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Radha G, Pragyandipta P, Naik PK, Lopus M. Biochemical and in silico analysis of the binding mode of erastin with tubulin. J Biomol Struct Dyn 2024:1-8. [PMID: 38375607 DOI: 10.1080/07391102.2024.2317984] [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: 09/05/2023] [Accepted: 02/05/2024] [Indexed: 02/21/2024]
Abstract
Erastin (ERN) is a small molecule that induces different forms of cell death. For example, it has been reported to induce ferroptosis by disrupting tubulin subunits that maintain the voltage-dependent anion channels (VDACs) of mitochondria. Although its possible binding to tubulin has been suggested, the fine details of the interaction between ERN and tubulin are poorly understood. Using a combination of biochemical, cell-model and in silico approaches, we elucidate the interactions of ERN with tubulin and their biological manifestations. After confirming ERN's antiproliferative efficacy (IC50, 20 ± 3.2 M) and induction of cell death in the breast cancer cell line MDA-MB-231, the binding interactions of ERN with tubulin were examined. ERN bound to tubulin in a concentration-dependent manner, disorganizing the structural integrity of the protein, as substantiated via the tryptophan-quenching assay and the aniline-naphthalene sulfonate binding assay, respectively. In silico studies based on molecular docking revealed a docking score of -5.863 kcal/mol, suggesting strong binding interactions of ERN with tubulin. Additionally, molecular dynamics simulation and Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) analyses evinced the binding free energy (ΔGbinding) of -31.235 kcal/mol, substantiating strong binding affinity of ERN with tubulin. Ligplot analysis showed hydrogen bonding with specific amino acids (Asn A226, Thr A223, Gln B247 and Val B355). QikProp-based ADME (absorption, distribution, metabolism and excretion) assessment showed considerable therapeutic potential for ERN.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Gudapureddy Radha
- School of Biological Sciences, UM-DAE Centre for Excellence in Basic Sciences, University of Mumbai, Mumbai, India
| | - Pratyush Pragyandipta
- Department of Biotechnology and Bioinformatics, Center of Excellence in Natural Products and Therapeutics, Sambalpur University, Sambalpur, India
| | - Pradeep Kumar Naik
- Department of Biotechnology and Bioinformatics, Center of Excellence in Natural Products and Therapeutics, Sambalpur University, Sambalpur, India
| | - Manu Lopus
- School of Biological Sciences, UM-DAE Centre for Excellence in Basic Sciences, University of Mumbai, Mumbai, India
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2
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Kovács D, Bodor A. The influence of random-coil chemical shifts on the assessment of structural propensities in folded proteins and IDPs. RSC Adv 2023; 13:10182-10203. [PMID: 37006359 PMCID: PMC10065145 DOI: 10.1039/d3ra00977g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 03/15/2023] [Indexed: 04/03/2023] Open
Abstract
In studying secondary structural propensities of proteins by nuclear magnetic resonance (NMR) spectroscopy, secondary chemical shifts (SCSs) serve as the primary atomic scale observables. For SCS calculation, the selection of an appropriate random coil chemical shift (RCCS) dataset is a crucial step, especially when investigating intrinsically disordered proteins (IDPs). The scientific literature is abundant in such datasets, however, the effect of choosing one over all the others in a concrete application has not yet been studied thoroughly and systematically. Hereby, we review the available RCCS prediction methods and to compare them, we conduct statistical inference by means of the nonparametric sum of ranking differences and comparison of ranks to random numbers (SRD-CRRN) method. We try to find the RCCS predictors best representing the general consensus regarding secondary structural propensities. The existence and the magnitude of resulting differences on secondary structure determination under varying sample conditions (temperature, pH) are demonstrated and discussed for globular proteins and especially IDPs.
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Affiliation(s)
- Dániel Kovács
- ELTE, Eötvös Loránd University, Institute of Chemistry, Analytical and BioNMR Laboratory Pázmány Péter sétány 1/A Budapest 1117 Hungary
- Eötvös Loránd University, Hevesy György PhD School of Chemistry Pázmány Péter sétány 1/A Budapest 1117 Hungary
| | - Andrea Bodor
- ELTE, Eötvös Loránd University, Institute of Chemistry, Analytical and BioNMR Laboratory Pázmány Péter sétány 1/A Budapest 1117 Hungary
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3
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Luo S, Wohl S, Zheng W, Yang S. Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery. Biomolecules 2023; 13:biom13030530. [PMID: 36979465 PMCID: PMC10046839 DOI: 10.3390/biom13030530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/07/2023] [Accepted: 03/10/2023] [Indexed: 03/17/2023] Open
Abstract
Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.
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Affiliation(s)
- Shuqi Luo
- Center for Proteomics and Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Samuel Wohl
- Department of Physics, Arizona State University, Tempe, AZ 85287, USA
| | - Wenwei Zheng
- College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ 85212, USA
- Correspondence: (W.Z.); (S.Y.)
| | - Sichun Yang
- Center for Proteomics and Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH 44106, USA
- Correspondence: (W.Z.); (S.Y.)
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Kouros CE, Makri V, Ouzounis CA, Chasapi A. Disease association and comparative genomics of compositional bias in human proteins. F1000Res 2023; 12:198. [PMID: 37082000 PMCID: PMC10111144 DOI: 10.12688/f1000research.129929.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/02/2023] [Indexed: 02/22/2023] Open
Abstract
Background: The evolutionary rate of disordered proteins varies greatly due to the lack of structural constraints. So far, few studies have investigated the presence/absence patterns of intrinsically disordered regions (IDRs) across phylogenies in conjunction with human disease. In this study, we report a genome-wide analysis of compositional bias association with disease in human proteins and their taxonomic distribution. Methods: The human genome protein set provided by the Ensembl database was annotated and analysed with respect to both disease associations and the detection of compositional bias. The Uniprot Reference Proteome dataset, containing 11297 proteomes was used as target dataset for the comparative genomics of a well-defined subset of the Human Genome, including 100 characteristic, compositionally biased proteins, some linked to disease. Results: Cross-evaluation of compositional bias and disease-association in the human genome reveals a significant bias towards low complexity regions in disease-associated genes, with charged, hydrophilic amino acids appearing as over-represented. The phylogenetic profiling of 17 disease-associated, low complexity proteins across 11297 proteomes captures characteristic taxonomic distribution patterns. Conclusions: This is the first time that a combined genome-wide analysis of low complexity, disease-association and taxonomic distribution of human proteins is reported, covering structural, functional, and evolutionary properties. The reported framework can form the basis for large-scale, follow-up projects, encompassing the entire human genome and all known gene-disease associations.
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Affiliation(s)
- Christos E. Kouros
- BCCB-AIIA, School of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Vasiliki Makri
- BCCB-AIIA, School of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Christos A. Ouzounis
- BCCB-AIIA, School of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
- BCPL, Chemical Process & Energy Resources Institute, Centre for Research & Technology Hellas (CERTH), Thessaloniki, Greece
| | - Anastasia Chasapi
- BCPL, Chemical Process & Energy Resources Institute, Centre for Research & Technology Hellas (CERTH), Thessaloniki, Greece
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Kouros CE, Makri V, Ouzounis CA, Chasapi A. Disease association and comparative genomics of compositional bias in human proteins. F1000Res 2023; 12:198. [PMID: 37082000 PMCID: PMC10111144.2 DOI: 10.12688/f1000research.129929.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/12/2023] [Indexed: 04/25/2023] Open
Abstract
Background: The evolutionary rate of disordered protein regions varies greatly due to the lack of structural constraints. So far, few studies have investigated the presence/absence patterns of compositional bias, indicative of disorder, across phylogenies in conjunction with human disease. In this study, we report a genome-wide analysis of compositional bias association with disease in human proteins and their taxonomic distribution. Methods: The human genome protein set provided by the Ensembl database was annotated and analysed with respect to both disease associations and the detection of compositional bias. The Uniprot Reference Proteome dataset, containing 11297 proteomes was used as target dataset for the comparative genomics of a well-defined subset of the Human Genome, including 100 characteristic, compositionally biased proteins, some linked to disease. Results: Cross-evaluation of compositional bias and disease-association in the human genome reveals a significant bias towards biased regions in disease-associated genes, with charged, hydrophilic amino acids appearing as over-represented. The phylogenetic profiling of 17 disease-associated, proteins with compositional bias across 11297 proteomes captures characteristic taxonomic distribution patterns. Conclusions: This is the first time that a combined genome-wide analysis of compositional bias, disease-association and taxonomic distribution of human proteins is reported, covering structural, functional, and evolutionary properties. The reported framework can form the basis for large-scale, follow-up projects, encompassing the entire human genome and all known gene-disease associations.
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Affiliation(s)
- Christos E. Kouros
- BCCB-AIIA, School of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Vasiliki Makri
- BCCB-AIIA, School of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Christos A. Ouzounis
- BCCB-AIIA, School of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
- BCPL, Chemical Process & Energy Resources Institute, Centre for Research & Technology Hellas (CERTH), Thessaloniki, Greece
| | - Anastasia Chasapi
- BCPL, Chemical Process & Energy Resources Institute, Centre for Research & Technology Hellas (CERTH), Thessaloniki, Greece
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Brender JR, Ramamoorthy A, Gursky O, Bhunia A. Intrinsic disorder and structural biology: Searching where the light isn't. Biophys Chem 2023; 292:106912. [PMID: 36335754 DOI: 10.1016/j.bpc.2022.106912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Jeffrey R Brender
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Ayyalusamy Ramamoorthy
- Biophysics, Department of Chemistry, Biomedical Engineering, and Macromolecular Science and Engineering, University of Michigan, Ann Arbor, MI 48109-1055, USA
| | - Olga Gursky
- Boston University School of Medicine, Department of Physiology & Biophysics, W302, 700 Albany St, Boston, MA 02118, USA
| | - Anirban Bhunia
- Biomolecular NMR and Drug Design Laboratory, Department of Biophysics, Bose Institute, P-1/12 CIT Scheme VII (M), Kolkata 700054, India
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Intrinsically Disordered Proteins: An Overview. Int J Mol Sci 2022; 23:ijms232214050. [PMID: 36430530 PMCID: PMC9693201 DOI: 10.3390/ijms232214050] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 11/16/2022] Open
Abstract
Many proteins and protein segments cannot attain a single stable three-dimensional structure under physiological conditions; instead, they adopt multiple interconverting conformational states. Such intrinsically disordered proteins or protein segments are highly abundant across proteomes, and are involved in various effector functions. This review focuses on different aspects of disordered proteins and disordered protein regions, which form the basis of the so-called "Disorder-function paradigm" of proteins. Additionally, various experimental approaches and computational tools used for characterizing disordered regions in proteins are discussed. Finally, the role of disordered proteins in diseases and their utility as potential drug targets are explored.
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Beniamino Y, Cenni V, Piccioli M, Ciurli S, Zambelli B. The Ni(II)-Binding Activity of the Intrinsically Disordered Region of Human NDRG1, a Protein Involved in Cancer Development. Biomolecules 2022; 12:biom12091272. [PMID: 36139110 PMCID: PMC9496542 DOI: 10.3390/biom12091272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/31/2022] [Accepted: 09/05/2022] [Indexed: 11/16/2022] Open
Abstract
Nickel exposure is associated with tumors of the respiratory tract such as lung and nasal cancers, acting through still-uncharacterized mechanisms. Understanding the molecular basis of nickel-induced carcinogenesis requires unraveling the mode and the effects of Ni(II) binding to its intracellular targets. A possible Ni(II)-binding protein and a potential focus for cancer treatment is hNDRG1, a protein induced by Ni(II) through the hypoxia response pathway, whose expression correlates with higher cancer aggressiveness and resistance to chemotherapy in lung tissue. The protein sequence contains a unique C-terminal sequence of 83 residues (hNDRG1*C), featuring a three-times-repeated decapeptide, involved in metal binding, lipid interaction and post-translational phosphorylation. In the present work, the biochemical and biophysical characterization of unmodified hNDRG1*C was performed. Bioinformatic analysis assigned it to the family of the intrinsically disordered regions and the absence of secondary and tertiary structure was experimentally proven by circular dichroism and NMR. Isothermal titration calorimetry revealed the occurrence of a Ni(II)-binding event with micromolar affinity. Detailed information on the Ni(II)-binding site and on the residues involved was obtained in an extensive NMR study, revealing an octahedral paramagnetic metal coordination that does not cause any major change of the protein backbone, which is coherent with CD analysis. hNDRG1*C was found in a monomeric form by light-scattering experiments, while the full-length hNDRG1 monomer was found in equilibrium between the dimer and tetramer, both in solution and in human cell lines. The results are the first essential step for understanding the cellular function of hNDRG1*C at the molecular level, with potential future applications to clarify its role and the role of Ni(II) in cancer development.
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Affiliation(s)
- Ylenia Beniamino
- Laboratory of Bioinorganic Chemistry, Department of Pharmacy and Biotechnology, University of Bologna, Viale Giuseppe Fanin 40, 40127 Bologna, Italy
| | - Vittoria Cenni
- CNR Institute of Molecular Genetics “Luigi-Luca Cavalli-Sforza” Unit of Bologna, Via di Barbiano 1/10, 40136 Bologna, Italy
| | - Mario Piccioli
- Department of Chemistry, Center for Magnetic Resonance, University of Florence, 50121 Florence, Italy
| | - Stefano Ciurli
- Laboratory of Bioinorganic Chemistry, Department of Pharmacy and Biotechnology, University of Bologna, Viale Giuseppe Fanin 40, 40127 Bologna, Italy
- Correspondence: (S.C.); (B.Z.); Tel.: +38-051-2096204 (S.C.); +38-051-2096233 (B.Z.)
| | - Barbara Zambelli
- Laboratory of Bioinorganic Chemistry, Department of Pharmacy and Biotechnology, University of Bologna, Viale Giuseppe Fanin 40, 40127 Bologna, Italy
- Correspondence: (S.C.); (B.Z.); Tel.: +38-051-2096204 (S.C.); +38-051-2096233 (B.Z.)
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