2
|
Tsai CY, Salawu EO, Li H, Lin GY, Kuo TY, Voon L, Sharma A, Hu KD, Cheng YY, Sahoo S, Stuart L, Chen CW, Chang YY, Lu YL, Ke S, Ortiz CLD, Fang BS, Wu CC, Lan CY, Fu HW, Yang LW. Helical structure motifs made searchable for functional peptide design. Nat Commun 2022; 13:102. [PMID: 35013238 PMCID: PMC8748493 DOI: 10.1038/s41467-021-27655-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 12/03/2021] [Indexed: 11/09/2022] Open
Abstract
The systematic design of functional peptides has technological and therapeutic applications. However, there is a need for pattern-based search engines that help locate desired functional motifs in primary sequences regardless of their evolutionary conservation. Existing databases such as The Protein Secondary Structure database (PSS) no longer serves the community, while the Dictionary of Protein Secondary Structure (DSSP) annotates the secondary structures when tertiary structures of proteins are provided. Here, we extract 1.7 million helices from the PDB and compile them into a database (Therapeutic Peptide Design database; TP-DB) that allows queries of compounded patterns to facilitate the identification of sequence motifs of helical structures. We show how TP-DB helps us identify a known purification-tag-specific antibody that can be repurposed into a diagnostic kit for Helicobacter pylori. We also show how the database can be used to design a new antimicrobial peptide that shows better Candida albicans clearance and lower hemolysis than its template homologs. Finally, we demonstrate how TP-DB can suggest point mutations in helical peptide blockers to prevent a targeted tumorigenic protein-protein interaction. TP-DB is made available at http://dyn.life.nthu.edu.tw/design/ .
Collapse
Affiliation(s)
- Cheng-Yu Tsai
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
- Graduate Institute of Medical Genomics and Proteomics, National Taiwan University College of Medicine, Taipei, 100025, Taiwan
- Department of Otolaryngology, National Taiwan University Hospital, Taipei, 100225, Taiwan
| | - Emmanuel Oluwatobi Salawu
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
- Bioinformatics Program, Institute of Information Sciences, Academia Sinica, Taipei, 115201, Taiwan
- Machine Learning Solutions Lab, Amazon Web Services (AWS), Herndon, VA, USA
| | - Hongchun Li
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
- Research Center for Computer-Aided Drug Discovery, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055, Shenzhen, China
- College of Chemistry and Chemical Engineering, Xiamen University, 361005, Xiamen, China
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Guan-Yu Lin
- Institute of Molecular and Cellular Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
| | - Ting-Yu Kuo
- Institute of Molecular and Cellular Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
| | - Liyin Voon
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
| | - Adarsh Sharma
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
| | - Kai-Di Hu
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
| | - Yi-Yun Cheng
- Praexisio Taiwan Inc., New Taipei, 221425, Taiwan
| | - Sobha Sahoo
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
| | - Lutimba Stuart
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
| | - Chih-Wei Chen
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
| | - Yuan-Yu Chang
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
- Praexisio Taiwan Inc., New Taipei, 221425, Taiwan
| | - Yu-Lin Lu
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
| | - Simai Ke
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
| | - Christopher Llynard D Ortiz
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan
- Chemical Biology and Molecular Biophysics Program, Institute of Biological Chemistry, Academia Sinica, Taipei, 115201, Taiwan
- Department of Chemistry, National Tsing Hua University, Hsinchu, 300044, Taiwan
| | - Bai-Shan Fang
- College of Chemistry and Chemical Engineering, Xiamen University, 361005, Xiamen, China
- The Key Laboratory for Chemical Biology of Fujian Province, Key Lab for Synthetic Biotechnology of Xiamen City, Xiamen University, 361005, Xiamen, China
| | - Chen-Chi Wu
- Department of Otolaryngology, National Taiwan University Hospital, Taipei, 100225, Taiwan
- Department of Medical Research, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, 302058, Taiwan
| | - Chung-Yu Lan
- Institute of Molecular and Cellular Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan.
- Department of Life Science, National Tsing Hua University, Hsinchu, 300044, Taiwan.
| | - Hua-Wen Fu
- Institute of Molecular and Cellular Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan.
- Department of Life Science, National Tsing Hua University, Hsinchu, 300044, Taiwan.
| | - Lee-Wei Yang
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300044, Taiwan.
- Bioinformatics Program, Institute of Information Sciences, Academia Sinica, Taipei, 115201, Taiwan.
- Physics Division, National Center for Theoretical Sciences, Taipei, 106319, Taiwan.
- PhD Program in Biomedical Artificial Intelligence, National Tsing Hua University, Hsinchu, 300044, Taiwan.
| |
Collapse
|
3
|
Hsu CF, Chang KC, Chen YL, Hsieh PS, Lee AI, Tu JY, Chen YT, Wen JD. Formation of frameshift-stimulating RNA pseudoknots is facilitated by remodeling of their folding intermediates. Nucleic Acids Res 2021; 49:6941-6957. [PMID: 34161580 PMCID: PMC8266650 DOI: 10.1093/nar/gkab512] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 05/27/2021] [Accepted: 06/04/2021] [Indexed: 12/15/2022] Open
Abstract
Programmed –1 ribosomal frameshifting is an essential regulation mechanism of translation in viruses and bacteria. It is stimulated by mRNA structures inside the coding region. As the structure is unfolded repeatedly by consecutive translating ribosomes, whether it can refold properly each time is important in performing its function. By using single-molecule approaches and molecular dynamics simulations, we found that a frameshift-stimulating RNA pseudoknot folds sequentially through its upstream stem S1 and downstream stem S2. In this pathway, S2 folds from the downstream side and tends to be trapped in intermediates. By masking the last few nucleotides to mimic their gradual emergence from translating ribosomes, S2 can be directed to fold from the upstream region. The results show that the intermediates are greatly suppressed, suggesting that mRNA refolding may be modulated by ribosomes. Moreover, masking the first few nucleotides of S1 favors the folding from S2 and yields native pseudoknots, which are stable enough to retrieve the masked nucleotides. We hypothesize that translating ribosomes can remodel an intermediate mRNA structure into a stable conformation, which may in turn stimulate backward slippage of the ribosome. This supports an interactive model of ribosomal frameshifting and gives an insightful account addressing previous experimental observations.
Collapse
Affiliation(s)
- Chiung-Fang Hsu
- Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 10617, Taiwan
| | - Kai-Chun Chang
- Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 10617, Taiwan
| | - Yi-Lan Chen
- Genome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, Taipei 10617, Taiwan
| | - Po-Szu Hsieh
- Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 10617, Taiwan
| | - An-I Lee
- Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 10617, Taiwan
| | - Jui-Yun Tu
- Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 10617, Taiwan
| | - Yu-Ting Chen
- Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 10617, Taiwan
| | - Jin-Der Wen
- Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 10617, Taiwan.,Genome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, Taipei 10617, Taiwan
| |
Collapse
|
4
|
Chang KC, Wen JD. Programmed -1 ribosomal frameshifting from the perspective of the conformational dynamics of mRNA and ribosomes. Comput Struct Biotechnol J 2021; 19:3580-3588. [PMID: 34257837 PMCID: PMC8246090 DOI: 10.1016/j.csbj.2021.06.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 06/11/2021] [Accepted: 06/12/2021] [Indexed: 11/01/2022] Open
Abstract
Programmed -1 ribosomal frameshifting (-1 PRF) is a translation mechanism that regulates the relative expression level of two proteins encoded on the same messenger RNA (mRNA). This regulation is commonly used by viruses such as coronaviruses and retroviruses but rarely by host human cells, and for this reason, it has long been considered as a therapeutic target for antiviral drug development. Understanding the molecular mechanism of -1 PRF is one step toward this goal. Minus-one PRF occurs with a certain efficiency when translating ribosomes encounter the specialized mRNA signal consisting of the frameshifting site and a downstream stimulatory structure, which impedes translocation of the ribosome. The impeded ribosome can still undergo profound conformational changes to proceed with translocation; however, some of these changes may be unique and essential to frameshifting. In addition, most stimulatory structures exhibit conformational dynamics and sufficient mechanical strength, which, when under the action of ribosomes, may in turn further promote -1 PRF efficiency. In this review, we discuss how the dynamic features of ribosomes and mRNA stimulatory structures may influence the occurrence of -1 PRF and propose a hypothetical frameshifting model that recapitulates the role of conformational dynamics.
Collapse
Affiliation(s)
- Kai-Chun Chang
- Department of Bioengineering and Therapeutic Sciences, Schools of Medicine and Pharmacy, University of California, San Francisco, CA 94158, United States
| | - Jin-Der Wen
- Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 10617, Taiwan
- Genome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, Taipei 10617, Taiwan
| |
Collapse
|
5
|
Krieger JM, Doruker P, Scott AL, Perahia D, Bahar I. Towards gaining sight of multiscale events: utilizing network models and normal modes in hybrid methods. Curr Opin Struct Biol 2020; 64:34-41. [PMID: 32622329 DOI: 10.1016/j.sbi.2020.05.013] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 05/13/2020] [Accepted: 05/20/2020] [Indexed: 11/28/2022]
Abstract
With the explosion of normal mode analyses (NMAs) based on elastic network models (ENMs) in the last decade, and the proven precision of MD simulations for visualizing interactions at atomic scale, many hybrid methods have been proposed in recent years. These aim at exploiting the best of both worlds: the atomic precision of MD that often fall short of exploring time and length scales of biological interest, and the capability of ENM-NMA to predict the cooperative and often functional rearrangements of large structures and assemblies, albeit at low resolution. We present an overview of recent progress in the field with examples of successful applications highlighting the utility of such hybrid methods and pointing to emerging future directions guided by advances in experimental characterization of biomolecular systems structure and dynamics.
Collapse
Affiliation(s)
- James M Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA
| | - Ana Ligia Scott
- Laboratory of Bioinformatics and Computational Biology, Federal University of ABC, Santo André, SP, Brazil
| | - David Perahia
- Laboratoire de Biologie et de Pharmacologie Appliquée, Ecole Normale Superieure Paris-Saclay, UMR 8113, CNRS, 4 Avenue des Sciences, 91190 Gif-sur-Yvette, France
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, 3501 Fifth Ave, Suite 3064 BST3, Pittsburgh, PA 15260, USA.
| |
Collapse
|
6
|
Huang BC, Yang LW. Molecular dynamics simulations and linear response theories jointly describe biphasic responses of myoglobin relaxation and reveal evolutionarily conserved frequent communicators. Biophys Physicobiol 2020; 16:473-484. [PMID: 31984199 PMCID: PMC6975898 DOI: 10.2142/biophysico.16.0_473] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 09/20/2019] [Indexed: 12/01/2022] Open
Abstract
In this study, we provide a time-dependent mechanical model, taking advantage of molecular dynamics simulations, quasiharmonic analysis of molecular dynamics trajectories, and time-dependent linear response theories to describe vibrational energy redistribution within the protein matrix. The theoretical description explained the observed biphasic responses of specific residues in myoglobin to CO-photolysis and photoexcitation on heme. The fast responses were found to be triggered by impulsive forces and propagated mainly by principal modes <40 cm−1. The predicted fast responses for individual atoms were then used to study signal propagation within the protein matrix and signals were found to propagate ~8 times faster across helices (4076 m/s) than within the helices, suggesting the importance of tertiary packing in the sensitivity of proteins to external perturbations. We further developed a method to integrate multiple intramolecular signal pathways and discover frequent “communicators”. These communicators were found to be evolutionarily conserved including those distant from the heme.
Collapse
Affiliation(s)
- Bang-Chieh Huang
- Institute of Bioinformatics and Structural Biology, National Tsing-Hua University, Hsinchu 30013, Taiwan
| | - Lee-Wei Yang
- Institute of Bioinformatics and Structural Biology, National Tsing-Hua University, Hsinchu 30013, Taiwan.,Bioinformatics Program, Taiwan International Graduate Program, Institute of Information Sciences, Academia Sinica, Taipei 11529, Taiwan.,Department of Life Science, National Tsing Hua University, Hsinchu 30013, Taiwan.,Physics Division, National Center for Theoretical Sciences, Hsinchu 30013, Taiwan
| |
Collapse
|