Identification of novel analgesics through a drug repurposing strategy

Unlocking the potential of approved drugs for the allosteric inhibition of tropomyosin-receptor kinase A using molecular docking and molecular dynamics studies

Tropomyosin-receptor kinase A (TrkA) is the primary isoform among the tropomyosin-receptor kinases that have been associated with human cancer development, contributing to approximately 7.4% of all cancer cases. TrkA represents an attractive target for cancer treatment; however, currently available TrkA inhibitors face limitations in terms of resistance development and potential toxicity. Hence, the objective of this study was to identify new allosteric-approved inhibitors of TrkA that can overcome these challenges and be employed in cancer therapy. To achieve this goal, a screening of 9,923 drugs from the ChEMBL database was conducted to assess their repurposing potential using molecular docking. The top 49 drug candidates, exhibiting the highest docking scores (-11.569 to -7.962 kcal/mol), underwent MM-GBSA calculations to evaluate their binding energies. Delanzomib and tibalosin, the top two drugs with docking scores of -10.643 and -10.184 kcal/mol, respectively, along with MM-GBSA dG bind values of -67.96 and -50.54 kcal/mol, were subjected to 200 ns molecular dynamic simulations, confirming their stable interactions with TrkA. Based on these findings, we recommend further experimental evaluation of delanzomib and tibalosin to determine their potential as allosteric inhibitors of TrkA. These drugs have the potential to provide more effective and less toxic therapeutic alternatives. The approach employed in this study, which involves repurposing drugs through molecular docking and molecular dynamics, serves as a valuable tool for identifying novel drug candidates with distinct therapeutic uses. This methodology can contribute to reducing the attrition rate and expediting the process of drug discovery.

Disruption of Irisin Dimerization by FDA-Approved Drugs: A Computational Repurposing Approach for the Potential Treatment of Lipodystrophy Syndromes

In this paper, we present the development of a computer-based repurposing approach to identify FDA-approved drugs that are potentially able to interfere with irisin dimerization. It has been established that altered levels of irisin dimers are a pure hallmark of lipodystrophy (LD) syndromes. Accordingly, the identification of compounds capable of slowing down or precluding the irisin dimers' formation could represent a valuable therapeutic strategy in LD. Combining several computational techniques, we identified five FDA-approved drugs with satisfactory computational scores (iohexol, XP score = -7.70 kcal/mol, SP score = -5.5 kcal/mol, ΔG_bind = -61.47 kcal/mol, ΔG_bind (average) = -60.71 kcal/mol; paromomycin, XP score = -7.23 kcal/mol, SP score = -6.18 kcal/mol, ΔG_bind = -50.14 kcal/mol, ΔG_bind (average) = -49.13 kcal/mol; zoledronate, XP score = -6.33 kcal/mol, SP score = -5.53 kcal/mol, ΔG_bind = -32.38 kcal/mol, ΔG_bind (average) = -29.42 kcal/mol; setmelanotide, XP score = -6.10 kcal/mol, SP score = -7.24 kcal/mol, ΔG_bind = -56.87 kcal/mol, ΔG_bind (average) = -62.41 kcal/mol; and theophylline, XP score = -5.17 kcal/mol, SP score = -5.55 kcal/mol, ΔG_bind = -33.25 kcal/mol, ΔG_bind (average) = -35.29 kcal/mol) that are potentially able to disrupt the dimerization of irisin. For this reason, they deserve further investigation to characterize them as irisin disruptors. Remarkably, the identification of drugs targeting this process can offer novel therapeutic opportunities for the treatment of LD. Furthermore, the identified drugs could provide a starting point for a repositioning approach, synthesizing novel analogs with improved efficacy and selectivity against the irisin dimerization process.

Knowledge Mapping of Drug Repositioning's Theme and Development

Background

In recent years, the emergence of new diseases and resistance to known diseases have led to increasing demand for new drugs. By means of bibliometric analysis, this paper studied the relevant articles on drug repositioning in recent years and analyzed the current research foci and trends.

Methodology

The Web of Science database was searched to collect all relevant literature on drug repositioning from 2001 to 2022. These data were imported into CiteSpace and bibliometric online analysis platforms for bibliometric analysis. The processed data and visualized images predict the development trends in the research field.

Results

The quality and quantity of articles published after 2011 have improved significantly, with 45 of them cited more than 100 times. Articles posted by journals from different countries have high citation values. Authors from other institutions have also collaborated to analyze drug rediscovery. Keywords found in the literature include molecular docking (N=223), virtual screening (N=170), drug discovery (N=126), machine learning (N=125), and drug-target interaction (N=68); these words represent the core content of drug repositioning.

Conclusion

The key focus of drug research and development is related to the discovery of new indications for drugs. Researchers are starting to retarget drugs after analyzing online databases and clinical trials. More and more drugs are being targeted at other diseases to treat more patients, based on saving money and time. It is worth noting that researchers need more financial and technical support to complete drug development.