Journal articles: 'Multi-target compound'

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Feldmann, Christian, Dimitar Yonchev, and Jürgen Bajorath. "Structured data sets of compounds with multi-target and corresponding single-target activity from biological assays." Future Science OA 7, no. 5 (June 2021): FSO685. http://dx.doi.org/10.2144/fsoa-2020-0209.

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Aim: Providing compound data sets for promiscuity analysis with single-target (ST) and multi-target (MT) activity, taking confirmed inactivity against targets into account. Methodology: Compounds and target annotations are extracted from screening assays. For a given combination of targets, MT and ST compounds are identified, ensuring test data completeness. Exemplary results & data: A total of 1242 MT compounds active against five or more targets and 6629 corresponding ST compounds are characterized, organized and made freely available. Limitations & next steps: Screening campaigns typically cover a smaller target space than compounds from the medicinal chemistry literature and their activity annotations might be of lesser quality. Reported compound groups will be subjected to target set-based promiscuity analysis and predictions.

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Feldmann, Christian, Dimitar Yonchev, and Jürgen Bajorath. "Analysis of Biological Screening Compounds with Single- or Multi-Target Activity via Diagnostic Machine Learning." Biomolecules 10, no. 12 (November 27, 2020): 1605. http://dx.doi.org/10.3390/biom10121605.

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Predicting compounds with single- and multi-target activity and exploring origins of compound specificity and promiscuity is of high interest for chemical biology and drug discovery. We present a large-scale analysis of compound promiscuity including two major components. First, high-confidence datasets of compounds with multi- and corresponding single-target activity were extracted from biological screening data. Positive and negative assay results were taken into account and data completeness was ensured. Second, these datasets were investigated using diagnostic machine learning to systematically distinguish between compounds with multi- and single-target activity. Models built on the basis of chemical structure consistently produced meaningful predictions. These findings provided evidence for the presence of structural features differentiating promiscuous and non-promiscuous compounds. Machine learning under varying conditions using modified datasets revealed a strong influence of nearest neighbor relationship on the predictions. Many multi-target compounds were found to be more similar to other multi-target compounds than single-target compounds and vice versa, which resulted in consistently accurate predictions. The results of our study confirm the presence of structural relationships that differentiate promiscuous and non-promiscuous compounds.

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Qureshi, Shahrukh, Ravina Khandelwal, Maddala Madhavi, Naveesha Khurana, Neha Gupta, Saurav K. Choudhary, Revathy A. Suresh, et al. "A Multi-target Drug Designing for BTK, MMP9, Proteasome and TAK1 for the Clinical Treatment of Mantle Cell Lymphoma." Current Topics in Medicinal Chemistry 21, no. 9 (May 26, 2021): 790–818. http://dx.doi.org/10.2174/1568026621666210119112336.

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Background: Mantle cell lymphoma (MCL) is a type of non-Hodgkin lymphoma characterized by the mutation and overexpression of the cyclin D1 protein by the reciprocal chromosomal translocation t(11;14)(q13:q32). Aim: The present study aims to identify potential inhibition of MMP9, Proteasome, BTK, and TAK1 and determine the most suitable and effective protein target for the MCL. Methodology: Nine known inhibitors for MMP9, 24 for proteasome, 15 for BTK and 14 for TAK1 were screened. SB-3CT (PubChem ID: 9883002), oprozomib (PubChem ID: 25067547), zanubrutinib (PubChem ID: 135565884) and TAK1 inhibitor (PubChem ID: 66760355) were recognized as drugs with high binding capacity with their respective protein receptors. 41, 72, 102 and 3 virtual screened compounds were obtained after the similarity search with compound (PubChem ID:102173753), PubChem compound SCHEMBL15569297 (PubChem ID:72374403), PubChem compound SCHEMBL17075298 (PubChem ID:136970120) and compound CID: 71814473 with best virtual screened compounds. Results: MMP9 inhibitors show commendable affinity and good interaction profile of compound holding PubChem ID:102173753 over the most effective established inhibitor SB-3CT. The pharmacophore study of the best virtual screened compound reveals its high efficacy based on various interactions. The virtual screened compound's better affinity with the target MMP9 protein was deduced using toxicity and integration profile studies. Conclusion: Based on the ADMET profile, the compound (PubChem ID: 102173753) could be a potent drug for MCL treatment. Similar to the established SB-3CT, the compound was non-toxic with LD50 values for both the compounds lying in the same range.

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Rodríguez-Pérez, Raquel, and Jürgen Bajorath. "Evaluation of multi-target deep neural network models for compound potency prediction under increasingly challenging test conditions." Journal of Computer-Aided Molecular Design 35, no. 3 (February 17, 2021): 285–95. http://dx.doi.org/10.1007/s10822-021-00376-8.

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AbstractMachine learning (ML) enables modeling of quantitative structure–activity relationships (QSAR) and compound potency predictions. Recently, multi-target QSAR models have been gaining increasing attention. Simultaneous compound potency predictions for multiple targets can be carried out using ensembles of independently derived target-based QSAR models or in a more integrated and advanced manner using multi-target deep neural networks (MT-DNNs). Herein, single-target and multi-target ML models were systematically compared on a large scale in compound potency value predictions for 270 human targets. By design, this large-magnitude evaluation has been a special feature of our study. To these ends, MT-DNN, single-target DNN (ST-DNN), support vector regression (SVR), and random forest regression (RFR) models were implemented. Different test systems were defined to benchmark these ML methods under conditions of varying complexity. Source compounds were divided into training and test sets in a compound- or analog series-based manner taking target information into account. Data partitioning approaches used for model training and evaluation were shown to influence the relative performance of ML methods, especially for the most challenging compound data sets. For example, the performance of MT-DNNs with per-target models yielded superior performance compared to single-target models. For a test compound or its analogs, the availability of potency measurements for multiple targets affected model performance, revealing the influence of ML synergies.

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Blaschke, Thomas, and Jürgen Bajorath. "Compound dataset and custom code for deep generative multi-target compound design." Future Science OA 7, no. 6 (July 2021): FSO715. http://dx.doi.org/10.2144/fsoa-2021-0033.

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Aim: Generating a data and software infrastructure for evaluating multi-target compound (MT-CPD) design via deep generative modeling. Methodology: The REINVENT 2.0 approach for generative modeling was extended for MT-CPD design and a large benchmark data set was curated. Exemplary results & data: Proof-of-concept for deep generative MT-CPD design was established. Custom code and the benchmark set comprising 2809 MT-CPDs, 61,928 single-target and 295,395 inactive compounds from biological screens are made freely available. Limitations & next steps: MT-CPD design via deep learning is still at its conceptual stages. It will be required to demonstrate experimental impact. The data and software we provide enable further investigation of MT-CPD design and generation of candidate molecules for experimental programs.

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Knez, Damijan, Izidor Sosič, Anja Pišlar, Ana Mitrović, Marko Jukič, Janko Kos, and Stanislav Gobec. "Biological Evaluation of 8-Hydroxyquinolines as Multi-Target Directed Ligands for Treating Alzheimer’s Disease." Current Alzheimer Research 16, no. 9 (October 29, 2019): 801–14. http://dx.doi.org/10.2174/1567205016666191010130351.

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Background: Accumulating evidence suggests that multi-target directed ligands have great potential for the treatment of complex diseases such as Alzheimer’s Disease (AD). Objective: To evaluate novel chimeric 8-hydroxyquinoline ligands with merged pharmacophores as potential multifunctional ligands for AD. Methods: Nitroxoline, PBT2 and compounds 2-4 were evaluated in-vitro for their inhibitory potencies on cathepsin B, cholinesterases, and monoamine oxidases. Furthermore, chelation, antioxidative properties and the permeability of Blood-Brain Barrier (BBB) were evaluated by spectroscopy-based assays and the inhibition of Amyloid β (Aβ) aggregation was determined in immunoassay. Cell-based assays were performed to determine cytotoxicity, neuroprotection against toxic Aβ species, and the effects of compound 2 on apoptotic cascade. Results: Compounds 2-4 competitively inhibited cathepsin B β-secretase activity, chelated metal ions and were weak antioxidants. All of the compounds inhibited Aβ aggregation, whereas only compound 2 had a good BBB permeability according to the parallel artificial membrane permeability assay. Tested ligands 2 and 3 were not cytotoxic to SH-SY5Y and HepG2 cells at 10 μM. Compound 2 exerted neuroprotective effects towards Aβ toxicity, reduced the activation of caspase-3/7 and diminished the apoptosis of cells treated with Aβ1-42. Conclusion: Taken together, our data suggest that compound 2 holds a promise to be used as a multifunctional ligand for AD.

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Goff, Aaron, Daire Cantillon, Leticia Muraro Wildner, and Simon J. Waddell. "Multi-Omics Technologies Applied to Tuberculosis Drug Discovery." Applied Sciences 10, no. 13 (July 3, 2020): 4629. http://dx.doi.org/10.3390/app10134629.

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Multi-omics strategies are indispensable tools in the search for new anti-tuberculosis drugs. Omics methodologies, where the ensemble of a class of biological molecules are measured and evaluated together, enable drug discovery programs to answer two fundamental questions. Firstly, in a discovery biology approach, to find new targets in druggable pathways for target-based investigation, advancing from target to lead compound. Secondly, in a discovery chemistry approach, to identify the mode of action of lead compounds derived from high-throughput screens, progressing from compound to target. The advantage of multi-omics methodologies in both of these settings is that omics approaches are unsupervised and unbiased to a priori hypotheses, making omics useful tools to confirm drug action, reveal new insights into compound activity, and discover new avenues for inquiry. This review summarizes the application of Mycobacterium tuberculosis omics technologies to the early stages of tuberculosis antimicrobial drug discovery.

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Hu, Ye, Disha Gupta-Ostermann, and Jürgen Bajorath. "EXPLORING COMPOUND PROMISCUITY PATTERNS AND MULTI-TARGET ACTIVITY SPACES." Computational and Structural Biotechnology Journal 9, no. 13 (January 2014): e201401003. http://dx.doi.org/10.5936/csbj.201401003.

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Bieler, Michael, Michael Reutlinger, Tiago Rodrigues, Petra Schneider, Jan M. Kriegl, and Gisbert Schneider. "Designing Multi-target Compound Libraries with Gaussian Process Models." Molecular Informatics 35, no. 5 (March 2, 2016): 192–98. http://dx.doi.org/10.1002/minf.201501012.

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Poliseno, Viviana, Sílvia Chaves, Leonardo Brunetti, Fulvio Loiodice, Antonio Carrieri, Antonio Laghezza, Paolo Tortorella, et al. "Derivatives of Tenuazonic Acid as Potential New Multi-Target Anti-Alzheimer’s Disease Agents." Biomolecules 11, no. 1 (January 15, 2021): 111. http://dx.doi.org/10.3390/biom11010111.

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Alzheimer’s disease (AD) is generally recognized as a multifactorial neurodegenerative pathology with an increasing impact on society. Tenuazonic acid (TA) is a natural compound that was recently identified as a potential multitarget ligand with anti-cholinesterase, anti-amyloidogenic and antioxidant activities. Using its structure as a chemical scaffold, we synthesized and evaluated new derivatives (1–5), including tenuazonic-donepezil (TA-DNP) hybrids (4 and 5) due to the clinical importance of the anti-AD drug donepezil. These novel compounds all achieved activity in the micromolar range towards all selected targets and demonstrated to be potentially orally absorbed. Moreover, a selected compound (1) was further investigated as a chelating agent towards copper (II), zinc (II) and iron (III) and showed good chelating ability (pFe = 16.6, pCu = 11.6, pZn = 6.0 at pH 7.4). Therefore, the TA motif can be considered an interesting building block in the search for innovative multi-functional anti-neurodegenerative drugs, as exemplified by hybrid 5, a promising non-cytotoxic lead compound adequate for the early stages of AD, and capable of ameliorating the oxidative status of SH-SY5Y human neuroblastoma cells.

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Piemontese, Luca, Gabriele Vitucci, Marco Catto, Antonio Laghezza, Filippo Perna, Mariagrazia Rullo, Fulvio Loiodice, Vito Capriati, and Michele Solfrizzo. "Natural Scaffolds with Multi-Target Activity for the Potential Treatment of Alzheimer’s Disease." Molecules 23, no. 9 (August 29, 2018): 2182. http://dx.doi.org/10.3390/molecules23092182.

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A few symptomatic drugs are currently available for Alzheimer’s Disease (AD) therapy, but these molecules are only able to temporary improve the cognitive capacity of the patients if administered in the first stages of the pathology. Recently, important advances have been achieved about the knowledge of this complex condition, which is now considered a multi-factorial disease. Researchers are, thus, more oriented toward the preparation of molecules being able to contemporaneously act on different pathological features. To date, the inhibition of acetylcholinesterase (AChE) and of β-amyloid (Aβ) aggregation as well as the antioxidant activity and the removal and/or redistribution of metal ions at the level of the nervous system are the most common investigated targets for the treatment of AD. Since many natural compounds show multiple biological properties, a series of secondary metabolites of plants or fungi with suitable structural characteristics have been selected and assayed in order to evaluate their potential role in the preparation of multi-target agents. Out of six compounds evaluated, 1 showed the best activity as an antioxidant (EC50 = 2.6 ± 0.2 μmol/µmol of DPPH) while compound 2 proved to be effective in the inhibition of AChE (IC50 = 6.86 ± 0.67 μM) and Aβ1–40 aggregation (IC50 = 74 ± 1 μM). Furthermore, compound 6 inhibited BChE (IC50 = 1.75 ± 0.59 μM) with a good selectivity toward AChE (IC50 = 86.0 ± 15.0 μM). Moreover, preliminary tests on metal chelation suggested a possible interaction between compounds 1, 3 and 4 and copper (II). Molecules with the best multi-target profiles will be used as starting hit compounds to appropriately address future studies of Structure-Activity Relationships (SARs).

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Chen, Shiyi, Wenkang Huang, Xiaoyu Li, Lijuan Gao, and Yiping Ye. "Identifying Active Compounds and Mechanisms of Citrus changshan-Huyou Y. B. Chang against URTIs-Associated Inflammation by Network Pharmacology in Combination with Molecular Docking." Evidence-Based Complementary and Alternative Medicine 2022 (July 13, 2022): 1–10. http://dx.doi.org/10.1155/2022/2156157.

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Purpose. The ripe fruits of Citrus changshan-huyou, known as Quzhou Fructus Aurantii (QFA), have been commonly used for respiratory diseases. The purpose of this study was to investigate their active compounds and demonstrate their mechanism in the treatment of upper respiratory tract infections (URTIs) through network pharmacology and molecular docking. Methods. The prominent compounds of QFA were acquired from TCMSP database. Their targets were retrieved from SwissTargetPrediction database, and target genes associated with URTIs were collected from DisGeNET and GeneCards databases. The target protein-protein interaction (PPI) network was constructed by using STRING database and Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were enriched. Visual compound-target-pathway network was established with Cytoscape. The effects of compounds were verified on the inhibitory activities against phosphoinositide 3-kinases (PI3Ks). Finally, the molecular docking was carried out to confirm the binding affinity of the bioactive compounds and target proteins. Results. Five important active compounds, naringenin (NAR), tangeretin (TAN), luteolin (LUT), hesperetin (HES), and auraptene (AUR), were obtained. The enrichment analysis demonstrated that the pathways associated with inflammation mainly contained PI3K/Akt signalling pathway, TNF signalling pathway, and so on. The most important targets covering inflammation-related proteins might be PI3Ks. In vitro assays and molecular docking exhibited that TAN, LUT, and AUR acted as PI3Kγ inhibitors. Conclusion. The results revealed that QFA could treat URTIs through a multi-compound, multi-target, multi-pathway network, in which TAN, LUT, and AUR acted as PI3Kγ inhibitors, probably contributing to a crucial role in treatment of URTIs.

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Lee, Sang-Hyeok, Sangjin Ahn, and Mi-hyun Kim. "Comparing a Query Compound with Drug Target Classes Using 3D-Chemical Similarity." International Journal of Molecular Sciences 21, no. 12 (June 12, 2020): 4208. http://dx.doi.org/10.3390/ijms21124208.

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3D similarity is useful in predicting the profiles of unprecedented molecular frameworks that are 2D dissimilar to known compounds. When comparing pairs of compounds, 3D similarity of the pairs depends on conformational sampling, the alignment method, the chosen descriptors, and the similarity coefficients. In addition to these four factors, 3D chemocentric target prediction of an unknown compound requires compound–target associations, which replace compound-to-compound comparisons with compound-to-target comparisons. In this study, quantitative comparison of query compounds to target classes (one-to-group) was achieved via two types of 3D similarity distributions for the respective target class with parameter optimization for the fitting models: (1) maximum likelihood (ML) estimation of queries, and (2) the Gaussian mixture model (GMM) of target classes. While Jaccard–Tanimoto similarity of query-to-ligand pairs with 3D structures (sampled multi-conformers) can be transformed into query distribution using ML estimation, the ligand pair similarity within each target class can be transformed into a representative distribution of a target class through GMM, which is hyperparameterized via the expectation–maximization (EM) algorithm. To quantify the discriminativeness of a query ligand against target classes, the Kullback–Leibler (K–L) divergence of each query was calculated and compared between targets. 3D similarity-based K–L divergence together with the probability and the feasibility index, (Fm), showed discriminative power with regard to some query–class associations. The K–L divergence of 3D similarity distributions can be an additional method for (1) the rank of the 3D similarity score or (2) the p-value of one 3D similarity distribution to predict the target of unprecedented drug scaffolds.

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Xiong, Dan-dan, Yue Qin, Wen-qing Xu, Rong-quan He, Hua-yu Wu, Dan-min Wei, Jing-jing Zeng, Yi-wu Dang, and Gang Chen. "A Network Pharmacology-Based Analysis of Multi-Target, Multi-Pathway, Multi-Compound Treatment for Ovarian Serous Cystadenocarcinoma." Clinical Drug Investigation 38, no. 10 (August 10, 2018): 909–25. http://dx.doi.org/10.1007/s40261-018-0683-8.

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Wang, Xiao-Qin, Chu-Ping Zhao, Long-Cheng Zhong, De-Ling Zhu, De-Hao Mai, Mei-Gui Liang, and Ming-Hua He. "Preparation of 4-Flexible Amino-2-Arylethenyl-Quinoline Derivatives as Multi-target Agents for the Treatment of Alzheimer’s Disease." Molecules 23, no. 12 (November 27, 2018): 3100. http://dx.doi.org/10.3390/molecules23123100.

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Alzheimer’s disease (AD) is a complex and multifactorial neurodegenerative disorder of aged people. The development of multitarget-directed ligands (MTDLs) to act as multifunctional agents to treat this disease is the mainstream of current research. As a continuation of our previous studies, a series of 4-flexible amino-2-arylethenylquinoline derivatives as multi-target agents was efficiently synthesized and evaluated for the treatment of AD. Among these synthesized derivatives, some compounds exhibited strong self-induced Aβ1–42 aggregation inhibition and antioxidant activity. The structure-activity relationship was summarized, which confirmed that the introduction of a flexible amino group featuring a N,N-dimethylaminoalkylamino moiety at the 4-position increased the Aβ1–42 aggregation inhibition activity, with an inhibition ratio of 95.3% at 20 μM concentration. Compound 6b1, the optimal compound, was able to selectively chelate copper (II), and inhibit Cu2+-induced Aβ aggregation effectively. It also could disassemble the self-induced Aβ1–42 aggregation fibrils with a ratio of 64.3% at 20 μM concentration. Moreover, compound 6b1 showed low toxicity and a good neuroprotective effect against Aβ1–42-induced toxicity in SH-SY5Y cells. Furthermore, the step-down passive avoidance test indicated compound 6b1 significantly reversed scopolamine-induced memory deficit in mice. Taken together, these results suggested that compound 6b1 was a promising multi-target compound worthy of further study for AD.

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Pansari, Pratibha. "COMPUTATIONAL APPROACHES FOR DRUG DISCOVERY FROM MEDICINAL PLANTS IN THE ERA OF DATA DRIVEN RESEARCH." INDIAN DRUGS 58, no. 08 (October 27, 2021): 7–23. http://dx.doi.org/10.53879/id.58.08.12930.

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The significant scientific work on the development of bio-active compound databases, computational technologies, and the integration of Information Technology with Biotechnology has brought a revolution in the domain of drug discovery. These tools facilitate the medicinal plant-based in silico drug discovery, which has become the frontier of pharmacological science. In this review article, we elucidate the methodology of in silico drug discovery for the medicinal plants and present an outlook on recent tools and technologies. Further, we explore the multi-component, multi-target, and multi-pathway mechanism of the bio-active compounds with the help of Network Pharmacology, which enables us to create a topological network between drug, target, gene, pathway, and disease.

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Ikram, Nazia, Muhammad Usman Mirza, Michiel Vanmeert, Matheus Froeyen, Outi M. H. Salo-Ahen, Muhammad Tahir, Aamer Qazi, and Sarfraz Ahmad. "Inhibition of Oncogenic Kinases: An In Vitro Validated Computational Approach Identified Potential Multi-Target Anticancer Compounds." Biomolecules 9, no. 4 (March 28, 2019): 124. http://dx.doi.org/10.3390/biom9040124.

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Tumorigenesis in humans is a multistep progression that imitates genetic changes leading to cell transformation and malignancy. Oncogenic kinases play a central role in cancer progression, rendering them putative targets for the design of anti-cancer drugs. The presented work aims to identify the potential multi-target inhibitors of oncogenic receptor tyrosine kinases (RTKs) and serine/threonine kinases (STKs). For this, chemoinformatics and structure-based virtual screening approaches were combined with an in vitro validation of lead hits on both cancerous and non-cancerous cell lines. A total of 16 different kinase structures were screened against ~739,000 prefiltered compounds using diversity selection, after which the top hits were filtered for promising pharmacokinetic properties. This led to the identification of 12 and 9 compounds against RTKs and STKs, respectively. Molecular dynamics (MD) simulations were carried out to better comprehend the stability of the predicted hit kinase-compound complexes. Two top-ranked compounds against each kinase class were tested in vitro for cytotoxicity, with compound F34 showing the most promising inhibitory activity in HeLa, HepG2, and Vero cell lines with IC50 values of 145.46 μM, 175.48 μM, and 130.52 μM, respectively. Additional docking of F34 against various RTKs was carried out to support potential multi-target inhibition. Together with reliable MD simulations, these results suggest the promising potential of identified multi-target STK and RTK scaffolds for further kinase-specific anti-cancer drug development toward combinatorial therapies.

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Iyer, Preeti, and Jürgen Bajorath. "Representation of Multi-Target Activity Landscapes Through Target Pair-Based Compound Encoding in Self-Organizing Maps." Chemical Biology & Drug Design 78, no. 5 (October 5, 2011): 778–86. http://dx.doi.org/10.1111/j.1747-0285.2011.01235.x.

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Tao, Ali, Xuehua Feng, Zurong Song, Rui Xu, and Ying Zhao. "A Study on the Mechanism of Action of Galangal in the Treatment of Gastric Cancer Using Network Pharmacology Technology." Processes 10, no. 10 (October 1, 2022): 1988. http://dx.doi.org/10.3390/pr10101988.

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To study the mechanism of galangal in the treatment of gastric cancer by network pharmacology. The TCMSP database was used to collect the effective compounds and potential targets of galangal, and the genes associated with gastric cancer were obtained through the GeneCards database, and Venn obtained the interaction genes of the effective compound targets of galangal and gastric cancer targets, plotted the interaction genes into PPI networks, and screened out key targets. The interacting genes were imported into Metascape database for GO enrichment analysis and KEGG signal enrichment. A total of 13 active compounds and 207 potential downstream target genes were screened by TCMSP database. Have 5222 gastric cancer target genes through GeneCards database, there were a total of 150 interactive genes and 6 key genes: TP53, AKT1, JUN, HSP90AA1, IL6, and CASP3. These interacting genes involved 30 typical GO entries and 20 KEGG signals. Galangal may play a role in the treatment of gastric cancer by means of multi-component, multi-target and multi-signal pathway.

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Mahnashi, Mater H., Waqas Alam, Mohammed A. Huneif, Alqahtani Abdulwahab, Mohammed Jamaan Alzahrani, Khaled S. Alshaibari, Umar Rashid, Abdul Sadiq, and Muhammad Saeed Jan. "Exploration of Succinimide Derivative as a Multi-Target, Anti-Diabetic Agent: In Vitro and In Vivo Approaches." Molecules 28, no. 4 (February 7, 2023): 1589. http://dx.doi.org/10.3390/molecules28041589.

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Diabetes mellitus (DM) is counted among one of the leading challenges in the recent era, and it is a life-threatening disorder. Compound 4-hydroxy 3-methoxy phenylacetone (compound 1) was previously isolated from Polygonum aviculare. This compound was reacted with N-benzylmaleimide to synthesize the targeted compound 3. The purpose of this research is to exhibit our developed compound 3’s ability to concurrently inhibit many targets that are responsible for hyperglycemia. Compound 3 was capable of inhibiting α-amylase, α-glucosidase, and protein tyrosine phosphatase 1 B. Even so, outstanding in vitro inhibition was shown by the compound against dipeptidyl peptidase-4 (DPP-4) with an IC50 value of 0.07 µM. Additionally, by using DPPH in the antioxidant activity, it exhibited good antioxidant potential. Similarly, in the in vivo activity, the experimental mice proved to be safe by treatment with compound 3. After 21 days of examination, the compound 3 activity pattern was found to be effective in experimental mice. Compound 3 decreased the excess peak of total triglycerides, total cholesterol, AST, ALT, ALP, LDL, BUN, and creatinine in the STZ-induced diabetic mice. Likewise, the histopathology of the kidneys, liver, and pancreas of the treated animals was also evaluated. Overall, the succinimde moiety, such as compound 3, can affect several targets simultaneously, and, finally, we were successful in synthesizing a multi-targeted preclinical therapy.

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Chen, Han-Sen, Su-Hua Qi, and Jian-Gang Shen. "One-Compound-Multi-Target: Combination Prospect of Natural Compounds with Thrombolytic Therapy in Acute Ischemic Stroke." Current Neuropharmacology 15, no. 1 (December 14, 2016): 134–56. http://dx.doi.org/10.2174/1570159x14666160620102055.

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Szemerédi, Nikoletta, Simona Dobiasová, Noemi Salardón-Jiménez, Annamária Kincses, Márta Nové, Giyaullah Habibullah, Clotilde Sevilla-Hernández, et al. "Cyano- and Ketone-Containing Selenoesters as Multi-Target Compounds against Resistant Cancers." Cancers 13, no. 18 (September 11, 2021): 4563. http://dx.doi.org/10.3390/cancers13184563.

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Fifteen selenocompounds, comprising of eight ketone-containing selenoesters (K1–K8, also known as oxoselenoesters) and seven cyano-containing selenoesters (N1–N7, known also as cyanoselenoesters), have been designed, synthesized, and evaluated as novel anticancer agents. These compounds are derivatives of previously reported active selenoesters and were prepared following a three-step one-pot synthetic route. The following evaluations were performed in their biological assessment: cytotoxicity determination, selectivity towards cancer cells in respect to non-cancer cells, checkerboard combination assay, ABCB1 inhibition and inhibition of ABCB1 ATPase activity, apoptosis induction, and wound healing assay. As key results, all the compounds showed cytotoxicity against cancer cells at low micromolar concentrations, with cyanoselenoesters being strongly selective. All of the oxoselenoesters, except K4, were potent ABCB1 inhibitors, and two of them, namely K5 and K6, enhanced the activity of doxorubicin in a synergistic manner. The majority of these ketone derivatives modulated the ATPase activity, showed wound healing activity, and induced apoptosis, with K3 being the most potent, with a potency close to that of the reference compound. To summarize, these novel derivatives have promising multi-target activity, and are worthy to be studied more in-depth in future works to gain a greater understanding of their potential applications against cancer.

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Pontiki, Eleni, and Dimitra Hadjipavlou-Litina. "Multi-Target Cinnamic Acids for Oxidative Stress and Inflammation: Design, Synthesis, Biological Evaluation and Modeling Studies." Molecules 24, no. 1 (December 20, 2018): 12. http://dx.doi.org/10.3390/molecules24010012.

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Inflammation is a complex phenomenon that results as a healing response of organisms to different factors, exerting immune signaling, excessive free radical activity and tissue destruction. Lipoxygenases and their metabolites e.g., LTB4, are associated with allergy, cell differentiation and carcinogenesis. Lipoxygenase 12/15 has been characterized as a mucosal-specific inhibitor of IgA and a contributor to the development of allergic sensitization and airway inflammation. Development of drugs that interfere with the formation or effects of these metabolites would be important for the treatment of various diseases like asthma, psoriasis, ulcerative colitis, rheumatoid arthritis, atherosclerosis, cancer and blood vessel disorders. In this study we extended our previous research synthesizing a series of multi-target cinnamic acids from the corresponding aldehydes with suitable 4-OH/Br substituted phenyl acetic acid by Knoevenagel condensation. The final products 1i, 3i, 3ii, 4i, 6i, 6ii, and 7i were obtained in high yields (52–98%) Their structures were verified spectrometrically, while their experimentally lipophilicity was determined as RM values. The novel derivatives were evaluated for their antioxidant activity using DPPH, hydroxyl radical, superoxide anion and ABTS+•, anti-lipid peroxidation and soybean lipoxygenase inhibition assays. The compounds presented medium interaction with DPPH (30–48% at 100 µM). In contrast all the synthesized derivatives strongly scavenge OH radicals (72–100% at 100 µM), ABTS+• (24–83% at 100 µM) and presented remarkable inhibition (87–100% at 100 µM) in linoleic acid peroxidation (AAPH). The topological polar surface of the compounds seems to govern the superoxide anion scavenging activity. Molecular docking studies were carried out on cinnamic acid derivative 3i and found to be in accordance with experimental biological results. All acids presented interesting lipoxygenase inhibition (IC50 = 7.4–100 µM) with compound 3i being the most potent LOX inhibitor with IC50 = 7.4 µM combining antioxidant activities. The antioxidant results support the LOX inhibitory activities. The recorded in vitro results highlight compound 3i as a lead compound for the design of new potent lipoxygenase inhibitors for the treatment of asthma, psoriasis, ulcerative colitis, rheumatoid arthritis, atherosclerosis, cancer and blood vessel disorders.

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Mumtaz, Saira, Mark J. Robertson, and Michael Oelgemöller. "Continuous Flow Photochemical and Thermal Multi-Step Synthesis of Bioactive 3-Arylmethylene-2,3-Dihydro-1H-Isoindolin-1-Ones." Molecules 24, no. 24 (December 11, 2019): 4527. http://dx.doi.org/10.3390/molecules24244527.

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An effective multi-step continuous flow approach towards N-diaminoalkylated 3-arylmethylene-2,3-dihydro-1H-isoindolin-1-ones, including the local anesthetic compound AL-12, has been realized. Compared to the traditional decoupled batch processes, the combined photochemical–thermal–thermal flow setup rapidly provides the desired target compounds in superior yields and significantly shorter reaction times.

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Dong, Ke Xiu, Nan Nan Wei, Jian Ping Shi, and Yan Qin Wang. "Compact Compound Imaging System with Large Target Surface." Key Engineering Materials 609-610 (April 2014): 863–66. http://dx.doi.org/10.4028/www.scientific.net/kem.609-610.863.

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Compact compound imaging system with large CCD target surface has been researched. The target surface reaches 50mmX50mm, and reduces the system processing and installation difficulty. We present the system overall plan and discuss the imaging characteristics. The imaging results for sector resolution target show that the system can image with multi channel crosstalk free. The results show that whether the single convex lens system or double convex lens system, the definition and contrast of single channel graphs are poor. However we can get the super resolution image by POCS algorithm. The reconstructed results show that image quality has been obviously improved compared with the single channel image, which proof the availability of the compact compound imaging system with large CCD target surface. Key words: Compact ompound imaging system, Microlens array, Doublet lens, POCS

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Wang, Ze-Feng, Ye-Qing Hu, Qi-Guo Wu, and Rui Zhang. "Virtual Screening of Potential Anti-fatigue Mechanism of Polygonati Rhizoma Based on Network Pharmacology." Combinatorial Chemistry & High Throughput Screening 22, no. 9 (January 1, 2020): 612–24. http://dx.doi.org/10.2174/1386207322666191106110615.

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Background and Objective: A large number of people are facing the danger of fatigue due to the fast-paced lifestyle. Fatigue is common in some diseases, such as cancer. The mechanism of fatigue is not definite. Traditional Chinese medicine is often used for fatigue, but the potential mechanism of Polygonati Rhizoma (PR) is still not clear. This study attempts to explore the potential anti-fatigue mechanism of Polygonati Rhizoma through virtual screening based on network pharmacology. Methods: The candidate compounds of PR and the known targets of fatigue are obtained from multiple professional databases. PharmMapper Server is designed to identify potential targets for the candidate compounds. We developed a Herbal medicine-Compound-Disease-Target network and analyzed the interactions. Protein-protein interaction network is developed through the Cytoscape software and analyzed by topological methods. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment are carried out by DAVID Database. Finally, we develop Compound-Target-Pathway network to illustrate the anti-fatigue mechanism of PR. Results: This approach identified 12 active compounds and 156 candidate targets of PR. The top 10 annotation terms for GO and KEGG were obtained by enrichment analysis with 35 key targets. The interaction between E2F1 and PI3K-AKT plays a vital role in the anti-fatigue effect of PR due to this study. Conclusions: This study demonstrates that PR has multi-component, multi-target and multipathway effects.

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Xie, Li, and Lei Xie. "Pathway-Centric Structure-Based Multi-Target Compound Screening for Anti-Virulence Drug Repurposing." International Journal of Molecular Sciences 20, no. 14 (July 17, 2019): 3504. http://dx.doi.org/10.3390/ijms20143504.

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The emergence of superbugs that are resistant to last-resort antibiotics poses a serious threat to human health, and we are in a “race against time to develop new antibiotics.” New approaches are urgently needed to control drug-resistant pathogens, and to reduce the emergence of new drug-resistant microbes. Targeting bacterial virulence has emerged as an important strategy for combating drug-resistant pathogens. It has been shown that pyocyanin, which is produced by the phenazine biosynthesis pathway, plays a key role in the virulence of Pseudomonas aeruginosa infection, making it an attractive target for anti-infective drug discovery. In order to discover efficient therapeutics that inhibit the phenazine biosynthesis in a timely fashion, we screen 2004 clinical and pre-clinical drugs to target multiple enzymes in the phenazine biosynthesis pathway, using a novel procedure of protein–ligand docking. Our detailed analysis suggests that kinase inhibitors, notably Lifirafenib, are promising lead compounds for inhibiting aroQ, phzG, and phzS enzymes that are involved in the phenazine biosynthesis, and merit further experimental validations. In principle, inhibiting multiple targets in a pathway will be more effective and have less chance of the emergence of drug resistance than targeting a single protein. Our multi-target structure-based drug design strategy can be applied to other pathways, as well as provide a systematic approach to polypharmacological drug repositioning.

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Zhuang, Xiao-Cui, Yong-Li Zhang, Gui-Lin Chen, Ye Liu, Xiao-Lan Hu, Na Li, Jian-Lin Wu, and Ming-Quan Guo. "Identification of Anti-Inflammatory and Anti-Proliferative Neolignanamides from Warburgia ugandensis Employing Multi-Target Affinity Ultrafiltration and LC-MS." Pharmaceuticals 14, no. 4 (April 1, 2021): 313. http://dx.doi.org/10.3390/ph14040313.

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Previous reports have illustrated that the incidence and mortality of cancer are increasing year by year worldwide. In addition, the occurrence, development, recurrence and metastasis of cancer are closely related to inflammation, which is a kind of defensive response of human body to various stimuli. As an important medicinal plant in Africa, Warburgia ugandensis has been reported to have certain anti-inflammatory and anti-proliferative activities, but its specific components and mechanisms of action remain elusive. To tackle this challenge, affinity ultrafiltration with drug targets of interest coupled to high-performance liquid chromatography-mass spectrometry (AUF-HPLC-MS/MS) could be utilized to quickly screen out bioactive constituents as ligands against target enzymes from complex extracts of this plant. AUF-HPLC-MS/MS with four drug targets, i.e., cyclooxygenase-2 (COX-2), 5-lipoxygenase (5-LOX), topoisomerase I (Top I) and topoisomerase II (Top II) were used to rapidly screen and characterize the anti-inflammatory and anti-proliferative natural ligands from W. ugandensis, and the resulting potential active compounds as ligands with specific binding affinity to COX-2, 5-LOX, Top I and Top II, were isolated with modern separation and purification techniques and identified with spectroscopic method like NMR, and then their antiinflammatory and anti-proliferative activities were tested to verify the screening results from AUF-HPLC-MS/MS. Compounds 1 and 2, which screened out and identified from W. ugandensis showed remarkable binding affinity to COX-2, 5-LOX, Top I and Top II with AUF-HPLC-MS/MS. In addition, 1 new compound (compound 3), together with 5 known compounds were also isolated and identified from W. ugandensis. The structure of compound 3 was elucidated by extensive 1D, 2D NMR data and UPLC-QTOF-MS/MS. Furthermore, compounds 1 and 2 were further proved to possess both anti-inflammatory and anti-proliferative activities which are in good agreement with the screening results using AUF-HPLC-MS/MS. This work showcased an efficient method for quickly screening out bioactive components with anti-inflammatory and anti-proliferative activity from complex medicinal plant extracts using AUF-HPLC-MS/MS with target enzymes of interest, and also demonstrated that neolignanamides (compounds 1 and 2) from W. ugandensis would be the active components responsible for its anti-inflammatory and anti-proliferative activity with the potential to treat cancer and inflammation.

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Yan, Zhao, Guangmei Liu, Yang Yang, Ling Chen, Ying Shang, and Qian Hong. "Identifying mechanisms of Epimedii Folium against Alzheimer’s disease via a network pharmacology approach Epimedii Folium treats Alzheimer’s disease via PI3K-AKT." European Journal of Inflammation 19 (January 2021): 205873922110414. http://dx.doi.org/10.1177/20587392211041435.

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To elucidate the mechanism of the multi-target action of Epimedii Folium on Alzheimer’s disease, this study focuses on the analysis of network pharmacology. Based on a bioinformatics approach, this study obtained the effective components of Epimedium through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, predicted the compound targets through the Pharmapper and Swiss target prediction database and then through Gene Expression Omnibus Datasets and Therapeutic Target Database. We collected and analysed of heral and disease targets, constructed the network. Through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene Ontology enrichment, then the key targets and pathways of Epimedii Folium to cope with Alzheimer’s disease have been identified. Twenty-three bioactive components and 477 potential target genes of Epimedii Folium were identified. A total of 1612 target diseases were identified. Through network module analysis, 30 hub target genes were identified. Through enrichment analysis of the KEGG pathway, hub target genes were largely enriched in the PI3K-AKT signaling pathway. Through the analysis of network pharmacology, it was found that Epimedii Folium might play the role of multi-compound and multi-target therapy through the PI3K-AKT signaling pathway. These findings provide helpful directions for future clinical studies.

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Queda, Fausto, Sonia Calò, Karolina Gwizdala, João D. Magalhães, Sandra M. Cardoso, Sílvia Chaves, Luca Piemontese, and M. Amélia Santos. "Novel Donepezil–Arylsulfonamide Hybrids as Multitarget-Directed Ligands for Potential Treatment of Alzheimer’s Disease." Molecules 26, no. 6 (March 16, 2021): 1658. http://dx.doi.org/10.3390/molecules26061658.

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Alzheimer’s disease (AD) is one of the most devastating neurodegenerative disorders, characterized by multiple pathological features. Therefore, multi-target drug discovery has been one of the most active fields searching for new effective anti-AD therapies. Herein, a series of hybrid compounds are reported which were designed and developed by combining an aryl-sulfonamide function with a benzyl-piperidine moiety, the pharmacophore of donepezil (a current anti-AD acetylcholinesterase AChE inhibitor drug) or its benzyl-piperazine analogue. The in vitro results indicate that some of these hybrids achieve optimized activity towards two main AD targets, by displaying excellent AChE inhibitory potencies, as well as the capability to prevent amyloid-β (Aβ) aggregation. Some of these hybrids also prevented Aβ-induced cell toxicity. Significantly, drug-like properties were predicted, including for blood-brain permeability. Compound 9 emerged as a promising multi-target lead compound (AChE inhibition (IC50 1.6 μM); Aβ aggregation inhibition 60.7%). Overall, this family of hybrids is worthy of further exploration, due to the wide biological activity of sulfonamides.

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Carradori, Simone, Marialuigia Fantacuzzi, Alessandra Ammazzalorso, Andrea Angeli, Barbara De Filippis, Salvatore Galati, Anél Petzer, et al. "Resveratrol Analogues as Dual Inhibitors of Monoamine Oxidase B and Carbonic Anhydrase VII: A New Multi-Target Combination for Neurodegenerative Diseases?" Molecules 27, no. 22 (November 13, 2022): 7816. http://dx.doi.org/10.3390/molecules27227816.

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Neurodegenerative diseases (NDs) are described as multifactorial and progressive syndromes with compromised cognitive and behavioral functions. The multi-target-directed ligand (MTDL) strategy is a promising paradigm in drug discovery, potentially leading to new opportunities to manage such complex diseases. Here, we studied the dual ability of a set of resveratrol (RSV) analogs to inhibit two important targets involved in neurodegeneration. The stilbenols 1–9 were tested as inhibitors of the human monoamine oxidases (MAOs) and carbonic anhydrases (CAs). The studied compounds displayed moderate to excellent in vitro enzyme inhibitory activity against both enzymes at micromolar/nanomolar concentrations. Among them, the best compound 4 displayed potent and selective inhibition against the MAO-B isoform (IC50 MAO-A 0.43 µM vs. IC50 MAO-B 0.01 µM) with respect to the parent compound resveratrol (IC50 MAO-A 13.5 µM vs. IC50 MAO-B > 100 µM). It also demonstrated a selective inhibition activity against hCA VII (KI 0.7 µM vs. KI 4.3 µM for RSV). To evaluate the plausible binding mode of 1–9 within the two enzymes, molecular docking and dynamics studies were performed, revealing specific and significant interactions in the active sites of both targets. The new compounds are of pharmacological interest in view of their considerably reduced toxicity previously observed, their physicochemical and pharmacokinetic profiles, and their dual inhibitory ability. Compound 4 is noteworthy as a promising lead in the development of MAO and CA inhibitors with therapeutic potential in neuroprotection.

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Lin, Haochang, Xinyue Zhang, Jiangya Li, Liju Liang, Qian Zhang, Yan Fang, Jingfeng Song, Weimin Yang, and Zhiying Weng. "Unraveling the Molecular Mechanism of Xuebijing Injection in the Treatment of Chronic Obstructive Pulmonary Disease by Combining Network Pharmacology and Affymetrix Array." Natural Product Communications 17, no. 4 (April 2022): 1934578X2210927. http://dx.doi.org/10.1177/1934578x221092705.

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Xuebijing injection (XBJ), one of the classical prescriptions for treating inflammation-related diseases, has been used to chronic obstructive pulmonary disease (COPD) in clinical practice. However, its molecular mechanism is still unclear. Network pharmacology combined with Affymetrix arrays and molecular docking techniques were applied to explore the molecular mechanism of XBJ for COPD. Predictive analysis of 728 active compounds in XBJ and 6 sets of Affymetrix arrays expression data resulted in 106 potential therapeutic targets. Next, based on the active compound-co-target network topology analysis, most of these targets were found to be modulated by quercetin, myricetin, and ellagic acid. Furthermore, protein–protein interaction (PPI) analysis revealed that the key targets may be EGFR, STAT3, AKT1, CCND1, MMP9, AR, ESR1, and PTGS2. Then, by constructing a component-target-pathway network, we found that XBJ was a multi-pathway, multi-target, multi-compound synergistic therapy for COPD, and four key targets were involved in the FoxO signaling pathway. Luteolin and salvianolic acid b had the optimal binding ability to several key proteins. Therefore, we hypothesize that quercetin, myricetin, ellagic acid, luteolin, and salvianolic acid b mainly contribute to the therapeutic effect of XBJ on COPD by modulating the FoxO signaling pathway by regulating EGFR, STAT3, AKT1, and CCND1. XBJ exerts anti-inflammatory and antioxidative stress effects through the PI3K/Akt/FoxO axis combined with MMP9, AR, ESR1, and PTGS2 to regulate other signaling pathways.

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Sánchez-Suárez, Jeysson, Luisa Villamil, Luis Díaz, and Ericsson Coy-Barrera. "Uncovering Streptomyces-Derived Compounds as Cosmeceuticals for the Development of Improved Skin Photoprotection Products: An In Silico Approach to Explore Multi-Targeted Agents." Scientia Pharmaceutica 90, no. 3 (August 16, 2022): 48. http://dx.doi.org/10.3390/scipharm90030048.

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The search for novel photoprotective substances has become a challenge in cosmeceutical research. Streptomyces-derived compounds can serve as a promising source of photoprotective agents to formulate skin photoprotection products, such as sunscreens. This study aimed to identify specialized metabolites with the potential to modulate UV-induced cellular damage in the skin by identifying potential multi-target-directed ligands. Using a combination of ligand- and target-based virtual screening approaches, a public compound library comprising 6524 Streptomyces-derived specialized metabolites was studied for their photoprotective capability. The compounds were initially filtered by safety features and then examined for their ability to interact with key targets in the photodamage pathway by molecular docking. A set of 50 commercially available UV filters was used as the benchmark. The protein–ligand stability of selected Streptomyces-derived compounds was also studied by molecular dynamics (MD) simulations. From the compound library, 1981 compounds were found to meet the safety criteria for topically applied products, such as low skin permeability and low or non-toxicity-alerting substructures. A total of 34 compounds had promising binding scores against crucial targets involved in UV-induced photodamage, such as serotonin-receptor subtype 5-HT2A, platelet-activating factor receptor, IL-1 receptor type 1, epidermal growth factor receptor, and cyclooxygenase-2. Among these compounds, aspergilazine A and phaeochromycin F showed the highest ranked interactions with four of the five targets and triggered complex stabilization over time. Additionally, the predicted UV-absorbing profiles also suggest a UV-filtering effect. Streptomyces is an encouraging biological source of compounds for developing topical products. After in silico protein–ligand interactions, binding mode and stabilization of aspergilazine A and phaeochromycin F led to the discovery of potential candidates as photodamage multi-target inhibitors. Therefore, they can be further explored for the formulation of skin photoprotection products.

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Oddsson, Sebastian, Natalia M. Kowal, Philip K. Ahring, Elin S. Olafsdottir, and Thomas Balle. "Structure-Based Discovery of Dual-Target Hits for Acetylcholinesterase and the α7 Nicotinic Acetylcholine Receptors: In Silico Studies and In Vitro Confirmation." Molecules 25, no. 12 (June 22, 2020): 2872. http://dx.doi.org/10.3390/molecules25122872.

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Despite extensive efforts in the development of drugs for complex neurodegenerative diseases, treatment often remains challenging or ineffective, and hence new treatment strategies are necessary. One approach is the design of multi-target drugs, which can potentially address the complex nature of disorders such as Alzheimer’s disease. We report a method for high throughput virtual screening aimed at identifying new dual target hit molecules. One of the identified hits, N,N-dimethyl-1-(4-(3-methyl-[1,2,4]triazolo[4,3-a]pyrimidin-6-yl)phenyl)ethan-1-amine (Ýmir-2), has dual-activity as an acetylcholinesterase (AChE) inhibitor and as an α7 nicotinic acetylcholine receptor (α7 nAChR) agonist. Using computational chemistry methods, parallel and independent screening of a virtual compound library consisting of 3,848,234 drug-like and commercially available molecules from the ZINC15 database, resulted in an intersecting set of 57 compounds, that potentially possess activity at both of the two protein targets. Based on ligand efficiency as well as scaffold and molecular diversity, 16 of these compounds were purchased for in vitro validation by Ellman’s method and two-electrode voltage-clamp electrophysiology. Ýmir-2 was shown to exhibit the desired activity profile (AChE IC50 = 2.58 ± 0.96 µM; α7 nAChR activation = 7.0 ± 0.9% at 200 µM) making it the first reported compound with this particular profile and providing further evidence of the feasibility of in silico methods for the identification of novel multi-target hit molecules.

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Cai, Dong, Tai Li, Qian Xie, Xiaofei Yu, Wei Xu, Yu Chen, Zhe Jin, and Chun Hu. "Synthesis, Characterization, and Biological Evaluation of Novel 7-Oxo-7H-thiazolo[3,2-b]-1,2,4-triazine-2-carboxylic Acid Derivatives." Molecules 25, no. 6 (March 13, 2020): 1307. http://dx.doi.org/10.3390/molecules25061307.

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A series of novel 7-oxo-7H-thiazolo[3,2-b]-1,2,4-triazine-2-carboxylic acid derivatives was synthesized in good yields by a multi-step procedure that included the generation of the S-alkylated derivatives from 6-substituted arylmethyl-3-mercapto-1,2,4-triazin-5-ones with ethyl 2-chloroacetoacetate, intramolecular cyclization with microwave irradiation, hydrolysis and amidation. All of the target compounds were fully characterized through 1H-NMR, 13C-NMR and HRMS spectra. The intramolecular cyclization occurred regioselectively at the N2-position of 1,2,4-triazine ring, which was confirmed by compound 3e using single-crystal X-ray diffraction analysis. The antibacterial and antitubercular activities of the target compounds were evaluated. Compared with Ciprofloxacin and Rifampicin, compounds 5d, 5f and 5g containing the terminal amide fragment exhibited broad spectrum antibacterial activity, and carboxylic acid derivatives or its corresponding ethyl esters had less effect on antibacterial properties. The most potent compound 5f also displayed excellent in vitro antitubercular activity against Mycobacterium smegmatis (minimum inhibitory concentration (MIC) = 50 μg/mL) and better growth inhibition activity of leucyl-tRNA synthetase (78.24 ± 4.05% at 15 μg/mL).

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Wang, Xu, De-xi Zhao, Jun-Ming Kan, Jun Wang, Xin Chen, Zi-Qiao Yu, Wei-sen Zhao, Mo-Xuan Han, and Jinhua Li. "Uncovering the Mechanism of Chuanhong Stroke Capsule in the Treatment of Stroke Based on Network Pharmacology and Molecular Docking Technology." Natural Product Communications 17, no. 5 (May 2022): 1934578X2210759. http://dx.doi.org/10.1177/1934578x221075988.

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Background and Objective: Chuanhong Stroke Capsule (CHSC) has good clinical efficacy in the treatment of cerebral ischemic stroke (CIS) patients. This study aimed to investigate the pharmacological mechanisms of CHSC in treating CIS using bioinformatics. Methods: The active compounds of CHSC were screened by searching Traditional Chinese Medicine System Pharmacological Database and Analysis Platform (TCMSP), Swiss absorption, distribution, metabolism, and excretion (ADME), PubMed, and China National Knowledge Infrastructure (CNKI) databases. Besides, the potential targets of active compounds were obtained through TCMSP and Swiss Target Prediction databases. CIS targets were obtained from GeneCards, Online Mendelian Inheritance in Man (OMIM), and Gene Expression Omnibus (GEO) databases. CHSC-CIS intersection targets were identified by matching the two, and prediction and analysis of biological functions and pathways of intersection targets was used the enrichments of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Furthermore, protein–protein interaction (PPI) network, herb-target, and compound-target network of CHSC-CIS were constructed by Cytoscape3.7.2, and herb-compound-pathway network was drawn with Sankey diagram. Finally, AutoDock was used for molecular docking verification, and identifying the active binding sites in target proteins. Results: A total of 293 putative targets were obtained from 62 active compounds in CHSC. Among them, 209 targets were related to CIS. PPI network showed that the top 16 key targets were RELA, JUN, FOS, MAPK1, AKT1, etc. KEGG pathway enrichment analysis demonstrated that CHSC was enriched in PI3K-Akt, MAPK, and TNF signaling pathways. In addition, GO enrichment analysis showed the significant enrichment of CHSC in the following categories: kinase binding, cellular response to nitrogen compound, etc. Network topology analysis showed that quercetin, luteolin, kaempferol, etc., were the key components in CHSC. Finally, molecular docking studies suggested that the active components in CHSC had a good binding ability with the key targets. Conclusions: Our study demonstrated that CHSC exerted the effect in treating CIS by the characteristics of multi-target and multi-pathway, thereby providing a theoretical basis for further study of the effective components and mechanism of CHSC in the treatment of CIS.

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Li, Xiang, Leihong Wu, Wei Liu, Yecheng Jin, Qian Chen, Linli Wang, Xiaohui Fan, Zheng Li, and Yiyu Cheng. "A Network Pharmacology Study of Chinese Medicine QiShenYiQi to Reveal Its Underlying Multi-Compound, Multi-Target, Multi-Pathway Mode of Action." PLoS ONE 9, no. 5 (May 9, 2014): e95004. http://dx.doi.org/10.1371/journal.pone.0095004.

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Sadiq, Abdul, Mater H. Mahnashi, Umer Rashid, Muhammad Saeed Jan, Mohammed Abdulrahman Alshahrani, and Mohammed A. Huneif. "3-(((1S,3S)-3-((R)-Hydroxy(4-(trifluoromethyl)phenyl)methyl)-4-oxocyclohexyl)methyl)pentane-2,4-dione: Design and Synthesis of New Stereopure Multi-Target Antidiabetic Agent." Molecules 27, no. 10 (May 19, 2022): 3265. http://dx.doi.org/10.3390/molecules27103265.

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The chiral drug candidates have more effective binding affinities for their specific protein or receptor site for the onset of pharmacological action. Achieving all carbon stereopure compounds is not trivial in chemical synthesis. However, with the development of asymmetric organocatalysis, the synthesis of certain vital chiral drug candidates is now possible. In this research, we have synthesized 3-(((1S,3S)-3-((R)-hydroxy(4-(trifluoromethyl)phenyl)methyl)-4-oxocyclohexyl)methyl)pentane-2,4-dione (S,S,R-5) and have evaluated it potential as multi-target antidiabetic agent. The stereopure compound S,S,R-5 was synthesized with a 99:1 enantiomeric ratio. The synthesized compound gave encouraging results against all in vitro antidiabetic targets, exhibiting IC50 values of 6.28, 4.58, 0.91, and 2.36 in α-glucosidase, α-amylase, PTP1B, and DPPH targets, respectively. The molecular docking shows the binding of the compound in homology models of the respective enzymes. In conclusion, we have synthesized a new chiral molecule (S,S,R-5). The compound proved to be a potential inhibitor of the tested antidiabetic targets. With the observed results and molecular docking, it is evident that S,S,R-5 is a potential multitarget antidiabetic agent. Our study laid the baseline for the animal-based studies of this compound in antidiabetic confirmation.

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Kaniakova, Martina, Eugenie Nepovimova, Lenka Kleteckova, Kristyna Skrenkova, Kristina Holubova, Zofia Chrienova, Vendula Hepnarova, et al. "Combination of Memantine and 6-Chlorotacrine as Novel Multi-Target Compound against Alzheimer’s Disease." Current Alzheimer Research 16, no. 9 (October 29, 2019): 821–33. http://dx.doi.org/10.2174/1567205016666190228122218.

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Background: Alzheimer’s disease (AD) is the most common form of dementia in the elderly. It is characterized as a multi-factorial disorder with a prevalent genetic component. Due to the unknown etiology, current treatment based on acetylcholinesterase (AChE) inhibitors and N–methyl-D-aspartate receptors (NMDAR) antagonist is effective only temporary. It seems that curative treatment will necessarily be complex due to the multifactorial nature of the disease. In this context, the so-called “multi-targeting" approach has been established. Objectives: The aim of this study was to develop a multi-target-directed ligand (MTDL) combining the support for the cholinergic system by inhibition of AChE and at the same time ameliorating the burden caused by glutamate excitotoxicity mediated by the NMDAR receptors. Methods: We have applied common approaches of organic chemistry to prepare a hybrid of 6-chlorotacrine and memantine. Then, we investigated its blocking ability towards AChE and NMDRS in vitro, as well as its neuroprotective efficacy in vivo in the model of NMDA-induced lessions. We also studied cytotoxic potential of the compound and predicted the ability to cross the blood-brain barrier. Results: novel molecule formed by combination of 6-chlorotacrine and memantine proved to be a promising multipotent hybrid capable of blocking the action of AChE as well as NMDARs. The presented hybrid surpassed the AChE inhibitory activity of the parent compound 6-Cl-THA twofold. According to results it has been revealed that our novel hybrid blocks NMDARs in the same manner as memantine, potently inhibits AChE and is predicted to cross the blood-brain barrier via passive diffusion. Finally, the MTDL design strategy was indicated by in vivo results which showed that the novel 6-Cl-THA-memantine hybrid displayed a quantitatively better neuroprotective effect than the parent compound memantine. Conclusion: We conclude that the combination of two pharmacophores with a synergistic mechanism of action into a single molecule offers great potential for the treatment of CNS disorders associated with cognitive decline and/or excitotoxicity mediated by NMDARs.

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Capurro, Valeria, Perrine Busquet, Joao Pedro Lopes, Rosalia Bertorelli, Glauco Tarozzo, Maria Laura Bolognesi, Daniele Piomelli, Angelo Reggiani, and Andrea Cavalli. "Pharmacological Characterization of Memoquin, a Multi-Target Compound for the Treatment of Alzheimer's Disease." PLoS ONE 8, no. 2 (February 18, 2013): e56870. http://dx.doi.org/10.1371/journal.pone.0056870.

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Maroto, Marcos, Antonio M. G. de Diego, Elisa Albiñana, José C. Fernandez-Morales, Afonso Caricati-Neto, Aron Jurkiewicz, Matilde Yáñez, et al. "Multi-target novel neuroprotective compound ITH33/IQM9.21 inhibits calcium entry, calcium signals and exocytosis." Cell Calcium 50, no. 4 (October 2011): 359–69. http://dx.doi.org/10.1016/j.ceca.2011.06.006.

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Carpenter, Kristy, Alexander Pilozzi, and Xudong Huang. "A Pilot Study of Multi-Input Recurrent Neural Networks for Drug-Kinase Binding Prediction." Molecules 25, no. 15 (July 24, 2020): 3372. http://dx.doi.org/10.3390/molecules25153372.

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The use of virtual drug screening can be beneficial to research teams, enabling them to narrow down potentially useful compounds for further study. A variety of virtual screening methods have been developed, typically with machine learning classifiers at the center of their design. In the present study, we created a virtual screener for protein kinase inhibitors. Experimental compound–target interaction data were obtained from the IDG-DREAM Drug-Kinase Binding Prediction Challenge. These data were converted and fed as inputs into two multi-input recurrent neural networks (RNNs). The first network utilized data encoded in one-hot representation, while the other incorporated embedding layers. The models were developed in Python, and were designed to output the IC50 of the target compounds. The performance of the models was assessed primarily through analysis of the Q2 values produced from runs of differing sample and epoch size; recorded loss values were also reported and graphed. The performance of the models was limited, though multiple changes are proposed for potential improvement of a multi-input recurrent neural network-based screening tool.

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Molga, Karol, Piotr Dittwald, and Bartosz A. Grzybowski. "Computational design of syntheses leading to compound libraries or isotopically labelled targets." Chemical Science 10, no. 40 (2019): 9219–32. http://dx.doi.org/10.1039/c9sc02678a.

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Network-search routines over large graphs of retrosynthetic scenarios are adapted to multi-target design operating on one common search graph enabling design of syntheses of compound libraries or isotopically labelled targets.

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Anastassova, Neda, Denitsa Aluani, Nadya Hristova-Avakumova, Virginia Tzankova, Magdalena Kondeva-Burdina, Miroslav Rangelov, Nadezhda Todorova, and Denitsa Yancheva. "Study on the Neuroprotective, Radical-Scavenging and MAO-B Inhibiting Properties of New Benzimidazole Arylhydrazones as Potential Multi-Target Drugs for the Treatment of Parkinson’s Disease." Antioxidants 11, no. 5 (April 29, 2022): 884. http://dx.doi.org/10.3390/antiox11050884.

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Oxidative stress is a key contributing factor in the complex degenerating cascade in Parkinson’s disease. The inhibition of MAO-B affords higher dopamine bioavailability and stops ROS formation. The incorporation of hydroxy and methoxy groups in the arylhydrazone moiety of a new series of 1,3-disubstituted benzimidazole-2-thiones could increase the neuroprotective activity. In vitro safety evaluation on SH-SY5Y cells and rat brain synaptosomes showed a strong safety profile. Antioxidant and neuroprotective effects were evaluated in H2O2-induced oxidative stress on SH-SY5Y cells and in a model of 6-OHDA-induced neurotoxicity in rat brain synaptosomes, where the dihydroxy compounds 3h and 3i demonstrated the most robust neuroprotective and antioxidant activity, more pronounced than the reference melatonin and rasagiline. Statistically significant MAO-B inhibitory effects were exerted by some of the compounds where again the catecholic compound 3h was the most potent inhibitor similar to selegiline and rasagiline. The most potent antioxidant effect in the ferrous iron induced lipid peroxidation assay was observed for the three catechols—3h and 3j, 3q. The catecholic compound 3h showed scavenging capability against superoxide radicals and antioxidant effect in the iron/deoxyribose system. The study outlines a perspective multifunctional compound with the best safety profile, neuroprotective, antioxidant and MAO-B inhibiting properties.

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Dong, Zhen, Mengting Liu, Xianglin Zou, Wenqing Sun, Xiubin Liu, Jianguo Zeng, and Zihui Yang. "Integrating Network Pharmacology and Molecular Docking to Analyse the Potential Mechanism of action of Macleaya cordata (Willd.) R. Br. in the Treatment of Bovine Hoof Disease." Veterinary Sciences 9, no. 1 (December 30, 2021): 11. http://dx.doi.org/10.3390/vetsci9010011.

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Based on network pharmacological analysis and molecular docking techniques, the main components of M. cordata for the treatment of bovine relevant active compounds in M. cordata were searched for through previous research bases and literature databases, and then screened to identify candidate compounds based on physicochemical properties, pharmacokinetic parameters, bioavailability, and drug-like criteria. Target genes associated with hoof disease were obtained from the GeneCards database. Compound−target, compound−target−pathway−disease visualization networks, and protein−protein interaction (PPI) networks were constructed by Cytoscape. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed in R language. Molecular docking analysis was done using AutoDockTools. The visual network analysis showed that four active compounds, sanguinarine, chelerythrine, allocryptopine and protopine, were associated with the 10 target genes/proteins (SRC, MAPK3, MTOR, ESR1, PIK3CA, BCL2L1, JAK2, GSK3B, MAPK1, and AR) obtained from the screen. The enrichment analysis indicated that the cAMP, PI3K-Akt, and ErbB signaling pathways may be key signaling pathways in network pharmacology. The molecular docking results showed that sanguinarine, chelerythrine, allocryptopine, and protopine bound well to MAPK3 and JAK2. A comprehensive bioinformatics-based network topology strategy and molecular docking study has elucidated the multi-component synergistic mechanism of action of M. cordata in the treatment of bovine hoof disease, offering the possibility of developing M. cordata as a new source of drugs for hoof disease treatment.

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Nguyen, Tan Khanh, Huy Hieu Phung, Won Jun Choi, and Hee-Chul Ahn. "Network Pharmacology and Molecular Docking Study on the Multi-Target Mechanisms of Aloe vera for Non-Alcoholic Steatohepatitis Treatment." Plants 11, no. 24 (December 19, 2022): 3585. http://dx.doi.org/10.3390/plants11243585.

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Non-alcoholic steatohepatitis (NASH) is a leading cause of chronic liver disease with limited treatment options. The widely distributed plant Aloe vera has shown protective effects against NASH in animals, yet the precise mechanism remains unknown. In this study, we investigated the potential mechanisms underlying the anti-NASH effects of Aloe vera using a network pharmacology and molecular docking approach. By searching online databases and analyzing the Gene Expression Omnibus dataset, we obtained 260 Aloe vera–NASH common targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the common targets were strongly associated with the key pathological processes implicated in NASH, including lipid and glucose metabolism, inflammation, apoptosis, oxidative stress, and liver fibrosis. Four core proteins, AKT serine/threonine kinase 1 (AKT1), tumor necrosis factor alpha (TNFα), transcription factor c-Jun, and tumor suppressor protein p53, were identified from compound–target–pathway and protein–protein interaction networks. Molecular docking analysis verified that the active ingredients of Aloe vera were able to interact with the core proteins, especially AKT1 and TNFα. The results demonstrate the multi-compound, multi-target, and multi-pathway mechanisms of Aloe vera against NASH. Our study has shown the scientific basis for further experiments in terms of the mechanism to develop Aloe vera-based natural products as complementary treatments for NASH. Furthermore, it identifies novel drug candidates based on the structures of Aloe vera’s active compounds.

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Such, Justyna, Krzysztof Jóźwiak, and Artur Wnorowski. "(R,R′)-4′-methoxy-1-naphthylfenoterol as a new multi-target compound of antitumorigenic properties." Postępy Polskiej Medycyny i Farmacji 5 (June 26, 2017): 9–15. http://dx.doi.org/10.5604/01.3001.0011.6190.

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Targeted therapies are based on the use of compounds that inhibit a specific target molecule within the tissue of interest. The recent advances in the molecular etiology of cancer significantly shifted the therapeutic approach from nonspecific cytotoxic agents towards molecules directed either at individual receptors or acting simultaneously on multiple molecular targets. This article is an overview of recent literature on (R,R′)-4′-methoxy-1-naphthylfenoterol (MNF), a novel bifunctional ligand that activates β2 adrenergic receptor (β2AR) and blocks GPR55 receptor. These two activities are important for MNF-dependent inhibition of cancer cell proliferation in vitro and in vivo, highlighting the potential applicability of MNF in multitarget anticancer therapies.

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Alfei, Silvana, Federica Turrini, Silvia Catena, Paola Zunin, Massimo Grilli, Anna Maria Pittaluga, and Raffaella Boggia. "Ellagic acid a multi-target bioactive compound for drug discovery in CNS? A narrative review." European Journal of Medicinal Chemistry 183 (December 2019): 111724. http://dx.doi.org/10.1016/j.ejmech.2019.111724.

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Caruso, Lucas, Nathalia Fonseca Nadur, Marina Brandão da Fonseca, Larissa de Almeida Peixoto Ferreira, Renata Barbosa Lacerda, Cedric Stephan Graebin, and Arthur Eugen Kümmerle. "The Design of Multi-target Drugs to Treat Cardiovascular Diseases: Two (or more) Birds on One Stone." Current Topics in Medicinal Chemistry 22, no. 5 (February 2022): 366–94. http://dx.doi.org/10.2174/1568026622666220201151248.

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Abstract: Cardiovascular diseases (CVDs) comprise a group of diseases and disorders of the heart and blood vessels, which together are the number one cause of death worldwide, being associated with multiple genetic and modifiable risk factors, and that may directly arise from different etiologies. For a long time, the search for cardiovascular drugs was based on the old paradigm “one compound - one target”, aiming to obtain a highly potent and selective molecule with only one desired molecular target. Although historically successful in the last decades, this approach ignores the multiple causes and the multifactorial nature of CVDs. Thus, over time, treatment strategies for cardiovascular diseases have changed, and, currently, pharmacological therapies for CVD are mainly based on the association of two or more drugs to control symptoms and reduce cardiovascular death. In this context, the development of multitarget drugs, i.e., compounds having the ability to act simultaneously at multiple sites, is an attractive and relevant strategy that can be even more advantageous to achieve predictable pharmacokinetic and pharmacodynamics correlations as well as better patient compliance. In this review, we aim to highlight the efforts and rational pharmacological bases for the design of some promising multitargeted compounds to treat important cardiovascular diseases like heart failure, atherosclerosis, acute myocardial infarction, pulmonary arterial hypertension, and arrhythmia.

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Fayyazi, Neda, Somayeh Esmaeili, Salman Taheri, Frederico F. Ribeiro, Marcus T. Scotti, Luciana Scotti, Jahan B. Ghasemi, Lotfollah Saghaei, and Afshin Fassihi. "Pharmacophore Modeling, Synthesis, Scaffold Hopping and Biological β- Hematin Inhibition Interaction Studies for Anti-malaria Compounds." Current Topics in Medicinal Chemistry 19, no. 30 (January 3, 2020): 2743–65. http://dx.doi.org/10.2174/1568026619666191116160326.

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Backgound: Exploring potent compounds is critical to generating multi-target drug discovery. Hematin crystallization is an important mechanism of malaria. Methods: A series of chloroquine analogues were designed using a repositioning approach to develop new anticancer compounds. Protein-ligand interaction fingerprints and ADMET descriptors were used to assess docking performance in virtual screenings to design chloroquine hybrid β-hematin inhibitors. A PLS algorithm was applied to correlate the molecular descriptors to IC50 values. The modeling presented excellent predictive power with correlation coefficients for calibration and cross-validation of r2 = 0.93 and q2 = 0.72. Using the model, a series of 4-aminoquinlin hybrids were synthesized and evaluated for their biological activity as an external test series. These compounds were evaluated for cytotoxic cell lines and β-hematin inhibition. Results: The target compounds exhibited high β-hematin inhibition activity and were 3-9 times more active than the positive control. Furthermore, all the compounds exhibited moderate to high cytotoxic activity. The most potent compound in the dataset was docked with hemoglobin and its pharmacophore features were generated. These features were used as input to the Pharmit server for screening of six databases. Conclusion: The compound with the best score from ChEMBL was 2016904, previously reported as a VEGFR-2 inhibitor. The 11 compounds selected presented the best Gold scores with drug-like properties and can be used for drug development.

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Journal articles on the topic 'Multi-target compound'

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