1
|
González-González A, Yañez O, Ballesteros GI, Palma-Millanao R, Figueroa CC, Niemeyer HM, Ramírez CC. A mutation increases the specificity to plant compounds in an insect chemosensory protein. J Mol Graph Model 2022; 114:108191. [DOI: 10.1016/j.jmgm.2022.108191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 04/07/2022] [Accepted: 04/08/2022] [Indexed: 11/16/2022]
|
2
|
Sequeiros-Borja CE, Surpeta B, Brezovsky J. Recent advances in user-friendly computational tools to engineer protein function. Brief Bioinform 2021; 22:bbaa150. [PMID: 32743637 PMCID: PMC8138880 DOI: 10.1093/bib/bbaa150] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 06/03/2020] [Accepted: 06/16/2020] [Indexed: 12/14/2022] Open
Abstract
Progress in technology and algorithms throughout the past decade has transformed the field of protein design and engineering. Computational approaches have become well-engrained in the processes of tailoring proteins for various biotechnological applications. Many tools and methods are developed and upgraded each year to satisfy the increasing demands and challenges of protein engineering. To help protein engineers and bioinformaticians navigate this emerging wave of dedicated software, we have critically evaluated recent additions to the toolbox regarding their application for semi-rational and rational protein engineering. These newly developed tools identify and prioritize hotspots and analyze the effects of mutations for a variety of properties, comprising ligand binding, protein-protein and protein-nucleic acid interactions, and electrostatic potential. We also discuss notable progress to target elusive protein dynamics and associated properties like ligand-transport processes and allosteric communication. Finally, we discuss several challenges these tools face and provide our perspectives on the further development of readily applicable methods to guide protein engineering efforts.
Collapse
Affiliation(s)
- Carlos Eduardo Sequeiros-Borja
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University and the International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Bartłomiej Surpeta
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University and the International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland
| | - Jan Brezovsky
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University and the International Institute of Molecular and Cell Biology in Warsaw
| |
Collapse
|
3
|
Supo-Escalante RR, Médico A, Gushiken E, Olivos-Ramírez GE, Quispe Y, Torres F, Zamudio M, Antiparra R, Amzel LM, Gilman RH, Sheen P, Zimic M. Prediction of Mycobacterium tuberculosis pyrazinamidase function based on structural stability, physicochemical and geometrical descriptors. PLoS One 2020; 15:e0235643. [PMID: 32735615 PMCID: PMC7394417 DOI: 10.1371/journal.pone.0235643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 06/19/2020] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Pyrazinamide is an important drug against the latent stage of tuberculosis and is used in both first- and second-line treatment regimens. Pyrazinamide-susceptibility test usually takes a week to have a diagnosis to guide initial therapy, implying a delay in receiving appropriate therapy. The continued increase in multi-drug resistant tuberculosis and the prevalence of pyrazinamide resistance in several countries makes the development of assays for prompt identification of resistance necessary. The main cause of pyrazinamide resistance is the impairment of pyrazinamidase function attributed to mutations in the promoter and/or pncA coding gene. However, not all pncA mutations necessarily affect the pyrazinamidase function. OBJECTIVE To develop a methodology to predict pyrazinamidase function from detected mutations in the pncA gene. METHODS We measured the catalytic constant (kcat), KM, enzymatic efficiency, and enzymatic activity of 35 recombinant mutated pyrazinamidase and the wild type (Protein Data Bank ID = 3pl1). From all the 3D modeled structures, we extracted several predictors based on three categories: structural stability (estimated by normal mode analysis and molecular dynamics), physicochemical, and geometrical characteristics. We used a stepwise Akaike's information criterion forward multiple log-linear regression to model each kinetic parameter with each category of predictors. We also developed weighted models combining the three categories of predictive models for each kinetic parameter. We tested the robustness of the predictive ability of each model by 6-fold cross-validation against random models. RESULTS The stability, physicochemical, and geometrical descriptors explained most of the variability (R2) of the kinetic parameters. Our models are best suited to predict kcat, efficiency, and activity based on the root-mean-square error of prediction of the 6-fold cross-validation. CONCLUSIONS This study shows a quick approach to predict the pyrazinamidase function only from the pncA sequence when point mutations are present. This can be an important tool to detect pyrazinamide resistance.
Collapse
Affiliation(s)
- Rydberg Roman Supo-Escalante
- Laboratorio de Bioinformática, Biología Molecular y Desarrollos Tecnológicos, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Aldhair Médico
- Laboratorio de Bioinformática, Biología Molecular y Desarrollos Tecnológicos, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Eduardo Gushiken
- Laboratorio de Bioinformática, Biología Molecular y Desarrollos Tecnológicos, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Gustavo E. Olivos-Ramírez
- Laboratorio de Bioinformática, Biología Molecular y Desarrollos Tecnológicos, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Yaneth Quispe
- Laboratorio de Bioinformática, Biología Molecular y Desarrollos Tecnológicos, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Fiorella Torres
- Laboratorio de Bioinformática, Biología Molecular y Desarrollos Tecnológicos, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Melissa Zamudio
- Laboratorio de Bioinformática, Biología Molecular y Desarrollos Tecnológicos, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Ricardo Antiparra
- Laboratorio de Bioinformática, Biología Molecular y Desarrollos Tecnológicos, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - L. Mario Amzel
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University, Baltimore, MD, United States of America
| | - Robert H. Gilman
- International Health Department, Johns Hopkins School of Public Health, Baltimore, MD, United States of America
| | - Patricia Sheen
- Laboratorio de Bioinformática, Biología Molecular y Desarrollos Tecnológicos, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Mirko Zimic
- Laboratorio de Bioinformática, Biología Molecular y Desarrollos Tecnológicos, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| |
Collapse
|
4
|
Goswami AM. Computational analyses prioritize and reveal the deleterious nsSNPs in human angiotensinogen gene. Comput Biol Chem 2020; 84:107199. [PMID: 31931433 DOI: 10.1016/j.compbiolchem.2019.107199] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 12/26/2019] [Accepted: 12/30/2019] [Indexed: 12/27/2022]
Abstract
Angiotensinogen (AGT) is a key component of renin-angiotensin-aldosterone system (RAAS), which plays central role in blood pressure homeostasis. Association of AGT polymorphisms have been investigated in different ethnic populations in variety of cardiovascular and non-cardiovascular conditions. In this study, 354 non-synonymous SNPs (nsSNPs) of AGT were evaluated to predict damaging and structurally important variants. Majority of the deleterious nsSNPs occurred in the evolutionary conserved regions. Several of these nsSNPs were found to affect post-translational modifications like methylation, glycosylation, phosphorylation, ubiquitination etc. Structural evaluations predicted 19 variants as destabilizing and some of them were also predicted to destabilize the renin-AGT interaction. Therefore, the present computational investigation predicted pathogenic and functionally important variants of human AGT gene. The study has also shown that AGT deregulation is associated with survival outcome in patients with gastric and breast cancer, using microarray gene expression profile. Furthermore, the computationally screened nsSNPs can be analyzed in population based genotyping studies and may help futuristic drug development in the area of AGT pharmacogenomics.
Collapse
Affiliation(s)
- Achintya Mohan Goswami
- Department of Physiology, Krishnagar Govt. College, Krishnagar, Nadia, West Bengal, 741101, India.
| |
Collapse
|
5
|
Ciezarek AG, Osborne OG, Shipley ON, Brooks EJ, Tracey SR, McAllister JD, Gardner LD, Sternberg MJE, Block B, Savolainen V. Phylotranscriptomic Insights into the Diversification of Endothermic Thunnus Tunas. Mol Biol Evol 2019; 36:84-96. [PMID: 30364966 PMCID: PMC6340463 DOI: 10.1093/molbev/msy198] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Birds, mammals, and certain fishes, including tunas, opahs and lamnid sharks, are endothermic, conserving internally generated, metabolic heat to maintain body or tissue temperatures above that of the environment. Bluefin tunas are commercially important fishes worldwide, and some populations are threatened. They are renowned for their endothermy, maintaining elevated temperatures of the oxidative locomotor muscle, viscera, brain and eyes, and occupying cold, productive high-latitude waters. Less cold-tolerant tunas, such as yellowfin tuna, by contrast, remain in warm-temperate to tropical waters year-round, reproducing more rapidly than most temperate bluefin tuna populations, providing resiliency in the face of large-scale industrial fisheries. Despite the importance of these traits to not only fisheries but also habitat utilization and responses to climate change, little is known of the genetic processes underlying the diversification of tunas. In collecting and analyzing sequence data across 29,556 genes, we found that parallel selection on standing genetic variation is associated with the evolution of endothermy in bluefin tunas. This includes two shared substitutions in genes encoding glycerol-3 phosphate dehydrogenase, an enzyme that contributes to thermogenesis in bumblebees and mammals, as well as four genes involved in the Krebs cycle, oxidative phosphorylation, β-oxidation, and superoxide removal. Using phylogenetic techniques, we further illustrate that the eight Thunnus species are genetically distinct, but found evidence of mitochondrial genome introgression across two species. Phylogeny-based metrics highlight conservation needs for some of these species.
Collapse
Affiliation(s)
- Adam G Ciezarek
- Department of Life Sciences, Silwood Park Campus, Imperial College London, Ascot, United Kingdom
| | - Owen G Osborne
- Department of Life Sciences, Silwood Park Campus, Imperial College London, Ascot, United Kingdom
| | - Oliver N Shipley
- Shark Research and Conservation Program, The Cape Eleuthera Institute, Rock Sound, Eleuthera, The Bahamas
- School of Marine and Atmospheric Science, Stony Brook University, Stony Brook, NY
| | - Edward J Brooks
- Shark Research and Conservation Program, The Cape Eleuthera Institute, Rock Sound, Eleuthera, The Bahamas
| | - Sean R Tracey
- Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, TAS, Australia
| | - Jaime D McAllister
- Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, TAS, Australia
| | - Luke D Gardner
- Department of Biology, Hopkins Marine Station, Stanford University, Pacific Grove, CA
| | - Michael J E Sternberg
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, Kensington, London, United Kingdom
| | - Barbara Block
- Department of Biology, Hopkins Marine Station, Stanford University, Pacific Grove, CA
| | - Vincent Savolainen
- Department of Life Sciences, Silwood Park Campus, Imperial College London, Ascot, United Kingdom
- Corresponding author: E-mail:
| |
Collapse
|