Article
Biochemical Research Methods
Ivan Martin Hernandez, Yves Dehouck, Ugo Bastolla, Jose Ramon Lopez-Blanco, Pablo Chacon
Summary: This article introduces a structure-based stability prediction method upon mutation, which is important for protein engineering and design, as well as understanding genetic diseases or drug resistance events. The method uses a simple residue-based orientational potential model and only requires parameterizing 12 amino acid-dependent weights for stability prediction. The method, called KORPM, accurately predicts mutational effects on an independent benchmark dataset, whether the wild-type or mutated structure is used as starting point. Compared with state-of-the-art methods, KORPM achieves better results in terms of root mean square error, correlation, receiver operating characteristics, and precision-recall curves.
Article
Biochemistry & Molecular Biology
Gen Li, Shailesh Kumar Panday, Emil Alexov
Summary: SAAFEC-SEQ is a gradient boosting decision tree machine learning method for predicting the change of folding free energy caused by amino acid substitutions. It does not require the 3D structure of the corresponding protein, making it suitable for genome-scale investigations with sparse structural information.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Biochemical Research Methods
Corrado Pancotti, Silvia Benevenuta, Giovanni Birolo, Virginia Alberini, Valeria Repetto, Tiziana Sanavia, Emidio Capriotti, Piero Fariselli
Summary: Predicting the difference in thermodynamic stability between protein variants is important for protein design and understanding genotype-phenotype relationships. This study introduces a new dataset and evaluates the prediction performance of 21 different tools. The results suggest that considering both direct and reverse variants improves the prediction accuracy.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemistry & Molecular Biology
Carlos H. M. Rodrigues, Douglas E. Pires, David B. Ascher
Summary: Protein-protein interactions are crucial in cellular functions and biological processes. Computational methods for assessing the effects of mutations on protein-protein binding affinity are limited to single point mutations, but mmCSM-PPI outperforms existing methods in evaluating changes caused by both single and multiple missense mutations.
NUCLEIC ACIDS RESEARCH
(2021)
Review
Biochemical Research Methods
Castrense Savojardo, Pier Luigi Martelli, Rita Casadio, Piero Fariselli
Summary: This study discusses biases in predicting protein stability changes upon mutation, presents a more general perspective on the problem, and introduces a machine learning-based method that directly addresses the bias issue. Analysis shows that this method is nearly insensitive to the addressed problem.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Chemistry, Physical
Zhonglang Yu, Haoran Yu, Jinling Xu, Zhe Wang, Ziyuan Wang, Tingting Kang, Kaitong Chen, Zhongji Pu, Jianping Wu, Lirong Yang, Gang Xu
Summary: PaL lipase, an important enzyme for producing l-menthol, suffers from poor thermostability, limiting its industrial applications. In this study, a strategy named CREATE was used to stabilize PaL. Through rational evaluation, four single-mutant variants with improved thermostability were identified. The best 4M variant showed significantly enhanced stability at high temperature.
CATALYSIS SCIENCE & TECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
Jing Zhao, Siqi Zhang, Yuan Jiang, Yan Liu, Qingwen Zhu
Summary: The study predicted the high-risk nsSNPs of WFS1 and their effects on the structure and function of wolframin protein using bioinformatics software. A total of 13 high-risk nsSNPs were obtained, with 11 of them previously reported or cited and 2 novel variants. These high-risk nsSNPs have significant impacts on amino acid properties and protein structure. Computational analysis provided valuable insights into the mechanism of WFS1 related diseases, but further experimental studies are needed for validation.
SCIENTIFIC REPORTS
(2023)
Article
Biochemistry & Molecular Biology
Silvia Benevenuta, Giovanni Birolo, Tiziana Sanavia, Emidio Capriotti, Piero Fariselli
Summary: An open challenge in computational and experimental biology is to understand the impact of non-synonymous DNA variations on protein function and human health. Predictive tools for protein stability are less accurate in predicting stabilizing variations compared to destabilizing ones, possibly due to the abundance of destabilizing variants in the available datasets. New methods should consider input features highly correlated with stabilizing variants and be tested on unbalanced datasets.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2023)
Article
Biochemical Research Methods
Yelu Jiang, Lijun Quan, Kailong Li, Yan Li, Yiting Zhou, Tingfang Wu, Qiang Lyu
Summary: Effectively predicting protein-protein interactions after amino acid mutations is crucial for understanding protein function and designing drugs. This study proposes a deep graph convolution (DGC) network-based framework, DGCddG, which accurately predicts changes in protein-protein binding affinity after mutation. The model achieves good performance for both single and multi-point mutations, and shows promising results in predicting ACE2 changes in blind tests related to the SARS-CoV-2 virus.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Mathematics, Applied
Jihoon Lee, Ngocthach Nguyen, Leonardo Pires
Summary: In this paper, we prove that the dynamical system induced by a reaction diffusion equation is generically Gromov-Hausdorff stable on its global attractor under Lipschitz perturbations of the domain and equation.
JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS
(2023)
Article
Chemistry, Multidisciplinary
Yingzhe Liu, Yilin Cao, Weipeng Lai, Tao Yu, Yiding Ma, Zhongxue Ge
Summary: Crystal structure predictions for high energy materials are crucial, and this study presents an alternative strategy based on packing similarity of homologous crystals for predicting organic crystal structures. By utilizing rules of molecular similarity and electrostatic matching, successful and rapid predictions were achieved for two energetic N-oxides. This approach is envisioned to provide a new method for predicting crystal structures of various high energy materials.
Article
Chemistry, Analytical
Farahnaz Fallahtafti, Sjoerd Bruijn, Arash Mohammadzadeh Gonabadi, Mohammad Sangtarashan, Julie Blaskewicz Boron, Carolin Curtze, Ka-Chun Siu, Sara A. Myers, Jennifer Yentes
Summary: Response to challenging situations is important to prevent falls, especially after medical disturbances that require active control. The relationship between trunk motion in response to disturbances and gait stability has not been well studied.
Article
Biology
Tingting Sun, Yuting Chen, Yuhao Wen, Zefeng Zhu, Minghui Li
Summary: Resistance to small-molecule drugs is a major cause of therapeutic drug failure in clinical practice, with missense mutations altering protein-ligand binding being a critical mechanism for genetic disease and drug resistance. PremPLI, a structure-based machine learning method, has shown robust predictive performance with higher accuracy in quantitatively estimating the effects of single mutations on ligand binding affinity changes.
COMMUNICATIONS BIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Shuyu Wang, Hongzhou Tang, Yuliang Zhao, Lei Zuo
Summary: Predicting changes in protein thermostability upon mutation is crucial for disease understanding and drug design. This study leverages advances in graph neural networks and Bayesian neural networks to tackle this prediction task. The method is validated on test datasets, showing strong generalization and symmetry performance, and provides insights into the inherent noise of the training datasets through uncertainty decomposition.
Article
Biochemistry & Molecular Biology
Shuyu Wang, Hongzhou Tang, Yuliang Zhao, Lei Zuo
Summary: This study leverages advances in graph neural networks and Bayesian neural networks to accurately predict protein thermostability changes, which is crucial for disease research and drug design.
Article
Biochemistry & Molecular Biology
Sneha Munshi, Soundhararajan Gopi, Gitanjali Asampille, Sandhyaa Subramanian, Luis A. Campos, Hanudatta S. Atreya, Athi N. Naganathan
NUCLEIC ACIDS RESEARCH
(2018)
Article
Multidisciplinary Sciences
Abhishek Narayan, Soundhararajan Gopi, David Fushman, Athi N. Naganathan
NATURE COMMUNICATIONS
(2019)
Article
Biochemistry & Molecular Biology
Abhishek Narayan, Soundhararajan Gopi, Bincy Lukose, Athi N. Naganathan
JOURNAL OF MOLECULAR BIOLOGY
(2020)
Article
Chemistry, Physical
Kabita Bhattacharjee, Soundhararajan Gopi, Athi N. Naganathan
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2020)
Article
Biology
Jacob Beal, Natalie G. Farny, Traci Haddock-Angelli, Vinoo Selvarajah, Geoff S. Baldwin, Russell Buckley-Taylor, Markus Gershater, Daisuke Kiga, John Marken, Vishal Sanchania, Abigail Sison, Christopher T. Workman
COMMUNICATIONS BIOLOGY
(2020)
Article
Chemistry, Physical
Soundhararajan Gopi, Bincy Lukose, Athi N. Naganathan
Summary: The research findings show that different paralogous transcription factors' ligand-binding domains (LBDs) have diverse native ensembles, including varying widths of native wells, different numbers and natures of partially structured states, and varying degrees of conformational order. Additionally, Monte Carlo simulations reveal that many functional conformations coexist in equilibrium, with their relative populations sensitive to both temperature and the strength of ligand binding. Furthermore, allosteric modulation of the degree of structure at a coregulator binding site on ligand binding is achieved through the redistribution of populations in the native ensembles of glucocorticoid and PPA LBDs.
JOURNAL OF PHYSICAL CHEMISTRY B
(2021)
Article
Multidisciplinary Sciences
Jacob Beal, Geoff S. Baldwin, Natalie G. Farny, Markus Gershater, Traci Haddock-Angelli, Russell Buckley-Taylor, Ari Dwijayanti, Daisuke Kiga, Meagan Lizarazo, John Marken, Kim de Mora, Randy Rettberg, Vishal Sanchania, Vinoo Selvarajah, Abigail Sison, Marko Storch, Christopher T. Workman
Summary: The research found that fluorescence measurements from engineered constructs are highly reproducible, but there is a critical need for quality controlled fluorescent calibrants for plate readers to improve reproducibility.
Article
Biochemistry & Molecular Biology
Athi N. Naganathan, Rahul Dani, Soundhararajan Gopi, Akashnathan Aranganathan, Abhishek Narayan
Summary: The interplay between folding mechanisms and function in large proteins is easier to decipher compared to smaller systems due to the direct impact of functional constraints and demands imposed at the sequence level on the folding landscape.
JOURNAL OF MOLECULAR BIOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Hemashree Golla, Adithi Kannan, Soundhararajan Gopi, Sowmiya Murugan, Lakshmi R. Perumalsamy, Athi N. Naganathan
Summary: The fluctuations in protein's native ensemble play a significant role in its functioning and determining the functional output is confounded by multiple variables. Through the study of the FF1 domain in human p190A RhoGAP protein, it was discovered that phosphorylation of a buried tyrosine, which is crucial in transcriptional activity, is regulated through the modulation of structural coupling and native ensemble characteristics. The unfavorable charge-charge interactions were found to be important in governing this functional event.
ACS CENTRAL SCIENCE
(2022)
Article
Biochemistry & Molecular Biology
Giovanni B. Brandani, Soundhararajan Gopi, Masataka Yamauchi, Shoji Takada
Summary: This review discusses recent molecular dynamics (MD) simulation studies on chromatin biology. It describes the latest method developments and factors affecting the structure and dynamics of chromatin, such as the structural fluctuations of nucleosomes and the organization of chromatin fibers. It also explores the interactions and dynamics of transcription factors on chromatin and how chromatin organization is modulated by molecular motors acting on DNA.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
C. A. Jabeena, Gayathri Govindaraju, Mukul Rawat, Soundhararajan Gopi, Devadathan Valiyamangalath Sethumadhavan, Abdul Jaleel, Dhakshmi Sasankan, Krishanpal Karmodiya, Arumugam Rajavelu
Summary: This study identified a novel histone modification, H3K64me3, in Plasmodium falciparum, showing dynamic changes throughout different stages of the parasite's life cycle. The researchers also found that this modification is selectively enriched on genes encoding exported proteins, indicating a potential role in regulating their expression in different stages.
JOURNAL OF BIOLOGICAL CHEMISTRY
(2021)
Article
Chemistry, Physical
Soundhararajan Gopi, Athi N. Naganathan
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2020)
Article
Biochemistry & Molecular Biology
Soundhararajan Gopi, Akashnathan Aranganathan, Athi N. Naganathan
CURRENT RESEARCH IN STRUCTURAL BIOLOGY
(2019)