Inhibition of phosphodiesterase 4 (PDE4) is a promising therapeutic approach for the treatment of inflammatory pulmonary disorders, i.e. asthma and chronic obstructive pulmonary disease. However, the treatment with non-selective PDE4 inhibitors is associated with side effects such as nausea and vomiting. Among the subtypes of PDE4 inhibited by these inhibitors, PDE4B is expressed in immune, inflammatory and airway smooth muscle cells, whereas, PDE4D is expressed in the area postrema and nucleus of the solitary tract. Thus, PDE4D inhibition is responsible for the emetic response. In this regard, a selective PDE4B inhibitor is expected to be a potential drug candidate for the treatment of inflammatory pulmonary disorders. Therefore, a shared feature pharmacophore model was developed and used as a query for the virtual screening of Maybridge and SPECS databases. A number of filters were applied to ensure only compounds with drug-like properties were selected. Accordingly, nine compounds have been identified as final hits, where HTS04529 showed the highest affinity and selectivity for PDE4B over PDE4D in molecular docking. The docked complexes of HTS04529 with PDE4B and PDE4D were subjected to molecular dynamics simulations for 100ns to assess their binding stability. The results showed that HTS04529 was bound tightly to PDE4B and formed a more stable complex with it than with PDE4D.
The major complaint that most of the schizophrenic patients' face is the cognitive impairment which affects the patient's quality of life. The current antipsychotic drugs treat only the positive symptoms without alleviating the negative or cognitive symptoms of the disease. In addition, the existing therapies are known to produce extrapyramidal side effects that affect the patient adherence to the treatment. PDE10A inhibitor is the new therapeutic approach which has been proven to be effective in alleviating the negative and cognitive symptoms of the disease. A number of PDE10A inhibitors have been developed, but no inhibitor has made it beyond the clinical trials so far. Thus, the present study has been conducted to identify a PDE10A inhibitor from natural sources to be used as a lead compound for the designing of novel selective PDE10A inhibitors. Ligand and structure-based pharmacophore models for PDE10A inhibitors were generated and employed for virtual screening of universal natural products database. From the virtual screening results, 37 compounds were docked into the active site of the PDE10A. Out of 37 compounds, three inhibitors showed the highest affinity for PDE10A where UNPD216549 showed the lowest binding energy and has been chosen as starting point for designing of novel PDE10A inhibitors. The structure-activity-relationship studies assisted in designing of selective PDE10A inhibitors. The optimization of the substituents on the phenyl ring resulted in 26 derivatives with lower binding energy with PDE10A as compared to the lead compound. Among these, MA 8 and MA 98 exhibited the highest affinity for PDE10A with binding energy (-10.90 Kcal/mol).
In recent years, the PDE1B enzyme has become a desirable drug target for the treatment of psychological and neurological disorders, particularly schizophrenia disorder, due to the expression of PDE1B in brain regions involved in volitional behaviour, learning and memory. Although several inhibitors of PDE1 have been identified using different methods, none of these inhibitors has reached the market yet. Thus, searching for novel PDE1B inhibitors is considered a major scientific challenge. In this study, pharmacophore-based screening, ensemble docking and molecular dynamics simulations have been performed to identify a lead inhibitor of PDE1B with a new chemical scaffold. Five PDE1B crystal structures have been utilised in the docking study to improve the possibility of identifying an active compound compared to the use of a single crystal structure. Finally, the structure-activity- relationship was studied, and the structure of the lead molecule was modified to design novel inhibitors with a high affinity for PDE1B. As a result, two novel compounds have been designed that exhibited a higher affinity to PDE1B compared to the lead compound and the other designed compounds.
Over the last two decades, computational technologies have played a crucial role in antiviral drug development. Whenever a virus spreads and becomes a threat to global health, it brings along the challenge of developing new therapeutics and prophylactics. Computational drug and vaccine discovery has evolved quickly over the years. Some interesting examples of computational drug discovery are anti-AIDS drugs, where HIV protease and reverse transcriptase have been targeted by agents developed using computational methods. Various computational methods that have been applied to anti-viral research include ligand-based methods that rely on known active compounds, i.e., pharmacophore modeling, machine learning or classical QSAR; structure-based methods that rely on an experimentally determined 3D structure of the targets, i.e., molecular docking and molecular dynamics and methods for the development of vaccines such as reverse vaccinology; structural vaccinology and vaccine epitope prediction. This review summarizes these approaches to battle viral diseases and underscores their importance for anti-viral research. We discuss the role of computational methods in developing small molecules and vaccines against human immunodeficiency virus, yellow fever, human papilloma virus, SARS-CoV-2, and other viruses. Various computational tools available for the abovementioned purposes have been listed and described. A discussion on applying artificial intelligence-based methods for antiviral drug discovery has also been included.
Phosphodiesterase 1B (PDE1B) and PDE10A are dual-specificity PDEs that hydrolyse both cyclic adenosine monophosphate and cyclic guanosine monophosphate, and are highly expressed in the striatum. Several reports have suggested that PDE10A inhibitors may present a promising approach for the treatment of positive symptoms of schizophrenia, whereas PDE1B inhibitors may present a novel mechanism to modulate cognitive deficits. Previously, we have reported a novel dual inhibitor of PDE1B and PDE10A, compound 2 [(3-fluorophenyl)(2-methyl-2,3-dihydro-4H-benzo[b][1,4]oxazin-4-yl)methanone] which has shown inhibitory activity for human recombinant PDE1B and PDE10A in vitro. In the present study, the safety profile of compound 2 has been evaluated in rats in the acute oral toxicity study, as well as; the antipsychotic-like effects in the rat model of schizophrenia. Compound 2 was tolerated up to 1 g/kg when administered at a single oral dose. Additionally, compound 2 has strongly suppressed ketamine-induced hyperlocomotion, which presented a model for the positive symptoms of schizophrenia. It has also shown an ability to attenuate social isolation induced by chronic administration of ketamine and enhanced recognition memory of rats in the novel object recognition test. Altogether, our results suggest that compound 2 represents a promising therapy for the treatment of the three symptomatic domains of schizophrenia.
Several studies have shown that the mammalian target of rapamycin (mTOR) inhibitor; everolimus (EV) improves patient survival in several types of cancer. However, the meaningful efficacy of EV as a single agent for the treatment of colorectal cancer (CRC) has failed to be proven in multiple clinical trials. Combination therapy is one of the options that could increase the efficacy and decrease the toxicity of the anticancer therapy. This study revealed that the β-cyclodextrin (β-CD):FGF7 complex has the potential to improve the antiproliferative effect of EV by preventing FGF receptor activation and by enhancing EV cellular uptake and intracellular retention. Molecular docking techniques were used to investigate the possible interaction between EV, β-CD, and FGF7. Molecular docking insights revealed that β-CD and EV are capable to form a stable inclusion complex with FGF at the molecular level. The aqueous solubility of the inclusion complex was increased (3.1 ± 0.23 μM) when compared to the aqueous solubility of pure EV (1.7 ± 0.16 μM). In addition, the in vitro cytotoxic activity of a FGF7:β-CD:EV complex on Caco-2 cell line was investigated using real-time xCELLigence technology. The FGF7:β-CD:EV complex has induced apoptosis of Caco-2 cells and shown higher cytotoxic activity than the parent drug EV. With the multitargets effect of β-CD:FGF7 and EV, the antiproliferative effect of EV was remarkably improved as the IC50 value of EV was reduced from 9.65 ± 1.42 to 1.87 ± 0.33 μM when compared to FGF7:β-CD:EV complex activity. In conclusion, the findings advance the understanding of the biological combinational effects of the β-CD:FGF7 complex and EV as an effective treatment to combat CRC.