Mycobacterium tuberculosis L-alanine dehydrogenase (L-MtAlaDH) plays an important role in catalyzing L-alanine to ammonia and pyruvate, which has been considered to be a potential target for tuberculosis treatment. In the present work, the functional domain motions encoded in the structure of L-MtAlaDH were investigated by using the Gaussian network model (GNM) and the anisotropy network model (ANM). The slowest modes for the open-apo and closed-holo structures of the enzyme show that the domain motions have a common hinge axis centered in residues Met133 and Met301. Accompanying the conformational transition, both the 1,4-dihydronicotinamide adenine dinucleotide (NAD)-binding domain (NBD) and the substrate-binding domain (SBD) move in a highly coupled way. The first three slowest modes of ANM exhibit the open-closed, rotation and twist motions of L-MtAlaDH, respectively. The calculation of the fast modes reveals the residues responsible for the stability of the protein, and some of them are involved in the interaction with the ligand. Then, the functionally-important residues relevant to the binding of the ligand were identified by using a thermodynamic method. Our computational results are consistent with the experimental data, which will help us to understand the physical mechanism for the function of L-MtAlaDH.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4691113PMC
http://dx.doi.org/10.3390/ijms161226170DOI Listing

Publication Analysis

Top Keywords

domain motions
12
network model
12
l-alanine dehydrogenase
8
slowest modes
8
domain
5
motions functionally-key
4
residues
4
functionally-key residues
4
residues l-alanine
4
dehydrogenase revealed
4

Similar Publications

Novel Human Activity Recognition (HAR) methodologies, which are built upon learning algorithms and employ ubiquitous sensors, have achieved remarkable precision in the identification of sports activities. Such progress benefits all age groups of humanity, and in the future, AI will be used to address difficult problems in scientific research. A novel approach is introduced in this article to utilize motion sensor data in order to categorize and distinguish various categories of sports activities.

View Article and Find Full Text PDF

Purpose: This study aims to develop a assessment system for evaluating shoulder joint muscle strength in patients with varying degrees of upper limb injuries post-stroke, using surface electromyographic (sEMG) signals and joint motion data.

Methods: The assessment system includes modules for acquiring muscle electromyography (EMG) signals and joint motion data. The EMG signals from the anterior, middle, and posterior deltoid muscles were collected, filtered, and denoised to extract time-domain features.

View Article and Find Full Text PDF

Surface electromyography (sEMG) data has been extensively utilized in deep learning algorithms for hand movement classification. This paper aims to introduce a novel method for hand gesture classification using sEMG data, addressing accuracy challenges seen in previous studies. We propose a U-Net architecture incorporating a MobileNetV2 encoder, enhanced by a novel Bidirectional Long Short-Term Memory (BiLSTM) and metaheuristic optimization for spatial feature extraction in hand gesture and motion recognition.

View Article and Find Full Text PDF

Polar Networks Mediate Ion Conduction of the SARS-CoV-2 Envelope Protein.

J Am Chem Soc

December 2024

Department of Chemistry, Massachusetts Institute of Technology, 170 Albany Street, Cambridge, Massachusetts 02139, United States.

The SARS-CoV-2 E protein conducts cations across the cell membrane to cause pathogenicity to infected cells. The high-resolution structures of the E transmembrane domain (ETM) in the closed state at neutral pH and in the open state at acidic pH have been determined. However, the ion conduction mechanism remains elusive.

View Article and Find Full Text PDF

Modeling Diffusive Motion of Ferredoxin and Plastocyanin on the PSI Domain of MIT9313.

J Phys Chem B

December 2024

Theoretical and Computational Biophysics Group, NIH Center for Macromolecular Modeling and Visualization, Beckman Institute for Advanced Science and Technology, University of Illinois Urbana─Champaign, Urbana, Illinois 61801-3028, United States.

Diffusion of mobile charge carriers, such as ferredoxin and plastocyanin, often constitutes a rate-determining step in photosynthetic energy conversion. The diffusion time scales typically exceed that of other primary bioenergetic processes and remain beyond the reach of direct simulation at the molecular level. We characterize the diffusive kinetics of ferredoxin and plastocyanin upon the photosystem I-rich domain of , the most abundant phototroph on Earth by mass.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!