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Timonina D, Sharapova Y, Švedas V, Suplatov D. Bioinformatic analysis of subfamily-specific regions in 3D-structures of homologs to study functional diversity and conformational plasticity in protein superfamilies. Comput Struct Biotechnol J 2021; 19:1302-1311. [PMID: 33738079 PMCID: PMC7933735 DOI: 10.1016/j.csbj.2021.02.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Revised: 02/08/2021] [Accepted: 02/09/2021] [Indexed: 02/07/2023] Open
Abstract
Local 3D-structural differences in homologous proteins contribute to functional diversity observed in a superfamily, but so far received little attention as bioinformatic analysis was usually carried out at the level of amino acid sequences. We have developed Zebra3D - the first-of-its-kind bioinformatic software for systematic analysis of 3D-alignments of protein families using machine learning. The new tool identifies subfamily-specific regions (SSRs) - patterns of local 3D-structure (i.e. single residues, loops, or secondary structure fragments) that are spatially equivalent within families/subfamilies, but are different among them, and thus can be associated with functional diversity and function-related conformational plasticity. Bioinformatic analysis of protein superfamilies by Zebra3D can be used to study 3D-determinants of catalytic activity and specific accommodation of ligands, help to prepare focused libraries for directed evolution or assist development of chimeric enzymes with novel properties by exchange of equivalent regions between homologs, and to characterize plasticity in binding sites. A companion Mustguseal web-server is available to automatically construct a 3D-alignment of functionally diverse proteins, thus reducing the minimal input required to operate Zebra3D to a single PDB code. The Zebra3D + Mustguseal combined approach provides the opportunity to systematically explore the value of SSRs in superfamilies and to use this information for protein design and drug discovery. The software is available open-access at https://biokinet.belozersky.msu.ru/Zebra3D.
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Affiliation(s)
- Daria Timonina
- Lomonosov Moscow State University, Faculty of Bioengineering and Bioinformatics, Lenin Hills 1-73, Moscow 119234, Russia
| | - Yana Sharapova
- Lomonosov Moscow State University, Faculty of Bioengineering and Bioinformatics, Lenin Hills 1-73, Moscow 119234, Russia
- Lomonosov Moscow State University, Belozersky Institute of Physicochemical Biology, Lenin Hills 1-73, Moscow 119234, Russia
| | - Vytas Švedas
- Lomonosov Moscow State University, Faculty of Bioengineering and Bioinformatics, Lenin Hills 1-73, Moscow 119234, Russia
- Lomonosov Moscow State University, Belozersky Institute of Physicochemical Biology, Lenin Hills 1-73, Moscow 119234, Russia
| | - Dmitry Suplatov
- Lomonosov Moscow State University, Belozersky Institute of Physicochemical Biology, Lenin Hills 1-73, Moscow 119234, Russia
- Corresponding author.
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Ribeiro VS, Santana CA, Fassio AV, Cerqueira FR, da Silveira CH, Romanelli JPR, Patarroyo-Vargas A, Oliveira MGA, Gonçalves-Almeida V, Izidoro SC, de Melo-Minardi RC, Silveira SDA. visGReMLIN: graph mining-based detection and visualization of conserved motifs at 3D protein-ligand interface at the atomic level. BMC Bioinformatics 2020; 21:80. [PMID: 32164574 PMCID: PMC7068867 DOI: 10.1186/s12859-020-3347-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Background Interactions between proteins and non-proteic small molecule ligands play important roles in the biological processes of living systems. Thus, the development of computational methods to support our understanding of the ligand-receptor recognition process is of fundamental importance since these methods are a major step towards ligand prediction, target identification, lead discovery, and more. This article presents visGReMLIN, a web server that couples a graph mining-based strategy to detect motifs at the protein-ligand interface with an interactive platform to visually explore and interpret these motifs in the context of protein-ligand interfaces. Results To illustrate the potential of visGReMLIN, we conducted two cases in which our strategy was compared with previous experimentally and computationally determined results. visGReMLIN allowed us to detect patterns previously documented in the literature in a totally visual manner. In addition, we found some motifs that we believe are relevant to protein-ligand interactions in the analyzed datasets. Conclusions We aimed to build a visual analytics-oriented web server to detect and visualize common motifs at the protein-ligand interface. visGReMLIN motifs can support users in gaining insights on the key atoms/residues responsible for protein-ligand interactions in a dataset of complexes.
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Affiliation(s)
- Vagner S Ribeiro
- Department of Computer Science, Universidade Federal de Viçosa, Viçosa, 36570-900, Brazil
| | - Charles A Santana
- Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil
| | - Alexandre V Fassio
- Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil
| | - Fabio R Cerqueira
- Department of Production Engineering, Universidade Federal Fluminense, Petrópolis, 25650-050, Brazil
| | - Carlos H da Silveira
- Department of Computer Engineering, Advanced Campus at Itabira, Universidade Federal de Itajubá, Itabira, 35903-087, Brazil
| | - João P R Romanelli
- Department of Computer Engineering, Advanced Campus at Itabira, Universidade Federal de Itajubá, Itabira, 35903-087, Brazil
| | - Adriana Patarroyo-Vargas
- Department of Biochemistry and Molecular Biology, Universidade Federal de Viçosa, Viçosa, 36570-900, Brazil
| | - Maria G A Oliveira
- Department of Biochemistry and Molecular Biology, Universidade Federal de Viçosa, Viçosa, 36570-900, Brazil.,Instituto de Biotecnologia aplicada à Agropecuária (BIOAGRO), Universidade Federal de Viçosa, Viçosa, 36570-900, Brazil
| | - Valdete Gonçalves-Almeida
- Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil
| | - Sandro C Izidoro
- Department of Computer Engineering, Advanced Campus at Itabira, Universidade Federal de Itajubá, Itabira, 35903-087, Brazil
| | - Raquel C de Melo-Minardi
- Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, 31270-901, Brazil
| | - Sabrina de A Silveira
- Department of Computer Science, Universidade Federal de Viçosa, Viçosa, 36570-900, Brazil. .,European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, CB10 1SD, UK.
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Abstract
How proteins evolved to recognize and bind their ligands is a key mystery in protein function evolution. To explore this mystery, we study how proteins bind adenine, an ancient fragment. We characterize physicochemical patterns of protein–adenine interactions and link these to proteins’ evolutionary origins. In conflict with previous findings, we see that all of adenine’s hydrogen donors and acceptors have been used to bind proteins, and that adenine binding is likely to have emerged multiple times in evolution. To identify adenine-binding sites of shared origin, we use “themes”: short amino acid segments suggested to constitute evolutionary building blocks. We detect specific themes that are engaged in adenine binding; the detection of these in a protein’s sequence might reveal its function. Proteins’ interactions with ancient ligands may reveal how molecular recognition emerged and evolved. We explore how proteins recognize adenine: a planar rigid fragment found in the most common and ancient ligands. We have developed a computational pipeline that extracts protein–adenine complexes from the Protein Data Bank, structurally superimposes their adenine fragments, and detects the hydrogen bonds mediating the interaction. Our analysis extends the known motifs of protein–adenine interactions in the Watson–Crick edge of adenine and shows that all of adenine’s edges may contribute to molecular recognition. We further show that, on the proteins' side, binding is often mediated by specific amino acid segments (“themes”) that recur across different proteins, such that different proteins use the same themes when binding the same adenine-containing ligands. We identify numerous proteins that feature these themes and are thus likely to bind adenine-containing ligands. Our analysis suggests that adenine binding has emerged multiple times in evolution.
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