Article
Multidisciplinary Sciences
Nobuyasu Koga, Rie Koga, Gaohua Liu, Javier Castellanos, Gaetano T. Montelione, David Baker
Summary: The study successfully applied the principles of designing ideal proteins with consistent local and non-local interactions to design larger proteins with five- and six-stranded beta-sheets flanked by alpha-helices. Investigation revealed that the global structures of the design models were more strained than the NMR structures. By incorporating explicit consideration of global backbone strain, proteins with the intended unswapped strand arrangements were successfully designed, highlighting the importance of global tertiary interactions in determining protein topology.
NATURE COMMUNICATIONS
(2021)
Article
Biochemistry & Molecular Biology
Matic Broz, Marko Jukic, Urban Bren
Summary: Protein structure prediction is a significant challenge in bioinformatics, and this study explores the use of a simple neural network model to predict protein structures. The results show surprising accuracy for predicting phi angles but slightly lower accuracy for predicting psi angles. Additionally, the study demonstrates that simple neural networks can also be used for protein secondary structure prediction.
Article
Biochemical Research Methods
M. A. Hakim Newton, Fereshteh Mataeimoghadam, Rianon Zaman, Abdul Sattar
Summary: This study proposes a protein backbone angle prediction method that trains separate models for different categories of secondary structures. By exploiting classification knowledge to restrict generalization, this method significantly improves prediction accuracy.
BMC BIOINFORMATICS
(2022)
Article
Biochemistry & Molecular Biology
Natan Nagar, Nir Ben Tal, Tal Pupko
Summary: Measuring evolutionary rates at the residue level is crucial for understanding protein structure and function. We present EvoRator, a machine-learning regression algorithm that predicts site-specific evolutionary rates based on protein structures. We demonstrate the superiority of EvoRator over traditional physicochemical features and showcase its application in three common protein evolution scenarios.
JOURNAL OF MOLECULAR BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Nicole Balasco, Luciana Esposito, Alfonso De Simone, Luigi Vitagliano
Summary: This study investigated the structural basis of conformational preferences of genetically encoded amino acid residues, revealing that different regions of the Ramachandran plot may exhibit similar or anticorrelated amino acid propensities.
Article
Multidisciplinary Sciences
Xusi Han, Genki Terashi, Charles Christoffer, Siyang Chen, Daisuke Kihara
Summary: The article presents VESPER, a program for EM density map search and alignment, which demonstrates accurate global and local alignment and comparison of EM maps using benchmark datasets.
NATURE COMMUNICATIONS
(2021)
Article
Biology
Quenisha Baldwin, Eleni Panagiotou
Summary: Protein folding, a crucial biological process, involves the relationship between local properties and global properties of proteins. Analysis of protein datasets and single domain proteins suggests that high local topological free energy conformations may impact the folding rates of proteins.
JOURNAL OF THEORETICAL BIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Mateusz Kurcinski, Sebastian Kmiecik, Mateusz Zalewski, Andrzej Kolinski
Summary: The study introduces a new straightforward approach for protein docking sampling, involving large-scale backbone rearrangements in one protein and small backbone fluctuations in the other protein using Replica Exchange Monte Carlo dynamics. Acceptable quality models were obtained for a significant number of cases in simulations of 62 protein-protein complexes.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Chemistry, Physical
Agnieszka G. Lipska, Adam K. Sieradzan, Su''meyye Atmaca, Cezary Czaplewski, Adam Liwo
Summary: A reliable representation of local interactions is crucial for accurate protein structure and dynamics modeling. Traditional approaches mainly focus on parameterizing preset formulas rather than physics-based derivation. Recent advancements suggest the consideration of virtual bond angles and multiple torsional terms. Furthermore, separating residue-based torsional potentials into regular and improper potentials is a new approach.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2023)
Article
Chemistry, Medicinal
Jaswinder Singh, Kuldip Paliwal, Jaspreet Singh, Yaoqi Zhou
Summary: The dilated convolutional neural network method SPOT-RNA-1D predicts RNA backbone torsion and pseudotorsion angles with smaller mean absolute errors compared to random and helix prediction methods. It accurately recovers overall patterns of angle distributions but faces difficulty in predicting angles further away from bases involved in tertiary interactions. SPOT-RNA-1D yields more accurate dihedral angles than the best models in RNA-puzzles experiments, showing potential as model quality indicators and restraints for RNA structure prediction.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Multidisciplinary Sciences
Byung Woo Cho, Tae-Ho Lee, Sungjun Kim, Chong-Hyuk Choi, Min Jung, Koo Yeon Lee, Sung-Hwan Kim
Summary: This study aimed to analyze the reproducibility and reliability of alignment parameters measured using the EOS image system. The results showed significant differences in femoro-tibial rotation and tibial torsion between anterior and posterior positions, good to very good inter-observer reliability, and varying inter-modality reliability between EOS and CT. Overall, the 3D EOS model demonstrated very good reliability for femur measurements but not for tibia measurements.
SCIENTIFIC REPORTS
(2021)
Article
Biochemical Research Methods
Wei Zhong, Feng Gu
Summary: Researchers have developed a new deep learning model called Clustering Recurrent Neural Network (CRNN) to improve the accuracy of local protein structure prediction. By dividing the protein dataset into multiple cluster subtrees and training a RNN for each cluster, the model excels in learning the relationship between local sequence and structure.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Review
Chemistry, Physical
Andrew H. Marcus, Dylan Heussman, Jack Maurer, Claire S. Albrecht, Patrick Herbert, Peter H. von Hippel
Summary: This article reviews the application of spectroscopic methods and analyses that combine linear absorbance and circular dichroism spectroscopy with nonlinear 2D fluorescence spectroscopy to study the local conformations of DNA in ssDNA-dsDNA fork constructs.
ANNUAL REVIEW OF PHYSICAL CHEMISTRY
(2023)
Article
Chemistry, Multidisciplinary
Zhuoya Dong, Enci Zhang, Yilan Jiang, Alvaro Mayoral, Qing Zhang, Yanhang Ma, Huaidong Jiang
Summary: In this study, electron ptychography was used to directly observe the local structures of two zeolites, Na-LTA and ZSM-5. The framework atoms and extra-framework cations were successfully imaged. This approach provides a new way to locally image zeolite structures and is important for further studying and tuning zeolite active sites at the atomic level.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
Article
Chemistry, Multidisciplinary
Emma E. Cawood, G. Marius Clore, Theodoros K. Karamanos
Summary: The T193A mutation in DNAJB6 reduces self-oligomerization and anti-aggregation activity while increasing the rate of formation of a partially folded state. This highlights the importance of chaperone dynamics in regulating protein aggregation and suggests potential therapeutic avenues targeting specific substrates.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2022)