Recently, using artificial intelligence (AI) in drug discovery has received much attention since it significantly shortens the time and cost of developing new drugs. Deep learning (DL)-based approaches are increasingly being used in all stages of drug development as DL technology advances, and drug-related data grows. Therefore, this paper presents a systematic Literature review (SLR) that integrates the recent DL technologies and applications in drug discovery Including, drug–target interactions (DTIs), drug–drug similarity interactions (DDIs), drug sensitivity and responsiveness, and drug-side effect predictions. We present a review of more than 300 articles between 2000 and 2022. The benchmark data sets, the databases, and the evaluation measures are also presented. In addition, this paper provides an overview of how explainable AI (XAI) supports drug discovery problems. The drug dosing optimization and success stories are discussed as well. Finally, digital twining (DT) and open issues are suggested as future research challenges for drug discovery problems. Challenges to be addressed, future research directions are identified, and an extensive bibliography is also included.

(1) Background: Drug repositioning is an unconventional drug discovery approach to explore new therapeutic benefits of existing drugs. Currently, it emerges as a rapid avenue to alleviate the COVID-19 pandemic disease. (2) Methods: Herein, we tested the antiviral activity of anti-microbial and anti-inflammatory Food and Drug Administration (FDA)-approved drugs, commonly prescribed to relieve respiratory symptoms, against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the viral causative agent of the COVID-19 pandemic. (3) Results: Of these FDA-approved antimicrobial drugs, Azithromycin, Niclosamide, and Nitazoxanide showed a promising ability to hinder the replication of a SARS-CoV-2 isolate, with IC₅₀ of 0.32, 0.16, and 1.29 µM, respectively. We provided evidence that several antihistamine and anti-inflammatory drugs could partially reduce SARS-CoV-2 replication in vitro. Furthermore, this study showed that Azithromycin can selectively impair SARS-CoV-2 replication, but not the Middle East Respiratory Syndrome Coronavirus (MERS-CoV). A virtual screening study illustrated that Azithromycin, Niclosamide, and Nitazoxanide bind to the main protease of SARS-CoV-2 (Protein data bank (PDB) ID: 6lu7) in binding mode similar to the reported co-crystalized ligand. Also, Niclosamide displayed hydrogen bond (HB) interaction with the key peptide moiety GLN: 493A of the spike glycoprotein active site. (4) Conclusions: The results suggest that Piroxicam should be prescribed in combination with Azithromycin for COVID-19 patients.

Spirooxindole is a promising chemo therapeutic agent. Possible targets include cancers of the liver, prostate, lung, stomach, colon, and breast. Here, we demonstrate a one-pot three-component reaction via a [3 + 2] cycloaddition/ring contraction sequence of a dipolarophile (activated alkene) with in situ-generated azomethine ylide (1,3-dipoles) without the use of any catalyst. The reaction provides efficient access to synthetically useful and biologically important spirooxindoles in high yield (69–94%) with high diastereoselectivity. The synthesized compounds were subjected to cytotoxicity evaluation using colorectal cancer (HCT-116), hepatocellular carcinoma (HepG2), and prostate cancer (PC-3) cells. Compounds 4i, 4j, and 4k showed potent cytotoxic activity and high selectivity against HCT-116 cells when compared to cisplatin. Meanwhile compound 4d retained high cytotoxic activity and selectivity against HepG2 and PC-3 cells in comparison to cisplatin. The mechanism of compound 4d was further studied using phosphodiesterase 1 enzyme and showed 74.2% inhibitory activity. A possible binding mode for compound 4d to PDE-1 was investigated by molecular modeling using OpenEye software. Pose predictions for the active compounds were demonstrated by ROCS alignments. Compound 4d has a special geometry and differs from other active compounds.