Previous Article in Journal
Ultrashort Echo Time and Fast Field Echo Imaging for Spine Bone Imaging with Application in Spondylolysis Evaluation
Previous Article in Special Issue
Minimizing Cohort Discrepancies: A Comparative Analysis of Data Normalization Approaches in Biomarker Research
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Identification and Dynamics Understanding of Novel Inhibitors of Peptidase Domain of Collagenase G from Clostridium histolyticum

1
Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
2
Department of Pathology and Laboratory Medicine, Security Forces Hospital Program, P.O Box 3643, Riyadh 11481, Saudi Arabia
3
College of Medicine, Alfaisal University, P.O. Box 50927, Riyadh 11533, Saudi Arabia
4
Department of Family and Community Medicine, College of Medicine, King Saud University (KSU), Riyadh 11481, Saudi Arabia
5
University Family Medicine Center, King Saud University Medical City, King Saud University (KSU), Riyadh 11481, Saudi Arabia
6
Department of Oral and Maxillofacial Surgery and Diagnostic Sciences, Faculty of Dentistry, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
7
Department of Basic Sciences for Nursing, Nursing College, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
*
Author to whom correspondence should be addressed.
Computation 2024, 12(8), 153; https://doi.org/10.3390/computation12080153
Submission received: 27 June 2024 / Revised: 18 July 2024 / Accepted: 21 July 2024 / Published: 25 July 2024
(This article belongs to the Special Issue 10th Anniversary of Computation—Computational Biology)

Abstract

Clostridium histolyticum is a Gram-positive anaerobic bacterium belonging to the Clostridium genus. It produces collagenase, an enzyme involved in breaking down collagen which is a key component of connective tissues. However, antimicrobial resistance (AMR) poses a great challenge in combating infections caused by this bacteria. The lengthy nature of traditional drug development techniques has resulted in a shift to computer-aided drug design and other modern drug discovery approaches. The above method offers a cost-effective means for gathering comprehensive information about how ligands interact with their target proteins. The objective of this study is to create novel, explicit drugs that specifically inhibit the C. histolyticum collagenase enzyme. Through structure-based virtual screening, a library containing 1830 compounds was screened to identify potential drug candidates against collagenase enzymes. Following that, molecular dynamic (MD) simulation was performed in an aqueous solution to evaluate the behavior of protein and ligand in a dynamic environment while density functional theory (DFT) analysis was executed to predict the molecular properties and structure of lead compounds, and the WaterSwap technique was utilized to obtain insights into the drug–protein interaction with water molecules. Furthermore, principal component analysis (PCA) was performed to reveal conformational changes, salt bridges to express electrostatic interaction and protein stability, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) to assess the pharmacokinetics profile of top compounds and control molecules. Three potent drug candidates were identified MSID000001, MSID000002, MSID000003, and the control with a binding score of −10.7 kcal/mol, −9.8 kcal/mol, −9.5 kcal/mol, and −8 kcal/mol, respectively. Furthermore, Molecular Mechanics Poisson–Boltzmann Surface Area (MMPBSA) analysis of the simulation trajectories revealed energy scores of −79.54 kcal/mol, −73.99 kcal/mol, −62.26 kcal/mol, and −70.66 kcal/mol, correspondingly. The pharmacokinetics properties exhibited were under the acceptable range. The compounds hold the potential to be novel drugs; therefore, further investigation needs to be conducted to find out their anti-collagenase action against C. histolyticum infections and antibiotic resistance.
Keywords: antimicrobial resistance; molecular dynamic simulation; principal component analysis; salt bridges; WaterSwap; structure-based drug design antimicrobial resistance; molecular dynamic simulation; principal component analysis; salt bridges; WaterSwap; structure-based drug design

Share and Cite

MDPI and ACS Style

Anjum, F.; Hazazi, A.; Alsaeedi, F.A.; Bakhuraysah, M.; Shafie, A.; Alshehri, N.A.; Hawsawi, N.; Ashour, A.A.; Banjer, H.J.; Alharthi, A.; et al. Identification and Dynamics Understanding of Novel Inhibitors of Peptidase Domain of Collagenase G from Clostridium histolyticum. Computation 2024, 12, 153. https://doi.org/10.3390/computation12080153

AMA Style

Anjum F, Hazazi A, Alsaeedi FA, Bakhuraysah M, Shafie A, Alshehri NA, Hawsawi N, Ashour AA, Banjer HJ, Alharthi A, et al. Identification and Dynamics Understanding of Novel Inhibitors of Peptidase Domain of Collagenase G from Clostridium histolyticum. Computation. 2024; 12(8):153. https://doi.org/10.3390/computation12080153

Chicago/Turabian Style

Anjum, Farah, Ali Hazazi, Fouzeyyah Ali Alsaeedi, Maha Bakhuraysah, Alaa Shafie, Norah Ali Alshehri, Nahed Hawsawi, Amal Adnan Ashour, Hamsa Jameel Banjer, Afaf Alharthi, and et al. 2024. "Identification and Dynamics Understanding of Novel Inhibitors of Peptidase Domain of Collagenase G from Clostridium histolyticum" Computation 12, no. 8: 153. https://doi.org/10.3390/computation12080153

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop