Article
Biochemistry & Molecular Biology
Moon Sajid, Parwinder Kaur
Summary: The characteristics of 22 UGTs were analyzed, and it was found that the N-terminal domain had a higher amino acid substitution rate, leading to a stronger specificity for isoflavonoids. Analysis of the physical and chemical parameters of active sites revealed key amino acids that likely influence the substrate preference, OH site specificity, and glycosylation efficiency of UGTs towards specific (iso)flavonoids. This study is important for heterologous biosynthesis of glycosylated isoflavonoids and protein engineering efforts to improve the substrate and site specificity of UGTs.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Biochemical Research Methods
Sou Sugiki, Teppei Niide, Yoshihiro Toya, Hiroshi Shimizu
Summary: This study proposes a method for estimating the contribution of each amino acid residue to substrate specificity using phylogenetic analysis and logistic regression. By using amino acid sequences of enzymes with different cofactor specificities as input data, a highly accurate machine learning model was obtained. This method can be applied in protein engineering.
ACS SYNTHETIC BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Yao Cheng, Haobo Wang, Hua Xu, Yuan Liu, Bin Ma, Xuemin Chen, Xin Zeng, Xianghe Wang, Bo Wang, Carina Shiau, Sergey Ovchinnikov, Xiao-Dong Su, Chu Wang
Summary: MetalNet is a co-evolution-based pipeline that can systematically predict metal-binding sites in proteomes. By applying MetalNet to proteomes of four prokaryotic species, we successfully predicted 4,849 potential metalloproteins, greatly expanding the currently annotated metalloproteomes. MetalNet also accurately identified known zinc-binding sites in the human spliceosome complex. This tool provides a unique and valuable resource for studying hidden metalloproteomes and metal biology.
NATURE CHEMICAL BIOLOGY
(2023)
Article
Biochemical Research Methods
Bruck Taddese, Antoine Garnier, Madeline Deniaud, Daniel Henrion, Marie Chabbert
Summary: Bios2cor is a framework that allows for the investigation and integration of dynamic correlations in protein sidechain motions during MD simulations and evolutionary correlations in MSAs. It provides tools for analyzing, visualizing, and interpreting the data.
Article
Biochemical Research Methods
Jun Hu, Lin-Lin Zheng, Yan-Song Bai, Ke-Wen Zhang, Dong-Jun Yu, Gui-Jun Zhang
Summary: DeepATPseq is a novel method for predicting protein-ATP binding residues without using protein three-dimensional structure or sequence-derived structural information. It achieves an accuracy of 77.71% and demonstrates the advantage of combining DCNN and SVM for extracting more discriminative information from PSFM profiles.
ANALYTICAL BIOCHEMISTRY
(2021)
Article
Biochemistry & Molecular Biology
Pablo Maturana, Maria S. Orellana, Sixto M. Herrera, Ignacio Martinez, Maximiliano Figueroa, Jose Martinez-Oyanedel, Victor Castro-Fernandez, Elena Uribe
Summary: In this study, the structure and catalytic mechanism of Escherichia coli agmatinase (EcAGM) were analyzed through X-ray crystallography and molecular dynamics simulations, providing a detailed insight into the high specificity of this enzyme. The results highlighted the importance of Trp68 in stabilizing the amino group of agmatine through cation-pi interaction, contributing to a better understanding of the enzyme's kinetic characteristics.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Peng Yang, Yanyan Ge, Yu Yao, Ying Yang
Summary: This study proposes a novel keyphrase generation model that utilizes graph convolutional networks to capture dependency structure information in text, and uses a variational selector network to determine the selection probability of each word, thereby improving keyphrase extraction performance.
KNOWLEDGE-BASED SYSTEMS
(2022)
Letter
Physics, Multidisciplinary
David Sigtermans
Summary: Modeling a causal association as a communication process between cause and effect enables the discovery of causal skeletons. By characterizing communication channels with stochastic tensors, linear algebra can be employed to reduce data dimensionality needed for testing conditional independence. This tensor-based approach only requires a minor extension to information theory, introducing the concept of path information.
Article
Biochemistry & Molecular Biology
Ioannis G. Riziotis, Antonio J. M. Ribeiro, Neera Borkakoti, Janet M. Thornton
Summary: Conformational variation in catalytic residues can be captured as alternative snapshots in enzyme crystal structures. The study reveals that catalytic centers of enzymes can exhibit inherent rigidity or flexibility, with structural variability most often involving a subset of catalytic residues. Furthermore, it is found that active sites are predominantly flexible, with side chains being the main contributors. The goal of this work is to characterize the extent of flexibility in catalysis and relate it to enzyme evolution and substrate binding.
JOURNAL OF MOLECULAR BIOLOGY
(2022)
Article
Genetics & Heredity
Katrisa M. Ward, Brandon D. Pickett, Mark T. W. Ebbert, John S. K. Kauwe, Justin B. Miller
Summary: This study developed a Protein Interactions Calculator (PIC) that efficiently identifies coevolving residues between two protein sequences using mutual information. The PIC can be used to prioritize potential protein interactions, leading to a better understanding of biological processes and additional therapeutic targets belonging to protein interaction groups.
Article
Biochemistry & Molecular Biology
Bosko M. Stojanovski, Enrico Di Cera
Summary: The sequence and position of the cleavage sites at R271 and R320 dictate the preferred pathway of prothrombin activation, with the former being preferentially cleaved in the absence of cofactor Va and the latter being preferentially cleaved in the presence of cofactor Va.
JOURNAL OF BIOLOGICAL CHEMISTRY
(2021)
Article
Biochemistry & Molecular Biology
Mingzhao Wang, Juanying Xie, Shengquan Xu
Summary: The study introduces two feature encoding algorithms to extract strong features for identifying m(6)A and non-m(6)A sites. The proposed M6A-BiNP predictor based on these algorithms outperforms existing methods and is currently the best model for identifying m(6)A and non-m(6)A sites.
Article
Biochemistry & Molecular Biology
Metehan Celebi, Ebru Demet Akten
Summary: This study investigates the effect of perturbation at the allosteric site on bacterial phosphofructokinase through molecular dynamics simulations. The results show that restraining the predicted allosteric site causes stiffness in one dimer while restraining the experimentally resolved site increases mobility. The analysis of C-alpha-C-alpha distances and cross-correlation of positional fluctuations reveals that restraining the predicted site enhances signal transmission and mutual correspondence between positional fluctuations.
JOURNAL OF MOLECULAR BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Jeffrey Skolnick, Mu Gao
Summary: The tertiary structure of a protein is determined by the interplay of local secondary structure propensities, hydrogen bonding, and tertiary interactions. The global structure of a protein sequence is collectively selected by the many-body, tertiary interactions among residues. Recent advances in deep-learning approaches have been successful in predicting protein side-chain contacts because they implicitly learned the many-body interactions among protein residues.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2021)
Article
Computer Science, Information Systems
Mingzhao Wang, Juanying Xie, Philip W. Grant, Shengquan Xu
Summary: In this paper, a feature representation algorithm called PSP-PJMI is proposed for identifying DNA N4-methylcytosine (4mC) sites. The algorithm extracts numerical features with rich categorical information from DNA sequences and constructs a 4mC-BiNP model using SVM. Experimental results show that the proposed algorithm outperforms existing algorithms in terms of feature extraction and predictive performance. Furthermore, the algorithm can also be used for identifying other DNA methylation sites and RNA methylation sites.
INFORMATION SCIENCES
(2022)
Article
Immunology
Saghar Kaabinejadian, Carolina Barra, Bruno Alvarez, Hooman Yari, William H. Hildebrand, Morten Nielsen
Summary: Mass spectrometry-based immunopeptidomics is an important technique in biomedical applications, but the complexity of the data and the lack of appropriate tools have hindered its large-scale application. In this study, a new tool called MHCMotifDecon is presented, which accurately deconvolutes immunopeptidome datasets and helps identify and characterize HLA binding motifs, thus facilitating the discovery of new T cell targets.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Multidisciplinary Sciences
Zeynep Kosaloglu-Yalcin, Jenny Lee, Jason Greenbaum, Stephen P. Schoenberger, Aaron Miller, Young J. Kim, Alessandro Sette, Morten Nielsen, Bjoern Peters
Summary: The prediction accuracy of antigen epitopes can be further improved by considering the abundance levels of peptides' source proteins. By incorporating biophysical principles, existing MHC binding prediction tools, and abundance estimates of source proteins, a function was derived to estimate the likelihood of a peptide to be an MHC class I ligand. The use of proteomic data showed the highest performance in improving epitope predictions.
Review
Biochemical Research Methods
Morten Nielsen, Nicola Ternette, Carolina Barra
Summary: This article discusses the concept, applications, and challenges of immunopeptidome and emphasizes the benefits and limitations of liquid chromatography-tandem mass spectrometry (MS) in obtaining large-scale immunopeptidome data sets. It highlights the importance of refined and highly optimized machine learning approaches for accurate analysis and interpretation of the data. Furthermore, it showcases the use of MS-immunopeptidomics data in improving the accuracy of immunoinformatics prediction methods and demonstrates the synergistic combination of MS experiments and in silico models for optimal antigen discovery.
EXPERT REVIEW OF PROTEOMICS
(2022)
Article
Biochemistry & Molecular Biology
Magnus Haraldson Hoie, Erik Nicolas Kiehl, Bent Petersen, Morten Nielsen, Ole Winther, Henrik Nielsen, Jeppe Hallgren, Paolo Marcatili
Summary: Recent advances in machine learning and natural language processing have enabled accurate prediction of protein structures and functions, with NetSurfP-3.0 standing out as a tool with drastically improved runtime and reliable prediction performance.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Multidisciplinary Sciences
Jeppe Sejero Holm, Samuel A. Funt, Annie Borch, Kamilla Kjaergaard Munk, Anne-Mette Bjerregaard, James L. Reading, Colleen Maher, Ashley Regazzi, Phillip Wong, Hikmat Al-Ahmadie, Gopa Iyer, Tripti Tamhane, Amalie Kai Bentzen, Nana Overgaard Herschend, Susan De Wolf, Alexandra Snyder, Taha Merghoub, Jedd D. Wolchok, Morten Nielsen, Jonathan E. Rosenberg, Dean F. Bajorin, Sine Reker Hadrup
Summary: This study demonstrates that the expansion of neoantigen-specific CD8(+) T cells can distinguish between patients with controlled disease and progressive disease in metastatic urothelial carcinoma treated with PD-L1 blockade. Furthermore, the peripheral NARTs derived from patients with disease control exhibit specific cell phenotypes and increased CD39 levels, suggesting their association with treatment response.
NATURE COMMUNICATIONS
(2022)
Article
Virology
Derek W. Wright, William T. Harvey, Joseph Hughes, MacGregor Cox, Thomas P. Peacock, Rachel Colquhoun, Ben Jackson, Richard Orton, Morten Nielsen, Nienyun Sharon Hsu, Ewan M. Harrison, Thushan de Silva, Andrew Rambaut, Sharon J. Peacock, David L. Robertson, Alessandro M. Carabelli
Summary: COG-UK Mutation Explorer is a web resource that provides knowledge and analysis on SARS-CoV-2 virus genome mutations and variants in the UK. It focuses on antigenic amino acid replacements that have immunological significance. The resource curates data from over 2 million genome sequences and cross-references them with experimental data from the literature. It tracks mutations that could impact the neutralizing activity of antibodies and vaccines, as well as changes in T cell epitopes and resistance to antiviral drugs.
Article
Biochemistry & Molecular Biology
Muhammad Saad Khilji, Pouya Faridi, Erika Pinheiro-Machado, Carolin Hoefner, Tina Dahlby, Ritchlynn Aranha, Soren Buus, Morten Nielsen, Justyna Klusek, Thomas Mandrup-Poulsen, Kirti Pandey, Anthony W. Purcell, Michal T. Marzec
Summary: The loss of GRP94 from the endoplasmic reticulum results in mishandling of proinsulin, ER stress, and activation of the immunoproteasome, leading to the sensitization of beta-cells to immune attack.
Article
Biochemical Research Methods
Raphael Trevizani, Zhen Yan, Jason A. Greenbaum, Alessandro Sette, Morten Nielsen, Bjoern Peters
Summary: An approach to assess the reliability of different metrics for evaluating the performance of MHC class I binding predictors was developed. The study found that using percentile-ranked results improved the stability of the ranks and identified the top-performing tools in the benchmark.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemistry & Molecular Biology
Zeynep Kosaloglu-Yalcin, Nina Blazeska, Randi Vita, Hannah Carter, Morten Nielsen, Stephen Schoenberger, Alessandro Sette, Bjoern Peters
Summary: CEDAR is a freely accessible database and analysis resource for cancer epitopes, which are molecular targets recognized by anti-cancer immune cells. Detailed knowledge of cancer epitopes is crucial for understanding and planning cancer prevention, treatment, and immune responses.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Multidisciplinary Sciences
Heli M. Garcia Alvarez, Zeynep Kosaloglu-Yalcin, Bjoern Peters, Morten Nielsen
Summary: This study finds that the prediction performance of HLA antigen presentation can be improved by integrating information on antigen abundance, which has important implications for immunotherapy and vaccine design.
Article
Oncology
Loulieta Nazerai, Shona Caroline Willis, Patricio Yankilevich, Luca Di Leo, Francesca Maria Bosisio, Alex Frias, Corine Bertolotto, Jacob Nersting, Maria Thastrup, Soren Buus, Allan Randrup Thomsen, Morten Nielsen, Kristoffer Staal Rohrberg, Kjeld Schmiegelow, Daniela De Zio
Summary: This study used the drug 6TG to induce mutations in tumor cells and increase the level of neoepitopes, enhancing the immune response. 6TG exposure increased tumor mutational burden and reshaped the tumor microenvironment, making the tumors more responsive to immune-checkpoint blockade.
Article
Biology
Helle Rus Povlsen, Amalie Kai Bentzen, Mohammad Kadivar, Leon Eyrich Jessen, Sine Reker Hadrup, Morten Nielsen, K. Christopher Garcia
Summary: Novel single-cell-based technologies enable high-throughput matching of T cell receptor (TCR) sequences with their cognate peptide-MHC recognition motif. A data-driven method called ITRAP is proposed to filter out likely artifacts and generate large sets of TCR-pMHC sequence data with high specificity and sensitivity. This approach has been validated in virus-specific T cell responses across multiple healthy donors.
Article
Biology
Jonas Birkelund Nilsson, Saghar Kaabinejadian, Hooman Yari, Bjoern Peters, Carolina Barra, Loren Gragert, William Hildebrand, Morten Nielsen
Summary: This study addresses the prediction of HLA-DQ antigen presentation and the contribution of trans-only variants in shaping the HLA-DQ immunopeptidome. By integrating immunoinformatics data mining models with mass spectrometry immunopeptidomics data, the study demonstrates improved predictive power and molecular coverage for models trained with novel HLA-DQ data. The study also reveals the limited contribution of trans-only HLA-DQ variants to the overall HLA-DQ immunopeptidome.
COMMUNICATIONS BIOLOGY
(2023)
Article
Immunology
Sandra Eltschkner, Samantha Mellinger, Soren Buus, Morten Nielsen, Kajsa M. M. Paulsson, Karin Lindkvist-Petersson, Helena Westerdahl
Summary: Long-distance migratory animals such as birds and bats have evolved a unique adaptive immunity with highly duplicated Major Histocompatibility Complex (MHC) genes to withstand diverse pathogens. A study on the MHC class I protein, Acar3, from the great reed warbler reveals a peculiar peptide-binding mode that potentially facilitates interactions with innate immune receptors. The investigation highlights the importance of studying the immune system of wild animals to uncover unique immune mechanisms absent in humans and model organisms.
FRONTIERS IN IMMUNOLOGY
(2023)
Article
Mathematical & Computational Biology
Yuchen Li, Peter Wad Sackett, Morten Nielsen, Carolina Barra
Summary: This article introduces a new protein allergenicity prediction method, which introduces MHC presentation propensity as a novel feature to overcome the limitations of previous methods in accurately predicting allergenicity when similarity diminishes.
BIOINFORMATICS ADVANCES
(2023)