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Epilepsy is a neurological disease with no defined cause, characterized by recurrent epileptic seizures. These occur due to the dysregulation of excitatory and inhibitory neurotransmitters in the central nervous system (CNS). Psychopharmaceuticals have undesirable side effects; many patients require more than one pharmacotherapy to control crises. With this in mind, this work emphasizes the discovery of new substances from natural products that can combat epileptic seizures. Using in silico techniques, this review aims to evaluate the antiepileptic and multi-target activity of phenylpropanoid derivatives. Initially, ligand-based virtual screening models (LBVS) were performed with 468 phenylpropanoid compounds to predict biological activities. The LBVS were developed for the targets alpha- amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), voltage-gated calcium channel Ttype (CaV), gamma-aminobutyric acid A (GABAA), gamma-aminobutyric acid transporter type 1 (GAT-1), voltage-gated potassium channel of the Q family (KCNQ), voltage-gated sodium channel (NaV), and N-methyl D-aspartate (NMDA). The compounds that had good results in the LBVS were analyzed for the absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters, and later, the best molecules were evaluated in the molecular docking consensus. The TR430 compound showed the best results in pharmacokinetic parameters; its oral absorption was 99.03%, it did not violate any Lipinski rule, it showed good bioavailability, and no cytotoxicity was observed either from the molecule or from the metabolites in the evaluated parameters. TR430 was able to bind with GABAA (activation) and AMPA (inhibition) targets and demonstrated good binding energy and significant interactions with both targets. The studied compound showed to be a promising molecule with a possible multi-target activity in both fundamental pharmacological targets for the treatment of epilepsy., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Alzheimer's disease (AD) has become the fourth leading cause of death in the world. Due to its complex pathogenesis, there is still a lack of effective drug treatments. Studies have found that the metal dyshomeostasis is closely related to other pathogeneses of AD such as oxidative stress, β-amyloid protein deposits, etc. Therefore, it becomes an important target to find the appropriate metal chelating agents to regulate the metal homeostasis. At the same time, because of the complex pathogenesis, single target drugs cannot achieve good effects. Therefore, current studies are mainly focused on exploring multi-target therapy for AD. In this work, the multi-target studies based on metal chelators and other targets with synergistic anti-AD activities were reviewed. The structural characteristics of different chelating agents were summarized and the structure-activity relationship was analyzed, which provided some valuable clues for the subsequent development of anti-AD multi-target drugs based on metal chelating agents., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Polypharmacology means drugs having interactions with multiple targets of a unique disease or many disease pathways. This concept has been greatly appreciated against complex diseases, such as oncology, CNS disorders, and anti-infectives., Methods: The integration of diverse compounds available on public databases initiates polypharmacological drug discovery research. Immunocompromised patients may suffer from complex diseases. Multiple-component drug formulations may produce side effects and resistance issues due to unintended drug-target interactions., Results: Polypharmacology remains a novel avenue to propose a more effective and less toxic treatment. The 4-amino quinoline scaffold has become an important construction motif for the development of new drugs against lifestyle diseases like cancer and infectious diseases like tuberculosis and malaria., Conclusion: The present study is an attempt to explore the polypharmacological effects of 4- aminoquinoline drugs to combat malaria, cancer, and tuberculosis., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Influenza viruses (INFV), the Orthomyxoviridae family, are mainly transmitted among humans via aerosols or droplets from the respiratory secretions. However, fomites could be a potential transmission pathway. Annually, seasonal INFV infections account for 290-650 thousand deaths worldwide. Currently, there are two classes of approved drugs to treat INFV infections, being neuraminidase (NA) inhibitors and blockers of matrix-2 (M2) ion channel. However, cases of resistance have been observed for both chemical classes, reducing the efficacy of treatment. The emergence of influenza outbreaks and pandemics calls for new antiviral molecules that are more effective, and that could overcome the current resistance to anti-influenza drugs. In this context, polyphenolic compounds are found in various plants, and these have displayed different multi-target approaches against diverse pathogens. Among these, green tea (Camellia sinensis) catechins, in special epigallocatechin-3-O-gallate (EGCG), have demonstrated significant activities against the two most relevant human INFV, subtypes A and lineages B. In this sense, EGCG has been found to be a promising multi-target agent against INFV since it can act inhibiting NA, hemagglutination (HA), RNA-dependent RNA polymerase (RdRp), and viral entry/adsorption. In general, the lack of knowledge about potential multi-target natural products prevents an adequate exploration of them, increasing the time for developing multi-target drugs. Then, this review aimed to compile most relevant studies showing the anti-INFV effects of EGCG and its derivatives, which could become antiviral drug prototypes in the future., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

In the drug development, the formation of highly selective ligands has been unsuccessful in the treatment of central nervous system disorders. Multi-target ligands, from the polypharmacology paradigm, are being proposed as treatments for these complex disorders, since they offer enhanced efficacy and a strong safety profile. Natural products are the best examples of multi-target compounds, so they are of high interest within this paradigm. Additionally, recent research on psychoactive drugs of natural origin, such as ayahuasca and cannabis, has demonstrated the promising therapeutic potential for the treatment of some psychiatric and neurological disorders. In this text, we describe how research on psychoactive drugs can be effectively combined with the polypharmacology paradigm, providing ayahuasca and cannabis research as examples. The advantages and disadvantages are also discussed., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Respiratory viruses continue to afflict mankind. Among them, pathogens such as coronaviruses [including the current pandemic agent known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)] and the one causing influenza A (IAV) are highly contagious and deadly. These can evade the immune system defenses while causing a hyperinflammatory response that can damage different tissues/organs. Simultaneously targeting several immunomodulatory proteins is a plausible antiviral strategy since it could lead to the discovery of indirect-acting pan-antiviral (IAPA) agents for the treatment of diseases caused by respiratory viruses. In this context, computational approaches, which are an essential part of the modern drug discovery campaigns, could accelerate the identification of multi-target immunomodulators. This perspective discusses the usefulness of computational multi-target drug discovery for the virtual screening (drug repurposing) of IAPA agents capable of boosting the immune system through the activation of the toll-like receptor 7 (TLR7) and/or the stimulator of interferon genes (STING) while inhibiting key inflammation-related proteins such as caspase-1 and tumor necrosis factor-alpha (TNF-α)., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Alzheimer's disease is characterized by a progressive pattern of cognitive and functional impairment, which ultimately leads to death. Computational approaches have played an important role in the context of drug discovery for anti-Alzheimer's therapies. However, most of the computational models reported to date have been focused on only one protein associated with Alzheimer's, while relying on small datasets of structurally related molecules., Objective: We introduce the first model combining perturbation theory and machine learning based on artificial neural networks (PTML-ANN) for simultaneous prediction and design of inhibitors of three Alzheimer's disease-related proteins, namely glycogen synthase kinase 3 beta (GSK3B), histone deacetylase 1 (HDAC1), and histone deacetylase 6 (HDAC6)., Methods: The PTML-ANN model was obtained from a dataset retrieved from ChEMBL, and it relied on a classification approach to predict chemicals as active or inactive., Results: The PTML-ANN model displayed sensitivity and specificity higher than 85% in both training and test sets. The physicochemical and structural interpretation of the molecular descriptors in the model permitted the direct extraction of fragments suggested to favorably contribute to enhancing the multitarget inhibitory activity. Based on this information, we assembled ten molecules from several fragments with positive contributions. Seven of these molecules were predicted as triple target inhibitors while the remaining three were predicted as dual-target inhibitors. The estimated physicochemical properties of the designed molecules complied with Lipinski's rule of five and its variants., Conclusion: This work opens new horizons toward the design of multi-target inhibitors for anti- Alzheimer's therapies., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Due to the three domains of the colchicine-site which is conducive to the combination with small molecule compounds, colchicine-site on the tubulin has become a common target for antitumor drug development, and accordingly, a large number of tubulin inhibitors binding to the colchicine-site have been reported and evaluated over the past years. In this study, tubulin inhibitors targeting the colchicine-site and their application as antitumor agents were reviewed based on the literature from 2015 to 2019. Tubulin inhibitors were classified into ten categories according to the structural features, including colchicine derivatives, CA-4 analogs, chalcone analogs, coumarin analogs, indole hybrids, quinoline and quinazoline analogs, lignan and podophyllotoxin derivatives, phenothiazine analogs, N-heterocycle hybrids and others. Most of them displayed potent antitumor activity, including antiproliferative effects against Multi-Drug-Resistant (MDR) cell lines and antivascular properties, both in vitro and in vivo. In this review, the design, synthesis and the analysis of the structure-activity relationship of tubulin inhibitors targeting the colchicine-site were described in detail. In addition, multi-target inhibitors, anti-MDR compounds, and inhibitors bearing antitumor activity in vivo are further listed in tables to present a clear picture of potent tubulin inhibitors, which could be beneficial for medicinal chemistry researchers., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Protein Kinase Inhibitors (PKIs) and Histone Deacetylase Inhibitors (HDACIs) are two important classes of anticancer agents and have provided a variety of small molecule drugs for the treatment of various types of human cancers. However, malignant tumors are of a multifactorial nature that can hardly be "cured" by targeting a single target, and treatment of cancers hence requires modulation of multiple biological targets to restore the physiological balance and generate sufficient therapeutic efficacy. Multi-target drugs have attracted great interest because of their advantages in the treatment of complex cancers by simultaneously targeting multiple signaling pathways and possibly leading to synergistic effects. Synergistic effects have been observed in the combination of kinase inhibitors, such as imatinib, dasatinib, or sorafenib, with an array of HDACIs including vorinostat, romidepsin, or panobinostat. A considerable number of multi-target agents based on PKIs and HDACIs have been developed. In this review, we summarize the recent literature on the development of multi-target kinase-HDAC inhibitors and provide our view on the challenges and future directions on this topic., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Since the last century, when scientists proposed the lock-and-key model, the discovery of drugs has focused on the development of drugs acting on single target. However, single-target drug therapies are not effective to complex diseases with multi-factorial pathogenesis. Moreover, the combination of single-target drugs readily causes drug resistance and side effects. In recent years, multi-target drugs have increasingly been represented among FDA-approved drugs. Alzheimer's Disease (AD) is a complex and multi-factorial disease for which the precise molecular mechanisms are still not fully understood. In recent years, rational multi-target drug design methods, which combine the pharmacophores of multiple drugs, have been increasingly applied in the development of anti-AD drugs. In this review, we give a brief description of the pathogenesis of AD and provide detailed discussions about the recent development of chemical structures of anti-AD agents (2013 up to present) that have multiple targets, such as amyloid-β peptide, Tau protein, cholinesterases, monoamine oxidase, β-site amyloid-precursor protein-cleaving enzyme 1, free radicals, metal ions (Fe2+, Cu2+, Zn2+) and so on. In this paper, we also added some novel targets or possible pathogenesis which have been reported in recent years for AD therapy. We hope that these findings may provide new perspectives for the pharmacological treatment of AD., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

The discovery of drugs for diseases of the central nervous system (CNS) faces high attrition rates in clinical trials. Neural diseases are extremely complex in nature and typically associated with multiple drug targets. A conception of multi-target directed ligands (MTDL), widely applied to the discovery of cancer pharmaceuticals, may be a perspective solution for CNS diseases. Special bioinformatics approaches have been developed which can assist the medicinal chemists in identification and structural optimization of MTDL. In this review, we analyze the current status of the development of multitarget approaches in quantitative structure-activity relationships (mt-QSAR) for CNS drug discovery; and describes applications of multi-target approaches in molecular modelling (which can be called mt-MM), as well as perspectives for multi-target approaches in bioinformatics in relation to Alzheimer's disease., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

The exponential growth of cancer cases worldwide together with recent advances concerning the pathophysiological mechanisms of the disease at the molecular level led to a paradigm shift in chemotherapy, from monotherapy to targeted drug combination regimens. However, adverse effects and the emergence of multidrug resistance (MDR) limit the effectiveness of these therapies. In this context, hybrid combinations mixing anticancer drugs and bioactive phytochemical components from medicinal plants, or even plant extracts, that can act synergistically on multiple targets and signaling pathways represent a promising approach with the potential to expand the current therapeutic arsenal. This review aims to provide a synopsis on anticancer hybrid combinations based on their multi-target mechanisms and synergistic effects from an extensive literature search focusing mainly on publications from the last ten years. In most of these combinations, the phytochemical component was shown to enhance the anticancer activity of the chemotherapeutic agent and to sensitize chemoresistant tumors in several types of cancer. Hybrid combinations, due to synergistic interactions, are also associated with less severe adverse events since lower doses can be used to achieve the same therapeutic effect. Further preclinical and clinical studies are needed, as well as the development of an adequate regulatory framework, before hybrid combination therapy can be translated into clinical practice., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Traumatic brain injury (TBI) is a major healthcare problem that affects millions of people worldwide. Despite advances in understanding and developing preventative and treatment strategies using preclinical animal models, clinical trials to date have failed, and a 'magic bullet' for effectively treating TBI-induced damage does not exist. Thus, novel pharmacological strategies to effectively manipulate the complex and heterogeneous pathophysiology of secondary injury mechanisms are needed. Given that goal, this paper discusses the relevance and advantages of combination therapies (COMTs) for 'multi-target manipulation' of the secondary injury cascade by administering multiple drugs to achieve an optimal therapeutic window of opportunity (e.g., temporally broad window) and compares these regimens to monotherapies that manipulate a single target with a single drug at a given time. Furthermore, we posit that integrated mechanistic multiscale models that combine primary injury biomechanics, secondary injury mechanobiology/neurobiology, physiology, pharmacology and mathematical programming techniques could account for vast differences in the biological space and time scales and help to accelerate drug development, to optimize pharmacological COMT protocols and to improve treatment outcomes., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

There has been a growing interest in the rational design of multi-targeted drugs with the aim of enhancing overall efficacy and/or improving safety. The development of multi-targeted drugs might yield new avenues in the treatment of cancers that involve multiple pathogenic factors. In this review, we focus on the multi-targeted metal-based anticancer agents, which include platinum, ruthenium, rhodium, gold, silver, copper, cobalt, zinc, and nickel complexes. Future directions for the development of multi-targeted metal-based anticancer agents are also proposed., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

Cancer is a multifactorial disease and most of its types still remain incurable, in spite of enormous efforts to explicate various tumor pathophysiology. The anti-cancer drug discovery paradigm "one-compound-one-target" has failed and subsequently shifted to two-drug cocktail and recently the "multi-target approach" in order to design and develop agents able to act simultaneously on multiple intracellular constituents and signaling pathways. Novel hybrid compounds are now designed by incorporating two covalently linked independently acting pharmacores, each efficient at combating cancer. They can deliver synergistic effects from the dual action of both independently acting moieties by interacting with multiple targets. These composite molecules are also less prone to drug resistance, leading to an improved pharmacological potency than each individual moiety. As indole nucleus is a central component of many natural and synthetic molecules with extensive biological activity, this review incorporates a variety of such hybrid compounds with indole moiety as one of the active units, where better therapeutic effect has been successfully achieved, by either simultaneous or sequential action of individual functional pharmacore. The current limitations and challenges encountered in the development of these hybrid agents are also discussed., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

Multi-target drugs against particular multiple targets get better protection, resistance profiles and curative influence by cooperative rules of a key beneficial target with resistance behavior and compensatory elements. Computational techniques can assist us in the efforts to design novel drugs (ligands) with a preferred bioactivity outline and alternative bioactive molecules at an early stage. A number of in silico methods have been explored extensively in order to facilitate the investigation of individual target agents and to propose a selective drug. A different, progressively more significant field which is used to predict the bioactivity of chemical compounds is the data mining method. Some of the previously mentioned methods have been investigated for multi-target drug design (MTDD) to find drug leads interact simultaneously with multiple targets. Several cheminformatics methods and structure-based approaches try to extract information from units working cooperatively in a biomolecular system to fulfill their task. To dominate the difficulties of the experimental specification of ligand-target structures, rational methods, namely molecular docking, SAR and QSAR are vital substitutes to obtain knowledge for each structure in atomic insight. These procedures are logically successful for the prediction of binding affinity and have shown promising potential in facilitating MTDD. Here, we review some of the important features of the multi-target therapeutics discoveries using the computational approach, highlighting the SAR, QSAR, docking and pharmacophore methods to discover interactions between drug-target that could be leveraged for curative benefits. A summary of each, followed by examples of its applications in drug design has been provided. Computational efficiency of each method has been represented according to its main strengths and limitations., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

Finding high quality beginning compounds is a critical job at the start of the lead generation stage for multi-target drug discovery (MTDD). Designing hybrid compounds as selective multitarget chemical entity is a challenge, opportunity, and new idea to better act against specific multiple targets. One hybrid molecule is formed by two (or more) pharmacophore group's participation. So, these new compounds often exhibit two or more activities going about as multi-target drugs (mtdrugs) and may have superior safety or efficacy. Application of integrating a range of information and sophisticated new in silico, bioinformatics, structural biology, pharmacogenomics methods may be useful to discover/design, and synthesis of the new hybrid molecules. In this regard, many rational and screening approaches have followed by medicinal chemists for the lead generation in MTDD. Here, we review some popular lead generation approaches that have been used for designing multiple ligands (DMLs). This paper focuses on dual- acting chemical entities that incorporate a part of two drugs or bioactive compounds to compose hybrid molecules. Also, it presents some of key concepts and limitations/strengths of lead generation methods by comparing combination framework method with screening approaches. Besides, a number of examples to represent applications of hybrid molecules in the drug discovery are included., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

The genus Cissampelos comprises of 21 species which have a wide global distribution and various pharmacological activities such as analgesic and antipyretic, antiinflammatory, anti-allergic, bronchodilation, and immunomodulation among others. Several compounds, mainly alkaloids with differing biological activities have been isolated from this genus. We will highlight antipyretic activities, anti-inflammatory, antiallergic, bronchodilatory, and immunomodulatory activities. In addition, we applied ligand-based-virtual screening associated with structure-based-virtual screening of a small dataset of 63 secondary metabolites from the Cissampelos genus of an in-house data bank, in order to select compounds with potential anti-inflammatory activity. Affinities were observed for hayatine (26), isochondrondendrine (30), pelosine (52), sepeerine (59), and warifteine (63) to the inhibiting enzymes MAPK p38 alpha, PKC beta, PKC theta and PKC zeta. The cissampeloflavone compound (8) alone showed no potential inhibitory activity for PKC zeta, or affinity for the PKC alpha. The compounds can be used as starting points for further studies on structures with potential anti-inflammatory activity., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)