1
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Martin DR, Mutombwera AT, Madiehe AM, Onani MO, Meyer M, Cloete R. Molecular modeling and simulation studies of SELEX-derived high-affinity DNA aptamers to the Ebola virus nucleoprotein. J Biomol Struct Dyn 2024:1-18. [PMID: 38217874 DOI: 10.1080/07391102.2024.2302922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 01/03/2024] [Indexed: 01/15/2024]
Abstract
Ebola viral disease (EVD) is a highly infectious and potentially fatal illness with a case fatality rate ranging from 25% to 90%. To effectively control its spread, there is a need for rapid, reliable and lowcost point-of-care (P OC) diagnostic tests. While various EVD diagnostic tests exist, few are P OC tests, and many are not cost-effective. The use of antibodies in these tests has limitations, prompting the exploration of aptamers as potential alternatives. Various proteins from the Ebola virus (EBOV) proteome, including EBOV nucleoprotein (NP), are considered viable targets for diagnostic assays. A previous study identified three aptamers (Apt1. Apt2 and Apt3) with high affinity for EBOV NP using systemic evolution of ligands by exponential enrichment (SELEX). This study aimed to employ in silico methods, such as Phyre2, RNAfold, RNAComposer, HADDOCK and GROMACS, to model the structures of EBOV NP and the aptamers, and to investigate their binding. The in silico analysis revealed successful binding of all the three aptamers to EBOV NP, with a suggested ranking of Apt1 > Apt2 > Apt3 based on binding affinity. Microscale thermophoresis (MST) analysis confirmed the binding, providing dissociation constants of 25 ± 2.84, 56 ± 2.76 and 140 ±3.69 nM for Apt1, Apt2 and Apt3, respectively. The study shows that the findings of the in silico analysis was in agreement with the MST analysis. Inclusion of these in silico approaches in diagnostic assay development can expedite the selection of candidate aptamers, potentially overcoming challenges associated with aptamer application in diagnostics.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- D R Martin
- Department of Science and Innovation/Mintek Nanotechnology Innovation Centre, Biolabels Node, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute (SANBI), University of the Western Cape, Bellville, South Africa Cape Town, South Africa
| | - A T Mutombwera
- Department of Biochemistry and Microbiology, Nelson Mandela University, Port Elizabeth, South Africa
| | - A M Madiehe
- Department of Science and Innovation/Mintek Nanotechnology Innovation Centre, Biolabels Node, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
- Nanobiotechnology Research Group, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - M O Onani
- Department of Chemistry, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - M Meyer
- Department of Science and Innovation/Mintek Nanotechnology Innovation Centre, Biolabels Node, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - R Cloete
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute (SANBI), University of the Western Cape, Bellville, South Africa Cape Town, South Africa
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2
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Uversky VN. Functional unfoldomics: Roles of intrinsic disorder in protein (multi)functionality. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2023; 138:179-210. [PMID: 38220424 DOI: 10.1016/bs.apcsb.2023.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
Intrinsically disordered proteins (IDPs), which are functional proteins without stable tertiary structure, and hybrid proteins containing ordered domains and intrinsically disordered regions (IDRs) constitute prominent parts of all proteomes collectively known as unfoldomes. IDPs/IDRs exist as highly dynamic structural ensembles of rapidly interconverting conformations and are characterized by the exceptional structural heterogeneity, where their different parts are (dis)ordered to different degree, and their overall structure represents a complex mosaic of foldons, inducible foldons, inducible morphing foldons, non-foldons, semifoldons, and even unfoldons. Despite their lack of unique 3D structures, IDPs/IDRs play crucial roles in the control of various biological processes and the regulation of different cellular pathways and are commonly involved in recognition and signaling, indicating that the disorder-based functional repertoire is complementary to the functions of ordered proteins. Furthermore, IDPs/IDRs are frequently multifunctional, and this multifunctionality is defined by their structural flexibility and heterogeneity. Intrinsic disorder phenomenon is at the roots of the structure-function continuum model, where the structure continuum is defined by the presence of differently (dis)ordered regions, and the function continuum arises from the ability of all these differently (dis)ordered parts to have different functions. In their everyday life, IDPs/IDRs utilize a broad spectrum of interaction mechanisms thereby acting as interaction specialists. They are crucial for the biogenesis of numerous proteinaceous membrane-less organelles driven by the liquid-liquid phase separation. This review introduces functional unfoldomics by representing some aspects of the intrinsic disorder-based functionality.
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Affiliation(s)
- Vladimir N Uversky
- Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, United States.
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3
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Intrinsically disordered BMP4 morphogen and the beak of the finch: Co-option of an ancient axial patterning system. Int J Biol Macromol 2022; 219:366-373. [PMID: 35931296 DOI: 10.1016/j.ijbiomac.2022.07.203] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 07/25/2022] [Indexed: 12/24/2022]
Abstract
Darwin's finches, with the primary diversity in the shape and size of their beaks, represent an excellent model system to study speciation and adaptive evolution. It is generally held that evolution depends on the natural selection of heritable phenotypic variations originating from the genetic mutations. However, it is now increasingly evident that epigenetic transgenerational inheritance of phenotypic variation can also guide evolutionary change. Several studies have shown that the bone morphogenetic protein BMP4 is a major driver of beak morphology. A recent study explored variability of the morphological, genetic, and epigenetic differences in the adjacent "urban" and "rural" populations of two species of ground Darwin's finches on the Galápagos Islands and revealed significant changes in methylation patterns in several genes including those involved in the BMP/TGFß pathway in the sperm DNA compared to erythrocyte DNA. These observations indicated that epigenetic changes caused by environmental fluctuations can be passed on to the offspring. Nonetheless, the mechanism by which dysregulated expression of BMP4 impacts beak morphology remains poorly understood. Here, we show that BMP4 is an intrinsically disordered protein and present a causal a link between epigenetic changes, BMP4 dysregulation and the evolution of the beak of the finch by natural selection.
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4
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Wu Y, Zhang Y, Qin Y, Cai W, Zhang X, Xu Y, Dou X, Wang Z, Han D, Wang J, Lin G, Wang L, Hao J, Fu S, Chen R, Sun Y, Bai Z, Gu M, Wang Z. Association analysis of single-nucleotide polymorphism in prolactin and its receptor with productive and body conformation traits in Liaoning cashmere goats. Arch Anim Breed 2022; 65:145-155. [PMID: 35505666 PMCID: PMC9051658 DOI: 10.5194/aab-65-145-2022] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 03/28/2022] [Indexed: 12/12/2022] Open
Abstract
The results of this study showed that the single-nucleotide polymorphism (SNP) sites of the PRL and PRLR genes have
a certain association with the milk production performance, body size and
cashmere performance of Liaoning cashmere goats (LCGs). Through our designed
experiment, the potential SNPs of LCG were
detected by sequence alignment, and two SNPs were found on two genes. The CC
genotype of the PRL gene is the dominant genotype among the three genotypes.
The GG genotype of the PRLR gene is the dominant genotype among the two
genotypes. At the same time, the two genotypes also have good performance in
cashmere production and body size. Through the screening of haplotype
combination, the milk fat rate > 7.6 %, the milk protein
rate > 5.6 %, the milk somatic cell number < 1500 × 103 mL-1, the cashmere fineness < 15.75 µm, the
chest girth > 105 cm, the chest depth > 33 cm, and the waist
height > 67.5 cm are considered as screening indexes for
comprehensive production performance of Liaoning cashmere goats. It is
concluded that the GCGC type is the dominant haplotype combination.
According to our research data, we found that the biological indicators of
Liaoning cashmere goat milk are higher than the national standards, so we
think it is very significant to study the milk production performance of our
experiment. Further research can be done on goat milk production and body
conformation traits around PRL gene and PRLR gene.
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Affiliation(s)
- Yanzhi Wu
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural
University, Shenyang 110866, China
| | - Yu Zhang
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural
University, Shenyang 110866, China
| | - Yuting Qin
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural
University, Shenyang 110866, China
| | - Weidong Cai
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural
University, Shenyang 110866, China
| | - Xinjiang Zhang
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural
University, Shenyang 110866, China
| | - Yanan Xu
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural
University, Shenyang 110866, China
| | - Xingtang Dou
- Liaoning Province Modern Agricultural Production Base Construction
Engineering Center, Liaoyang 110000, China
| | - Zhanhong Wang
- Liaoning Province Modern Agricultural Production Base Construction
Engineering Center, Liaoyang 110000, China
| | - Di Han
- Liaoning Province Modern Agricultural Production Base Construction
Engineering Center, Liaoyang 110000, China
| | - Jiaming Wang
- Liaoning Province Modern Agricultural Production Base Construction
Engineering Center, Liaoyang 110000, China
| | - Guangyu Lin
- Liaoning Province Modern Agricultural Production Base Construction
Engineering Center, Liaoyang 110000, China
| | - Lingling Wang
- Liaoning Province Modern Agricultural Production Base Construction
Engineering Center, Liaoyang 110000, China
| | - Jianjun Hao
- Administration Bureau of Zhungeer Banner, Ordos City, Inner Mongolia
010399, China
| | - Shuqing Fu
- Lantian Sub-district Office, Zhungeer Banner, Ordos City, Inner Mongolia
010399, China
| | - Rui Chen
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural
University, Shenyang 110866, China
| | - Yinggang Sun
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural
University, Shenyang 110866, China
| | - Zhixian Bai
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural
University, Shenyang 110866, China
| | - Ming Gu
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural
University, Shenyang 110866, China
| | - Zeying Wang
- College of Animal Science & Veterinary Medicine, Shenyang Agricultural
University, Shenyang 110866, China
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5
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Coskuner-Weber O, Habiboglu MG, Teplow D, Uversky VN. From Quantum Mechanics, Classical Mechanics, and Bioinformatics to Artificial Intelligence Studies in Neurodegenerative Diseases. Methods Mol Biol 2022; 2340:139-173. [PMID: 35167074 DOI: 10.1007/978-1-0716-1546-1_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The amyloid β-protein is an intrinsically disordered protein that has the potential to assemble into myriad structures, including oligomers and fibrils. These structures are neurotoxic and are thought to initiate a cascade of events leading to Alzheimer's disease. Understanding this pathogenetic process and elucidating targets for drug therapy depends on elucidation of the structural dynamics of Aβ assembly. In this chapter, we describe work packages required to determine the three-dimensional structures of Aβ and of smaller bioactive fragments thereof, which may be important in AD pathogenesis. These packages include density functional theory, Car-Parrinello molecular dynamics simulations, temperature-dependent replica exchange molecular dynamics simulations, disorder predictors based on bioinformatics, and neural network deep learning.
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Affiliation(s)
| | - M Gokhan Habiboglu
- Electrical and Electronics Engineering, Turkish-German University, Istanbul, Turkey
| | - David Teplow
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Vladimir N Uversky
- Department of Molecular Medicine and USF Health Byrd Alzheimer Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
- Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moskow Region, Russia
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6
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Gutierrez‐Beltran E, Elander PH, Dalman K, Dayhoff GW, Moschou PN, Uversky VN, Crespo JL, Bozhkov PV. Tudor staphylococcal nuclease is a docking platform for stress granule components and is essential for SnRK1 activation in Arabidopsis. EMBO J 2021; 40:e105043. [PMID: 34287990 PMCID: PMC8447601 DOI: 10.15252/embj.2020105043] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 06/23/2021] [Accepted: 07/01/2021] [Indexed: 12/19/2022] Open
Abstract
Tudor staphylococcal nuclease (TSN; also known as Tudor-SN, p100, or SND1) is a multifunctional, evolutionarily conserved regulator of gene expression, exhibiting cytoprotective activity in animals and plants and oncogenic activity in mammals. During stress, TSN stably associates with stress granules (SGs), in a poorly understood process. Here, we show that in the model plant Arabidopsis thaliana, TSN is an intrinsically disordered protein (IDP) acting as a scaffold for a large pool of other IDPs, enriched for conserved stress granule components as well as novel or plant-specific SG-localized proteins. While approximately 30% of TSN interactors are recruited to stress granules de novo upon stress perception, 70% form a protein-protein interaction network present before the onset of stress. Finally, we demonstrate that TSN and stress granule formation promote heat-induced activation of the evolutionarily conserved energy-sensing SNF1-related protein kinase 1 (SnRK1), the plant orthologue of mammalian AMP-activated protein kinase (AMPK). Our results establish TSN as a docking platform for stress granule proteins, with an important role in stress signalling.
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Affiliation(s)
- Emilio Gutierrez‐Beltran
- Instituto de Bioquímica Vegetal y FotosíntesisConsejo Superior de Investigaciones Científicas (CSIC)‐Universidad de SevillaSevillaSpain
- Departamento de Bioquímica Vegetal y Biología MolecularFacultad de BiologíaUniversidad de SevillaSevillaSpain
| | - Pernilla H Elander
- Department of Molecular SciencesUppsala BioCenterSwedish University of Agricultural Sciences and Linnean Center for Plant BiologyUppsalaSweden
| | - Kerstin Dalman
- Department of Molecular SciencesUppsala BioCenterSwedish University of Agricultural Sciences and Linnean Center for Plant BiologyUppsalaSweden
| | - Guy W Dayhoff
- Department of ChemistryCollege of Art and SciencesUniversity of South FloridaTampaFLUSA
| | - Panagiotis N Moschou
- Institute of Molecular Biology and BiotechnologyFoundation for Research and Technology ‐ HellasHeraklionGreece
- Department of Plant BiologyUppsala BioCenterSwedish University of Agricultural Sciences and Linnean Center for Plant BiologyUppsalaSweden
- Department of BiologyUniversity of CreteHeraklionGreece
| | - Vladimir N Uversky
- Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of MedicineUniversity of South FloridaTampaFLUSA
- Institute for Biological Instrumentation of the Russian Academy of SciencesFederal Research Center “Pushchino Scientific Center for Biological Research of the Russian Academy of Sciences”PushchinoRussia
| | - Jose L Crespo
- Instituto de Bioquímica Vegetal y FotosíntesisConsejo Superior de Investigaciones Científicas (CSIC)‐Universidad de SevillaSevillaSpain
| | - Peter V Bozhkov
- Department of Molecular SciencesUppsala BioCenterSwedish University of Agricultural Sciences and Linnean Center for Plant BiologyUppsalaSweden
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7
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Paré P, Reales G, Paixão-Côrtes VR, Vargas-Pinilla P, Viscardi LH, Fam B, Pissinatti A, Santos FR, Bortolini MC. Molecular evolutionary insights from PRLR in mammals. Gen Comp Endocrinol 2021; 309:113791. [PMID: 33872604 DOI: 10.1016/j.ygcen.2021.113791] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 04/02/2021] [Accepted: 04/13/2021] [Indexed: 12/12/2022]
Abstract
Prolactin (PRL) is a pleiotropic neurohormone secreted by the mammalian pituitary gland into the blood, thus reaching many tissues and organs beyond the brain. PRL binds to its receptor, PRLR, eliciting a molecular signaling cascade. This system modulates essential mammalian behaviors and promotes notable modifications in the reproductive female tissues and organs. Here, we explore how the intracellular domain of PRLR (PRLR-ICD) modulates the expression of the PRLR gene. Despite differences in the reproductive strategies between eutherian and metatherian mammals, there is no clear distinction between PRLR-ICD functional motifs. However, we found selection signatures that showed differences between groups, with many conserved functional elements strongly maintained through purifying selection across the class Mammalia. We observed a few residues under relaxed selection, the levels of which were more pronounced in Eutheria and particularly striking in primates (Simiiformes), which could represent a pre-adaptive genetic element protected from purifying selection. Alternative, new motifs, such as YLDP (318-321) and others with residues Y283 and Y290, may already be functional. These motifs would have been co-opted in primates as part of a complex genetic repertoire related to some derived adaptive phenotypes, but these changes would have no impact on the primordial functions that characterize the mammals as a whole and that are related to the PRL-PRLR system.
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Affiliation(s)
- Pamela Paré
- Laboratório de Evolução Humana e Molecular, Programa de Pós-Graduação em Genética e Biologia Molecular, Departamento de Genética, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Guillermo Reales
- Laboratório de Evolução Humana e Molecular, Programa de Pós-Graduação em Genética e Biologia Molecular, Departamento de Genética, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambridge, Puddicombe Way, Cambridge CB2 0AW, UK; Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Vanessa R Paixão-Côrtes
- Laboratório de Biologia Evolutiva e Genômica (LABEG), Programa de Pós-Graduação em Biodiversidade e Evolução, Instituto de Biologia, Universidade Federal da Bahia (UFBA), Salvador, BA, Brazil
| | - Pedro Vargas-Pinilla
- Laboratório de Evolução Humana e Molecular, Programa de Pós-Graduação em Genética e Biologia Molecular, Departamento de Genética, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Faculdade de Medicina de Ribeirão Preto, Departamento de Bioquímica e Imunologia, Universidade de São Paulo, Ribeirão Preto, SP, Brazil
| | - Lucas Henriques Viscardi
- Laboratório de Evolução Humana e Molecular, Programa de Pós-Graduação em Genética e Biologia Molecular, Departamento de Genética, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Bibiana Fam
- Laboratório de Evolução Humana e Molecular, Programa de Pós-Graduação em Genética e Biologia Molecular, Departamento de Genética, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | | | - Fabrício R Santos
- Laboratório de Biodiversidade e Evolução Molecular, Departamento de Genética, Ecologia e Evolução da Universidade Federal de Minas Gerais (UFMG), Belo-Horizonte, MG, Brazil.
| | - Maria Cátira Bortolini
- Laboratório de Evolução Humana e Molecular, Programa de Pós-Graduação em Genética e Biologia Molecular, Departamento de Genética, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil.
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8
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Katuwawala A, Kurgan L. Comparative Assessment of Intrinsic Disorder Predictions with a Focus on Protein and Nucleic Acid-Binding Proteins. Biomolecules 2020; 10:E1636. [PMID: 33291838 PMCID: PMC7762010 DOI: 10.3390/biom10121636] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 11/26/2020] [Accepted: 12/03/2020] [Indexed: 01/18/2023] Open
Abstract
With over 60 disorder predictors, users need help navigating the predictor selection task. We review 28 surveys of disorder predictors, showing that only 11 include assessment of predictive performance. We identify and address a few drawbacks of these past surveys. To this end, we release a novel benchmark dataset with reduced similarity to the training sets of the considered predictors. We use this dataset to perform a first-of-its-kind comparative analysis that targets two large functional families of disordered proteins that interact with proteins and with nucleic acids. We show that limiting sequence similarity between the benchmark and the training datasets has a substantial impact on predictive performance. We also demonstrate that predictive quality is sensitive to the use of the well-annotated order and inclusion of the fully structured proteins in the benchmark datasets, both of which should be considered in future assessments. We identify three predictors that provide favorable results using the new benchmark set. While we find that VSL2B offers the most accurate and robust results overall, ESpritz-DisProt and SPOT-Disorder perform particularly well for disordered proteins. Moreover, we find that predictions for the disordered protein-binding proteins suffer low predictive quality compared to generic disordered proteins and the disordered nucleic acids-binding proteins. This can be explained by the high disorder content of the disordered protein-binding proteins, which makes it difficult for the current methods to accurately identify ordered regions in these proteins. This finding motivates the development of a new generation of methods that would target these difficult-to-predict disordered proteins. We also discuss resources that support users in collecting and identifying high-quality disorder predictions.
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Affiliation(s)
| | - Lukasz Kurgan
- Department of Computer Science, Virginia Commonwealth University, Richmond, VA 23284, USA;
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9
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Abstract
Intrinsically disordered proteins (IDPs) can adopt a range of conformations from globules to swollen coils. This large range of conformational preferences for different IDPs raises the question of how conformational preferences are encoded by sequence. Global compositional features of a sequence such as the fraction of charged residues and the net charge per residue engender certain conformational biases. However, more specific sequence features such as the patterning of oppositely charged residues, expansion driving residues, or residues that can undergo posttranslational modifications can also influence the conformational ensembles of an IDP. Here, we outline how to calculate important global compositional features and patterning metrics that can be used to classify IDPs into different conformational classes and predict relative changes in conformation for sequences with the same amino acid composition. Although increased effort has been devoted to determining conformational properties of IDPs in recent years, quantitative predictions of conformation directly from sequence remain difficult and often inaccurate. Thus, if quantitative predictions of conformational properties are desired, then sequence-specific simulations must be performed.
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Affiliation(s)
- Kiersten M Ruff
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA.
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10
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Abstract
Intrinsically disordered proteins (IDPs) and regions (IDRs) are commonly found in all proteomes analyzed so far. These proteins/regions are subject to numerous posttranslational modifications (PTMs) and alternative splicing, are involved in a wide range of cellular functions, and often facilitate protein-protein interactions (PPIs). Some of these proteins contain molecular recognition features (MoRFs), which are IDRs that bind to partner proteins and undergo disorder-to-order transitions. Although many IDPs/IDRs can fold upon binding, a large fraction of these proteins are known to maintain significant amounts of disorder in their bound states. Being well-recognized interaction specialists, IDPs/IDRs can participate in one-to-many and many-to-one interactions, where one IDP/IDR binds to multiple partners potentially gaining very different structures in the bound state, or where multiple unrelated IDPs/IDRs bind to one partner. As a result, IDPs frequently serve as hubs (i.e., proteins with many links) in complex PPI networks. The goal of this chapter is to describe computational and bioinformatics tools that can be used to look at the disorder status of proteins within a given PPI network and also to gain some knowledge on the disorder-based functionality of the members of this network. To this end, description is provided for some of the use of UniProt and DisProt databases, several databases generating PPI networks (BioGRID, IntAct, DIP, MINT, HPRD, APID, KEGG, and STRING), Composition profiler, some tools for the per-residue disorder predictions (PONDR® VLXT, PONDR® VL3, PONDR® VSL2, PONDR-FIT, and IUPred), binary disorder classifiers CH-plot and CDF-plot and their combined CH-CDF analysis, web-based tools for the visualization of disorder distribution in a query protein (D2P2 and MobiDB), as well as some tools for evaluation disorder-based functionality of proteins (ANCHOR, MoRFpred, DEPP, and ModPred).
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Affiliation(s)
- Vladimir N Uversky
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA. .,USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA. .,Laboratory of New Methods in Biology, Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow Region, Russian Federation.
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11
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Hakeem S, Singh I, Sharma P, Uppal A, Khajuria Y, Verma V, Uversky VN, Chandra R. Molecular dynamics analysis of the effects of GTP, GDP and benzimidazole derivative on structural dynamics of a cell division protein FtsZ from Mycobacterium tuberculosis. J Biomol Struct Dyn 2019; 37:4361-4373. [PMID: 30466358 DOI: 10.1080/07391102.2018.1548979] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
The prevailing multi-drug resistance in Mycobacterium tuberculosis continues to remain one of the main challenges to combat tuberculosis. Hence, it becomes imperative to focus on novel drug targets. Filamenting temperature-sensitive mutant Z (FtsZ) is an essential cell division protein, a eukaryotic tubulin homologue and a promising drug target. During cytokinesis, FtsZ polymerises in the presence of GTP to form Z-ring and recruits other proteins at this site that eventually lead to the formation of daughter cells. Benzimidazoles were experimentally shown to inhibit Mtb-FtsZ, with one of the benzimidazole derivatives, M1, being reported to have the minimum inhibitory concentration (MIC) value of 3.13 µg/mL. In the present study, mechanism of destabilisation of FtsZ in the presence of M1 was computationally investigated in the presence of its substrate GTP/GDP employing molecular dynamics (MD) simulation analysis, principal component analysis (PCA), molecular mechanics combined with the generalised Born and surface area continuum salvation (MM-GBSA) and density functional theory (DFT). From the analyses, it is proposed that binding of M1 in the inter-domain cleft induces structural changes in the GTP-binding region that affect GTP binding, thus switching the preference of this protein towards depolymerised state and eventually inhibiting the cell division. Hence, this study provides mechanistic insights into the design of novel benzimidazole inhibitors against Mtb-FtsZ. Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Supriya Hakeem
- School of Biotechnology, Shri Mata Vaishno Devi University (SMVDU) , Katra , India.,Bioinformatics Infrastructure Facility, School of Biotechnology, Shri Mata Vaishno Devi University (SMVDU) , Katra , India
| | - Inderpal Singh
- School of Biotechnology, Shri Mata Vaishno Devi University (SMVDU) , Katra , India.,Bioinformatics Infrastructure Facility, School of Biotechnology, Shri Mata Vaishno Devi University (SMVDU) , Katra , India
| | - Preeti Sharma
- School of Biotechnology, Shri Mata Vaishno Devi University (SMVDU) , Katra , India
| | - Anshul Uppal
- School of Physics, Shri Mata Vaishno Devi University (SMVDU) , Katra , India
| | - Yugal Khajuria
- School of Physics, Shri Mata Vaishno Devi University (SMVDU) , Katra , India
| | - Vijeshwar Verma
- School of Biotechnology, Shri Mata Vaishno Devi University (SMVDU) , Katra , India.,Bioinformatics Infrastructure Facility, School of Biotechnology, Shri Mata Vaishno Devi University (SMVDU) , Katra , India
| | - Vladimir N Uversky
- Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida , Tampa , FL , USA.,Laboratory of New Methods in Biology, Institute for Biological Instrumentation, Russian Academy of Sciences , Pushchino , Russia
| | - Ratna Chandra
- School of Biotechnology, Shri Mata Vaishno Devi University (SMVDU) , Katra , India
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Uversky VN. Intrinsic Disorder, Protein-Protein Interactions, and Disease. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2017; 110:85-121. [PMID: 29413001 DOI: 10.1016/bs.apcsb.2017.06.005] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
It is recognized now that biologically active proteins without stable tertiary structure (known as intrinsically disordered proteins, IDPs) and hybrid proteins containing ordered domains and intrinsically disordered protein regions (IDPRs) are important players found in any given proteome. These IDPs/IDPRs possess functions that complement functional repertoire of their ordered counterparts, being commonly related to recognition, as well as control and regulation of various signaling pathways. They are interaction masters, being able to utilize a wide spectrum of interaction mechanisms, ranging from induced folding to formation of fuzzy complexes where significant levels of disorder are preserved, to polyvalent stochastic interactions playing crucial roles in the liquid-liquid phase transitions leading to the formation of proteinaceous membrane-less organelles. IDPs/IDPRs are tightly controlled themselves via various means, including alternative splicing, precisely controlled expression and degradation, binding to specific partners, and posttranslational modifications. Distortions in the regulation and control of IDPs/IDPRs, as well as their aberrant interactivity are commonly associated with various human diseases. This review presents some aspects of the intrinsic disorder-based functionality and dysfunctionality, paying special attention to the normal and pathological protein-protein interactions.
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Affiliation(s)
- Vladimir N Uversky
- USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, United States; Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow Region, Russia.
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