1
|
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.
Collapse
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
| |
Collapse
|
2
|
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).
Collapse
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.
| |
Collapse
|
3
|
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.
Collapse
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
| |
Collapse
|
4
|
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?".
Collapse
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
| | | | | |
Collapse
|
5
|
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.
Collapse
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
| |
Collapse
|
6
|
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]
|
7
|
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.
Collapse
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
| |
Collapse
|
8
|
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.
Collapse
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.
| |
Collapse
|
9
|
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.
Collapse
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).
| |
Collapse
|
10
|
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
| |
Collapse
|
11
|
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
|
12
|
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
| |
Collapse
|
13
|
Rubenstein AB, Pethe MA, Khare SD. MFPred: Rapid and accurate prediction of protein-peptide recognition multispecificity using self-consistent mean field theory. PLoS Comput Biol 2017; 13:e1005614. [PMID: 28650961 PMCID: PMC5507473 DOI: 10.1371/journal.pcbi.1005614] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Revised: 07/11/2017] [Accepted: 06/02/2017] [Indexed: 11/24/2022] Open
Abstract
Multispecificity-the ability of a single receptor protein molecule to interact with multiple substrates-is a hallmark of molecular recognition at protein-protein and protein-peptide interfaces, including enzyme-substrate complexes. The ability to perform structure-based prediction of multispecificity would aid in the identification of novel enzyme substrates, protein interaction partners, and enable design of novel enzymes targeted towards alternative substrates. The relatively slow speed of current biophysical, structure-based methods limits their use for prediction and, especially, design of multispecificity. Here, we develop a rapid, flexible-backbone self-consistent mean field theory-based technique, MFPred, for multispecificity modeling at protein-peptide interfaces. We benchmark our method by predicting experimentally determined peptide specificity profiles for a range of receptors: protease and kinase enzymes, and protein recognition modules including SH2, SH3, MHC Class I and PDZ domains. We observe robust recapitulation of known specificities for all receptor-peptide complexes, and comparison with other methods shows that MFPred results in equivalent or better prediction accuracy with a ~10-1000-fold decrease in computational expense. We find that modeling bound peptide backbone flexibility is key to the observed accuracy of the method. We used MFPred for predicting with high accuracy the impact of receptor-side mutations on experimentally determined multispecificity of a protease enzyme. Our approach should enable the design of a wide range of altered receptor proteins with programmed multispecificities.
Collapse
Affiliation(s)
- Aliza B. Rubenstein
- Computational Biology & Molecular Biophysics Program, Rutgers, The State University of New Jersey, Piscataway, NJ
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ
| | - Manasi A. Pethe
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ
- Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ
| | - Sagar D. Khare
- Computational Biology & Molecular Biophysics Program, Rutgers, The State University of New Jersey, Piscataway, NJ
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ
- Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ
| |
Collapse
|
14
|
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.
Collapse
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.
| |
Collapse
|
15
|
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.
Collapse
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
| |
Collapse
|
16
|
Xiao X, Agris PF, Hall CK. Designing peptide sequences in flexible chain conformations to bind RNA: a search algorithm combining Monte Carlo, self-consistent mean field and concerted rotation techniques. J Chem Theory Comput 2016; 11:740-52. [PMID: 26579605 DOI: 10.1021/ct5008247] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
A search algorithm combining Monte Carlo, self-consistent mean field, and concerted rotation techniques was developed to discover peptide sequences that are reasonable HIV drug candidates due to their exceptional binding to human tRNAUUU(Lys3), the primer of HIV replication. The search algorithm allows for iteration between sequence mutations and conformation changes during sequence evolution. Searches conducted for different classes of peptides identified several potential peptide candidates. Analysis of the energy revealed that the asparagine and cysteine at residues 11 and 12 play important roles in "recognizing" tRNA(Lys3) via van der Waals interactions, contributing to binding specificity. Arginines preferentially attract the phosphate linkage via charge-charge interaction, contributing to binding affinity. Evaluation of the RNA/peptide complex's structure revealed that adding conformation changes to the search algorithm yields peptides with better binding affinity and specificity to tRNA(Lys3) than a previous mutation-only algorithm.
Collapse
Affiliation(s)
- Xingqing Xiao
- Chemical and Biomolecular Engineering Department, North Carolina State University , Raleigh, North Carolina 27695-7905, United States
| | - Paul F Agris
- The RNA Institute, University at Albany, State University of New York , Albany, New York 12222, United States
| | - Carol K Hall
- Chemical and Biomolecular Engineering Department, North Carolina State University , Raleigh, North Carolina 27695-7905, United States
| |
Collapse
|
17
|
Xiao X, Agris PF, Hall CK. Introducing folding stability into the score function for computational design of RNA-binding peptides boosts the probability of success. Proteins 2016; 84:700-11. [PMID: 26914059 DOI: 10.1002/prot.25021] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2015] [Revised: 01/26/2016] [Accepted: 02/10/2016] [Indexed: 12/30/2022]
Abstract
A computational strategy that integrates our peptide search algorithm with atomistic molecular dynamics simulation was used to design rational peptide drugs that recognize and bind to the anticodon stem and loop domain (ASL(Lys3)) of human tRNAUUULys3 for the purpose of interrupting HIV replication. The score function of the search algorithm was improved by adding a peptide stability term weighted by an adjustable factor λ to the peptide binding free energy. The five best peptide sequences associated with five different values of λ were determined using the search algorithm and then input in atomistic simulations to examine the stability of the peptides' folded conformations and their ability to bind to ASL(Lys3). Simulation results demonstrated that setting an intermediate value of λ achieves a good balance between optimizing the peptide's binding ability and stabilizing its folded conformation during the sequence evolution process, and hence leads to optimal binding to the target ASL(Lys3). Thus, addition of a peptide stability term significantly improves the success rate for our peptide design search.
Collapse
Affiliation(s)
- Xingqing Xiao
- Chemical and Biomolecular Engineering Department, North Carolina State University, Raleigh, North Carolina, 27695-7905
| | - 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, 27695-7905
| |
Collapse
|
18
|
Exploiting tRNAs to Boost Virulence. Life (Basel) 2016; 6:life6010004. [PMID: 26797637 PMCID: PMC4810235 DOI: 10.3390/life6010004] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Revised: 01/08/2016] [Accepted: 01/14/2016] [Indexed: 01/22/2023] Open
Abstract
Transfer RNAs (tRNAs) are powerful small RNA entities that are used to translate nucleotide language of genes into the amino acid language of proteins. Their near-uniform length and tertiary structure as well as their high nucleotide similarity and post-transcriptional modifications have made it difficult to characterize individual species quantitatively. However, due to the central role of the tRNA pool in protein biosynthesis as well as newly emerging roles played by tRNAs, their quantitative assessment yields important information, particularly relevant for virus research. Viruses which depend on the host protein expression machinery have evolved various strategies to optimize tRNA usage—either by adapting to the host codon usage or encoding their own tRNAs. Additionally, several viruses bear tRNA-like elements (TLE) in the 5′- and 3′-UTR of their mRNAs. There are different hypotheses concerning the manner in which such structures boost viral protein expression. Furthermore, retroviruses use special tRNAs for packaging and initiating reverse transcription of their genetic material. Since there is a strong specificity of different viruses towards certain tRNAs, different strategies for recruitment are employed. Interestingly, modifications on tRNAs strongly impact their functionality in viruses. Here, we review those intersection points between virus and tRNA research and describe methods for assessing the tRNA pool in terms of concentration, aminoacylation and modification.
Collapse
|
19
|
Post-Transcriptional Modifications of RNA: Impact on RNA Function and Human Health. MODIFIED NUCLEIC ACIDS IN BIOLOGY AND MEDICINE 2016. [DOI: 10.1007/978-3-319-34175-0_5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
|
20
|
Spears JL, Xiao X, Hall CK, Agris PF. Amino acid signature enables proteins to recognize modified tRNA. Biochemistry 2014; 53:1125-33. [PMID: 24483944 PMCID: PMC3985708 DOI: 10.1021/bi401174h] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
![]()
Human tRNALys3UUU is the primer for HIV replication.
The HIV-1 nucleocapsid protein, NCp7, facilitates htRNALys3UUU recruitment from the host cell by binding to and remodeling
the tRNA structure. Human tRNALys3UUU is post-transcriptionally
modified, but until recently, the importance of those modifications
in tRNA recognition by NCp7 was unknown. Modifications such as the
5-methoxycarbonylmethyl-2-thiouridine at anticodon wobble position-34
and 2-methylthio-N6-threonylcarbamoyladenosine,
adjacent to the anticodon at position-37, are important to the recognition
of htRNALys3UUU by NCp7. Several short peptides
selected from phage display libraries were found to also preferentially
recognize these modifications. Evolutionary algorithms (Monte Carlo
and self-consistent mean field) and assisted model building with energy
refinement were used to optimize the peptide sequence in silico, while fluorescence assays were developed and conducted to verify
the in silico results and elucidate a 15-amino acid
signature sequence (R-W-Q/N-H-X2-F-Pho-X-G/A-W-R-X2-G, where X can be most amino acids, and Pho is hydrophobic)
that recognized the tRNA’s fully modified anticodon stem and
loop domain, hASLLys3UUU. Peptides of this sequence
specifically recognized and bound modified htRNALys3UUU with an affinity 10-fold higher than that of the starting
sequence. Thus, this approach provides an effective means of predicting
sequences of RNA binding peptides that have better binding properties.
Such peptides can be used in cell and molecular biology as well as
biochemistry to explore RNA binding proteins and to inhibit those
protein functions.
Collapse
Affiliation(s)
- Jessica L Spears
- The RNA Institute, University at Albany-SUNY , Life Sciences Research Building, Albany, New York 12222, United States
| | | | | | | |
Collapse
|
21
|
Xiao X, Agris PF, Hall CK. Molecular recognition mechanism of peptide chain bound to the tRNA(Lys3) anticodon loop in silico. J Biomol Struct Dyn 2014; 33:14-27. [PMID: 24417415 DOI: 10.1080/07391102.2013.869660] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
The mechanism by which proteins recognize and bind the post-transcriptional modifications of RNAs is unknown, yet these interactions play important functions in biology. Atomistic molecular dynamics simulations were performed to examine the folding of the model peptide chain -RVTHHAFLGAHRTVG- and the complex formed by the folded peptide with the native anticodon stem and loop of the human tRNA(Lys3) (hASL(Lys3)) in order to explore the binding mechanism. By analyzing and comparing two folded conformations of this peptide obtained from the folding simulation, we found that the van der Waals (VDW) energy is necessary for the thermal stability of the peptide, and the charge-charge (ELE + EGB) energy is crucial for determining the three-dimensional folded structure of the peptide backbone. Subsequently, two conformations of the peptide were employed to investigate their binding behaviors to hASL(Lys3). The metastable folded peptide was found to bind to hASL(Lys3) much easier than the stable folded peptide in the binding simulations. An energetic analysis reveals that the VDW energy favors the binding, whereas the ELE + EGB energies disfavor the binding. Arginines on the peptide preferentially attract the phosphate backbone via the inter-chain ELE + EGB interaction, significantly contributing to the binding affinity. The hydrophobic phenylalanine interacts with the anticodon loop of hASL(Lys3) via the inter-chain VDW interaction, significantly contributing to the binding specificity.
Collapse
Affiliation(s)
- Xingqing Xiao
- a Chemical and Biomolecular Engineering Department , North Carolina State University , Engineering Building I, 911 Partners Way, Raleigh , NC 27695-7905 , USA
| | | | | |
Collapse
|