MDM2 Inhibitors for Cancer Therapy: The Past, Present, and Future DOI Creative Commons
Wei Wang,

Najah Albadari,

Yi Du

et al.

Pharmacological Reviews, Journal Year: 2024, Volume and Issue: 76(3), P. 414 - 453

Published: March 15, 2024

Since its discovery over 35 years ago, MDM2 has emerged as an attractive target for the development of cancer therapy. MDM29s activities extend from carcinogenesis to immunity, response various therapies. report first inhibitor more than 30 approaches inhibit have been attempted, with hundreds small molecule inhibitors evaluated in preclinical studies and numerous molecules tested clinical trials. Although many degraders trials, there is currently no FDA-approved on market. Nevertheless, are several current trials promising agents that may overcome past failures, including granted FDA orphan drug or fast-track status. We herein summarize research efforts discover develop inhibitors, focusing those induce degradation exert anticancer activity, regardless p53 status cancer. also describe how investigations moved towards combining other agents, immune checkpoint inhibitors. Finally, we discuss challenges future directions accelerate application In conclusion, targeting remains a treatment approach, protein represents novel strategy downregulate without side effects existing blocking p53-MDM2 binding. Additional needed finally realize full potential inhibition treating chronic diseases where implicated. Significance Statement Overexpression/amplification oncogene detected human cancers associated disease progression, resistance, poor patient outcomes. Herein, review previous, emerging MDM2-targeted therapies chemotherapy immunotherapy regimens. The findings these contemporary lead safer effective treatments patients overexpressing MDM2.

Language: Английский

A Perspective on Multi-target Drugs for Alzheimer’s Disease DOI
Ondřej Benek, Jan Korábečný, Ondřej Soukup

et al.

Trends in Pharmacological Sciences, Journal Year: 2020, Volume and Issue: 41(7), P. 434 - 445

Published: May 21, 2020

Language: Английский

Citations

204
<p>Potential Impact of the Multi-Target Drug Approach in the Treatment of Some Complex Diseases</p> DOI Creative Commons
Xolani Henry Makhoba, Cláudio Viegas, Rebamang A. Mosa

et al.

Drug Design Development and Therapy, Journal Year: 2020, Volume and Issue: Volume 14, P. 3235 - 3249

Published: Aug. 1, 2020

Abstract: It is essential to acknowledge the efforts made thus far manage or eliminate various disease burden faced by humankind. However, rising global trends of so-called incurable diseases continue put pressure on Pharma industries and other drug discovery platforms. In past, drugs with more than one target were deemed as undesirable options interest being one-drug-single target. Despite successes single-target drugs, it currently beyond doubt that these have limited efficacy against complex in which pathogenesis dependent a set biochemical events several bioreceptors operating concomitantly. Different approaches been proposed come up effective combat even diseases. focus was producing from screening plant compounds; today, we talk about combination therapy multi-targeting drugs. The multi-target recently attracted much attention promising tools fight most challenging diseases, new research area. This review will discuss potential impact approach malaria, tuberculosis (TB), diabetes neurodegenerative main representatives multifactorial We also alternative ideas solve current problems bearing mind fourth industrial revolution discovery. Keywords: diabetes,

Language: Английский

Citations

197
Dual Inhibitors of Human DNA Topoisomerase II and Other Cancer-Related Targets DOI Creative Commons
Žiga Skok, Nace Zidar, D. Kikelj

et al.

Journal of Medicinal Chemistry, Journal Year: 2019, Volume and Issue: 63(3), P. 884 - 904

Published: Oct. 8, 2019

Human DNA topoisomerase II is an important target in anticancer therapy. Despite the clinical success of drugs that II, development resistant cancer cells can limit their efficacy. To maximize therapeutic potential drugs, combination therapies and multitarget have been suggested many studies, where use advantageous from a pharmacokinetic point view. There are various different options for preparation dual-target or multiple-target inhibitors, as both structurally (e.g., I, Hsp90, kinases) functionally histone deacetylases proteasome) connected to validated targets. In this Perspective, we discuss scientific background behind targeting together with number other targets therapy, review present status, further field.

Language: Английский

Citations

171
An omics perspective on drug target discovery platforms DOI Creative Commons
Jussi Paananen, Vittorio Fortino

Briefings in Bioinformatics, Journal Year: 2019, Volume and Issue: 21(6), P. 1937 - 1953

Published: Aug. 27, 2019

The drug discovery process starts with identification of a disease-modifying target. This critical step traditionally begins manual investigation scientific literature and biomedical databases to gather evidence linking molecular target disease, evaluate the efficacy, safety commercial potential high-throughput affordability current omics technologies, allowing quantitative measurements many putative targets (e.g. DNA, RNA, protein, metabolite), has exponentially increased volume data available for this arduous task. Therefore, computational platforms identifying ranking disease-relevant from existing sources, including databases, are needed. To date, more than 30 (DTD) exist. They provide information-rich graphical user interfaces help scientists identify pre-evaluate their therapeutic efficacy side effects. Here we survey compare set popular DTD that utilize multiple sources omics-driven knowledge bases (either directly or indirectly) targets. We also description technologies related repositories which important tasks.

Language: Английский

Citations

164
Anticancer Therapy with HDAC Inhibitors: Mechanism-Based Combination Strategies and Future Perspectives DOI Open Access
Robert Jenke,

Nina Reßing,

Finn K. Hansen

et al.

Cancers, Journal Year: 2021, Volume and Issue: 13(4), P. 634 - 634

Published: Feb. 5, 2021

The increasing knowledge of molecular drivers tumorigenesis has fueled targeted cancer therapies based on specific inhibitors. Beyond “classic” oncogene inhibitors, epigenetic therapy is an emerging field. Epigenetic alterations can occur at any time during progression, altering the structure chromatin, accessibility for transcription factors and thus genes. They rely post-translational histone modifications, particularly acetylation lysine residues, are determined by inverse action acetyltransferases (HATs) deacetylases (HDACs). Importantly, HDACs often aberrantly overexpressed, predominantly leading to transcriptional repression tumor suppressor Thus, deacetylase inhibitors (HDACis) powerful drugs, with some already approved certain hematological cancers. Albeit HDACis show activity in solid tumors as well, further refinement development novel drugs needed. This review describes capability influence various pathways and, this knowledge, gives a comprehensive overview preclinical clinical studies tumors. A particular focus placed strategies achieving higher efficacy combination therapies, including phosphoinositide 3-kinase (PI3K)-EGFR hormone- or immunotherapy. also includes new bifunctional well approaches HDAC degradation via PROteolysis-TArgeting Chimeras (PROTACs).

Language: Английский

Citations

137
Medicinal chemistry strategies for discovering antivirals effective against drug-resistant viruses DOI
Yue Ma, Estrella Frutos-Beltrán, Dongwei Kang

et al.

Chemical Society Reviews, Journal Year: 2021, Volume and Issue: 50(7), P. 4514 - 4540

Published: Jan. 1, 2021

This review summarizes current advances in medicinal chemistry aimed at the discovery of antiviral compounds specifically targeted against drug-resistant strains.

Language: Английский

Citations

135
TranSynergy: Mechanism-driven interpretable deep neural network for the synergistic prediction and pathway deconvolution of drug combinations DOI Creative Commons
Qiao Liu, Lei Xie

PLoS Computational Biology, Journal Year: 2021, Volume and Issue: 17(2), P. e1008653 - e1008653

Published: Feb. 12, 2021

Drug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. The fast-growing number of anti-cancer drugs has caused the experimental investigation all to become costly time-consuming. Computational techniques can efficiency combination screening. Despite recent advances applying machine learning synergistic prediction, several challenges remain. First, performance existing methods is suboptimal. There still much space for improvement. Second, biological knowledge not been fully incorporated into model. Finally, many models are lack interpretability, limiting their clinical applications. To address these challenges, we developed a knowledge-enabled self-attention transformer boosted deep model, TranSynergy, which improves interpretability prediction. TranSynergy designed so that cellular effect actions be explicitly modeled through cell-line gene dependency, gene-gene interaction, genome-wide drug-target interaction. A novel Shapley Additive Gene Set Enrichment Analysis (SA-GSEA) method deconvolute genes contribute model interpretability. Extensive benchmark studies demonstrate outperforms state-of-the-art method, suggesting mechanism-driven learning. Novel pathways associated with revealed supported by evidences. may provide new insights identifying biomarkers precision medicine discovering therapies. Several predicted high confidence ovarian few treatment options. code available at https://github.com/qiaoliuhub/drug_combination.

Language: Английский

Citations

123
Network-based modeling of herb combinations in traditional Chinese medicine DOI Creative Commons
Yinyin Wang, Hongbin Yang, Linxiao Chen

et al.

Briefings in Bioinformatics, Journal Year: 2021, Volume and Issue: 22(5)

Published: March 11, 2021

Traditional Chinese medicine (TCM) has been practiced for thousands of years treating human diseases. In comparison to modern medicine, one the advantages TCM is principle herb compatibility, known as formulae. A formula usually consists multiple herbs achieve maximum treatment effects, where their interactions are believed elicit therapeutic effects. Despite being a fundamental component TCM, rationale combining specific combinations remains unclear. this study, we proposed network-based method quantify in pairs. We constructed protein-protein interaction network given pair by retrieving associated ingredients and protein targets, determined distances including closest, shortest, center, kernel, separation, both at ingredient target levels. found that frequently used pairs tend have shorter compared random pairs, suggesting more likely affect neighboring proteins interactome. Furthermore, center distance level improves discrimination top-frequent from considering topologically important inferring mechanisms action TCM. Taken together, provided pharmacology framework degree interactions, which shall help explore space effectively identify synergistic compound based on topology.

Language: Английский

Citations

106
Chalcone and its analogs: Therapeutic and diagnostic applications in Alzheimer’s disease DOI
Pritam Thapa, Sunil P. Upadhyay,

William Z. Suo

et al.

Bioorganic Chemistry, Journal Year: 2021, Volume and Issue: 108, P. 104681 - 104681

Published: Jan. 29, 2021

Language: Английский

Citations

105
Polypharmacology: The science of multi-targeting molecules DOI

Abbas Kabir,

Aaron Muth

Pharmacological Research, Journal Year: 2022, Volume and Issue: 176, P. 106055 - 106055

Published: Jan. 3, 2022

Language: Английский

Citations

102