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Computational Biology and Bioinformatics in Anti-SARS-CoV-2 Drug Development
Published in Debmalya Barh, Kenneth Lundstrom, COVID-19, 2022
It is now recognized that the desired effects of most therapeutics are exerted via modulation of multiple targets and pathways [164–167], whereas severe side effects can sometimes be associated with the excessive selectivity of a drug for a single target [168]. Moreover, it deals with pharmaceutical agents characterized by the promiscuous binding to multiple targets and acting on multiple disease pathways, thereby generating different phenotypic or pharmacological effects [167]. Polypharmacology deals with multi-target binding, drug off targeting, and molecular promiscuity, and thereby opposes the “single drug, single target” approach. Therefore, polypharmacology has emerged as a powerful alternative paradigm for development of versatile therapeutic agents capable of modulating multiple biological targets simultaneously, often displaying higher efficacy, less resistance, and an improved safety profile [169]. It is important to emphasize that, while in the past the identification of multi-targeting agents has largely been fortuitous and serendipitous, recent advances in computational sciences enable rational design of drug polypharmacology (reviewed in [167, 170, 171]). Since a single therapeutic can act on multiple targets and a single target can be affected by multiple therapeutics, one can differentiate ligand-based and target-based polypharmacology, whereas network pharmacology integrates multi-omics technologies and systems biology for drug discovery and development [172].
Computer-Aided Drug Design for the Identification of Multi-Target Directed Ligands (MTDLs) in Complex Diseases: An Overview
Published in Peter Grunwald, Pharmaceutical Biocatalysis, 2019
Complex diseases such as cancer, multiple sclerosis, osteoporosis, and neurodegenerative diseases, whose origin is multi-factorial in nature, are caused by a combination of several factors associated with genetic, environment, and lifestyle (Craig, 2008). Thus, in the present scenario, drugs acting on a single target enzyme or receptor are inadequate for the treatment of complex diseases. An emerging approach, i.e., multi-target drug designing (MTDD), focuses on the development of a single ligand that can act on multiple targets simultaneously. Such ligands are termed as multi-target directed ligands (MTDLs). Polypharmacology is a branch of pharmaceutical science that deals with the development of MTDLs that can hit multiple targets for same or multiple disease pathways (Jalencas and Mestres, 2013). It has emerged as the next paradigm in rational drug design (RDD) under drug discovery, particularly for the complex diseases (Ambure and Roy, 2017; Roy, 2019).
Development and Commercialization of Asiaticoside in Madagascar
Published in Charles Wambebe, African Indigenous Medical Knowledge and Human Health, 2018
Philippe Rasoanaivo, Alain Loiseau, Lucile Allorge-Boiteau, Vinany Loharanombato
One relevant example of drug polypharmacology and drug repositioning is the plant-derived drug aspirin, often used as an analgesic to relieve minor pains or as an antipyretic to reduce fever, and also acts as an anti-inflammatory medication to treat rheumatoid arthritis, pericarditis, and Kawasaki diseases. Additionally, it has been used in the prevention of transient ischemic attacks, strokes, and heart attacks. Triterpenoids of C. asiatica are also a good example of drug polypharmacology and drug repositioning. First used as a wound healing drug, they became key compounds in the cosmetic industry (Loiseau and Mercier, 2000). It was speculated that “the origins of polypharmacology lie precisely at the heart of protein evolution” (Jalencas and Mestres, 2013), meaning that natural products preferentially target proteins, which are essential to an organism, because these are effective defense substances (Dancik et al., 2010). Polypharmacology thus reflects the mechanisms of adaptation of biological systems to increase the chances of survival in an adverse environment. As exemplified by C. asiatica, many medicinal plants have multipurpose applications. It is therefore worthwhile to investigate medicinal plants within the paradigm of polypharmacology. Serendipitous observations using reverse pharmacology may help in this approach. At the African Network for Drug and Diagnostic Innovation (ANDI) meeting in Nairobi in 2010, Bernard Munos said: “Innovation thrives from the interaction between innovators and users; the majority (59%) of drug innovation come not from drug companies, but from doctors trying to help patients for whom standard therapy had failed.”
Antihistamines, phenothiazine-based antipsychotics, and tricyclic antidepressants potently activate pharmacologically relevant human carbonic anhydrase isoforms II and VII
Published in Journal of Enzyme Inhibition and Medicinal Chemistry, 2023
Francesco Fiorentino, Alessio Nocentini, Dante Rotili, Claudiu T. Supuran, Antonello Mai
In line with the importance of hCA activation in the CNS, many psychoactive drugs and therapeutically used histamine receptor modulators, including antihistamines, all of which bear potential PSMs (i.e. protonable moieties such as imidazole, amine, guanidine or its bioisosteres), have been recently indicated to also act as CAAs.49,50 Similarly, selective serotonin reuptake inhibitors antidepressants such as fluoxetine, sertraline, and citalopram have been shown to act as hCAI and II activators.51 In contrast, no antipsychotic drugs have been shown to activate CAs, with the atypical antipsychotics sulpiride and aripiprazole actually inhibiting hCAI/II and hCAI/II/IV, respectively.52,53 Overall, these data suggest that the therapeutic and/or adverse effects of many marketed drugs may be linked to a polypharmacology-based mode of action.
Promiscuity in drug discovery on the verge of the structural revolution: recent advances and future chances
Published in Expert Opinion on Drug Discovery, 2023
Sarah Naomi Bolz, Michael Schroeder
Polypharmacology is believed to be particularly important for the treatment of complex diseases like cancer, neurodegenerative diseases, or infection. The development and progression of such multifactorial diseases usually involve multiple signaling pathways and physiological processes. Therefore, modulating a single target may not be sufficient to achieve a therapeutic effect, and increasing attention is being paid to developing promiscuous drugs [41–44]. In cancer, multi-kinase inhibitors targeting several processes contributing to tumor growth and metastasis are already used in the clinic [39,45]. Another example are antibiotics, where the manipulation of multiple targets can increase efficacy and delay the development of resistance [46,47]. The most successful long-established antibiotics actually act on multiple targets or genes [47].
Reinforcement learning for systems pharmacology-oriented and personalized drug design
Published in Expert Opinion on Drug Discovery, 2022
Ryan K. Tan, Yang Liu, Lei Xie
Recently, the attention to polypharmacology is constantly increasing owing to its therapeutic potential in some complex pathologies. Dual-target ligand generative network (DLGN), leveraging RL and adversarial training, was developed to generate molecules that have bioactivities toward two targets [74]. With SMILES string as input, DLGN uses an RNN-based generator to produce novel molecules that satisfy the predefined constraints. To make generated molecules dual-targeted, DLGN utilizes two discriminators to monitor the generative process and encourages the generated molecules lying in the intersection of the two bioactive-compound distributions. The drawback of this model is that, although the generator does not need to be trained with labeled data, the discriminators require reliable labeled data to control the qualities of generated molecules.