An integrated computational investigation to unveil the structural impacts of mutation on the InhA structural gene of Mycobacterium tuberculosis

Mechanistic insights into the conformational changes and alterations in residual communications due to the mutations in the pncA Gene of Mycobacterium tuberculosis: A computational perspective for effective therapeutic solutions

Due to its emerging resistance to first-line anti-TB medications, tuberculosis (TB) is one of the most contagious illness in the world. According to reports, the effectiveness of treating TB is severely impacted by drug resistance, notably resistance caused by mutations in the pncA gene-encoded pyrazinamidase (PZase) to the front-line drug pyrazinamide (PZA). The present study focused on investigating the resistance mechanism caused by the mutations D12N, T47A, and H137R to better understand the structural and molecular events responsible for the resistance acquired by the pncA gene of Mycobacterium tuberculosis (MTB) at the structural level. Bioinformatics analysis predicted that all three mutations were deleterious and located near the active centre of the pncA, affecting its functional activity. Furthermore, molecular dynamics simulation (MDS) results established that mutations significantly reduced the structural stability and caused the rearrangement of FE2+ in the active centre of pncA. Moreover, essential dynamics analysis, including principal component analysis (PCA) and free energy landscape (FEL), concluded variations in the protein motion and decreased conformational space in the mutants. Additionally, the mutations potentially impacted the network topologies and altered the residual communications in the network. The complex simulation study results established the significant movement of the flap region from the active centre of mutant complexes, further supporting the flap region's significance in developing resistance to the PZA drug. This study advances our knowledge of the primary cause of the mechanism of PZA resistance and the structural dynamics of pncA mutants, which will help us to design new and potent chemical scaffolds to treat drug-resistant TB (DR-TB).

Computational identification and analysis of deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in the human POR gene: a structural and functional impact

Cytochrome P450 oxidoreductase (POR) protein is essential for steroidogenesis, and POR gene mutations are frequently associated with P450 Oxidoreductase Deficiency (PORD), a disorder of hormone production. To our knowledge, no previous attempt has been made to identify and analyze the deleterious/pathogenic non-synonymous single nucleotide polymorphisms (nsSNPs) in the human POR gene through an extensive computational approach. Computational algorithms and tools were employed to identify, characterize, and validate the pathogenic SNPs associated with certain diseases. To begin with, all the high-confidence SNPs were collected, and their structural and functional impacts on the protein structures were explored. The results of various in silico analyses affirm that the A287P and R457H variants of POR could destabilize the interactions between the amino acids and the hydrogen bond networks, resulting in functional deviations of POR. The literature study further confirms that the pathogenic mutations (A287P and R457H) are associated with the onset of PORD. Molecular dynamics simulations (MDS) and essential dynamics (ED) studies characterized the structural consequences of prioritized deleterious mutations, representing the structural destabilization that might disrupt POR biological function. The identified deleterious mutations at the cofactor's binding domains might interfere with the essential interactions between the protein and cofactors, thus inhibiting POR catalytic activity. The consolidated insights from the computational analyses can be used to predict potential deleterious mutants and understand the disease's pathological basis and the molecular mechanism of drug metabolism for the application of personalized medication. HIGHLIGHTSNADPH cytochrome P450 oxidoreductase (POR) mutations are associated with a broad spectrum of human diseasesIdentified and analyzed the most deleterious nsSNPs of POR through the sequence and structure-based prediction toolsInvestigated the structural and functional impacts of the most significant mutations (A287P and R457H) associated with PORDMolecular dynamics and PCA-based FEL analysis were utilized to probe the mutation-induced structural alterations in PORCommunicated by Ramaswamy H. Sarma.

Computational insights into potential marine natural products as selective inhibitors of Mycobacterium tuberculosis InhA: A structure-based virtual screening study

Several factors are associated with the emergence of drug resistance mechanisms, such as impermeable cell walls, gene mutations, and drug efflux systems. Consequently, bacteria acquire resistance, leading to a decrease in drug efficacy. A new and innovative strategy is required to combat drug resistance in tuberculosis (TB) effectively. Therefore, targeting the mycolic acid biosynthesis pathway, which is involved in synthesising mycolic acids (MAs), essential structural components responsible for mycobacterial pathogenicity, has garnered interest in TB research and the concept of drug resistance. In this context, InhA, which plays a crucial role in the fatty acid synthase-II (FAS-II) system of the MA biosynthetic pathway, was selected as a druggable target for screening investigation. To identify potential lead molecules against InhA, diverse marine natural products (MNPs) were collected from the comprehensive marine natural products database (CMNPD). Virtual screening studies aided in selecting potential lead molecules that best fit within the substrate-binding pocket (SBP) of InhA, forming crucial hydrogen bond interaction with the catalytic residue Tyr158. Three MNPs, CMNPD30814, CMNPD1702, and CMNPD27355, were chosen as prospective alternative molecules due to their favorable pharmacokinetic properties and lack of toxicity according to ProTox-II predictions. Additionally, improved reactivity of the MNPs was observed in the results of density functional theory (DFT) studies. Furthermore, comparative molecular dynamics simulation (MDS), principal component (PC)-based free energy landscape (FEL) analysis, and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) were employed to show enhanced structural stability, increased H-bond potential, and high binding affinity toward the target InhA. Moreover, the hot spot residues that contributed to the high binding energy profile and anchored the stability of the complexes were revealed with their individual interaction energy. The computational insights from this study provide potential avenues to combat TB through the multifaceted mode of action of these marine lead molecules, which can be further explored in future experimental investigations.

Impact of PmrB mutations on clinical Klebsiella pneumoniae with variable colistin-susceptibilities: Structural insights and potent therapeutic solutions

Carbapenem-resistant Klebsiella pneumoniae (CRKP) infections continue to impose high morbidity threats to hospitalized patients worldwide, limiting therapeutic options to last-resort antibiotics like colistin. However, the dynamic genomic landscape of colistin-resistant K. pneumoniae (COLR-Kp) invoked ardent exploration of underlying molecular signatures for therapeutic propositions/designs. We unveiled the structural impact of the widespread and emerging PmrB mutations involved in colistin resistance (COLR) in K. pneumoniae. In the present study, clinical isolates of K. pneumoniae expressed variable susceptibilities to colistin (>0.5 μg/mL for resistant and ≤0.25 μg/mL for susceptible) despite mutations such as T157P, G207D and T246A. The protein sequences extracted from in-house sequenced genomes were used to model mutant PmrB proteins and analyze the underlying structural alterations. The mutations were contrasted based on molecular dynamics simulation trajectories, free-energy landscapes and structural flexibility profiles. The altered backbone flexibilities can be an essential factor for mutant selection by COLR K. pneumoniae and can provide clues to deal with emerging mutants. Furthermore, PmrB having high druggability confidence (>0.99), was explored as a potential target for 1396 virtually screened FDA-approved drug candidates. Among the top-10 compounds (scores >70), amphotericin B was found to be potential candidate with high affinity (Binding energy <-8 kcal/mol) and stable interactions (RMSF <0.7 Å) against PmrB druggable pockets, despite the mutations, which encourages future adjunct therapeutic research against COLR-Kp.

Differential gene expression analysis combined with molecular dynamics simulation study to elucidate the novel potential biomarker involved in pulmonary TB

Tuberculosis (TB) is a lethal multisystem disease that attacks the lungs' first line of defense. A substantial threat to public health and a primary cause of death is pulmonary TB. This study aimed to identify and investigate the probable differentially expressed genes (DEGs) primarily involved in Pulmonary TB. Accordingly, three independent gene expression data sets, numbered GSE139825, GSE139871, and GSE54992, were utilized for this purpose. The identified DEGs were used for bioinformatics-based analysis, including physical gene interaction, Gene Ontology (GO), network analysis and pathway studies using the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG). The computational analysis predicted that TNFAIP6 is the significant DEG in the gene expression profiling of TB datasets. According to gene ontology analysis, TNFAIP6 is also essential in injury and inflammation. Further, TNFA1P6 is strongly linked to arsenic poisoning, evident from the results of NetworkAnalyst, a comprehensive and interactive platform for gene expression profiling via network visual analytics. As a result, the TNFAIP6 gene was ultimately chosen as a candidate DEG and subsequently employed for in silico structural characterization studies. The tertiary structure of TNFAIP6 was modelled using the ROBETTA server, followed by validation with SAVES and ProSA webserver. Additionally, structural dynamic studies, including molecular dynamics simulation (MDS) and essential dynamics analysis, including principal component (PC) based free energy landscape (FEL) analysis, was used for checking the stability of TNFAIP6 models. The dynamics result established the structural rigidity of modelled TNFAIP6 through RMSD, RMSF and RoG results. The FEL analysis revealed the restricted conformational flexibility of TNFAIP6 by displaying a single minimum energy basin in the contour plot. The comprehensive computational analysis established that TNFAIP6 could serve as a viable biomarker to assess the severity of pulmonary TB.

Computational investigations of indanedione and indanone derivatives in drug discovery: Indanone derivatives inhibits cereblon, an E3 ubiquitin ligase component

BACKGROUND

Cereblon, an extensively studied multifunctional protein, is a Cullin 4-RING E3 ubiquitin ligase complex component. Cereblon is a well-known target of thalidomide and its derivatives. Cereblon is involved in multiple myeloma cell apoptosis. When ligands such as thalidomide and lenalidomide bind to cereblon, it recognizes various neosubstrates based on the ligand shape and properties. We have identified novel CRBN inhibitors, namely DHFO and its analogs, with structural features that are slightly different from thalidomide but stronger cereblon-binding affinity. We selected indanedione and indanone derivatives from the literature to understand and compare their cereblon-mediated substrate recognition potential.

METHODS

Computational investigations of possible CRBN inhibitors were investigated by molecular docking with Autodock Vina and DockThor programs. The properties of the compounds' ADME/T and drug-likeness were investigated. A molecular dynamics study was carried out for four selected molecules, and the molecular interactions were analyzed using PCA-based FEL methods. The binding affinity was calculated using the MM/PBSA method.

RESULTS

We conducted computational investigations on 68 indanedione and indanone derivatives binding with cereblon. Ten molecules showed better CRBN binding affinity than thalidomide. We studied the drug-likeness properties of the selected ten molecules, and four of the most promising molecules (DHFO, THOH, DIMS, and DTIN) were chosen for molecular dynamics studies. The MM/PBSA calculations showed that the DHFO, already shown to be a 5-LOX/COX2 inhibitor, has the highest binding affinity of - 163.16 kJ/mol with cereblon.

CONCLUSION

The selected CRBN inhibitor DHFO has demonstrated the highest binding affinity with cereblon protein compared to other molecules. Thalidomide and its derivatives have a new substitute in the form of DHFO, which produces an interaction hotspot on the surface of the cereblon. Ease of chemical synthesis, low toxicity, versatile therapeutic options, and pleiotropism of DHFO analogs provide an opportunity for exploring clinical alternatives with versatile therapeutic potential for a new category of indanedione molecules as novel modulators of E3 ubiquitin ligases.

Structural analyses and classification of novel isoniazid resistance coupled mutational landscapes in Mycobacterium tuberculosis: a combined molecular docking and MD simulation study

Drug resistance in Mycobacterium tuberculosis has become a major challenge to the current regime of treatment as well as to the containment of the disease globally. The molecular and genetic studies identified frequently occurring point mutations in the virulent protein such as KatG of M. tuberculosis resulted in the development of isoniazid tolerance in the pathogen. This study aims to analyze the structural basis of the disease mutations available in the literature as well as to predict novel alteration in the KatG which may cause similar deleterious effects. Around 15 experimentally derived mutations were included in this study and pathogenic mutational landscapes containing 60 site-specific alterations were predicted using the available in silico techniques. The effects of these mutations on the stability of the protein were studied and an exhaustive docking study was conducted for each classified perturbations, which identify the highest changes in the binding energies in p.Meth255Ile among experimental and p.Ala222Arg in computationally predicted mutations. Furthermore, the structural effects on these substitutions were analyzed using the principles of molecular dynamic simulations each for a 100 ns time scale, which validated the interaction studies. The outcome of this study may enable the identification of the novel drug resistance-associated point mutations which were not previously reported and may contribute significantly in a variety of experimental studies as well as facilitate the process of drug design and discovery.Communicated by Ramaswamy H. Sarma.