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Sidhanta SPD, Sowdhamini R, Srinivasan N. Comparative analysis of permanent and transient domain-domain interactions in multi-domain proteins. Proteins 2023. [PMID: 37828826 DOI: 10.1002/prot.26581] [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] [Received: 05/31/2023] [Revised: 08/09/2023] [Accepted: 08/11/2023] [Indexed: 10/14/2023]
Abstract
Protein domains are structural, functional, and evolutionary units. These domains bring out the diversity of functionality by means of interactions with other co-existing domains and provide stability. Hence, it is important to study intra-protein inter-domain interactions from the perspective of types of interactions. Domains within a chain could interact over short timeframes or permanently, rather like protein-protein interactions (PPIs). However, no systematic study has been carried out between two classes, namely permanent and transient domain-domain interactions. In this work, we studied 263 two-domain proteins, belonging to either of these classes and their interfaces on the basis of several factors, such as interface area and details of interactions (number, strength, and types of interactions). We also characterized them based on residue conservation at the interface, correlation of residue motions across domains, its involvement in repeat formation, and their involvement in particular molecular processes. Finally, we could analyze the interactions arising from domains in two-domain monomeric proteins, and we observed significant differences between these two classes of domain interactions and a few similarities. This study will help to obtain a better understanding of structure-function and folding principles of multi-domain proteins.
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Affiliation(s)
| | - Ramanathan Sowdhamini
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
- Computational Approaches to Protein Science, National Centre for Biological Sciences, Bangalore, India
- Computational Biology, Institute of Bioinformatics and Applied Biotechnology, Bangalore, India
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Xie J, Pan G, Li Y, Lai L. How protein topology controls allosteric regulations. J Chem Phys 2023; 158:105102. [PMID: 36922138 DOI: 10.1063/5.0138279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023] Open
Abstract
Allostery is an important regulatory mechanism of protein functions. Among allosteric proteins, certain protein structure types are more observed. However, how allosteric regulation depends on protein topology remains elusive. In this study, we extracted protein topology graphs at the fold level and found that known allosteric proteins mainly contain multiple domains or subunits and allosteric sites reside more often between two or more domains of the same fold type. Only a small fraction of fold-fold combinations are observed in allosteric proteins, and homo-fold-fold combinations dominate. These analyses imply that the locations of allosteric sites including cryptic ones depend on protein topology. We further developed TopoAlloSite, a novel method that uses the kernel support vector machine to predict the location of allosteric sites on the overall protein topology based on the subgraph-matching kernel. TopoAlloSite successfully predicted known cryptic allosteric sites in several allosteric proteins like phosphopantothenoylcysteine synthetase, spermidine synthase, and sirtuin 6, demonstrating its power in identifying cryptic allosteric sites without performing long molecular dynamics simulations or large-scale experimental screening. Our study demonstrates that protein topology largely determines how its function can be allosterically regulated, which can be used to find new druggable targets and locate potential binding sites for rational allosteric drug design.
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Affiliation(s)
- Juan Xie
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Gaoxiang Pan
- BNLMS, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Yibo Li
- Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Luhua Lai
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
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Kennedy EN, Foster CA, Barr SA, Bourret RB. General strategies for using amino acid sequence data to guide biochemical investigation of protein function. Biochem Soc Trans 2022; 50:1847-1858. [PMID: 36416676 PMCID: PMC10257402 DOI: 10.1042/bst20220849] [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: 08/18/2022] [Revised: 11/04/2022] [Accepted: 11/09/2022] [Indexed: 11/24/2022]
Abstract
The rapid increase of '-omics' data warrants the reconsideration of experimental strategies to investigate general protein function. Studying individual members of a protein family is likely insufficient to provide a complete mechanistic understanding of family functions, especially for diverse families with thousands of known members. Strategies that exploit large amounts of available amino acid sequence data can inspire and guide biochemical experiments, generating broadly applicable insights into a given family. Here we review several methods that utilize abundant sequence data to focus experimental efforts and identify features truly representative of a protein family or domain. First, coevolutionary relationships between residues within primary sequences can be successfully exploited to identify structurally and/or functionally important positions for experimental investigation. Second, functionally important variable residue positions typically occupy a limited sequence space, a property useful for guiding biochemical characterization of the effects of the most physiologically and evolutionarily relevant amino acids. Third, amino acid sequence variation within domains shared between different protein families can be used to sort a particular domain into multiple subtypes, inspiring further experimental designs. Although generally applicable to any kind of protein domain because they depend solely on amino acid sequences, the second and third approaches are reviewed in detail because they appear to have been used infrequently and offer immediate opportunities for new advances. Finally, we speculate that future technologies capable of analyzing and manipulating conserved and variable aspects of the three-dimensional structures of a protein family could lead to broad insights not attainable by current methods.
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Affiliation(s)
- Emily N. Kennedy
- Department of Microbiology & Immunology, University of North Carolina, Chapel Hill, NC, United States of America
| | - Clay A. Foster
- Department of Pediatrics, Section Hematology/Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Sarah A. Barr
- Department of Microbiology & Immunology, University of North Carolina, Chapel Hill, NC, United States of America
| | - Robert B. Bourret
- Department of Microbiology & Immunology, University of North Carolina, Chapel Hill, NC, United States of America
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Vymětal J, Mertová K, Boušová K, Šulc J, Tripsianes K, Vondrasek J. Fusion of two unrelated protein domains in a chimera protein and its 3D prediction: Justification of the x-ray reference structures as a prediction benchmark. Proteins 2022; 90:2067-2079. [PMID: 35833233 PMCID: PMC9796088 DOI: 10.1002/prot.26398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 05/20/2022] [Accepted: 07/08/2022] [Indexed: 12/30/2022]
Abstract
Proteins are naturally formed by domains edging their functional and structural properties. A domain out of the context of an entire protein can retain its structure and to some extent also function on its own. These properties rationalize construction of artificial fusion multidomain proteins with unique combination of various functions. Information on the specific functional and structural characteristics of individual domains in the context of new artificial fusion proteins is inevitably encoded in sequential order of composing domains defining their mutual spatial positions. So the challenges in designing new proteins with new domain combinations lie dominantly in structure/function prediction and its context dependency. Despite the enormous body of publications on artificial fusion proteins, the task of their structure/function prediction is complex and nontrivial. The degree of spatial freedom facilitated by a linker between domains and their mutual orientation driven by noncovalent interactions is beyond a simple and straightforward methodology to predict their structure with reasonable accuracy. In the presented manuscript, we tested methodology using available modeling tools and computational methods. We show that the process and methodology of such prediction are not straightforward and must be done with care even when recently introduced AlphaFold II is used. We also addressed a question of benchmarking standards for prediction of multidomain protein structures-x-ray or Nuclear Magnetic Resonance experiments. On the study of six two-domain protein chimeras as well as their composing domains and their x-ray structures selected from PDB, we conclude that the major obstacle for justified prediction is inappropriate sampling of the conformational space by the explored methods. On the other hands, we can still address particular steps of the methodology and improve the process of chimera proteins prediction.
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Affiliation(s)
- Jiří Vymětal
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of SciencesPrague 6Czech Republic
| | - Kateřina Mertová
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of SciencesPrague 6Czech Republic,Faculty of Natural SciencesCharles UniversityPraha 2Czech Republic
| | - Kristýna Boušová
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of SciencesPrague 6Czech Republic
| | - Josef Šulc
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of SciencesPrague 6Czech Republic,Faculty of Natural SciencesCharles UniversityPraha 2Czech Republic
| | | | - Jiri Vondrasek
- Institute of Organic Chemistry and Biochemistry of the Czech Academy of SciencesPrague 6Czech Republic
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Vass LR, Branscum KM, Bourret RB, Foster CA. Generalizable strategy to analyze domains in the context of parent protein architecture: A CheW case study. Proteins 2022; 90:1973-1986. [PMID: 35668544 PMCID: PMC9561059 DOI: 10.1002/prot.26390] [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: 03/02/2022] [Revised: 05/31/2022] [Accepted: 06/02/2022] [Indexed: 11/08/2022]
Abstract
Domains are the three-dimensional building blocks of proteins. An individual domain can occur in a variety of domain architectures that perform unique functions and are subject to different evolutionary selective pressures. We describe an approach to evaluate the variability in amino acid sequences of a single domain across architectural contexts. The ability to distinguish different evolutionary outcomes of one protein domain can help determine whether existing knowledge about a specific domain will apply to an uncharacterized protein, lead to insights and hypotheses about function, and guide experimental priorities. We developed and tested our approach on CheW-like domains (PF01584), which mediate protein/protein interactions and are difficult to compare experimentally. CheW-like domains occur in CheW scaffolding proteins, CheA kinases, and CheV proteins that regulate bacterial chemotaxis. We analyzed 16 domain architectures that included 94% of all CheW-like domains found in nature. We identified six Classes of CheW-like domains with presumed functional differences. CheV and most CheW proteins contained Class 1 domains, whereas some CheW proteins contained Class 6 (~20%) or Class 2 (~1%) domains instead. Most CheA proteins contained Class 3 domains. CheA proteins with multiple Hpt domains contained Class 4 domains. CheA proteins with two CheW-like domains contained one Class 3 and one Class 5. We also created SimpLogo, an innovative method for visualizing amino acid composition across large sets of multiple sequence alignments of arbitrary length. SimpLogo offers substantial advantages over standard sequence logos for comparison and analysis of related protein sequences. The R package for SimpLogo is freely available.
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Affiliation(s)
- Luke R. Vass
- Department of Microbiology & Immunology, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Current Address: Department of Pathology, University of Virginia, Charlottesville, Virginia, United States of America
| | - Katie M. Branscum
- Current Address: Department of Pediatrics, Section Hematology/Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Robert B. Bourret
- Department of Microbiology & Immunology, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Clay A. Foster
- Department of Microbiology & Immunology, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Current Address: Department of Pediatrics, Section Hematology/Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
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Mondal B, Nagesh J, Reddy G. Double Domain Swapping in Human γC and γD Crystallin Drives Early Stages of Aggregation. J Phys Chem B 2021; 125:1705-1715. [PMID: 33566611 DOI: 10.1021/acs.jpcb.0c07833] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Human γD (HγD) and γC (HγC) are two-domain crystallin (Crys) proteins expressed in the nucleus of the eye lens. Structural perturbations in the protein often trigger aggregation, which eventually leads to cataract. To decipher the underlying molecular mechanism, it is important to characterize the partially unfolded conformations, which are aggregation-prone. Using a coarse grained protein model and molecular dynamics simulations, we studied the role of on-pathway folding intermediates in the early stages of aggregation. The multidimensional free energy surface revealed at least three different folding pathways with the population of partially structured intermediates. The two dominant pathways confirm sequential folding of the N-terminal [Ntd] and the C-terminal domains [Ctd], while the third, least favored, pathway involves intermediates where both the domains are partially folded. A native-like intermediate (I*), featuring the folded domains and disrupted interdomain contacts, gets populated in all three pathways. I* forms domain swapped dimers by swapping the entire Ntds and Ctds with other monomers. Population of such oligomers can explain the increased resistance to unfolding resulting in hysteresis observed in the folding experiments of HγD Crys. An ensemble of double domain swapped dimers are also formed during refolding, where intermediates consisting of partially folded Ntds and Ctds swap secondary structures with other monomers. The double domain swapping model presented in our study provides structural insights into the early events of aggregation in Crys proteins and identifies the key secondary structural swapping elements, where introducing mutations will aid in regulating the overall aggregation propensity.
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Affiliation(s)
- Balaka Mondal
- Solid State and Structural Chemistry Unit, Indian Institute of Science, Bengaluru, Karnataka, India 560012
| | - Jayashree Nagesh
- Solid State and Structural Chemistry Unit, Indian Institute of Science, Bengaluru, Karnataka, India 560012
| | - Govardhan Reddy
- Solid State and Structural Chemistry Unit, Indian Institute of Science, Bengaluru, Karnataka, India 560012
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