Polamarasetty Aparoy

Mammalian arachidonic acid lipoxygenases (ALOXs) are lipid-peroxidizing enzymes, which have been implicated in inflammatory, hyperproliferative and neurodegenerative diseases. Nordihydroguaiaretic acid (NDGA) is a naturally occurring antioxidant and a potent lipoxygenase inhibitor. Unfortunately, the molecular basis of the NDGA–ALOX interaction remains unexplored. Here, we show by in silico docking studies and by molecular dynamics simulations that NDGA binds in the substrate binding pocket of human ALOX15 and that Gln595 plays a major role in this interaction. In silico mutagenesis studies (Glu595Ala, Glu595Leu, Glu595Glu, Glu595Ile) modified the stability of the ALOX15–NDGA complex and altered the ligand binding behavior of the enzyme. To validate the in silico findings, we expressed human ALOX15 and the enzyme mutants as recombinant proteins, characterized their functional properties and quantified the IC₅₀ values for NDGA-induced inhibition. Consistent with our in silico predictions, the experimental IC₅₀ values demonstrated that NDGA strongly inhibited wildtype ALOX15 and its Gln595Glu and Gln595Ile mutants. In contrast, the IC₅₀ values for the Gln595Ala and Gln595Leu mutants were more than one order of magnitude higher. These findings highlight the role of Gln595 for the NDGA–ALOX15 interaction and may facilitate the future development of isoform-specific ALOX15 inhibitors.

Inhibition of Cyclooxygenase-2 (COX-2) represents a well-established and promising strategy in the development of anti-inflammatory drugs, given its pivotal role in mediating inflammation. Selective inhibition of COX-2 over COX-1 is critical for reducing the gastrointestinal side effects commonly associated with traditional nonsteroidal anti-inflammatory drugs (NSAIDs). Celecoxib is a widely recognized selective COX-2 inhibitor that has been extensively studied for its therapeutic efficacy. Its structural analogues differ in their biological activities despite their close structural resemblance. The objective of the present work is to systematically investigate the influence of subtle structural modifications on celecoxib, focusing on its COX-2 inhibitory activity profile. A dataset comprising 375 analogues was curated based on the structural similarity with celecoxib. Molecular descriptors were calculated using RDKit and Mordred, followed by correlation analysis. Weak correlation was observed between the computed molecular descriptors and biological activity. Molecular docking studies were performed using Genetic Optimisation for Ligand Docking (GOLD). Critical interactions were identified by interaction analysis. Further, the Structure-Activity Landscape Index (SALI) analysis aided in identifying the activity cliffs in the dataset. The findings from the interaction analysis and SALI offer a comprehensive understanding of the Structure-Activity relationship of celecoxib analogues and deliver valuable insights for further lead optimization.

The study developed machine learning models to predict the key hotspots within the allosteric inhibitor binding site of mutant Isocitrate Dehydrogenase 1 (IDH1) enzyme and validated the inhibition by in silico and in vitro screening.

Pseudomonas aeruginosa is regarded as the most opportunistic pathogen. It can induce ferroptosis in humans. It secretes a unique lipoxygenase (LOX) isoform, pLoxA that can oxidize polyenoic fatty acids. Unlike other lipoxygenases, pLoxA can oxygenate membrane phospholipids like phosphatidylethanolamine, leading to hemolysis of red blood cells (RBC). This functional overlap with human 15-LOX that uses the same substrate has provided a bottleneck to the discovery of pLoxA-specific inhibitors and there is an immediate need to find pLoxA specific drugs. The active site of pLoxA is much larger than LOX enzymes, reflecting its ability to accommodate bulky substrates, such as phospholipids. The molecular docking of two experimentally established inhibitors and the further molecular dynamics simulations provided possible key residues in the active site of pLoxA. Our study found that this region is essentially hydrophobic including His 377 and His 382 that are placed to the non-heme iron atom and help to stabilize the inhibitors in the binding site along with hydrophobic residues contribute well toward ligand interactions that involve Phe 415, Ile 416 and Leu 424. MD simulations showed that interactions with those residues were dynamic in nature. Main contribution to binding stability arose via π-π stacking, π-cation, and alkyl interactions. Graphical Abstract

RNA-dependent RNA polymerase (RdRP) is a critical component of the RNA virus life cycle, including SCoV-2. Among the Coronavirus-encoded proteins, non-structural protein 12 ( NSP12 ) exhibits polymerase activity in collaboration with one unit of NSP7 and two units of NSP8 , constituting the RdRp holoenzyme. While there is abundant information on SCoV-2 RdRp-mediated RNA replication, the influence of interplay among NSP12, NSP7 , and NSP8 on template RNA binding and primer extension activity remains relatively unexplored and poorly understood. Here, we recreated a functional RdRp holoenzyme in vitro using recombinant SCoV-2 NSP12, NSP7 , and NSP8 , and established its functional activity. Subsequently, molecular interactions among the NSP s in the presence of a variety of templates and their effects on polymerase activity were studied, wherein we found that NSP12 alone exhibited notable polymerase activity that increased significantly in the presence of NSP7 and NSP8 . However, this activity was completely shut down, and the template RNA-primer complex was detached from NSP12 when one of the two cofactors was present. Through computational analysis, we found that the template RNA entry channel was more constricted in the presence of one of the two cofactors, which was relatively more constricted in the presence of NSP8 compared to that in the presence of NSP7 . In conclusion, we report that NSP7 and NSP8 together synergise to enhance the activity of NSP12 , but antagonise when present alone. Our findings have implications for novel drug development, and compounds that obstruct the binding of NSP7 or NSP8 to NSP12 can have lethal effects on viral RNA replication.

Post-genomic era has led to the discovery of several new targets posing challenges for structure-based drug design efforts to identify lead compounds. Multiple computational methodologies exist to predict the high ranking hit/lead compounds. Among them, free energy methods provide the most accurate estimate of predicted binding affinity. Pathway-based Free Energy Perturbation (FEP), Thermodynamic Integration (TI) and Slow Growth (SG) as well as less rigorous end-point methods such as Linear interaction energy (LIE), Molecular Mechanics-Poisson Boltzmann./Generalized Born Surface Area (MM-PBSA/GBSA) and λ-dynamics have been applied to a variety of biologically relevant problems. The recent advances in free energy methods and their applications including the prediction of protein-ligand binding affinity for some of the important drug targets have been elaborated. Results using a recently developed Quantum Mechanics (QM)/Molecular Mechanics (MM) based Free Energy Perturbation (FEP) method, which has the potential to provide a very accurate estimation of binding affinities to date has been discussed. A case study for the optimization of inhibitors for the fructose 1,6- bisphosphatase inhibitors has been described.