Erythromycin A and roxithromycin are clinically important macrolide antibiotics that selectively act on the bacterial 50S large ribosomal subunit to inhibit bacteria's protein elongation process by blocking the exit tunnel for the nascent peptide away from ribosome. The detailed molecular mechanism of macrolide binding is yet to be elucidated as it is currently known to the most general idea only. In this study, molecular dynamics (MD) simulation was employed to study their interaction at the molecular level, and the binding free energies for both systems were calculated using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. The calculated binding free energies for both systems were slightly overestimated compared to the experimental values, but individual energy terms enabled better understanding in the binding for both systems. Decomposition of results into residue basis was able to show the contribution of each residue at the binding pocket toward the binding affinity of macrolides and hence identified several key interacting residues that were in agreement with previous experimental and computational data. Results also indicated the contributions from van der Waals are more important and significant than electrostatic contribution in the binding of macrolides to the binding pocket. The findings from this study are expected to contribute to the understanding of a detailed mechanism of action in a quantitative matter and thus assisting in the development of a safer macrolide antibiotic.
Rhinoviruses (RV), especially Human rhinovirus (HRVs) have been accepted as the most common cause for upper respiratory tract infections (URTIs). Pleconaril, a broad spectrum anti-rhinoviral compound, has been used as a drug of choice for URTIs for over a decade. Unfortunately, for various complications associated with this drug, it was rejected, and a replacement is highly desirable. In silico screening and prediction methods such as sub-structure search and molecular docking have been widely used to identify alternative compounds. In our study, we have utilised sub-structure search to narrow down our quest in finding relevant chemical compounds. Molecular docking studies were then used to study their binding interaction at the molecular level. Interestingly, we have identified 3 residues that is worth further investigation in upcoming molecular dynamics simulation systems of their contribution in stable interaction.
Macrolides are a group of diverse class of naturally occurring and synthetic antibiotics made of macrocyclic-lactone ring carrying one or more sugar moieties linked to various atoms of the lactone ring. These macrolides selectively bind to a single high affinity site on the prokaryotic 50S ribosomal subunit, making them highly effective towards a wide range of bacterial pathogens. The understanding of binding between macrolides and ribosome serves a good basis in elucidating how they work at the molecular level and these findings would be important in rational drug design. Here, we report refinement of reconstructed PDB structure of erythromycin-ribosome system using molecular dynamics (MD) simulation. Interesting findings were observed in this refinement stage that could improve the understanding of the binding of erythromycin A (ERYA) onto the 50S subunit. The results showed ERYA was highly hydrated and water molecules were found to be important in bridging hydrogen bond at the binding pocket during the simulation time. ERYA binding to ribosome was also strengthened by hydrogen bond network and hydrophobic interactions between the antibiotic and the ribosome. Our MD simulation also demonstrated direct interaction of ERYA with Domains II, V and with C1773 (U1782EC), a residue in Domain IV that has yet been described of its role in ERYA binding. It is hoped that this refinement will serve as a starting model for a further enhancement of our understanding towards the binding of ERYA to ribosome.
Understanding the basal gut bacterial community structure and the host metabolic composition is pivotal for the interpretation of laboratory treatments designed to answer questions pertinent to host-microbe interactions. In this study, we report for the first time the underlying gut microbiota and systemic metabolic composition in BALB/c mice during the acclimatisation period. Our results showed that stress levels were reduced in the first three days of the study when the animals were subjected to repetitive handling daily but the stress levels were increased when handling was carried out at lower frequencies (weekly). We also observed a strong influence of stress on the host metabolism and commensal compositional variability. In addition, temporal biological compartmental variations in the responses were observed. Based on these results, we suggest that consistency in the frequency and duration of laboratory handling is crucial in murine models to minimise the impact of stress levels on the commensal and host metabolism dynamics. Furthermore, caution is advised in consideration of the temporal delay effect when integrating metagenomics and metabonomics data across different biological matrices (i.e. faeces and urine).
Heat shock proteins (Hsps) 60 and 70 are postulated as a potential drug target for toxoplasmosis due to its importance in the developmental and survival of Toxoplasma gondii (T. gondii). As of today, there have been no reports on three-dimensional (3D) structure of Hsp60 and Hsp70 deposited in the Brookhaven Protein Data Bank. Hence, this study was conducted to predict 3D structures for Hsp60 and Hsp70 in T. gondii by homology modeling. Selection of the best predicted model was done based on multiple scoring functions. In addition, virtual screening was performed to short-list chemical compounds from the National Cancer Institute (NCI) Diversity Set III in search of potential inhibitor against Hsp60 and Hsp70 in T. gondii. Prior to virtual screening, binding sites of Hsp60 and Hsp70 were predicted using various servers and were used as the center in docking studies. The Hsps were docked against known natural ligands to validate the method used in estimating free energy of binding (FEB) and possible interactions between ligand and protein. Virtual screening was performed with a total of 1560 compounds from the NCI Diversity Set III. The compounds were ranked subsequently according to their FEB. Molecular basis of interactions of the top five ranked compounds was investigated using Ligplot(+). The major interactions exhibited were hydrogen bonding and hydrophobic interactions in binding to Hsp60 and Hsp70. The results obtained provided information and guidelines for the development of inhibitors for Hsp60 and Hsp70 in T. gondii.
The Human Immunodeficiency Virus (HIV) infection is a global pandemic that has claimed 33 million lives to-date. One of the most efficacious treatments for naïve or pretreated HIV patients is the HIV integrase strand transfer inhibitors (INSTIs). However, given that HIV treatment is life-long, the emergence of HIV strains resistant to INSTIs is an imminent challenge. In this work, we showed two best regression QSAR models that were constructed using a boosted Random Forest algorithm (r2 = 0.998, q210CV = 0.721, q2external_test = 0.754) and a boosted K* algorithm (r2 = 0.987, q210CV = 0.721, q2external_test = 0.758) to predict the pIC50 values of INSTIs. Subsequently, the regression QSAR models were deployed against the Drugbank database for drug repositioning. The top-ranked compounds were further evaluated for their target engagement activity using molecular docking studies and accelerated Molecular Dynamics simulation. Lastly, their potential as INSTIs were also evaluated from our literature search. Our study offers the first example of a large-scale regression QSAR modelling effort for discovering highly active INSTIs to combat HIV infection.Communicated by Ramaswamy H. Sarma.
High-risk (HR) Human papillomavirus (e.g. HPV16 and HPV18) causes approximately two-thirds of all cervical cancers in women. Although the first and second-generation vaccines confer some protection against individuals, there are no approved drugs to treat HR-HPV infections to-date. The HPV E1 protein is an attractive drug target because the protein is highly conserved across all HPV types and is crucial for the regulation of viral DNA replication. Hence, we used the Random Forest algorithm to construct a Quantitative-Structure Activity Relationship (QSAR) model to predict the potential inhibitors against the HPV E1 protein. Our QSAR classification model achieved an accuracy of 87.5%, area under the receiver operating characteristic curve of 1.00, and F-measure of 0.87 when evaluated using an external test set. We conducted a drug repurposing campaign by deploying the model to screen the Drugbank database. The top three compounds, namely Cinalukast, Lobeglitazone, and Efatutazone were analyzed for their cell membrane permeability, toxicity, and carcinogenicity. Finally, these three compounds were subjected to molecular docking and 200 ns-long Molecular Dynamics (MD) simulations. The predicted binding free energies for the candidates were calculated using the MM-GBSA method. The binding free energies for Cinalukast, Lobeglitazone, and Efatutazone were -37.84 kcal/mol, -25.30 kcal/mol, and -29.89 kcal/mol respectively. Therefore, we propose their chemical scaffolds for future rational design of E1 inhibitors.Communicated by Ramaswamy H. Sarma.
Precursor mRNA (pre-mRNA) splicing is catalyzed by a large ribonucleoprotein complex known as the spliceosome. Numerous studies have indicated that aberrant splicing patterns or mutations in spliceosome components, including the splicing factor 3b subunit 1 (SF3B1), are associated with hallmark cancer phenotypes. This has led to the identification and development of small molecules with spliceosome-modulating activity as potential anticancer agents. Jerantinine A (JA) is a novel indole alkaloid which displays potent anti-proliferative activities against human cancer cell lines by inhibiting tubulin polymerization and inducing G2/M cell cycle arrest. Using a combined pooled-genome wide shRNA library screen and global proteomic profiling, we showed that JA targets the spliceosome by up-regulating SF3B1 and SF3B3 protein in breast cancer cells. Notably, JA induced significant tumor-specific cell death and a significant increase in unspliced pre-mRNAs. In contrast, depletion of endogenous SF3B1 abrogated the apoptotic effects, but not the G2/M cell cycle arrest induced by JA. Further analyses showed that JA stabilizes endogenous SF3B1 protein in breast cancer cells and induced dissociation of the protein from the nucleosome complex. Together, these results demonstrate that JA exerts its antitumor activity by targeting SF3B1 and SF3B3 in addition to its reported targeting of tubulin polymerization.