; 124:61-68. [DOI: 10.1021/acs.jpcb.9b09439] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Xingqing Xiao
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Zhifeng Kuang
- Materials and Manufacturing Directorate and & 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson Air Force Base, Dayton, Ohio 45433, United States
| | - B. J. Burke
- Materials and Manufacturing Directorate and & 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson Air Force Base, Dayton, Ohio 45433, United States
| | - Yaroslav Chushak
- Materials and Manufacturing Directorate and & 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson Air Force Base, Dayton, Ohio 45433, United States
| | - Barry L. Farmer
- Materials and Manufacturing Directorate and & 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson Air Force Base, Dayton, Ohio 45433, United States
| | - Peter A. Mirau
- Materials and Manufacturing Directorate and & 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson Air Force Base, Dayton, Ohio 45433, United States
| | - Rajesh R. Naik
- Materials and Manufacturing Directorate and & 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson Air Force Base, Dayton, Ohio 45433, United States
| | - Carol K. Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
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12
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Orr AA, Gonzalez-Rivera JC, Wilson M, Bhikha PR, Wang D, Contreras LM, Tamamis P. A high-throughput and rapid computational method for screening of RNA post-transcriptional modifications that can be recognized by target proteins. Methods 2018; 143:34-47. [DOI: 10.1016/j.ymeth.2018.01.015] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Revised: 01/14/2018] [Accepted: 01/26/2018] [Indexed: 12/25/2022] Open
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13
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Xiao X, Kuang Z, Slocik JM, Tadepalli S, Brothers M, Kim S, Mirau PA, Butkus C, Farmer BL, Singamaneni S, Hall CK, Naik RR. Advancing Peptide-Based Biorecognition Elements for Biosensors Using in-Silico Evolution. ACS Sens 2018; 3:1024-1031. [PMID: 29741092 DOI: 10.1021/acssensors.8b00159] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Sensors for human health and performance monitoring require biological recognition elements (BREs) at device interfaces for the detection of key molecular biomarkers that are measurable biological state indicators. BREs, including peptides, antibodies, and nucleic acids, bind to biomarkers in the vicinity of the sensor surface to create a signal proportional to the biomarker concentration. The discovery of BREs with the required sensitivity and selectivity to bind biomarkers at low concentrations remains a fundamental challenge. In this study, we describe an in-silico approach to evolve higher sensitivity peptide-based BREs for the detection of cardiac event marker protein troponin I (cTnI) from a previously identified BRE as the parental affinity peptide. The P2 affinity peptide, evolved using our in-silico method, was found to have ∼16-fold higher affinity compared to the parent BRE and ∼10 fM (0.23 pg/mL) limit of detection. The approach described here can be applied towards designing BREs for other biomarkers for human health monitoring.
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Affiliation(s)
- Xingqing Xiao
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
| | | | | | - Sirimuvva Tadepalli
- Department of Mechanical Engineering and Materials Science, Institute of Materials Science and Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | | | | | | | | | | | - Srikanth Singamaneni
- Department of Mechanical Engineering and Materials Science, Institute of Materials Science and Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Carol K. Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
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Xiao X, Wang Y, Leonard JN, Hall CK. Extended Concerted Rotation Technique Enhances the Sampling Efficiency of the Computational Peptide-Design Algorithm. J Chem Theory Comput 2017; 13:5709-5720. [DOI: 10.1021/acs.jctc.7b00714] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Xingqing Xiao
- Chemical
and Biomolecular Engineering Department, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
| | - Yiming Wang
- Chemical
and Biomolecular Engineering Department, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
| | - Joshua N. Leonard
- Chemical
and Biological Engineering Department and Chemistry of Life Processes
Institute, Northwestern University, Evanston, Illinois 60208, United States
| | - Carol K. Hall
- Chemical
and Biomolecular Engineering Department, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
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15
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Xiao X, Hung ME, Leonard JN, Hall CK. Adding energy minimization strategy to peptide-design algorithm enables better search for RNA-binding peptides: Redesigned λ N peptide binds boxB RNA. J Comput Chem 2016; 37:2423-35. [PMID: 27487990 PMCID: PMC5314887 DOI: 10.1002/jcc.24466] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2015] [Revised: 04/20/2016] [Accepted: 07/13/2016] [Indexed: 11/10/2022]
Abstract
Our previously developed peptide-design algorithm was improved by adding an energy minimization strategy which allows the amino acid sidechains to move in a broad configuration space during sequence evolution. In this work, the new algorithm was used to generate a library of 21-mer peptides which could substitute for λ N peptide in binding to boxB RNA. Six potential peptides were obtained from the algorithm, all of which exhibited good binding capability with boxB RNA. Atomistic molecular dynamics simulations were then conducted to examine the ability of the λ N peptide and three best evolved peptides, viz. Pept01, Pept26, and Pept28, to bind to boxB RNA. Simulation results demonstrated that our evolved peptides are better at binding to boxB RNA than the λ N peptide. Sequence searches using the old (without energy minimization strategy) and new (with energy minimization strategy) algorithms confirm that the new algorithm is more effective at finding good RNA-binding peptides than the old algorithm. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Xingqing Xiao
- Chemical and Biomolecular Engineering Department, North Carolina State University, Raleigh, North Carolina, 27695-7905
| | - Michelle E Hung
- Chemical and Biological Engineering Department, and Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois, 60208
| | - Joshua N Leonard
- Chemical and Biological Engineering Department, and Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois, 60208
| | - Carol K Hall
- Chemical and Biomolecular Engineering Department, North Carolina State University, Raleigh, North Carolina, 27695-7905.
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16
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Xiao X, Zhao B, Agris PF, Hall CK. Simulation study of the ability of a computationally-designed peptide to recognize target tRNA Lys3 and other decoy tRNAs. Protein Sci 2016; 25:2243-2255. [PMID: 27680513 DOI: 10.1002/pro.3056] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Accepted: 09/25/2016] [Indexed: 11/06/2022]
Abstract
In this paper, we investigate the ability of our computationally-designed peptide, Pept10 (PNWNGNRWLNNCLRG), to recognize the anticodon stem and loop (ASL) domain of the hypermodified tRNALys3 (mcm5 s2 U34 ,ms2 t6 A37 ), a reverse transcription primer of HIV replication. Five other ASLs, the singly modified ASLLys3 (ms2 t6 A37 ), ASLLys3 (s2 U34 ), ASLLys3 (Ψ39 ), ASLLys1,2 (t6 A37 ), and ASLGlu (s2 U34 ), were used as decoys. Explicit-solvent atomistic molecular dynamics simulations were performed to examine the process of binding of Pept10 with the target ASLLys3 (mcm5 s2 U34 ,ms2 t6 A37 ) and the decoy ASLs. Simulation results demonstrated that Pept10 is capable of recognizing the target ASLLys3 (mcm5 s2 U34 ,ms2 t6 A37 ) as well as one of the decoys, ASLLys3 (Ψ39 ), but screens out the other four decoy ASLs. The interchain van der Waals (VDW) and charge-charge (ELE + EGB) energies for the two best complexes were evaluated to shed light on the molecular recognition mechanism between Pept10 and ASLs. The results indicated that Pept10 recognizes and binds to the target ASLLys3 (mcm5 s2 U34 ,ms2 t6 A37 ) through residues W3 and R7 which interact with the nucleotides mcm5 s2 U34 , U35 , and ms2 t6 A37 via the interchain VDW energy. Pept10 also recognizes the decoy ASLLys3 (Ψ39 ) through residue R14 which contacts the nucleotide U36 via the interchain VDW energy. Regardless of the type of ASL, the positively charged arginines on Pept10 are attracted to the negatively charged phosphate linkages on the ASL via the interchain ELE + EGB energy, thereby enhancing the binding affinity.
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Affiliation(s)
- Xingqing Xiao
- Chemical and Biomolecular Engineering Department, North Carolina State University, Raleigh, North Carolina, 95-2767905
| | - Binwu Zhao
- Chemical and Biomolecular Engineering Department, North Carolina State University, Raleigh, North Carolina, 95-2767905
| | - Paul F Agris
- The RNA Institute, University at Albany, State University of New York, Albany, New York, 12222
| | - Carol K Hall
- Chemical and Biomolecular Engineering Department, North Carolina State University, Raleigh, North Carolina, 95-2767905
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