Article
Biochemical Research Methods
Yuki Ogawa, Yohei Katsuyama, Yasuo Ohnishi
Summary: This study applied deep mutational scanning to alter the ligand specificity of the transcriptional regulator XylS and identified the importance of the G71 residue. The results demonstrate the potential of deep mutational scanning in engineering ligand specificity of transcriptional regulators without full structural information.
ACS SYNTHETIC BIOLOGY
(2022)
Article
Biochemical Research Methods
Yongcan Chen, Ruyun Hu, Keyi Li, Yating Zhang, Lihao Fu, Jianzhi Zhang, Tong Si
Summary: In this study, deep mutational scanning was used to systematically analyze oxygen-independent flavin mononucleotide-based fluorescent proteins. New empirical data and design rules were obtained, providing insights for engineering protein variants.
ACS SYNTHETIC BIOLOGY
(2023)
Article
Biotechnology & Applied Microbiology
Ming Lei, Vikas D. Trivedi, Nikhil U. Nair, Kyongbum Lee, James A. Van Deventer
Summary: Synthetic cell-cell interaction systems are important for understanding multicellular communities and screening binding molecules. In this study, a previously characterized set of synthetic nanobody-antigen pairs was adapted to a yeast-bacteria coincubation format and evaluated using flow cytometry and fluorescence-activated cell sorting. The results demonstrate the efficiency of this system in evaluating ligand-target interactions and its potential for systematic characterization and high-throughput discovery of bacterial surface-binding molecules.
BIOTECHNOLOGY AND BIOENGINEERING
(2023)
Article
Biology
Allyson Li, Rashmi Voleti, Minhee Lee, Dejan Gagoski, Neel H. Shah
Summary: Tyrosine kinases and SH2 domains have specific binding preferences based on the surrounding amino acid sequence of the target tyrosine residue. A platform combining genetic peptide libraries and deep sequencing was developed to study sequence recognition by these domains. The method accurately predicted phosphorylation rates and identified mutations that affect tyrosine kinase recognition. It also assessed the impact of non-canonical and post-translationally modified amino acids on sequence recognition.
Article
Medicine, Research & Experimental
Tiphanie Pruvost, Magali Mathieu, Steven Dubois, Bernard Maillere, Emmanuelle Vigne, Herve Nozach
Summary: Delineating the specific regions on an antigen that antibodies target is crucial for antibody therapeutics development. This study used deep mutational scanning (DMS) and next-generation sequencing to observe the effects of individual mutants on the binding of two antibodies and determine their functional epitopes on the antigen. By combining AlphaFold predicted structure with DMS data, precise mapping of antibody epitopes was achieved. The accuracy of the method was confirmed through comparison with a co-crystal structure and models of non-human antigens were used to understand lack of cross-reactivity. This study promotes the application of AlphaFold for accelerating antibody engineering optimization.
Article
Biochemical Research Methods
Kanchan Jha, Sriparna Saha
Summary: This study investigates the consistency of performance in multi-modal protein-protein interaction (PPI) models and explores factors such as dataset distribution and feature extraction algorithms. By integrating multiple sources of protein information, including sequence, 3D structure, and Gene Ontology, and using deep learning techniques, the study demonstrates the potential of multi-modal approaches in predicting protein interactions.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Alistair S. Dunham, Pedro Beltrao
Summary: Amino acids serve diverse functions in proteins, utilizing their chemical properties in different contexts to create required functions; deep mutational scanning studies reveal the role of amino acids in various circumstances, supporting their diversity in proteins.
MOLECULAR SYSTEMS BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Fiona Whelan, Aleix Lafita, James Gilburt, Clement Degut, Samuel C. Griffiths, Huw T. Jenkins, Alexander N. St John, Emanuele Paci, James W. B. Moir, Michael J. Plevin, Christoph G. Baumann, Alex Bateman, Jennifer R. Potts
Summary: Changes at the cell surface enable bacteria to survive in dynamic environments, with Periscope Proteins identified as a common mechanism for bacterial surface alteration through protein length variation. These proteins, forming elongated rod-like structures, can have over 50 distinct variants implicated in host colonization and biofilm formation. While sequence divergence in large multidomain proteins may reduce misfolding between domains, Periscope Proteins break this rule and suggest that their length variability is crucial in regulating bacterial interactions with host surfaces and the immune system.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Biology
Jiahui Chen, Daniel R. Woldring, Faqing Huang, Xuefei Huang, Guo-Wei Wei
Summary: High-throughput deep mutational scanning (DMS) experiments have revolutionized various fields such as protein engineering, drug discovery, immunology, cancer biology, and evolutionary biology by providing systematic understanding of protein functions. However, the enormous mutational space associated with proteins exceeds current experimental capabilities, necessitating alternative approaches for DMS. In this study, we propose a topological deep learning (TDL) paradigm that utilizes a new topological data analysis (TDA) technique based on the persistent spectral theory. Our results demonstrate the accuracy and reliability of the TDL-DMS model in predicting binding interface mutations using SARS-CoV-2 datasets. This finding has significant implications for SARS-CoV-2 variant forecasting, antibody design, vaccine development, precision medicine, and protein engineering.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Review
Microbiology
Vera Vozandychova, Pavla Stojkova, Kamil Hercik, Pavel Rehulka, Jiri Stulik
Summary: Ubiquitination, similar to phosphorylation and acetylation, plays a crucial role in regulating various cell processes. Understanding how pathogens manipulate host ubiquitination processes is important for vaccine development and disease treatment. Pathogenic bacteria encode effector proteins targeting the host ubiquitin machinery to disrupt host defense processes.
Article
Biochemical Research Methods
Thomas C. Donahue, Guanghui Zong, Chong Ou, Philip DeShong, Lai -Xi Wang
Summary: In this study, catanionic vesicles were used as a stable lipid-based nanoparticle scaffold for displaying multivalent glycans, which showed enhanced affinity for lectins and could be used for drug delivery and intervention of protein-carbohydrate interactions implicated in disease.
BIOCONJUGATE CHEMISTRY
(2023)
Article
Biology
Yunfan Fu, Justin Bedo, Anthony T. Papenfuss, Alan F. Rubin
Summary: In this study, a linear regression-based predictor was extended to improve the prediction of amino acid variant impacts by incorporating data from alanine scanning. The results showed that the improvement in model performance is closely related to the correlation between DMS and AS results.
Article
Biochemical Research Methods
Xiaoshuai Zhang, Lixin Wang, Hucheng Liu, Xiaofeng Zhang, Bo Liu, Yadong Wang, Junyi Li
Summary: Protein is essential in living organisms and understanding its function is crucial for drug discovery and disease treatment. In this article, the authors propose the Prot2GO model, which integrates protein sequence and PPI network data to predict protein functions. The model achieves state-of-the-art performance on multiple metrics.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Zhendong Li, John Z. H. Zhang
Summary: This study investigated the quantitative effect of some major mutants of the spike protein of SARS-CoV-2 on the binding to ACE2. The results showed that several mutations, including those found in the Alpha, Beta, Gamma, and Delta variants, increased the binding of the spike protein to ACE2. Additionally, most of the mutations in the Omicron variant enhanced the binding as well. The computational predictions provided insights into the rapid global dominance of the Omicron variant.
Article
Immunology
Coline Sivelle, Raphael Sierocki, Youen Lesparre, Aurore Lomet, Wagner Quintilio, Steven Dubois, Evelyne Correia, Ana Maria Moro, Bernard Maillere, Herve Nozach
Summary: The flexibility of antibody sequences was evaluated to reduce the affinity of corresponding peptides for HLA II molecules and maintain antibody binding to its target. Permissive substitutions were identified through T-cell epitope prediction tools and deep mutational scanning to reduce affinity for HLA II molecules and preserve binding to the target. This approach identified mutants with lower HLA binding scores and higher affinity for TNF-α and neutralization ability compared to adalimumab. The study also highlights the permissiveness of antibody sequences in terms of functionality and predicted T cell epitopes.
FRONTIERS IN IMMUNOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Vincent Frappier, Madeleine Duran, Amy E. Keating
Article
Multidisciplinary Sciences
Raheleh Rezaei Araghi, Gregory H. Bird, Jeremy A. Ryan, Justin M. Jenson, Marina Godes, Jonathan R. Pritz, Robert A. Grant, Anthony Letai, Loren D. Walensky, Amy E. Keating
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2018)
Article
Multidisciplinary Sciences
Jiayi Dou, Anastassia A. Vorobieva, William Sheffler, Lindsey A. Doyle, Hahnbeom Park, Matthew J. Bick, Binchen Mao, Glenna W. Foight, Min Yen Lee, Lauren A. Gagnon, Lauren Carter, Banumathi Sankaran, Sergey Ovchinnikov, Enrique Marcos, Po-Ssu Huang, Joshua C. Vaughan, Barry L. Stoddard, David Baker
Correction
Biochemistry & Molecular Biology
Vincent Frappier, Madeleine Duran, Amy E. Keating
Article
Multidisciplinary Sciences
Justin M. Jenson, Vincent Xue, Lindsey Stretz, Tirtha Mandal, Lothar 'Luther' Reich, Amy E. Keating
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2018)
Article
Chemistry, Multidisciplinary
Daniel Cunningham-Bryant, Emily M. Dieter, Glenna W. Foight, John C. Rose, Dana E. Loutey, Dustin J. Maly
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2019)
Article
Biochemistry & Molecular Biology
Vincent Frappier, Justin M. Jenson, Jianfu Zhou, Gevorg Grigoryan, Amy E. Keating
Article
Biotechnology & Applied Microbiology
Glenna Wink Foight, Zhizhi Wang, Cindy T. Wei, Per Greisen, Katrina M. Warner, Daniel Cunningham-Bryant, Keunwan Park, T. J. Brunette, William Sheffler, David Baker, Dustin J. Maly
NATURE BIOTECHNOLOGY
(2019)
Article
Biochemistry & Molecular Biology
Vincent Frappier, Amy E. Keating
Summary: Computational protein design has the capability to generate proteins with desired structures and novel functions not found in nature. The success of this approach relies heavily on utilizing extensive data on existing proteins and their variants, ranging from sequences to structures and functions. Creative uses of multiple-sequence alignments, protein structures, and high-throughput functional assays have been demonstrated in recent studies, with the potential for deep learning to play an increasingly important role in maximizing the value of data for protein design.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2021)
Article
Biology
Theresa Hwang, Sara S. Parker, Samantha M. Hill, Meucci W. Ilunga, Robert A. Grant, Ghassan Mouneimne, Amy E. Keating
Summary: The study reveals that the protein PCARE has a high specificity for binding to ENAH over paralogs VASP and EVL, inhibiting ENAH-dependent adhesion in cells. PCARE achieves specificity by stabilizing a conformation of the ENAH EVH1 domain that is inaccessible to other family members. The research uncovers a mechanism of interaction specificity that can differentiate highly similar paralogs and provides tools for studying Ena/VASP functions in processes such as cancer cell invasion.
Article
Biochemistry & Molecular Biology
Sebastian Swanson, Venkatesh Sivaraman, Gevorg Grigoryan, Amy E. Keating
Summary: Despite the challenges in de novo design of small proteins or peptides that bind to a desired target, this study presents a method that utilizes tertiary motifs (TERMs) mined from known structures to construct custom peptide structures that complement a target surface. The results demonstrate that TERM-based seeds can accurately describe known binding structures and known peptide structures can be reconstructed with high accuracy from peptide-covering seeds. This method has potential in efficiently designing novel target-complementing binders.
Article
Biochemistry & Molecular Biology
Jackson C. Halpin, Dustin Whitney, Federica Rigoldi, Venkat Sivaraman, Avinoam Singer, Amy E. Keating
Summary: TRAF6 is an adaptor protein involved in important signaling pathways. By screening a peptide library, researchers identified peptides that bind tightly to TRAF6 and built structural models to understand the binding preferences. The study showed that native interactions are not optimized for affinity, suggesting the potential for designing peptide-based inhibitors with higher affinities.
Article
Biochemistry & Molecular Biology
Alex J. Li, Mindren Lu, Israel Desta, Vikram Sundar, Gevorg Grigoryan, Amy E. Keating
Summary: Designing new proteins with desired functions is a key objective in synthetic biology. Computational methods, such as energy-based frameworks and neural network models, can aid in this process. This study combines these two methods to improve the suitability of neural structure-based models for protein design. The results show that utilizing sequence-structure statistics and backbone coordinate features together can enhance the performance of native sequence recovery and protein folding predictions. The findings also suggest that these structure-based neural models have utility for various applications in protein science.
Article
Biochemistry & Molecular Biology
Fiona Aguilar, Stacey Yu, Robert A. Grant, Sebastian Swanson, Dia Ghose, Bonnie G. Su, Kristopher A. Sarosiek, Amy E. Keating
Summary: Apoptosis is a crucial process for development and tissue homeostasis, and its dysregulation is linked to diseases, including cancer. This study used computational protein design, yeast surface display screening, and structure-based energy scoring to identify 10 diverse peptides that can activate BAK, an apoptotic effector. These peptides, including ones from human proteins BNIP5 and PXT1, were found to induce cell death by disrupting the mitochondrial outer membrane. The findings provide insights into the peptide sequence space that can modulate BAK function and have implications for therapeutic development.
Article
Multidisciplinary Sciences
Dia A. Ghose, Kaitlyn E. Przydzial, Emily M. Mahoney, Amy E. Keating, Michael T. Laub
Summary: The evolution of novel functions in biology relies on gene duplication and divergence, creating large paralogous protein families. However, the specificity of these paralogs to their interaction partners can be sensitive to mutation. Through deep mutational scanning, it was demonstrated that a family of bacterial signaling proteins exhibits marginal specificity, with individual substitutions leading to substantial cross-talk between pathways. These findings suggest that the evolution of bacterial signaling proteins is constrained by sequence space crowding, and that evolution selects for good enough rather than optimized phenotypes in paralogs.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)