1
|
Grossman AS, Gell DA, Wu DG, Carper DL, Hettich RL, Goodrich-Blair H. Bacterial hemophilin homologs and their specific type eleven secretor proteins have conserved roles in heme capture and are diversifying as a family. J Bacteriol 2024; 206:e0044423. [PMID: 38506530 PMCID: PMC11332152 DOI: 10.1128/jb.00444-23] [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: 01/05/2024] [Accepted: 02/18/2024] [Indexed: 03/21/2024] Open
Abstract
Cellular life relies on enzymes that require metals, which must be acquired from extracellular sources. Bacteria utilize surface and secreted proteins to acquire such valuable nutrients from their environment. These include the cargo proteins of the type eleven secretion system (T11SS), which have been connected to host specificity, metal homeostasis, and nutritional immunity evasion. This Sec-dependent, Gram-negative secretion system is encoded by organisms throughout the phylum Proteobacteria, including human pathogens Neisseria meningitidis, Proteus mirabilis, Acinetobacter baumannii, and Haemophilus influenzae. Experimentally verified T11SS-dependent cargo include transferrin-binding protein B (TbpB), the hemophilin homologs heme receptor protein C (HrpC), hemophilin A (HphA), the immune evasion protein factor-H binding protein (fHbp), and the host symbiosis factor nematode intestinal localization protein C (NilC). Here, we examined the specificity of T11SS systems for their cognate cargo proteins using taxonomically distributed homolog pairs of T11SS and hemophilin cargo and explored the ligand binding ability of those hemophilin cargo homologs. In vivo expression in Escherichia coli of hemophilin homologs revealed that each is secreted in a specific manner by its cognate T11SS protein. Sequence analysis and structural modeling suggest that all hemophilin homologs share an N-terminal ligand-binding domain with the same topology as the ligand-binding domains of the Haemophilus haemolyticus heme binding protein (Hpl) and HphA. We term this signature feature of this group of proteins the hemophilin ligand-binding domain. Network analysis of hemophilin homologs revealed five subclusters and representatives from four of these showed variable heme-binding activities, which, combined with sequence-structure variation, suggests that hemophilins are diversifying in function.IMPORTANCEThe secreted protein hemophilin and its homologs contribute to the survival of several bacterial symbionts within their respective host environments. Here, we compared taxonomically diverse hemophilin homologs and their paired Type 11 secretion systems (T11SS) to determine if heme binding and T11SS secretion are conserved characteristics of this family. We establish the existence of divergent hemophilin sub-families and describe structural features that contribute to distinct ligand-binding behaviors. Furthermore, we demonstrate that T11SS are specific for their cognate hemophilin family cargo proteins. Our work establishes that hemophilin homolog-T11SS pairs are diverging from each other, potentially evolving into novel ligand acquisition systems that provide competitive benefits in host niches.
Collapse
Affiliation(s)
- Alex S. Grossman
- Department of Microbiology, University of Tennessee Knoxville, Knoxville, Tennessee, USA
| | - David A. Gell
- School of Medicine, University of Tasmania, Hobart, Tasmania, Australia
| | - Derek G. Wu
- Department of Microbiology, University of Tennessee Knoxville, Knoxville, Tennessee, USA
- Department of Plant and Soil Sciences, University of Delaware, Newark, Delaware, USA
| | - Dana L. Carper
- Bioscience Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Robert L. Hettich
- Bioscience Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Heidi Goodrich-Blair
- Department of Microbiology, University of Tennessee Knoxville, Knoxville, Tennessee, USA
| |
Collapse
|
2
|
Aktaş E, Özdemir Özgentürk N. A comprehensive examination of ACE2 receptor and prediction of spike glycoprotein and ACE2 interaction based on in silico analysis of ACE2 receptor. J Biomol Struct Dyn 2024; 42:4412-4428. [PMID: 37349943 DOI: 10.1080/07391102.2023.2220814] [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] [Received: 02/12/2023] [Accepted: 05/28/2023] [Indexed: 06/24/2023]
Abstract
The ACE2 receptor plays a vital role not only in the SARS-CoV-induced epidemic but also in various other diseases, including cardiovascular diseases and ARDS. While studies have explored the interactions between ACE2 and SARS-CoV proteins, comprehensive research utilizing bioinformatic tools on the ACE2 protein has been lacking. The one aim of present study was to extensively analyze the regions of the ACE2 protein. After utilizing all bioinformatics tools especially G104 and L108 regions on ACE2 were come forward. The results of our analysis revealed that possible mutations or deletions in the G104 and L108 regions play a critical role in both the biological functioning and the determination of the chemical-physical properties of ACE2. Additionally, these regions were found to be more susceptible to mutations or deletions compared to other regions of the ACE2 protein. Notably, the randomly selected peptide, LQQNGSSVLS (100-109), which includes G104 and L108, exhibited a crucial role in binding the RBD of the spike protein, as supported by docking scores. Furthermore, both MDs and iMODs results provided evidence that G104 and L108 influence the dynamics of ACE2-spike complexes. This study is expected to offer a new perspective on the ACE2-SARS-CoV interaction and other research areas where ACE2 plays a significant role, such as biotechnology (protein engineering, enzyme optimization), medicine (RAS, pulmonary and cardiac diseases), and basic research (structural motifs, stabilizing protein folds, or facilitating important inter molecular contacts, protein's proper structure and function).Communicated by Ramaswamy H. Sarma.
Collapse
Affiliation(s)
- Emre Aktaş
- Faculty of Art and Science, Molecular Biology and Genetics, Yıldız Technical University, Istanbul, Turkey
| | - Nehir Özdemir Özgentürk
- Faculty of Art and Science, Molecular Biology and Genetics, Yıldız Technical University, Istanbul, Turkey
| |
Collapse
|
3
|
Cia G, Kwasigroch J, Stamatopoulos B, Rooman M, Pucci F. pyScoMotif: discovery of similar 3D structural motifs across proteins. BIOINFORMATICS ADVANCES 2023; 3:vbad158. [PMID: 38023327 PMCID: PMC10640396 DOI: 10.1093/bioadv/vbad158] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 10/12/2023] [Accepted: 11/01/2023] [Indexed: 12/01/2023]
Abstract
Motivation The fast and accurate detection of similar geometrical arrangements of protein residues, known as 3D structural motifs, is highly relevant for many applications such as binding region and catalytic site detection, drug discovery and structure conservation analyses. With the recent publication of new protein structure prediction methods, the number of available protein structures is exploding, which makes efficient and easy-to-use tools for identifying 3D structural motifs essential. Results We present an open-source Python package that enables the search for both exact and mutated motifs with position-specific residue substitutions. The tool is efficient, flexible, accurate, and suitable to run both on computer clusters and personal laptops. Two successful applications of pyScoMotif for catalytic site identification are showcased. Availability and implementation The pyScoMotif package can be installed from the PyPI repository and is also available at https://github.com/3BioCompBio/pyScoMotif. It is free to use for non-commercial purposes.
Collapse
Affiliation(s)
- Gabriel Cia
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, 1050, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Triomflaan, Brussels,1050, Belgium
| | - Jean Kwasigroch
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, 1050, Belgium
| | - Basile Stamatopoulos
- Laboratory of Clinical Cell Therapy, Jules Bordet Institute, Université Libre de Bruxelles, Brussels, 1070, Belgium
| | - Marianne Rooman
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, 1050, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Triomflaan, Brussels,1050, Belgium
| | - Fabrizio Pucci
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, 1050, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Triomflaan, Brussels,1050, Belgium
| |
Collapse
|
4
|
Ghani NSA, Emrizal R, Moffit SM, Hamdani HY, Ramlan EI, Firdaus-Raih M. GrAfSS: a webserver for substructure similarity searching and comparisons in the structures of proteins and RNA. Nucleic Acids Res 2022; 50:W375-W383. [PMID: 35639505 PMCID: PMC9252811 DOI: 10.1093/nar/gkac402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/28/2022] [Accepted: 05/08/2022] [Indexed: 12/03/2022] Open
Abstract
The GrAfSS (Graph theoretical Applications for Substructure Searching) webserver is a platform to search for three-dimensional substructures of: (i) amino acid side chains in protein structures; and (ii) base arrangements in RNA structures. The webserver interfaces the functions of five different graph theoretical algorithms – ASSAM, SPRITE, IMAAAGINE, NASSAM and COGNAC – into a single substructure searching suite. Users will be able to identify whether a three-dimensional (3D) arrangement of interest, such as a ligand binding site or 3D motif, observed in a protein or RNA structure can be found in other structures available in the Protein Data Bank (PDB). The webserver also allows users to determine whether a protein or RNA structure of interest contains substructural arrangements that are similar to known motifs or 3D arrangements. These capabilities allow for the functional annotation of new structures that were either experimentally determined or computationally generated (such as the coordinates generated by AlphaFold2) and can provide further insights into the diversity or conservation of functional mechanisms of structures in the PDB. The computed substructural superpositions are visualized using integrated NGL viewers. The GrAfSS server is available at http://mfrlab.org/grafss/.
Collapse
Affiliation(s)
- Nur Syatila Ab Ghani
- Institute of Systems Biology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
| | - Reeki Emrizal
- Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
| | - Sabrina Mohamed Moffit
- Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
| | - Hazrina Yusof Hamdani
- Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, Kepala Batas 13200, Pulau Pinang, Malaysia
| | | | - Mohd Firdaus-Raih
- Institute of Systems Biology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia.,Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
| |
Collapse
|
5
|
Lin K, Quan X, Jin C, Shi Z, Yang J. An Interpretable Double-Scale Attention Model for Enzyme Protein Class Prediction Based on Transformer Encoders and Multi-Scale Convolutions. Front Genet 2022; 13:885627. [PMID: 35432476 PMCID: PMC9012241 DOI: 10.3389/fgene.2022.885627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 03/07/2022] [Indexed: 12/01/2022] Open
Abstract
Background Classification and annotation of enzyme proteins are fundamental for enzyme research on biological metabolism. Enzyme Commission (EC) numbers provide a standard for hierarchical enzyme class prediction, on which several computational methods have been proposed. However, most of these methods are dependent on prior distribution information and none explicitly quantifies amino-acid-level relations and possible contribution of sub-sequences. Methods In this study, we propose a double-scale attention enzyme class prediction model named DAttProt with high reusability and interpretability. DAttProt encodes sequence by self-supervised Transformer encoders in pre-training and gathers local features by multi-scale convolutions in fine-tuning. Specially, a probabilistic double-scale attention weight matrix is designed to aggregate multi-scale features and positional prediction scores. Finally, a full connection linear classifier conducts a final inference through the aggregated features and prediction scores. Results On DEEPre and ECPred datasets, DAttProt performs as competitive with the compared methods on level 0 and outperforms them on deeper task levels, reaching 0.788 accuracy on level 2 of DEEPre and 0.967 macro-F1 on level 1 of ECPred. Moreover, through case study, we demonstrate that the double-scale attention matrix learns to discover and focus on the positions and scales of bio-functional sub-sequences in the protein. Conclusion Our DAttProt provides an effective and interpretable method for enzyme class prediction. It can predict enzyme protein classes accurately and furthermore discover enzymatic functional sub-sequences such as protein motifs from both positional and spatial scales.
Collapse
Affiliation(s)
- Ken Lin
- College of Artificial Intelligence, Nankai University, Tianjin, China
| | - Xiongwen Quan
- College of Artificial Intelligence, Nankai University, Tianjin, China
- *Correspondence: Xiongwen Quan,
| | - Chen Jin
- College of Computer Science, Nankai University, Tianjin, China
| | - Zhuangwei Shi
- College of Artificial Intelligence, Nankai University, Tianjin, China
| | - Jinglong Yang
- College of Artificial Intelligence, Nankai University, Tianjin, China
| |
Collapse
|
6
|
Fatima I, Ahmad S, Abbasi SW, Ashfaq UA, Shahid F, Tahir Ul Qamar M, Rehman A, Allemailem KS. Designing of a multi-epitopes-based peptide vaccine against rift valley fever virus and its validation through integrated computational approaches. Comput Biol Med 2021; 141:105151. [PMID: 34942394 DOI: 10.1016/j.compbiomed.2021.105151] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 12/10/2021] [Accepted: 12/14/2021] [Indexed: 01/23/2023]
Abstract
Since its discovery, the Rift Valley Fever virus (RVFV) has been the source of numerous outbreaks in the Arab Peninsulas and Africa, wreaking havoc on humans and animals. The lack of therapeutics or licensed human vaccines limits the options for controlling RVFV outbreaks. Therefore, RVFV has been prioritized for rapid research and innovation of prevention strategies to control and prevent its outbreaks. The purpose of this study was to design a multi-epitope-based peptide vaccine (MEBPV) against RVFV. Bioinformatics approaches were used to design a potent MEBPV that can potentially activate both CD8+ and CD4+ T-cell immune responses, and several computational tools were employed to investigate its biological activities. Three antigenic proteins (Nucleocapsid (N), Glycoprotein C (GC), and Glycoprotein N (GN)) from the RVFV were chosen and potential immunogenic T- and B -cell epitopes were predicted from them. Based on in silico analysis, a MEBPV based on highly scored T and B-cell epitopes (6 CTL, 5 HTL, and 4 LBL) combined with linkers and adjuvants was developed. The finest predicted model was used for docking studies with Toll-like receptors (TLR3 and TLR8) and MHC molecules (MHC I and MHC II) after predicting and analyzing the tertiary structure of MEBPV. The designed MEBPV was then tested for stability with TLR3 and TLR8 receptors using molecular dynamics (MD) simulation and MMGBSA analysis. The MEBPV -TLR3, MEBPV -TLR8, MEBPV-MHC I and MEBPV -MHC II docked models were found stable during simulation time in MD and MMGBSA studies. In silico analysis revealed that the constructed vaccine could elicit both cell-mediated and humoral immune responses simultaneously. The proposed MEBPV could be a strong candidate against RVFV, but it will need to be tested in the laboratory to guarantee its safety and immunogenicity.
Collapse
Affiliation(s)
- Israr Fatima
- Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan.
| | - Sajjad Ahmad
- Department of Health and Biological Sciences, Abasyn University, Peshawar, Pakistan.
| | - Sumra Wajid Abbasi
- NUMS Department of Biological Sciences, National University of Medical Sciences, Rawalpindi, Pakistan.
| | - Usman Ali Ashfaq
- Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan.
| | - Farah Shahid
- Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan.
| | | | - Abdur Rehman
- Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan.
| | - Khaled S Allemailem
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia.
| |
Collapse
|
7
|
Kondra S, Sarkar T, Raghavan V, Xu W. Development of a TSR-Based Method for Protein 3-D Structural Comparison With Its Applications to Protein Classification and Motif Discovery. Front Chem 2021; 8:602291. [PMID: 33520934 PMCID: PMC7838567 DOI: 10.3389/fchem.2020.602291] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 12/14/2020] [Indexed: 11/24/2022] Open
Abstract
Development of protein 3-D structural comparison methods is important in understanding protein functions. At the same time, developing such a method is very challenging. In the last 40 years, ever since the development of the first automated structural method, ~200 papers were published using different representations of structures. The existing methods can be divided into five categories: sequence-, distance-, secondary structure-, geometry-based, and network-based structural comparisons. Each has its uniqueness, but also limitations. We have developed a novel method where the 3-D structure of a protein is modeled using the concept of Triangular Spatial Relationship (TSR), where triangles are constructed with the Cα atoms of a protein as vertices. Every triangle is represented using an integer, which we denote as “key,” A key is computed using the length, angle, and vertex labels based on a rule-based formula, which ensures assignment of the same key to identical TSRs across proteins. A structure is thereby represented by a vector of integers. Our method is able to accurately quantify similarity of structure or substructure by matching numbers of identical keys between two proteins. The uniqueness of our method includes: (i) a unique way to represent structures to avoid performing structural superimposition; (ii) use of triangles to represent substructures as it is the simplest primitive to capture shape; (iii) complex structure comparison is achieved by matching integers corresponding to multiple TSRs. Every substructure of one protein is compared to every other substructure in a different protein. The method is used in the studies of proteases and kinases because they play essential roles in cell signaling, and a majority of these constitute drug targets. The new motifs or substructures we identified specifically for proteases and kinases provide a deeper insight into their structural relations. Furthermore, the method provides a unique way to study protein conformational changes. In addition, the results from CATH and SCOP data sets clearly demonstrate that our method can distinguish alpha helices from beta pleated sheets and vice versa. Our method has the potential to be developed into a powerful tool for efficient structure-BLAST search and comparison, just as BLAST is for sequence search and alignment.
Collapse
Affiliation(s)
- Sarika Kondra
- The Center for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, LA, United States
| | - Titli Sarkar
- The Center for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, LA, United States
| | - Vijay Raghavan
- The Center for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, LA, United States
| | - Wu Xu
- Department of Chemistry, University of Louisiana at Lafayette, Lafayette, LA, United States
| |
Collapse
|
8
|
Sánchez-Aparicio JE, Tiessler-Sala L, Velasco-Carneros L, Roldán-Martín L, Sciortino G, Maréchal JD. BioMetAll: Identifying Metal-Binding Sites in Proteins from Backbone Preorganization. J Chem Inf Model 2020; 61:311-323. [PMID: 33337144 DOI: 10.1021/acs.jcim.0c00827] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
With a large amount of research dedicated to decoding how metallic species bind to proteins, in silico methods are interesting allies for experimental procedures. To date, computational predictors mostly work by identifying the best possible sequence or structural match of the target protein with metal-binding templates. These approaches are fundamentally focused on the first coordination sphere of the metal. Here, we present the BioMetAll predictor that is based on a different postulate: the formation of a potential metal-binding site is related to the geometric organization of the protein backbone. We first report the set of convenient geometric descriptors of the backbone needed for the algorithm and their parameterization from a statistical analysis. Then, the successful benchmark of BioMetAll on a set of more than 90 metal-binding X-ray structures is presented. Because BioMetAll allows structural predictions regardless of the exact geometry of the side chains, it appears extremely valuable for systems whose structures (either experimental or theoretical) are not optimal for metal-binding sites. We report here its application on three different challenging cases: (i) the modulation of metal-binding sites during conformational transition in human serum albumin, (ii) the identification of possible routes of metal migration in hemocyanins, and (iii) the prediction of mutations to generate convenient metal-binding sites for de novo biocatalysts. This study shows that BioMetAll offers a versatile platform for numerous fields of research at the interface between inorganic chemistry and biology and allows to highlight the role of the preorganization of the protein backbone as a marker for metal binding. BioMetAll is an open-source application available at https://github.com/insilichem/biometall.
Collapse
Affiliation(s)
- José-Emilio Sánchez-Aparicio
- Insilichem, Departament de Química, Universitat Autònoma de Barcelona, Edifici C.n., 08193 Cerdanyola del Vallés, Barcelona, Spain
| | - Laura Tiessler-Sala
- Insilichem, Departament de Química, Universitat Autònoma de Barcelona, Edifici C.n., 08193 Cerdanyola del Vallés, Barcelona, Spain
| | - Lorea Velasco-Carneros
- Biofisika Institute (UPV/EHU, CSIC) and Department of Biochemistry and Molecular Biology, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Barrio Sarriena s/n, 48940 Leioa, Spain
| | - Lorena Roldán-Martín
- Insilichem, Departament de Química, Universitat Autònoma de Barcelona, Edifici C.n., 08193 Cerdanyola del Vallés, Barcelona, Spain
| | - Giuseppe Sciortino
- Insilichem, Departament de Química, Universitat Autònoma de Barcelona, Edifici C.n., 08193 Cerdanyola del Vallés, Barcelona, Spain.,Institute of Chemical Research of Catalonia (ICIQ), Av. Països Catalans 16, 43007 Tarragona, Spain
| | - Jean-Didier Maréchal
- Insilichem, Departament de Química, Universitat Autònoma de Barcelona, Edifici C.n., 08193 Cerdanyola del Vallés, Barcelona, Spain
| |
Collapse
|
9
|
Alonso-Cotchico L, Rodrı́guez-Guerra J, Lledós A, Maréchal JD. Molecular Modeling for Artificial Metalloenzyme Design and Optimization. Acc Chem Res 2020; 53:896-905. [PMID: 32233391 DOI: 10.1021/acs.accounts.0c00031] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Artificial metalloenzymes (ArMs) are obtained by inserting homogeneous catalysts into biological scaffolds and are among the most promising strategies in the quest for new-to-nature biocatalysts. The quality of their design strongly depends on how three partners interact: the biological host, the "artificial cofactor," and the substrate. However, structural characterization of functional artificial metalloenzymes by X-ray or NMR is often partial, elusive, or absent. How the cofactor binds to the protein, how the receptor reorganizes upon the binding of the cofactor and the substrate, and which are the binding mode(s) of the substrate for the reaction to proceed are key questions that are frequently unresolved yet crucial for ArM design. Such questions may eventually be solved by molecular modeling but require a step change beyond the current state-of-the-art methodologies.Here, we summarize our efforts in the study of ArMs, presenting both the development of computational strategies and their application. We first focus on our integrative computational framework that incorporates a variety of methods such as protein-ligand docking, classical molecular dynamics (MD), and pure quantum mechanical (QM) methods, which, when properly combined, are able to depict questions that range from host-cofactor binding predictions to simulations of entire catalytic mechanisms. We also pay particular attention to the protein-ligand docking strategies that we have developed to accurately predict the binding of transition metal-containing molecules to proteins. While this aspect is fundamental to many bioinorganic fields beyond ArMs, it has been disregarded from the molecular modeling landscape until very recently.Next we describe how to apply this computational framework to particular ArMs including systems previously characterized experimentally as well as others where computation served to guide the design. We start with the prediction of the interactions between homogeneous catalysts and biological hosts. Protein-ligand docking is pivotal at that stage, but it needs to be combined with QM/MM or MD approaches when the binding of the cofactor implies significant conformational changes of the protein or involve changes of the electronic state of the metal.Then, we summarize molecular modeling studies aimed at identifying cofactor-substrate arrangements inside the ArM active pocket that are consistent with its reactivity. These calculations stand on "Theozyme"-like dockings, MD-refined or not, which provide molecular rationale of the catalytic profiles of the artificial systems.In the third section, we present case studies to decode the entire catalytic mechanism of two ArMs: (1) an iridium based asymmetric transfer hydrogenase obtained by insertion of Noyori's catalyst into streptavidin and (2) a metallohydrolase achieved by including a receptor. Transition states, second coordination sphere effects, as well as motions of the cofactors are identified as drivers of the enantiomeric profiles.Finally, we report computer-aided designs of ArMs to guide experiments toward chemical and mutational changes that improve their activity and/or enantioselective profiles and expand toward future directions.
Collapse
Affiliation(s)
- Lur Alonso-Cotchico
- Departament de Quı́mica, Universitat Autònoma de Barcelona, Edifici C.n., 08193 Cerdanyola del Vallès, Barcelona Spain
| | - Jaime Rodrı́guez-Guerra
- Departament de Quı́mica, Universitat Autònoma de Barcelona, Edifici C.n., 08193 Cerdanyola del Vallès, Barcelona Spain
| | - Agustí Lledós
- Departament de Quı́mica, Universitat Autònoma de Barcelona, Edifici C.n., 08193 Cerdanyola del Vallès, Barcelona Spain
| | - Jean-Didier Maréchal
- Departament de Quı́mica, Universitat Autònoma de Barcelona, Edifici C.n., 08193 Cerdanyola del Vallès, Barcelona Spain
| |
Collapse
|
10
|
Kaiser F, Labudde D. Unsupervised Discovery of Geometrically Common Structural Motifs and Long-Range Contacts in Protein 3D Structures. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2019; 16:671-680. [PMID: 29990265 DOI: 10.1109/tcbb.2017.2786250] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The essential role of small evolutionarily conserved structural units in proteins has been extensively researched and validated. A popular example are serine proteases, where the peptide cleavage reaction is realized by a configuration of only three residues. Brought to spatial proximity during the protein folding process, such structural motifs are often long-range contacts and usually hard to detect at sequence level. Due to the constantly increasing resource of protein 3D structure data, the computational identification of structural motifs can contribute significantly to the understanding of protein fold and function. Thus, we propose a method to discover structural motifs of high geometrical similarity and desired sequence separation in protein 3D structure data. By utilizing methods originated from data mining, no a priori knowledge is required. The applicability of the method is demonstrated by the identification of the catalytic unit of serine proteases and the ion-coordination center of cupredoxins. Furthermore, large-scale analysis of the entire Protein Data Bank points towards the presence of ubiquitous structural motifs, independent of any specific fold or function. We envision that our method is suitable to uncover functional mechanisms and to derive fingerprint libraries of structural motifs, which could be used to assess protein family association.
Collapse
|
11
|
Berenger F, Simoncini D, Voet A, Shrestha R, Zhang KYJ. Fragger: a protein fragment picker for structural queries. F1000Res 2017; 6:1722. [PMID: 29399321 PMCID: PMC5773926 DOI: 10.12688/f1000research.12486.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/05/2018] [Indexed: 12/02/2022] Open
Abstract
Protein modeling and design activities often require querying the Protein Data Bank (PDB) with a structural fragment, possibly containing gaps. For some applications, it is preferable to work on a specific subset of the PDB or with unpublished structures. These requirements, along with specific user needs, motivated the creation of a new software to manage and query 3D protein fragments. Fragger is a protein fragment picker that allows protein fragment databases to be created and queried. All fragment lengths are supported and any set of PDB files can be used to create a database. Fragger can efficiently search a fragment database with a query fragment and a distance threshold. Matching fragments are ranked by distance to the query. The query fragment can have structural gaps and the allowed amino acid sequences matching a query can be constrained via a regular expression of one-letter amino acid codes. Fragger also incorporates a tool to compute the backbone RMSD of one versus many fragments in high throughput. Fragger should be useful for protein design, loop grafting and related structural bioinformatics tasks.
Collapse
Affiliation(s)
- Francois Berenger
- System Cohort Division, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
| | | | - Arnout Voet
- Laboratory of Biomolecular Modelling and Design, KU Leuven, Heverlee, Belgium
| | - Rojan Shrestha
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Kam Y J Zhang
- Structural Bioinformatics Team, Division of Structural and Synthetic Biology, Center for Life Science Technologies, RIKEN, Yokohama, Kanagawa, Japan
| |
Collapse
|
12
|
Evolution acting on the same target, but at multiple levels: Proteins as the test case. J Biosci 2017; 42:1-3. [DOI: 10.1007/s12038-017-9672-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
|
13
|
Nastri F, Chino M, Maglio O, Bhagi-Damodaran A, Lu Y, Lombardi A. Design and engineering of artificial oxygen-activating metalloenzymes. Chem Soc Rev 2016; 45:5020-54. [PMID: 27341693 PMCID: PMC5021598 DOI: 10.1039/c5cs00923e] [Citation(s) in RCA: 133] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Many efforts are being made in the design and engineering of metalloenzymes with catalytic properties fulfilling the needs of practical applications. Progress in this field has recently been accelerated by advances in computational, molecular and structural biology. This review article focuses on the recent examples of oxygen-activating metalloenzymes, developed through the strategies of de novo design, miniaturization processes and protein redesign. Considerable progress in these diverse design approaches has produced many metal-containing biocatalysts able to adopt the functions of native enzymes or even novel functions beyond those found in Nature.
Collapse
Affiliation(s)
- Flavia Nastri
- Department of Chemical Sciences, University of Naples “Federico II”, Via Cintia, 80126 Naples, Italy
| | - Marco Chino
- Department of Chemical Sciences, University of Naples “Federico II”, Via Cintia, 80126 Naples, Italy
| | - Ornella Maglio
- Department of Chemical Sciences, University of Naples “Federico II”, Via Cintia, 80126 Naples, Italy
- IBB, CNR, Via Mezzocannone 16, 80134 Naples, Italy
| | - Ambika Bhagi-Damodaran
- Department of Chemistry, University of Illinois at Urbana-Champaign, A322 CLSL, 600 South Mathews Avenue, Urbana, IL 61801
| | - Yi Lu
- Department of Chemistry, University of Illinois at Urbana-Champaign, A322 CLSL, 600 South Mathews Avenue, Urbana, IL 61801
| | - Angela Lombardi
- Department of Chemical Sciences, University of Naples “Federico II”, Via Cintia, 80126 Naples, Italy
| |
Collapse
|
14
|
Ruiz-Gómez G, Hawkins JC, Philipp J, Künze G, Wodtke R, Löser R, Fahmy K, Pisabarro MT. Rational Structure-Based Rescaffolding Approach to De Novo Design of Interleukin 10 (IL-10) Receptor-1 Mimetics. PLoS One 2016; 11:e0154046. [PMID: 27123592 PMCID: PMC4849758 DOI: 10.1371/journal.pone.0154046] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2015] [Accepted: 04/07/2016] [Indexed: 12/25/2022] Open
Abstract
Tackling protein interfaces with small molecules capable of modulating protein-protein interactions remains a challenge in structure-based ligand design. Particularly arduous are cases in which the epitopes involved in molecular recognition have a non-structured and discontinuous nature. Here, the basic strategy of translating continuous binding epitopes into mimetic scaffolds cannot be applied, and other innovative approaches are therefore required. We present a structure-based rational approach involving the use of a regular expression syntax inspired in the well established PROSITE to define minimal descriptors of geometric and functional constraints signifying relevant functionalities for recognition in protein interfaces of non-continuous and unstructured nature. These descriptors feed a search engine that explores the currently available three-dimensional chemical space of the Protein Data Bank (PDB) in order to identify in a straightforward manner regular architectures containing the desired functionalities, which could be used as templates to guide the rational design of small natural-like scaffolds mimicking the targeted recognition site. The application of this rescaffolding strategy to the discovery of natural scaffolds incorporating a selection of functionalities of interleukin-10 receptor-1 (IL-10R1), which are relevant for its interaction with interleukin-10 (IL-10) has resulted in the de novo design of a new class of potent IL-10 peptidomimetic ligands.
Collapse
Affiliation(s)
- Gloria Ruiz-Gómez
- Structural Bioinformatics, BIOTEC TU Dresden, Tatzberg, Dresden, Germany
- * E-mail: (GRG); (MTB)
| | - John C. Hawkins
- Structural Bioinformatics, BIOTEC TU Dresden, Tatzberg, Dresden, Germany
| | - Jenny Philipp
- Helmholtz-Zentrum Dresden Rossendorf, Institute of Resource Ecology, Dresden, Germany
| | - Georg Künze
- Institute of Medical Physics and Biophysics, University of Leipzig, Leipzig, Germany
| | - Robert Wodtke
- Helmholtz-Zentrum Dresden Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Reik Löser
- Helmholtz-Zentrum Dresden Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Karim Fahmy
- Helmholtz-Zentrum Dresden Rossendorf, Institute of Resource Ecology, Dresden, Germany
| | - M. Teresa Pisabarro
- Structural Bioinformatics, BIOTEC TU Dresden, Tatzberg, Dresden, Germany
- * E-mail: (GRG); (MTB)
| |
Collapse
|
15
|
Núñez-Vivanco G, Valdés-Jiménez A, Besoaín F, Reyes-Parada M. Geomfinder: a multi-feature identifier of similar three-dimensional protein patterns: a ligand-independent approach. J Cheminform 2016; 8:19. [PMID: 27092185 PMCID: PMC4834829 DOI: 10.1186/s13321-016-0131-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 04/04/2016] [Indexed: 11/15/2022] Open
Abstract
Background Since the structure of proteins is more conserved than the sequence, the identification of conserved three-dimensional (3D) patterns among a set of proteins, can be important for protein function prediction, protein clustering, drug discovery and the establishment of evolutionary relationships. Thus, several computational applications to identify, describe and compare 3D patterns (or motifs) have been developed. Often, these tools consider a 3D pattern as that described by the residues surrounding co-crystallized/docked ligands available from X-ray crystal structures or homology models. Nevertheless, many of the protein structures stored in public databases do not provide information about the location and characteristics of ligand binding sites and/or other important 3D patterns such as allosteric sites, enzyme-cofactor interaction motifs, etc. This makes necessary the development of new ligand-independent methods to search and compare 3D patterns in all available protein structures. Results Here we introduce Geomfinder, an intuitive, flexible, alignment-free and ligand-independent web server for detailed estimation of similarities between all pairs of 3D patterns detected in any two given protein structures. We used around 1100 protein structures to form pairs of proteins which were assessed with Geomfinder. In these analyses each protein was considered in only one pair (e.g. in a subset of 100 different proteins, 50 pairs of proteins can be defined). Thus: (a) Geomfinder detected identical pairs of 3D patterns in a series of monoamine oxidase-B structures, which corresponded to the effectively similar ligand binding sites at these proteins; (b) we identified structural similarities among pairs of protein structures which are targets of compounds such as acarbose, benzamidine, adenosine triphosphate and pyridoxal phosphate; these similar 3D patterns are not detected using sequence-based methods; (c) the detailed evaluation of three specific cases showed the versatility of Geomfinder, which was able to discriminate between similar and different 3D patterns related to binding sites of common substrates in a range of diverse proteins. Conclusions Geomfinder allows detecting similar 3D patterns between any two pair of protein structures, regardless of the divergency among their amino acids sequences. Although the software is not intended for simultaneous multiple comparisons in a large number of proteins, it can be particularly useful in cases such as the structure-based design of multitarget drugs, where a detailed analysis of 3D patterns similarities between a few selected protein targets is essential. Electronic supplementary material The online version of this article (doi:10.1186/s13321-016-0131-9) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Gabriel Núñez-Vivanco
- Escuela de Ingeniería Civil en Bioinformática, Universidad de Talca, Avenida Lircay s/n, Talca, Chile ; Centro de Bioinformática y Simulación Molecular, Universidad de Talca, 2 Norte 685, Talca, Chile
| | - Alejandro Valdés-Jiménez
- Escuela de Ingeniería Civil en Bioinformática, Universidad de Talca, Avenida Lircay s/n, Talca, Chile
| | - Felipe Besoaín
- Escuela de Ingeniería Civil en Bioinformática, Universidad de Talca, Avenida Lircay s/n, Talca, Chile ; Estudis d'Informática, Multimedia i Telecomunicacio, Universitat Oberta de Catalunya, Rambla del Poblenou 15, Barcelona, Spain ; Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya, Av. Carl Friedrich Gauss, 5, Castelldefels, Barcelona, Spain
| | - Miguel Reyes-Parada
- School of Medicine, Faculty of Medical Sciences, Universidad de Santiago de Chile, Avenida Libertador Bernardo O'Higgins 3363, Santiago, Chile ; Facultad de Ciencias de la Salud, Universidad Autonóma de Chile, 5 Poniente 1670, Talca, Chile
| |
Collapse
|
16
|
Guyon F, Martz F, Vavrusa M, Bécot J, Rey J, Tufféry P. BCSearch: fast structural fragment mining over large collections of protein structures. Nucleic Acids Res 2015; 43:W378-82. [PMID: 25977292 PMCID: PMC4489267 DOI: 10.1093/nar/gkv492] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2015] [Accepted: 05/02/2015] [Indexed: 01/23/2023] Open
Abstract
Resources to mine the large amount of protein structures available today are necessary to better understand how amino acid variations are compatible with conformation preservation, to assist protein design, engineering and, further, the development of biologic therapeutic compounds. BCSearch is a versatile service to efficiently mine large collections of protein structures. It relies on a new approach based on a Binet-Cauchy kernel that is more discriminative than the widely used root mean square deviation criterion. It has statistics independent of size even for short fragments, and is fast. The systematic mining of large collections of structures such as the complete SCOPe protein structural classification or comprehensive subsets of the Protein Data Bank can be performed in few minutes. Based on this new score, we propose four innovative applications: BCFragSearch and BCMirrorSearch, respectively, search for fragments similar and anti-similar to a query and return information on the diversity of the sequences of the hits. BCLoopSearch identifies candidate fragments of fixed size matching the flanks of a gaped structure. BCSpecificitySearch analyzes a complete protein structure and returns information about sites having few similar fragments. BCSearch is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/BCSearch.
Collapse
Affiliation(s)
- Frédéric Guyon
- Molécules Thérapeutiques in Silico, INSERM UMR-S 973, Université Paris Diderot, Sorbone Paris Cité, 75205 Paris Cedex 13, France
| | - François Martz
- Molécules Thérapeutiques in Silico, INSERM UMR-S 973, Université Paris Diderot, Sorbone Paris Cité, 75205 Paris Cedex 13, France
| | - Marek Vavrusa
- Molécules Thérapeutiques in Silico, INSERM UMR-S 973, Université Paris Diderot, Sorbone Paris Cité, 75205 Paris Cedex 13, France
| | - Jérôme Bécot
- Molécules Thérapeutiques in Silico, INSERM UMR-S 973, Université Paris Diderot, Sorbone Paris Cité, 75205 Paris Cedex 13, France
| | - Julien Rey
- Molécules Thérapeutiques in Silico, INSERM UMR-S 973, Université Paris Diderot, Sorbone Paris Cité, 75205 Paris Cedex 13, France
| | - Pierre Tufféry
- Molécules Thérapeutiques in Silico, INSERM UMR-S 973, Université Paris Diderot, Sorbone Paris Cité, 75205 Paris Cedex 13, France
| |
Collapse
|
17
|
Fujieda N, Schätti J, Stuttfeld E, Ohkubo K, Maier T, Fukuzumi S, Ward TR. Enzyme repurposing of a hydrolase as an emergent peroxidase upon metal binding. Chem Sci 2015; 6:4060-4065. [PMID: 29218172 PMCID: PMC5707476 DOI: 10.1039/c5sc01065a] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2015] [Accepted: 05/07/2015] [Indexed: 01/09/2023] Open
Abstract
Adding a metal cofactor to a protein bearing a latent metal binding site endows the macromolecule with nascent catalytic activity.
As an alternative to Darwinian evolution relying on catalytic promiscuity, a protein may acquire auxiliary function upon metal binding, thus providing it with a novel catalytic machinery. Here we show that addition of cupric ions to a 6-phosphogluconolactonase 6-PGLac bearing a putative metal binding site leads to the emergence of peroxidase activity (kcat 7.8 × 10–2 s–1, KM 1.1 × 10–5 M). Both X-ray crystallographic and EPR data of the copper-loaded enzyme Cu·6-PGLac reveal a bis-histidine coordination site, located within a shallow binding pocket capable of accommodating the o-dianisidine substrate.
Collapse
Affiliation(s)
- Nobutaka Fujieda
- Department of Chemistry , University of Basel , Spitalstrasse 51 , CH-4056 Basel , Switzerland . ;
| | - Jonas Schätti
- Department of Chemistry , University of Basel , Spitalstrasse 51 , CH-4056 Basel , Switzerland . ;
| | - Edward Stuttfeld
- Biozentrum , University of Basel , Klingelbergstr. 50/70 , CH-4056 Basel , Switzerland
| | - Kei Ohkubo
- Department of Material and Life Science , Graduate School of Engineering , Osaka University , ALCA and SENTAN , Japan Science and Technology Agency (JST) , 2-1 Yamada-oka , Suita , Osaka 565-0871 , Japan.,Department of Bioinspired Science , Ewha Womans University , Seoul 120-750 , Korea
| | - Timm Maier
- Biozentrum , University of Basel , Klingelbergstr. 50/70 , CH-4056 Basel , Switzerland
| | - Shunichi Fukuzumi
- Department of Material and Life Science , Graduate School of Engineering , Osaka University , ALCA and SENTAN , Japan Science and Technology Agency (JST) , 2-1 Yamada-oka , Suita , Osaka 565-0871 , Japan.,Department of Bioinspired Science , Ewha Womans University , Seoul 120-750 , Korea.,Faculty of Science and Technology , Meijo University and ALCA and SENTAN , Japan Science and Technology Agency (JST) , Tempaku , Nagoya , Aichi 468-8502 , Japan
| | - Thomas R Ward
- Department of Chemistry , University of Basel , Spitalstrasse 51 , CH-4056 Basel , Switzerland . ;
| |
Collapse
|
18
|
Kaiser F, Eisold A, Labudde D. A Novel Algorithm for Enhanced Structural Motif Matching in Proteins. J Comput Biol 2015; 22:698-713. [PMID: 25695840 DOI: 10.1089/cmb.2014.0263] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
As widely discussed in literature, spatial patterns of amino acids, so-called structural motifs, play an important role in protein function. The functionally responsible part of proteins often lies in an evolutionarily highly conserved spatial arrangement of only a few amino acids, which are held in place tightly by the rest of the structure. Those recurring amino acid arrangements can be seen as patterns in the three-dimensional space and are known as structural motifs. In general, these motifs can mediate various functional interactions, such as DNA/RNA targeting and binding, ligand interactions, substrate catalysis, and stabilization of the protein structure. Hence, characterizing and identifying such conserved structural motifs can contribute to the understanding of structure-function relationships. Therefore, and because of the rapidly increasing number of solved protein structures, it is highly desirable to identify, understand, and moreover to search for structurally scattered amino acid motifs. This work aims at the development and the implementation of a novel and robust matching algorithm to detect structural motifs in large sets of target structures. The proposed methods were combined and implemented to a feature-rich and easy-to-use command line software tool written in Java.
Collapse
Affiliation(s)
- Florian Kaiser
- Department of Bioinformatics, University of Applied Sciences Mittweida , Mittweida, Germany
| | - Alexander Eisold
- Department of Bioinformatics, University of Applied Sciences Mittweida , Mittweida, Germany
| | - Dirk Labudde
- Department of Bioinformatics, University of Applied Sciences Mittweida , Mittweida, Germany
| |
Collapse
|
19
|
Chiu YY, Tseng JH, Liu KH, Lin CT, Hsu KC, Yang JM. Homopharma: a new concept for exploring the molecular binding mechanisms and drug repurposing. BMC Genomics 2014; 15 Suppl 9:S8. [PMID: 25521038 PMCID: PMC4290623 DOI: 10.1186/1471-2164-15-s9-s8] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Background Drugs that simultaneously target multiple proteins often improve efficacy, particularly in the treatment of complex diseases such as cancers and central nervous system disorders. Many approaches have been proposed to identify the potential targets of a drug. Recently, we have introduced Space-Related Pharmamotif (SRPmotif) method to recognize the proteins that share similar binding environments. In addition, compounds with similar topology may bind to similar proteins and have similar protein-compound interactions. However, few studies have focused on exploring the relationships between binding environments and protein-compound interactions, which is important for understanding molecular binding mechanisms and helpful to be used in discovering drug repurposing. Results In this study, we propose a new concept of "Homopharma", combining similar binding environments and protein-compound interaction profiles, to explore the molecular binding mechanisms and drug repurposing. A Homopharma consists of a set of proteins which have the conserved binding environment and a set of compounds that share similar structures and functional groups. These proteins and compounds present conserved interactions and similar physicochemical properties. Therefore, these compounds are often able to inhibit the proteins in a Homopharma. Our experimental results show that the proteins and compounds in a Homopharma often have similar protein-compound interactions, comprising conserved specific residues and functional sites. Based on the Homopharma concept, we selected four flavonoid derivatives and 32 human protein kinases for enzymatic profiling. Among these 128 bioassays, the IC50 of 56 and 25 flavonoid-kinase inhibitions are less than 10 μM and 1 μM, respectively. Furthermore, these experimental results suggest that these flavonoids can be used as anticancer compounds, such as oral and colorectal cancer drugs. Conclusions The experimental results show that the Homopharma is useful for identifying key binding environments of proteins and compounds and discovering new inhibitory effects. We believe that the Homopharma concept can have the potential for understanding molecular binding mechanisms and providing new clues for drug development.
Collapse
|
20
|
Joice R, Yasuda K, Shafquat A, Morgan XC, Huttenhower C. Determining microbial products and identifying molecular targets in the human microbiome. Cell Metab 2014; 20:731-741. [PMID: 25440055 PMCID: PMC4254638 DOI: 10.1016/j.cmet.2014.10.003] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Human-associated microbes are the source of many bioactive microbial products (proteins and metabolites) that play key functions both in human host pathways and in microbe-microbe interactions. Culture-independent studies now provide an accelerated means of exploring novel bioactives in the human microbiome; however, intriguingly, a substantial fraction of the microbial metagenome cannot be mapped to annotated genes or isolate genomes and is thus of unknown function. Meta'omic approaches, including metagenomic sequencing, metatranscriptomics, metabolomics, and integration of multiple assay types, represent an opportunity to efficiently explore this large pool of potential therapeutics. In combination with appropriate follow-up validation, high-throughput culture-independent assays can be combined with computational approaches to identify and characterize novel and biologically interesting microbial products. Here we briefly review the state of microbial product identification and characterization and discuss possible next steps to catalog and leverage the large uncharted fraction of the microbial metagenome.
Collapse
Affiliation(s)
- Regina Joice
- Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Koji Yasuda
- Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Afrah Shafquat
- Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Xochitl C Morgan
- Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Curtis Huttenhower
- Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| |
Collapse
|
21
|
Angelucci F, Morea V, Angelaccio S, Saccoccia F, Contestabile R, Ilari A. The crystal structure of archaeal serine hydroxymethyltransferase reveals idiosyncratic features likely required to withstand high temperatures. Proteins 2014; 82:3437-49. [PMID: 25257552 DOI: 10.1002/prot.24697] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2014] [Revised: 09/09/2014] [Accepted: 09/10/2014] [Indexed: 01/19/2023]
Abstract
Serine hydroxymethyltransferases (SHMTs) play an essential role in one-carbon unit metabolism and are used in biomimetic reactions. We determined the crystal structure of free (apo) and pyridoxal-5'-phosphate-bound (holo) SHMT from Methanocaldococcus jannaschii, the first from a hyperthermophile, from the archaea domain of life and that uses H₄MPT as a cofactor, at 2.83 and 3.0 Å resolution, respectively. Idiosyncratic features were observed that are likely to contribute to structure stabilization. At the dimer interface, the C-terminal region folds in a unique fashion with respect to SHMTs from eubacteria and eukarya. At the active site, the conserved tyrosine does not make a cation-π interaction with an arginine like that observed in all other SHMT structures, but establishes an amide-aromatic interaction with Asn257, at a different sequence position. This asparagine residue is conserved and occurs almost exclusively in (hyper)thermophile SHMTs. This led us to formulate the hypothesis that removal of frustrated interactions (such as the Arg-Tyr cation-π interaction occurring in mesophile SHMTs) is an additional strategy of adaptation to high temperature. Both peculiar features may be tested by designing enzyme variants potentially endowed with improved stability for applications in biomimetic processes.
Collapse
Affiliation(s)
- Francesco Angelucci
- Department of Life, Health and Environmental Sciences, University of L'Aquila, P.le Salvatore Tommasi 1, L'Aquila, Italy
| | | | | | | | | | | |
Collapse
|
22
|
Vangone A, Abdel-Azeim S, Caputo I, Sblattero D, Di Niro R, Cavallo L, Oliva R. Structural basis for the recognition in an idiotype-anti-idiotype antibody complex related to celiac disease. PLoS One 2014; 9:e102839. [PMID: 25076134 PMCID: PMC4116137 DOI: 10.1371/journal.pone.0102839] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2014] [Accepted: 06/21/2014] [Indexed: 11/19/2022] Open
Abstract
Anti-idiotype antibodies have potential therapeutic applications in many fields, including autoimmune diseases. Herein we report the isolation and characterization of AIM2, an anti-idiotype antibody elicited in a mouse model upon expression of the celiac disease-specific autoantibody MB2.8 (directed against the main disease autoantigen type 2 transglutaminase, TG2). To characterize the interaction between the two antibodies, a 3D model of the MB2.8-AIM2 complex has been obtained by molecular docking. Analysis and selection of the different obtained docking solutions was based on the conservation within them of the inter-residue contacts. The selected model is very well representative of the different solutions found and its stability is confirmed by molecular dynamics simulations. Furthermore, the binding mode it adopts is very similar to that observed in most of the experimental structures available for idiotype-anti-idiotype antibody complexes. In the obtained model, AIM2 is directed against the MB2.8 CDR region, especially on its variable light chain. This makes the concurrent formation of the MB2.8-AIM2 complex and of the MB2.8-TG2 complex incompatible, thus explaining the experimentally observed inhibitory effect on the MB2.8 binding to TG2.
Collapse
Affiliation(s)
- Anna Vangone
- Department of Chemistry and Biology, University of Salerno, Fisciano, Salerno, Italy
| | - Safwat Abdel-Azeim
- Kaust Catalysis Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Ivana Caputo
- Department of Chemistry and Biology, University of Salerno, Fisciano, Salerno, Italy
- European Laboratory for the Investigation of Food-Induced Diseases (ELFID), University Federico II, Naples, Italy
| | - Daniele Sblattero
- Department of Health Sciences and Interdisciplinary Research Center of Autoimmune Diseases (IRCAD), University of Eastern Piedmont, Novara, Italy
| | - Roberto Di Niro
- Department of Immunology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Luigi Cavallo
- Department of Chemistry and Biology, University of Salerno, Fisciano, Salerno, Italy
- Kaust Catalysis Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Romina Oliva
- Department of Sciences and Technologies, University “Parthenope” of Naples, Naples, Italy
- * E-mail:
| |
Collapse
|
23
|
Hanson B, Westin C, Rosa M, Grier A, Osipovitch M, MacDonald ML, Dodge G, Boli PM, Corwin CW, Kessler H, McKay T, Bernstein HJ, Craig PA. Estimation of protein function using template-based alignment of enzyme active sites. BMC Bioinformatics 2014; 15:87. [PMID: 24669788 PMCID: PMC4229977 DOI: 10.1186/1471-2105-15-87] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2013] [Accepted: 01/24/2014] [Indexed: 11/25/2022] Open
Abstract
Background The accumulation of protein structural data occurs more rapidly than it can be characterized by traditional laboratory means. This has motivated widespread efforts to predict enzyme function computationally. The most useful/accurate strategies employed to date are based on the detection of motifs in novel structures that correspond to a specific function. Functional residues are critical components of predictively useful motifs. We have implemented a novel method, to complement current approaches, which detects motifs solely on the basis of distance restraints between catalytic residues. Results ProMOL is a plugin for the PyMOL molecular graphics environment that can be used to create active site motifs for enzymes. A library of 181 active site motifs has been created with ProMOL, based on definitions published in the Catalytic Site Atlas (CSA). Searches with ProMOL produce better than 50% useful Enzyme Commission (EC) class suggestions for level 1 searches in EC classes 1, 4 and 5, and produce some useful results for other classes. 261 additional motifs automatically translated from Jonathan Barker’s JESS motif set [Bioinformatics 19:1644–1649, 2003] and a set of NMR motifs is under development. Alignments are evaluated by visual superposition, Levenshtein distance and root-mean-square deviation (RMSD) and are reasonably consistent with related search methods. Conclusion The ProMOL plugin for PyMOL provides ready access to template-based local alignments. Recent improvements to ProMOL, including the expanded motif library, RMSD calculations and output selection formatting, have greatly increased the program’s usability and speed, and have improved the way that the results are presented.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | - Paul A Craig
- Rochester Institute of Technology, School of Chemistry & Materials Science, 1 Lomb Memorial Drive, Rochester, NY 14623, USA.
| |
Collapse
|
24
|
Kubrycht J, Sigler K, Souček P, Hudeček J. Structures composing protein domains. Biochimie 2013; 95:1511-24. [DOI: 10.1016/j.biochi.2013.04.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2013] [Accepted: 04/02/2013] [Indexed: 12/21/2022]
|
25
|
Nadzirin N, Willett P, Artymiuk PJ, Firdaus-Raih M. IMAAAGINE: a webserver for searching hypothetical 3D amino acid side chain arrangements in the Protein Data Bank. Nucleic Acids Res 2013; 41:W432-40. [PMID: 23716645 PMCID: PMC3692123 DOI: 10.1093/nar/gkt431] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
We describe a server that allows the interrogation of the Protein Data Bank for hypothetical 3D side chain patterns that are not limited to known patterns from existing 3D structures. A minimal side chain description allows a variety of side chain orientations to exist within the pattern, and generic side chain types such as acid, base and hydroxyl-containing can be additionally deployed in the search query. Moreover, only a subset of distances between the side chains need be specified. We illustrate these capabilities in case studies involving arginine stacks, serine-acid group arrangements and multiple catalytic triad-like configurations. The IMAAAGINE server can be accessed at http://mfrlab.org/grafss/imaaagine/.
Collapse
Affiliation(s)
- Nurul Nadzirin
- School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Malaysia
| | | | | | | |
Collapse
|
26
|
De D, Datta Chakraborty P, Mitra J, Sharma K, Mandal S, Das A, Chakrabarti S, Bhattacharyya D. Ubiquitin-like protein from human placental extract exhibits collagenase activity. PLoS One 2013; 8:e59585. [PMID: 23555718 PMCID: PMC3608664 DOI: 10.1371/journal.pone.0059585] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2012] [Accepted: 02/15/2013] [Indexed: 11/18/2022] Open
Abstract
An aqueous extract of human placenta exhibits strong gelatinase/collagenase activity in zymography. 2-D gel electrophoresis of the extract with gelatin zymography in the second dimension displayed a single spot, identified as ubiquitin-like component upon MALDI/TOF MS/MS analysis. Immunoblot indicated presence of ubiquitin and absence of collagenase in the extract. Collagenase activity of the ubiquitin-like component was confirmed from the change in solubility of collagen in aqueous buffer, degradation of collagen by size-exclusion HPLC and atomic force microscopy. Quantification with DQ-gelatin showed that the extract contains 0.04 U/ml of collagenase activity that was inhibited up to 95% by ubiquitin antibody. Ubiquitin from bovine erythrocytes demonstrated mild collagenase activity. Bioinformatics studies suggest that placental ubiquitin and collagenase follow structurally divergent evolution. This thermostable intrinsic collagenase activity of placental extract might have wide physiological relevance in degrading and remodeling collagen as it is used as a drug for wound healing and pelvic inflammatory diseases.
Collapse
Affiliation(s)
- Debashree De
- Division of Structural Biology and Bioinformatics, Council of Scientific and Industrial Research - Indian Institute of Chemical Biology, Calcutta, West Bengal, India
| | | | - Jyotirmoy Mitra
- Division of Structural Biology and Bioinformatics, Council of Scientific and Industrial Research - Indian Institute of Chemical Biology, Calcutta, West Bengal, India
| | - Kanika Sharma
- Division of Structural Biology and Bioinformatics, Council of Scientific and Industrial Research - Indian Institute of Chemical Biology, Calcutta, West Bengal, India
| | - Somnath Mandal
- Division of Structural Biology and Bioinformatics, Council of Scientific and Industrial Research - Indian Institute of Chemical Biology, Calcutta, West Bengal, India
| | - Aneesha Das
- Division of Structural Biology and Bioinformatics, Council of Scientific and Industrial Research - Indian Institute of Chemical Biology, Calcutta, West Bengal, India
| | - Saikat Chakrabarti
- Division of Structural Biology and Bioinformatics, Council of Scientific and Industrial Research - Indian Institute of Chemical Biology, Calcutta, West Bengal, India
| | - Debasish Bhattacharyya
- Division of Structural Biology and Bioinformatics, Council of Scientific and Industrial Research - Indian Institute of Chemical Biology, Calcutta, West Bengal, India
- * E-mail:
| |
Collapse
|
27
|
Chiu YY, Lin CY, Lin CT, Hsu KC, Chang LZ, Yang JM. Space-related pharma-motifs for fast search of protein binding motifs and polypharmacological targets. BMC Genomics 2012; 13 Suppl 7:S21. [PMID: 23281852 PMCID: PMC3521469 DOI: 10.1186/1471-2164-13-s7-s21] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Background To discover a compound inhibiting multiple proteins (i.e. polypharmacological targets) is a new paradigm for the complex diseases (e.g. cancers and diabetes). In general, the polypharmacological proteins often share similar local binding environments and motifs. As the exponential growth of the number of protein structures, to find the similar structural binding motifs (pharma-motifs) is an emergency task for drug discovery (e.g. side effects and new uses for old drugs) and protein functions. Results We have developed a Space-Related Pharmamotifs (called SRPmotif) method to recognize the binding motifs by searching against protein structure database. SRPmotif is able to recognize conserved binding environments containing spatially discontinuous pharma-motifs which are often short conserved peptides with specific physico-chemical properties for protein functions. Among 356 pharma-motifs, 56.5% interacting residues are highly conserved. Experimental results indicate that 81.1% and 92.7% polypharmacological targets of each protein-ligand complex are annotated with same biological process (BP) and molecular function (MF) terms, respectively, based on Gene Ontology (GO). Our experimental results show that the identified pharma-motifs often consist of key residues in functional (active) sites and play the key roles for protein functions. The SRPmotif is available at http://gemdock.life.nctu.edu.tw/SRP/. Conclusions SRPmotif is able to identify similar pharma-interfaces and pharma-motifs sharing similar binding environments for polypharmacological targets by rapidly searching against the protein structure database. Pharma-motifs describe the conservations of binding environments for drug discovery and protein functions. Additionally, these pharma-motifs provide the clues for discovering new sequence-based motifs to predict protein functions from protein sequence databases. We believe that SRPmotif is useful for elucidating protein functions and drug discovery.
Collapse
Affiliation(s)
- Yi-Yuan Chiu
- Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 30050, Taiwan
| | | | | | | | | | | |
Collapse
|
28
|
Tlatli R, Nozach H, Collet G, Beau F, Vera L, Stura E, Dive V, Cuniasse P. Grafting of functional motifs onto protein scaffolds identified by PDB screening--an efficient route to design optimizable protein binders. FEBS J 2012; 280:139-59. [PMID: 23121732 DOI: 10.1111/febs.12056] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2012] [Revised: 10/19/2012] [Accepted: 10/30/2012] [Indexed: 12/23/2022]
Abstract
Artificial miniproteins that are able to target catalytic sites of matrix metalloproteinases (MMPs) were designed using a functional motif-grafting approach. The motif corresponded to the four N-terminal residues of TIMP-2, a broad-spectrum protein inhibitor of MMPs. Scaffolds that are able to reproduce the functional topology of this motif were obtained by exhaustive screening of the Protein Data Bank (PDB) using STAMPS software (search for three-dimensional atom motifs in protein structures). Ten artificial protein binders were produced. The designed proteins bind catalytic sites of MMPs with affinities ranging from 450 nm to 450 μm prior to optimization. The crystal structure of one artificial binder in complex with the catalytic domain of MMP-12 showed that the inter-molecular interactions established by the functional motif in the artificial binder corresponded to those found in the MMP-14-TIMP-2 complex, albeit with some differences in geometry. Molecular dynamics simulations of the ten binders in complex with MMP-14 suggested that these scaffolds may allow partial reproduction of native inter-molecular interactions, but differences in geometry and stability may contribute to the lower affinity of the artificial protein binders compared to the natural protein binder. Nevertheless, these results show that the in silico design method used provides sets of protein binders that target a specific binding site with a good rate of success. This approach may constitute the first step of an efficient hybrid computational/experimental approach to protein binder design.
Collapse
Affiliation(s)
- Rym Tlatli
- Service d'Ingénierie Moléculaire des Protéines, Institut de Biologie et Technologies de Saclay (IBITEC-S), Commissariat à l'Energie Atomique, Gif-sur-Yvette, France
| | | | | | | | | | | | | | | |
Collapse
|
29
|
Nadzirin N, Firdaus-Raih M. Proteins of unknown function in the Protein Data Bank (PDB): an inventory of true uncharacterized proteins and computational tools for their analysis. Int J Mol Sci 2012. [PMID: 23202924 PMCID: PMC3497298 DOI: 10.3390/ijms131012761] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Proteins of uncharacterized functions form a large part of many of the currently available biological databases and this situation exists even in the Protein Data Bank (PDB). Our analysis of recent PDB data revealed that only 42.53% of PDB entries (1084 coordinate files) that were categorized under “unknown function” are true examples of proteins of unknown function at this point in time. The remainder 1465 entries also annotated as such appear to be able to have their annotations re-assessed, based on the availability of direct functional characterization experiments for the protein itself, or for homologous sequences or structures thus enabling computational function inference.
Collapse
Affiliation(s)
- Nurul Nadzirin
- School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Malaysia.
| | | |
Collapse
|
30
|
Johansson MU, Zoete V, Michielin O, Guex N. Defining and searching for structural motifs using DeepView/Swiss-PdbViewer. BMC Bioinformatics 2012; 13:173. [PMID: 22823337 PMCID: PMC3436773 DOI: 10.1186/1471-2105-13-173] [Citation(s) in RCA: 217] [Impact Index Per Article: 18.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2011] [Accepted: 07/06/2012] [Indexed: 11/10/2022] Open
Abstract
Background Today, recognition and classification of sequence motifs and protein folds is a mature field, thanks to the availability of numerous comprehensive and easy to use software packages and web-based services. Recognition of structural motifs, by comparison, is less well developed and much less frequently used, possibly due to a lack of easily accessible and easy to use software. Results In this paper, we describe an extension of DeepView/Swiss-PdbViewer through which structural motifs may be defined and searched for in large protein structure databases, and we show that common structural motifs involved in stabilizing protein folds are present in evolutionarily and structurally unrelated proteins, also in deeply buried locations which are not obviously related to protein function. Conclusions The possibility to define custom motifs and search for their occurrence in other proteins permits the identification of recurrent arrangements of residues that could have structural implications. The possibility to do so without having to maintain a complex software/hardware installation on site brings this technology to experts and non-experts alike.
Collapse
Affiliation(s)
- Maria U Johansson
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | | | | |
Collapse
|
31
|
Nadzirin N, Gardiner EJ, Willett P, Artymiuk PJ, Firdaus-Raih M. SPRITE and ASSAM: web servers for side chain 3D-motif searching in protein structures. Nucleic Acids Res 2012; 40:W380-6. [PMID: 22573174 PMCID: PMC3394286 DOI: 10.1093/nar/gks401] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
Similarities in the 3D patterns of amino acid side chains can provide insights into their function despite the absence of any detectable sequence or fold similarities. Search for protein sites (SPRITE) and amino acid pattern search for substructures and motifs (ASSAM) are graph theoretical programs that can search for 3D amino side chain matches in protein structures, by representing the amino acid side chains as pseudo-atoms. The geometric relationship of the pseudo-atoms to each other as a pattern can be represented as a labeled graph where the pseudo-atoms are the graph's nodes while the edges are the inter-pseudo-atomic distances. Both programs require the input file to be in the PDB format. The objective of using SPRITE is to identify matches of side chains in a query structure to patterns with characterized function. In contrast, a 3D pattern of interest can be searched for existing occurrences in available PDB structures using ASSAM. Both programs are freely accessible without any login requirement. SPRITE is available at http://mfrlab.org/grafss/sprite/ while ASSAM can be accessed at http://mfrlab.org/grafss/assam/.
Collapse
Affiliation(s)
- Nurul Nadzirin
- School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Malaysia
| | | | | | | | | |
Collapse
|
32
|
Amrein B, Schmid M, Collet G, Cuniasse P, Gilardoni F, Seebeck FP, Ward TR. Identification of two-histidines one-carboxylate binding motifs in proteins amenable to facial coordination to metals. Metallomics 2012; 4:379-88. [DOI: 10.1039/c2mt20010d] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
|
33
|
Chakraborty S, Minda R, Salaye L, Bhattacharjee SK, Rao BJ. Active site detection by spatial conformity and electrostatic analysis--unravelling a proteolytic function in shrimp alkaline phosphatase. PLoS One 2011; 6:e28470. [PMID: 22174814 PMCID: PMC3234256 DOI: 10.1371/journal.pone.0028470] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2011] [Accepted: 11/08/2011] [Indexed: 11/30/2022] Open
Abstract
Computational methods are increasingly gaining importance as an aid in identifying active sites. Mostly these methods tend to have structural information that supplement sequence conservation based analyses. Development of tools that compute electrostatic potentials has further improved our ability to better characterize the active site residues in proteins. We have described a computational methodology for detecting active sites based on structural and electrostatic conformity - CataLytic Active Site Prediction (CLASP). In our pipelined model, physical 3D signature of any particular enzymatic function as defined by its active sites is used to obtain spatially congruent matches. While previous work has revealed that catalytic residues have large pKa deviations from standard values, we show that for a given enzymatic activity, electrostatic potential difference (PD) between analogous residue pairs in an active site taken from different proteins of the same family are similar. False positives in spatially congruent matches are further pruned by PD analysis where cognate pairs with large deviations are rejected. We first present the results of active site prediction by CLASP for two enzymatic activities - β-lactamases and serine proteases, two of the most extensively investigated enzymes. The results of CLASP analysis on motifs extracted from Catalytic Site Atlas (CSA) are also presented in order to demonstrate its ability to accurately classify any protein, putative or otherwise, with known structure. The source code and database is made available at www.sanchak.com/clasp/. Subsequently, we probed alkaline phosphatases (AP), one of the well known promiscuous enzymes, for additional activities. Such a search has led us to predict a hitherto unknown function of shrimp alkaline phosphatase (SAP), where the protein acts as a protease. Finally, we present experimental evidence of the prediction by CLASP by showing that SAP indeed has protease activity in vitro.
Collapse
Affiliation(s)
- Sandeep Chakraborty
- Department of Biological Sciences, Tata Institute of Fundamental Research, Mumbai, India
| | | | | | | | | |
Collapse
|
34
|
Wu CY, Chen YC, Lim C. A structural-alphabet-based strategy for finding structural motifs across protein families. Nucleic Acids Res 2010; 38:e150. [PMID: 20525797 PMCID: PMC2919736 DOI: 10.1093/nar/gkq478] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Proteins with insignificant sequence and overall structure similarity may still share locally conserved contiguous structural segments; i.e. structural/3D motifs. Most methods for finding 3D motifs require a known motif to search for other similar structures or functionally/structurally crucial residues. Here, without requiring a query motif or essential residues, a fully automated method for discovering 3D motifs of various sizes across protein families with different folds based on a 16-letter structural alphabet is presented. It was applied to structurally non-redundant proteins bound to DNA, RNA, obligate/non-obligate proteins as well as free DNA-binding proteins (DBPs) and proteins with known structures but unknown function. Its usefulness was illustrated by analyzing the 3D motifs found in DBPs. A non-specific motif was found with a ‘corner’ architecture that confers a stable scaffold and enables diverse interactions, making it suitable for binding not only DNA but also RNA and proteins. Furthermore, DNA-specific motifs present ‘only’ in DBPs were discovered. The motifs found can provide useful guidelines in detecting binding sites and computational protein redesign.
Collapse
Affiliation(s)
- Chih Yuan Wu
- Department of Chemistry, National Tsing Hua University, Hsinchu, Taiwan
| | | | | |
Collapse
|
35
|
Konc J, Janezic D. ProBiS algorithm for detection of structurally similar protein binding sites by local structural alignment. ACTA ACUST UNITED AC 2010; 26:1160-8. [PMID: 20305268 PMCID: PMC2859123 DOI: 10.1093/bioinformatics/btq100] [Citation(s) in RCA: 184] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Motivation: Exploitation of locally similar 3D patterns of physicochemical properties on the surface of a protein for detection of binding sites that may lack sequence and global structural conservation. Results: An algorithm, ProBiS is described that detects structurally similar sites on protein surfaces by local surface structure alignment. It compares the query protein to members of a database of protein 3D structures and detects with sub-residue precision, structurally similar sites as patterns of physicochemical properties on the protein surface. Using an efficient maximum clique algorithm, the program identifies proteins that share local structural similarities with the query protein and generates structure-based alignments of these proteins with the query. Structural similarity scores are calculated for the query protein's surface residues, and are expressed as different colors on the query protein surface. The algorithm has been used successfully for the detection of protein–protein, protein–small ligand and protein–DNA binding sites. Availability: The software is available, as a web tool, free of charge for academic users at http://probis.cmm.ki.si Contact:dusa@cmm.ki.si Supplementary information:Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Janez Konc
- National Institute of Chemistry, Ljubljana, Slovenia
| | | |
Collapse
|