Letters in Drug Design & Discovery - Volume 19, Issue 2, 2022

Background: Oxidative stress is a significant player in the pathogenesis of diabetes mellitus and the Kelch-like ECH-associated protein1/nuclear factor erythroid 2-related factor 2/antioxidant response element (Keap1/Nrf2/ARE) signaling pathway serves as the essential defense system to mitigate oxidative stress. Nrf2 is responsible for the mitigation of oxidative stress while Keap1 represses Nrf2’s activation upon binding. Identification of Nrf2 activators has started to pick up enthusiasm as they can be used as therapeutic agents against diabetes mellitus. One of the ongoing mechanisms in the activation of Nrf2 is to disrupt Keap1/Nrf2 protein-protein interaction. This study aimed at using computational analysis to screen natural compounds capable of inhibiting Keap1/Nrf2 protein-protein interaction. Methods: A manual curated library of natural compounds was screened against crystal structure of Keap1 using glide docking algorithm. Binding free energy of the docked complexes, and adsorption, digestion, metabolism and excretion (ADME) properties were further employed to identify the hit compounds. The bioactivity of the identified hit against Keap1 was predicted using quantitative structure-activity relationship (QSAR) model. Results: A total of 7 natural compounds (Compound 222, 230, 310, 208, 210, 229 and 205) identified from different medicinal plants were found to be potent against Keap1 based on their binding affinity and binding free energy. The internal validated model kpls_radial_30 with R² of 0.9109, Q² of 0.7287 was used to predict the compounds’ bioactivities. Compound 205 was considered as the ideal drug candidate because it showed moderation for ADME properties, had predicted pIC50 of 6.614 and obeyed Lipinski’s rule of five. Conclusion: This study revealed that Compound 205, a compound isolated from Amphipterygium adstringens is worth considering for further experimental analysis.

Background: Clostridioides difficile (CD) is an enteric multi-drug resistant pathogenic bacterium. CD-associated infections are the leading cause of nosocomial diarrhea that can further lead to pseudomembranous colitis, toxic mega-colon or sepsis with greater mortality and morbidity risks. CD infection possesses higher rates of recurrence due to its greater resistance to antibiotics. Considering its higher rates of recurrence, it has become a major burden on healthcare facilities. Therefore, there is a dire need to identify novel drug targets to combat antibiotic resistance of Clostridioides difficile. Objective: To identify and propose new and novel drug targets against the Clostridioides difficile. Methods: In the current study, a computational subtractive genomics approach was applied to obtain a set of potential drug targets that exist in the multi-drug resistant strain of Clostridioides difficile. Here, the uncharacterized proteins were studied as potential drug targets. The methodology involved several bioinformatics databases and tools. The druggable proteins sequences were retrieved based on non-homology with host proteome and essentiality for the survival of the pathogen. The uncharacterized proteins were functionally characterized using different computational tools, and sub-cellular localization was also predicted. The metabolic pathways were analyzed using the KEGG database. Eventually, the druggable proteome has been fetched using sequence similarity with the already available drug targets present in the DrugBank database. These druggable proteins were further explored for the structural details to identify drug candidates. Results: A priority list of potential drug targets was provided with the help of the applied method on the complete proteome set of the C. difficile. Moreover, the drug-like compounds have been screened against the potential drug targets to prioritize potential drug candidates. To facilitate the need for drug targets and therapies, the study proposed five potential protein drug targets, out of which three proposed drug targets were subjected to homology modeling to explore their structural and functional activities. Conclusion: In conclusion, we proposed three unique, unexplored drug targets against C. difficile. The structure-based methods were applied and resulted in a list of top-scoring compounds as potential inhibitors to proposed drug targets.

Background: Treatment of the Covid-19 pandemic caused by the highly contagious and pathogenic SARS-CoV-2 is a global menace. Day by day, this pandemic is getting worse. Doctors, scientists and researchers across the world are urgently scrambling for a cure for novel corona virus and continuously working at break neck speed to develop vaccines or drugs. But to date, there are no specific drugs or vaccines available in the market to cope up with the virus. Objective: The present study helps us to elucidate 3D structures of SARS-CoV-2 proteins and also to identify natural compounds as potential inhibitors against COVID-19. Methods: The 3D structures of the proteins were constructed using Modeller 9.16 modeling tool. Modelled proteins were validated with PROCHECK by Ramachandran plot analysis. In this study, a small library of natural compounds (fifty compounds) was docked to the hACE2 binding site of the modelled surface glycoprotein of SARS-CoV-2 using AutoDock Vina to repurpose these inhibitors against SARS-CoV-2. Conceptual density functional theory calculations of the best eight compounds had been performed by Gaussian-09. Geometry optimizations for these molecules were done at M06-2X/ def2-TZVP level of theory. ADME parameters, pharmacokinetic properties and drug likeness of the compounds were analyzed using swissADME website. Results: In this study, we analysed the sequences of surface glycoprotein, nucleocapsid phosphoprotein and envelope protein obtained from different parts of the globe. We modelled all the different sequences of surface glycoprotein and envelop protein in order to derive 3D structure of a molecular target, which is essential for the development of therapeutics. Different electronic properties of the inhibitors have been calculated using DFT through M06-2X functional with def2-TZVP basis set. Docking result at the hACE2 binding site of all modelled surface glycoproteins of SARSCoV- 2 showed that all the eight inhibitors (actinomycin D, avellanin C, ichangin, kanglemycin A, obacunone, ursolic acid, ansamiotocin P-3 and isomitomycin A) studied here were many folds better compared to hydroxychloroquine which has been found to be effective to treat patients suffering from COVID-19. All the inhibitors meet most of the criteria of drug likeness assessment. Conclusion: We expect that eight compounds (actinomycin D, avellanin C, ichangin, kanglemycin A, obacunone, ursolic acid, ansamiotocin P-3 and isomitomycin A) can be used as potential inhibitors against SARS-CoV-2.

Background: Various challenges exist in the treatment of infectious diseases due to the significant rise in drug resistance, resulting in the failure of antibiotic treatment. As a consequence, a dire need has arisen for the rethinking of the drug discovery cycle because of the challenge of drug resistance. The underlying cause of the infectious diseases depends upon associations within the Host-pathogen Protein- Protein Interactions (HP-PPIs) network, which represents a key to unlock new pathogenesis mechanisms. Hence, the elucidation of significant PPIs is a promising approach for the identification of potential drug targets. Objective: Identification of the most significant HP-PPIs and their partners, and targeting them to prioritize potential new drug targets against Vancomycin-resistant Enterococcus faecalis (VRE). Methods: We applied a computational approach based on one of the emerging techniques i.e. Interolog methodology to predict the significant Host-Pathogen PPIs. Structure-Based Studies were applied to model shortlisted protein structures and validate them through PSIPRED, PROCHECK, VERIFY3D, and ERRAT tools. Furthermore, 18,000 drug-like compounds from the ZINC library were docked against these proteins to study protein-chemical interactions using the AutoDock based molecular docking method. Results: The study resulted in the identification of 118 PPIs for Enterococcus faecalis, and prioritized two novel drug targets i.e. Exodeoxyribonuclease (ExoA) and ATP-dependent Clp protease proteolytic subunit (ClpP). Consequently, the docking program ranked 2,670 and 3,154 compounds as potential binders against Exodeoxyribonuclease and ATP-dependent Clp protease proteolytic subunit, respectively. Conclusion: Thereby, the current study enabled us to identify and prioritize potential PPIs in VRE and their interacting proteins in human hosts along with the pool of novel drug candidates.

Background: Due to the broad influence and reversible nature of microRNA (miRNA) on the expression and regulation of target genes, researchers suggest that miRNAs and single nucleotide polymorphisms (SNPs) in miRNA genes interfere with 5-fluorouracil (5-FU) drug resistance in colorectal cancer chemotherapy. Methods: Computational assessment and cataloging of miRNA gene polymorphisms that target mRNA transcripts directly or indirectly through regulation of 5-FU chemoresistance in CRC were screened out by applying various universally accessible datasets such as miRNA SNP3.0 software. Results: 1255 SNPs in 85 miRNAs affecting 5-FU resistance (retrieved from literature) were detected. Computational analysis showed that 167 from 1255 SNPs alter microRNA expression levels leading to inadequate response to 5-FU resistance in CRC. Among these 167 SNPs, 39 were located in the seed region of 25/85 miRNA and were more critical than other SNPs. Has-miR-320a-5p with 4 SNP in seed region was miRNA with the most number of SNPs. On the other hand, it has been identified that proteoglycan in cancer, adherents junction, ECM-receptor interaction, Hippo signaling pathway, TGF-beta signaling cascade, biosynthesis of fatty acid, and fatty acid metabolism were the most important pathways targeted by these 85 predicted miRNAs. Conclusion: Our data suggest 39 SNPs in the seed region of 25 miRNAs as catalog in miRNA genes that control the 5-FU resistance in CRC. These data also identify the most important pathways regulated by miRNA.

Background: One of the leading global metabolic diseases marked by insulin resistance and chronic hyperglycemia is type 2 diabetes mellitus (T2DM). Since the last decade, DPP-4 enzyme inhibition has proven to be a successful, safe, and well-established therapy for the treatment of T2DM. Objective: The present work reports the synthesis, characterization, and screening of some novel 2- methyl-N'-[(Z)-substituted-phenyl ethylidene] imidazo [1, 2-a] pyridine-3-carbohydrazide derivatives as DPP-IV inhibitors for the treatment of T2DM. Methods: The molecular docking was performed to study these derivatives' binding mode in the enzyme's allosteric site. All the synthesized compounds were subjected for DPP-IV enzyme assay and in vivo antihyperglycemic activity in STZ-induced diabetic rats. Results: The synthesized derivatives exhibited potent antidiabetic activity as compared to the standard drug Sitagliptin. Out of sixteen compounds, A1, A4, B4, C2, C3, and D4 have shown promising antidiabetic activity against the DPP-IV enzyme. The most promising compound, C2, showed a percentage inhibition of 72.02±0.27 at 50 μM concentration. On the 21st-day, compound C2 showed a significant reduction in serum blood glucose level, i.e., 156.16±4.87 mg/dL, then diabetic control, which was 280.00±13.29 mg/dL whereas, standard Sitagliptin showed 133.50±11.80 mg/dL. In the in vivo antihyperglycemic activity, the compounds have exhibited good hypoglycemic potential in fasting blood glucose in the T2DM animal model. All the docked molecules have exhibited perfect binding affinity towards the active pocket of the enzyme. The synthesized derivatives were screened through Lipinski's rule of five for better optimization, and fortunately, none of them violated the rule. Conclusion: The above results indicate that compound C2 is a relatively active and selective hit molecule that can be structurally modified to enhance the DPP-IV inhibitor's potency and overall pharmacological profile. From the present work, it has been concluded that substituted pyridine-3-carbohydrazide derivatives possess excellent DPP-IV inhibitory potential and can be better optimized further by generating more in vivo, in vitro models.