1
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Azevedo LG, Sosa E, de Queiroz ATL, Barral A, Wheeler RJ, Nicolás MF, Farias LP, Do Porto DF, Ramos PIP. High-throughput prioritization of target proteins for development of new antileishmanial compounds. Int J Parasitol Drugs Drug Resist 2024; 25:100538. [PMID: 38669848 PMCID: PMC11068527 DOI: 10.1016/j.ijpddr.2024.100538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 03/11/2024] [Accepted: 04/04/2024] [Indexed: 04/28/2024]
Abstract
Leishmaniasis, a vector-borne disease, is caused by the infection of Leishmania spp., obligate intracellular protozoan parasites. Presently, human vaccines are unavailable, and the primary treatment relies heavily on systemic drugs, often presenting with suboptimal formulations and substantial toxicity, making new drugs a high priority for LMIC countries burdened by the disease, but a low priority in the agenda of most pharmaceutical companies due to unattractive profit margins. New ways to accelerate the discovery of new, or the repositioning of existing drugs, are needed. To address this challenge, our study aimed to identify potential protein targets shared among clinically-relevant Leishmania species. We employed a subtractive proteomics and comparative genomics approach, integrating high-throughput multi-omics data to classify these targets based on different druggability metrics. This effort resulted in the ranking of 6502 ortholog groups of protein targets across 14 pathogenic Leishmania species. Among the top 20 highly ranked groups, metabolic processes known to be attractive drug targets, including the ubiquitination pathway, aminoacyl-tRNA synthetases, and purine synthesis, were rediscovered. Additionally, we unveiled novel promising targets such as the nicotinate phosphoribosyltransferase enzyme and dihydrolipoamide succinyltransferases. These groups exhibited appealing druggability features, including less than 40% sequence identity to the human host proteome, predicted essentiality, structural classification as highly druggable or druggable, and expression levels above the 50th percentile in the amastigote form. The resources presented in this work also represent a comprehensive collection of integrated data regarding trypanosomatid biology.
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Affiliation(s)
- Lucas G Azevedo
- Center for Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, Bahia, Brazil; Post-graduate Program in Biotechnology and Investigative Medicine, Instituto Gonçalo Moniz, Salvador, Bahia, Brazil.
| | - Ezequiel Sosa
- Universidad de Buenos Aires, Buenos Aires, Argentina.
| | - Artur T L de Queiroz
- Center for Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, Bahia, Brazil; Post-graduate Program in Biotechnology and Investigative Medicine, Instituto Gonçalo Moniz, Salvador, Bahia, Brazil.
| | - Aldina Barral
- Laboratório de Medicina e Saúde Pública de Precisão (MeSP2), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, Bahia, Brazil.
| | - Richard J Wheeler
- Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
| | - Marisa F Nicolás
- Laboratório Nacional de Computação Científica, Petrópolis, Rio de Janeiro, Brazil.
| | - Leonardo P Farias
- Post-graduate Program in Biotechnology and Investigative Medicine, Instituto Gonçalo Moniz, Salvador, Bahia, Brazil; Laboratório de Medicina e Saúde Pública de Precisão (MeSP2), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, Bahia, Brazil.
| | | | - Pablo Ivan P Ramos
- Center for Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz (Fiocruz Bahia), Salvador, Bahia, Brazil; Post-graduate Program in Biotechnology and Investigative Medicine, Instituto Gonçalo Moniz, Salvador, Bahia, Brazil.
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2
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Guerrero RF, Dorji T, Harris RM, Shoulders MD, Ogbunugafor CB. Evolutionary druggability for low-dimensional fitness landscapes toward new metrics for antimicrobial applications. eLife 2024; 12:RP88480. [PMID: 38833384 PMCID: PMC11149929 DOI: 10.7554/elife.88480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2024] Open
Abstract
The term 'druggability' describes the molecular properties of drugs or targets in pharmacological interventions and is commonly used in work involving drug development for clinical applications. There are no current analogues for this notion that quantify the drug-target interaction with respect to a given target variant's sensitivity across a breadth of drugs in a panel, or a given drug's range of effectiveness across alleles of a target protein. Using data from low-dimensional empirical fitness landscapes composed of 16 β-lactamase alleles and 7 β-lactam drugs, we introduce two metrics that capture (i) the average susceptibility of an allelic variant of a drug target to any available drug in a given panel ('variant vulnerability'), and (ii) the average applicability of a drug (or mixture) across allelic variants of a drug target ('drug applicability'). Finally, we (iii) disentangle the quality and magnitude of interactions between loci in the drug target and the seven drug environments in terms of their mutation by mutation by environment (G x G x E) interactions, offering mechanistic insight into the variant variability and drug applicability metrics. Summarizing, we propose that our framework can be applied to other datasets and pathogen-drug systems to understand which pathogen variants in a clinical setting are the most concerning (low variant vulnerability), and which drugs in a panel are most likely to be effective in an infection defined by standing genetic variation in the pathogen drug target (high drug applicability).
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Affiliation(s)
- Rafael F Guerrero
- Department of Biological Sciences, North Carolina State UniversityRaleighUnited States
| | - Tandin Dorji
- Department of Mathematics and Statistics, University of VermontBurlingtonUnited States
| | - Ra'Mal M Harris
- Department of Chemistry, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Matthew D Shoulders
- Department of Chemistry, Massachusetts Institute of TechnologyCambridgeUnited States
| | - C Brandon Ogbunugafor
- Department of Chemistry, Massachusetts Institute of TechnologyCambridgeUnited States
- Department of Ecology and Evolutionary Biology, Yale UniversityNew HavenUnited States
- Santa Fe InstituteSanta FeUnited States
- Public Health Modeling Unit, Yale School of Public HealthNew HavenUnited States
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3
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Al Otaibi AA, Alshammari SL, Dhahi Alsukaibi AK, Jamal A, Rajendrasozhan S, Alenezi KM, Hussain A, Khan I, Mushtaque M, Haque A. Synthesis, anticancer activity, molecular docking and molecular dynamics studies of some pyrazole-chalcone hybrids. J Biomol Struct Dyn 2024; 42:1381-1391. [PMID: 37071766 DOI: 10.1080/07391102.2023.2199867] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 03/31/2023] [Indexed: 04/20/2023]
Abstract
Four new hybrid compounds (H1-H4) bearing pyrazole (S1 and S2) and chalcone (P1 and P2) fragments were synthesized and characterized. Compounds were assayed for their ability to inhibit the proliferation of human lung (A549) and colon (Caco-2) cancer cell lines. Besides, toxicity against normal cells was determined using the human umbilical vein endothelial cells (HUVEC). In silico molecular docking, molecular dynamics (MD) simulation and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies were carried out to predict the binding modes, protein stability, drug-likeness and toxicity of the reported compounds. The in vitro anticancer activity of the tested compounds revealed dose-dependent cell-specific cytotoxicity. In silico studies revealed that the compounds have a good binding affinity, possess appropriate drug-likeness properties and have low toxicity profiles.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Ahmed A Al Otaibi
- Department of Chemistry, College of Science, University of Ha'il, Ha'il, Saudi Arabia
| | - Sinad L Alshammari
- Department of Chemistry, College of Science, University of Ha'il, Ha'il, Saudi Arabia
| | | | - Azfar Jamal
- Department of Biology, College of Science, Al-Zulfi, Majmaah University, Majmaah, Riyadh Region, Saudi Arabia
- Health and Basic Science Research Centre, Majmaah University, Majmaah, Saudi Arabia
| | | | - Khalaf M Alenezi
- Department of Chemistry, College of Science, University of Ha'il, Ha'il, Saudi Arabia
| | - Afzal Hussain
- Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Imran Khan
- Department of Chemistry, College of Science, Sultan Qaboos University, Muscat, Oman
| | - Md Mushtaque
- Department of Chemistry, Millat College (A Constituent College of Lalit Narayan Mithila University), Darbhanga, Bihar, India
| | - Ashanul Haque
- Department of Chemistry, College of Science, University of Ha'il, Ha'il, Saudi Arabia
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Liu M, Srivastava G, Ramanujam J, Brylinski M. Augmented drug combination dataset to improve the performance of machine learning models predicting synergistic anticancer effects. Sci Rep 2024; 14:1668. [PMID: 38238448 PMCID: PMC10796434 DOI: 10.1038/s41598-024-51940-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 01/11/2024] [Indexed: 01/22/2024] Open
Abstract
Combination therapy has gained popularity in cancer treatment as it enhances the treatment efficacy and overcomes drug resistance. Although machine learning (ML) techniques have become an indispensable tool for discovering new drug combinations, the data on drug combination therapy currently available may be insufficient to build high-precision models. We developed a data augmentation protocol to unbiasedly scale up the existing anti-cancer drug synergy dataset. Using a new drug similarity metric, we augmented the synergy data by substituting a compound in a drug combination instance with another molecule that exhibits highly similar pharmacological effects. Using this protocol, we were able to upscale the AZ-DREAM Challenges dataset from 8798 to 6,016,697 drug combinations. Comprehensive performance evaluations show that ML models trained on the augmented data consistently achieve higher accuracy than those trained solely on the original dataset. Our data augmentation protocol provides a systematic and unbiased approach to generating more diverse and larger-scale drug combination datasets, enabling the development of more precise and effective ML models. The protocol presented in this study could serve as a foundation for future research aimed at discovering novel and effective drug combinations for cancer treatment.
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Affiliation(s)
- Mengmeng Liu
- Division of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - Gopal Srivastava
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - J Ramanujam
- Division of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA
- Center for Computation and Technology, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - Michal Brylinski
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, 70803, USA.
- Center for Computation and Technology, Louisiana State University, Baton Rouge, LA, 70803, USA.
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Haque A, Alenezi KM, Al-Otaibi A, Alsukaibi AKD, Rahman A, Hsieh MF, Tseng MW, Wong WY. Synthesis, Characterization, Cytotoxicity, Cellular Imaging, Molecular Docking, and ADMET Studies of Piperazine-Linked 1,8-Naphthalimide-Arylsulfonyl Derivatives. Int J Mol Sci 2024; 25:1069. [PMID: 38256142 PMCID: PMC10816875 DOI: 10.3390/ijms25021069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/06/2024] [Accepted: 01/08/2024] [Indexed: 01/24/2024] Open
Abstract
To reduce the mortality and morbidity associated with cancer, new cancer theranostics are in high demand and are an emerging area of research. To achieve this goal, we report the synthesis and characterization of piperazine-linked 1,8-naphthalimide-arylsulfonyl derivatives (SA1-SA7). These compounds were synthesized in good yields following a two-step protocol and characterized using multiple analytical techniques. In vitro cytotoxicity and fluorescent cellular imaging of the compounds were assessed against non-cancerous fibroblast (3T3) and breast cancer (4T1) cell lines. Although the former study indicated the safe nature of the compounds (viability = 82-95% at 1 μg/mL), imaging studies revealed that the designed probes had good membrane permeability and could disperse in the whole cell cytoplasm. In silico studies, including molecular docking, molecular dynamics (MD) simulation, and ADME/Tox results, indicated that the compounds had the ability to target CAIX-expressing cancers. These findings suggest that piperazine-linked 1,8-naphthalimide-arylsulfonyl derivatives are potential candidates for cancer theranostics and a valuable backbone for future research.
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Affiliation(s)
- Ashanul Haque
- Department of Chemistry, College of Science, University of Ha’il, Ha’il 81451, Saudi Arabia; (A.H.); (K.M.A.); (A.A.-O.); (A.K.D.A.)
- Medical and Diagnostic Research Centre, University of Ha’il, Ha’il 55473, Saudi Arabia
| | - Khalaf M. Alenezi
- Department of Chemistry, College of Science, University of Ha’il, Ha’il 81451, Saudi Arabia; (A.H.); (K.M.A.); (A.A.-O.); (A.K.D.A.)
- Medical and Diagnostic Research Centre, University of Ha’il, Ha’il 55473, Saudi Arabia
| | - Ahmed Al-Otaibi
- Department of Chemistry, College of Science, University of Ha’il, Ha’il 81451, Saudi Arabia; (A.H.); (K.M.A.); (A.A.-O.); (A.K.D.A.)
- Medical and Diagnostic Research Centre, University of Ha’il, Ha’il 55473, Saudi Arabia
| | - Abdulmohsen Khalaf Dhahi Alsukaibi
- Department of Chemistry, College of Science, University of Ha’il, Ha’il 81451, Saudi Arabia; (A.H.); (K.M.A.); (A.A.-O.); (A.K.D.A.)
- Medical and Diagnostic Research Centre, University of Ha’il, Ha’il 55473, Saudi Arabia
| | - Ataur Rahman
- Jamia Senior Secondary School, Jamia Millia Islamia, New Delhi 110025, India;
| | - Ming-Fa Hsieh
- Department of Biomedical Engineering, Chung Yuan Christian University, 200 Chung Pei Road, Chung Li District, Taoyuan City 32023, Taiwan;
| | - Mei-Wen Tseng
- Department of Biomedical Engineering, Chung Yuan Christian University, 200 Chung Pei Road, Chung Li District, Taoyuan City 32023, Taiwan;
| | - Wai-Yeung Wong
- Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
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6
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Stoorza AM, Duerfeldt AS. Guiding the Way: Traditional Medicinal Chemistry Inspiration for Rational Gram-Negative Drug Design. J Med Chem 2024; 67:65-80. [PMID: 38134355 PMCID: PMC11342810 DOI: 10.1021/acs.jmedchem.3c01831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2023]
Abstract
The discovery and development of small-molecule therapeutics effective against Gram-negative pathogens are highly challenging tasks. Most compounds that are active in biochemical settings fail to exhibit whole-cell activity. The major reason for this lack of activity is the effectiveness of bacterial cell envelopes as permeability barriers. These barriers originate from the nutrient-selective outer membranes, which act synergistically with polyspecific efflux pumps. Guiding principles to enable rational optimization of small molecules for efficient penetration and intracellular accumulation in Gram-negative bacteria would have a transformative impact on the discovery and design of chemical probes and therapeutics. In this Perspective, we draw on inspiration from traditional medicinal chemistry approaches for eukaryotic drug design to present a broader call for action in developing comparable approaches for Gram-negative bacteria.
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Affiliation(s)
- Alexis M Stoorza
- Department of Medicinal Chemistry, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota 55414, United States
| | - Adam S Duerfeldt
- Department of Medicinal Chemistry, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota 55414, United States
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7
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Riyad P, Purohit A, Sen K, Panwar A, Ram H. HMG – CoA reductase inhibition mediated hypocholesterolemic potential of myricetin and quercetin: in-silico and in-vivo studies. CYTA - JOURNAL OF FOOD 2023. [DOI: 10.1080/19476337.2022.2162976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Affiliation(s)
- Priyanka Riyad
- Department of Zoology, Jai Narain Vyas University, Jodhpur, India
| | - Ashok Purohit
- Department of Zoology, Jai Narain Vyas University, Jodhpur, India
| | - Karishma Sen
- Department of Zoology, Jai Narain Vyas University, Jodhpur, India
| | - Anil Panwar
- Department of Molecular Biology, Biotechnology & Bioinformatics, College of Basic Sciences & Humanities, CCS Haryana Agricultural University, Hisar, India
| | - Heera Ram
- Department of Zoology, Jai Narain Vyas University, Jodhpur, India
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8
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Zekri A, Harkati D, Kenouche S, Saleh BA, Alnajjar R. A computational study of potent series of selective estrogen receptor degraders for breast cancer therapy. J Biomol Struct Dyn 2023; 41:11078-11100. [PMID: 36537313 DOI: 10.1080/07391102.2022.2159877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022]
Abstract
A detailed multistep framework combining quantitative structure-activity relationship, global reactivity, absorption, distribution, metabolism and elimination properties, molecular docking and molecular dynamics simulation (MD) on a series of Selective Estrogen Receptor Down-Regulators (SERDs) interacting with Estrogen Receptor α (ERα) has been performed. The partial least squares regression method derived an empirical model with better predictive capability. The results of global reactivity descriptors revealed that all the compounds are considered strong electrophiles, allowing them to participate in polar reactions more easily. The Brain Or IntestinaL EstimateD permeation diagram revealed that compounds 49 and 31 were predicted to be well absorbed by the human gastrointestinal tract and would not enter the brain. The elucidation of the binding mode between the most active compounds that comply with Lipinski's and Veber's rules from the dataset and ERα targets was explored by molecular docking. The MD simulations were performed for 100 ns on the best compounds, which indicated their stability state under dynamics simulations. These findings are expected to help predict the anticancer activities of the studied SERD compounds and better understand their binding mechanism with ERα targets.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Afaf Zekri
- Group of Computational and Pharmaceutical Chemistry, LMCE Laboratory, University of Biskra, Biskra, Algeria
| | - Dalal Harkati
- Group of Computational and Pharmaceutical Chemistry, LMCE Laboratory, University of Biskra, Biskra, Algeria
| | - Samir Kenouche
- Group of Modeling of Chemical Systems Using Quantum Calculations, Applied Chemistry Laboratory, University of Biskra, Biskra, Algeria
| | - Basil A Saleh
- Department of Chemistry, College of Science, University of Basrah, Basrah, Iraq
| | - Radwan Alnajjar
- Department of Chemistry, Faculty of Science, University of Benghazi, Benghazi, Libya
- Department of Chemistry, University of Cape Town, Rondebosch, South Africa
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Rehman MU, Ali A, Ansar R, Arafah A, Imtiyaz Z, Wani TA, Zargar S, Ganie SA. In Silico molecular docking and dynamic analysis of natural compounds against major non-structural proteins of SARS-COV-2. J Biomol Struct Dyn 2023; 41:9072-9088. [PMID: 36326281 DOI: 10.1080/07391102.2022.2139766] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 10/19/2022] [Indexed: 11/06/2022]
Abstract
COVID-19 has infected millions and significantly affected the global economy and healthcare systems. Despite continuous lockdowns, symptomatic management with currently available medications, and numerous vaccination drives, it is still far more difficult to control. Against COVID-19 infection, the pressure to develop vaccines and drugs has led to using some currently available medications like remdesivir, azithromycin, hydroxychloroquine and ritonavir. Understanding the importance and potential of harmless molecules to tackle SARS-COV-2, we designed the present study to identify potential natural phytocompounds. In the present study, we docked natural compounds and standard drugs against SARS-COV-2 proteins: papain-like protease, main protease and helicase. ADME/T and ProTox-II analyses were used to determine the toxicity of phytocompounds and drugs. The docking analysis revealed that podophyllotoxin gave the highest binding affinity scores of -8.1, -7.1 and -7.4 kcal/mol against PLpro, Mpro and helicase, respectively. Among the control drugs, doxycycline hydrochloride showed the highest binding affinity of -10.5, -8.4 and -8.8 kcal/mol against PLpro, Mpro and helicase. The results of this study revealed that podophyllotoxin and doxycycline hydrochloride could be promising inhibitors against SARS-Cov-2. Molecular dynamic simulations were executed for the best docked (PLpro-podophyllotoxin) complex, and the results displayed stable conformation and convergence. Energy plot results predicted a global minima average energy of -95 kcal/mol and indicated podophyllotoxin's role in stabilizing protein and making it compact and complex. FarPPI server used MM/GBSA approach to determine free binding affinity, and helicase-gallic acid complex showed the highest affinity, respectively. Therefore, it can be concluded that there is still a need for in vitro and in vivo studies to support further and validate these findings and validate these findings.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Muneeb U Rehman
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Aarif Ali
- Department of Clinical Biochemistry, School of Biological Sciences, University of Kashmir, Hazratbal, Srinagar, J&K, India
| | - Ruhban Ansar
- Department of Clinical Biochemistry, School of Biological Sciences, University of Kashmir, Hazratbal, Srinagar, J&K, India
| | - Azher Arafah
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Zuha Imtiyaz
- Department of Pathology, University Maryland School of Medicine, University of Maryland, Baltimore, MD, USA
| | - Tanveer A Wani
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Seema Zargar
- Department of Biochemistry, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Showkat A Ganie
- Department of Clinical Biochemistry, School of Biological Sciences, University of Kashmir, Hazratbal, Srinagar, J&K, India
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Malla BA, Ali A, Maqbool I, Dar NA, Ahmad SB, Alsaffar RM, Rehman MU. Insights into molecular docking and dynamics to reveal therapeutic potential of natural compounds against P53 protein. J Biomol Struct Dyn 2023; 41:8762-8781. [PMID: 36281711 DOI: 10.1080/07391102.2022.2137241] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 10/11/2022] [Indexed: 10/31/2022]
Abstract
P53 is eminent tumour suppressor protein that plays a prominent role in cell cycle arrest, DNA repair, senescence, differentiation and initiation of apoptosis. P53 is an attractive drug target and the high toxicity of some cancer chemotherapy drugs increase the demand for new anti-cancer drugs from natural products. In this current scenario, identification of promising anticancer compounds from natural sources by repurposing approach is still relevant for the early prevention and effective management of cancer. In present study, we docked natural compounds like podophyllotoxin, quercetin and rutin along standard drugs (MG-132 and Bay 61-3606) against p53 protein. ADME/T analysis predicted toxicity of phytochemicals and drugs. In silico docking analysis of podophyllotoxin, quercetin and rutin gave HDOCK docking scores of -187.87, -148. 97 and -143.85, whereas control drugs MG-132 and Bay 61-3606 showed docking scores of -159.59 and -140.71 against p53 respectively. AutoDock analysis of rutin and MG-132 showed highest binding affinity scores of -7.3 and -6.8 kcal/mol against p53. Molecular dynamic simulation for p53 protein displayed stable conformation and convergence. In this study, P53-rutin complex showed free binding energy score of 11.84 kcal/mol and P53-MG-132 complex reported free energy score of 16.3 kcal/mol. Protein contacts atlas gives non-covalent contacts framework by exploring interfaces of individual subunits and protein-ligand interactions. STRING tool predicts physical and functional interactions between proteins. The results of this study revealed that rutin and MG-132 could be promising inhibitors against targeted p53 protein and this could prove detrimental for molecular therapeutics and drug-designing strategies.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Bashir Ahmad Malla
- Department of Biochemistry, School of Biological Sciences, University of Kashmir, Srinagar, J&K, India
| | - Aarif Ali
- Department of Clinical Biochemistry, School of Biological Sciences, University of Kashmir, Srinagar, J&K, India
| | - Irfan Maqbool
- Department of Clinical Biochemistry, SKIMS Soura, Srinagar, J&K, India
| | - Nazir Ahmad Dar
- Department of Biochemistry, School of Biological Sciences, University of Kashmir, Srinagar, J&K, India
| | - Sheikh Bilal Ahmad
- Division of Veterinary Biochemistry, SKUAST-K, Shuhama Alusteng, J&K, India
| | - Rana M Alsaffar
- Department Of Pharmacology & Toxicology, College Of Pharmacy Girls Section, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Muneeb U Rehman
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
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Sarker P, Mitro A, Hoque H, Hasan MN, Nurnabi Azad Jewel GM. Identification of potential novel therapeutic drug target against Elizabethkingia anophelis by integrative pan and subtractive genomic analysis: An in silico approach. Comput Biol Med 2023; 165:107436. [PMID: 37690289 DOI: 10.1016/j.compbiomed.2023.107436] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 07/08/2023] [Accepted: 08/28/2023] [Indexed: 09/12/2023]
Abstract
Elizabethkingia anophelis is a human pathogen responsible for severe nosocomial infections in neonates and immunocompromised patients. The significantly higher mortality rate from E. anophelis infections and the lack of available regimens highlight the critical need to explore novel drug targets. The current study investigated effective novel drug targets by employing a comprehensive in silico subtractive genomic approach integrated with pangenomic analysis of E. anophelis strains. A total of 2809 core genomic proteins were found by pangenomic analysis of non-paralogous proteins. Subsequently, 156 pathogen-specific, 442 choke point, 202 virulence factor, 53 antibiotic resistant and 119 host-pathogen interacting proteins were identified in E. anophelis. By subtractive genomic approach, at first 791 proteins were found to be indispensable for the survival of E. anophelis. 558 and 315 proteins were detected as non-homologous to human and gut microflora respectively. Following that 245 cytoplasmic, 245 novel, and 23 broad-spectrum targets were selected and finally four proteins were considered as potential therapeutic targets of E. anophelis based on highest degree score in PPI network. Among those, three proteins were subjected to molecular docking and subsequent MD simulation as one protein did not contain a plausible binding pocket with sufficient surface area and volume. All the complexes were found to be stable and compact in 100 ns molecular dynamics simulation studies as measured by RMSD, RMSF, and Rg. These three short-listed targets identified in this study may lead to the development of novel antimicrobials capable of curing infections and pave the way to prevent and control the disease progression caused by the deadly agent E. anophelis.
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Affiliation(s)
- Parth Sarker
- Dept. of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, University Ave, Sylhet-3114, Bangladesh; Computational Biology and Bioinformatics Lab, Dept. of GEB, SUST, Sylhet-3114, Bangladesh
| | - Arnob Mitro
- Dept. of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, University Ave, Sylhet-3114, Bangladesh; Computational Biology and Bioinformatics Lab, Dept. of GEB, SUST, Sylhet-3114, Bangladesh
| | - Hammadul Hoque
- Dept. of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, University Ave, Sylhet-3114, Bangladesh
| | - Md Nazmul Hasan
- Dept. of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, University Ave, Sylhet-3114, Bangladesh
| | - G M Nurnabi Azad Jewel
- Dept. of Genetic Engineering and Biotechnology, Shahjalal University of Science and Technology, University Ave, Sylhet-3114, Bangladesh; Computational Biology and Bioinformatics Lab, Dept. of GEB, SUST, Sylhet-3114, Bangladesh.
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Fjodorova N, Novič M, Venko K, Rasulev B, Türker Saçan M, Tugcu G, Sağ Erdem S, Toropova AP, Toropov AA. Cheminformatics and Machine Learning Approaches to Assess Aquatic Toxicity Profiles of Fullerene Derivatives. Int J Mol Sci 2023; 24:14160. [PMID: 37762462 PMCID: PMC10531479 DOI: 10.3390/ijms241814160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 09/05/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
Fullerene derivatives (FDs) are widely used in nanomaterials production, the pharmaceutical industry and biomedicine. In the present study, we focused on the potential toxic effects of FDs on the aquatic environment. First, we analyzed the binding affinity of 169 FDs to 10 human proteins (1D6U, 1E3K, 1GOS, 1GS4, 1H82, 1OG5, 1UOM, 2F9Q, 2J0D, 3ERT) obtained from the Protein Data Bank (PDB) and showing high similarity to proteins from aquatic species. Then, the binding activity of 169 FDs to the enzyme acetylcholinesterase (AChE)-as a known target of toxins in fathead minnows and Daphnia magna, causing the inhibition of AChE-was analyzed. Finally, the structural aquatic toxicity alerts obtained from ToxAlert were used to confirm the possible mechanism of action. Machine learning and cheminformatics tools were used to analyze the data. Counter-propagation artificial neural network (CPANN) models were used to determine key binding properties of FDs to proteins associated with aquatic toxicity. Predicting the binding affinity of unknown FDs using quantitative structure-activity relationship (QSAR) models eliminates the need for complex and time-consuming calculations. The results of the study show which structural features of FDs have the greatest impact on aquatic organisms and help prioritize FDs and make manufacturing decisions.
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Affiliation(s)
- Natalja Fjodorova
- Laboratory for Chemoinformatics, Theory Department, National Institute of Chemistry, Hajdrihova 19, 1001 Ljubljana, Slovenia; (M.N.); (K.V.)
| | - Marjana Novič
- Laboratory for Chemoinformatics, Theory Department, National Institute of Chemistry, Hajdrihova 19, 1001 Ljubljana, Slovenia; (M.N.); (K.V.)
| | - Katja Venko
- Laboratory for Chemoinformatics, Theory Department, National Institute of Chemistry, Hajdrihova 19, 1001 Ljubljana, Slovenia; (M.N.); (K.V.)
| | - Bakhtiyor Rasulev
- Department of Coatings and Polymeric Materials, North Dakota State University, NDSU Dept 2510, P.O. Box 6050, Fargo, ND 58108, USA;
| | - Melek Türker Saçan
- Ecotoxicology and Chemometrics Lab, Institute of Environmental Sciences, Bogazici University, Hisar Campus, 34342 Istanbul, Turkey;
| | - Gulcin Tugcu
- Department of Toxicology, Faculty of Pharmacy, Yeditepe University, Atasehir, 34755 Istanbul, Turkey;
| | - Safiye Sağ Erdem
- Department of Chemistry, Marmara University, 34722 Istanbul, Turkey;
| | - Alla P. Toropova
- Laboratory of Environmental Chemistry and Toxicology, Istituto di Ricerche Farmacologiche Mario Negri, Via Mario Negri 2, 20156 Milano, Italy; (A.P.T.); (A.A.T.)
| | - Andrey A. Toropov
- Laboratory of Environmental Chemistry and Toxicology, Istituto di Ricerche Farmacologiche Mario Negri, Via Mario Negri 2, 20156 Milano, Italy; (A.P.T.); (A.A.T.)
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Guerrero RF, Dorji T, Harris RM, Shoulders MD, Ogbunugafor CB. Evolutionary druggability: leveraging low-dimensional fitness landscapes towards new metrics for antimicrobial applications. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.08.536116. [PMID: 37066376 PMCID: PMC10104179 DOI: 10.1101/2023.04.08.536116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
The term "druggability" describes the molecular properties of drugs or targets in pharmacological interventions and is commonly used in work involving drug development for clinical applications. There are no current analogues for this notion that quantify the drug-target interaction with respect to a given target variant's sensitivity across a breadth of drugs in a panel, or a given drug's range of effectiveness across alleles of a target protein. Using data from low-dimensional empirical fitness landscapes composed of 16 β-lactamase alleles and seven β-lactam drugs, we introduce two metrics that capture (i) the average susceptibility of an allelic variant of a drug target to any available drug in a given panel ("variant vulnerability"), and (ii) the average applicability of a drug (or mixture) across allelic variants of a drug target ("drug applicability"). Finally, we (iii) disentangle the quality and magnitude of interactions between loci in the drug target and the seven drug environments in terms of their mutation by mutation by environment (G × G × E) interactions, offering mechanistic insight into the variant variability and drug applicability metrics. Summarizing, we propose that our framework can be applied to other datasets and pathogen-drug systems to understand which pathogen variants in a clinical setting are the most concerning (low variant vulnerability), and which drugs in a panel are most likely to be effective in an infection defined by standing genetic variation in the pathogen drug target (high drug applicability).
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Affiliation(s)
| | - Tandin Dorji
- Department of Mathematics and Statistics, University of Vermont, Burlington, VT
| | - Ra’Mal M. Harris
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA
| | | | - C. Brandon Ogbunugafor
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA
- DDepartment of Ecology and Evolutionary Biology, Yale University, New Haven, CT
- Santa Fe Institute, Santa Fe, NM
- Public Health Modeling Unit, Yale School of Public Health, New Haven, CT
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14
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Wang X, Chen C, Yan J, Xu Y, Pan D, Wang L, Yang M. Druggability of Targets for Diagnostic Radiopharmaceuticals. ACS Pharmacol Transl Sci 2023; 6:1107-1119. [PMID: 37588760 PMCID: PMC10425999 DOI: 10.1021/acsptsci.3c00081] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Indexed: 08/18/2023]
Abstract
Targets play an indispensable and pivotal role in the development of radiopharmaceuticals. However, the initial stages of drug discovery projects are often plagued by frequent failures due to inadequate information on druggability and suboptimal target selection. In this context, we aim to present a comprehensive review of the factors that influence target druggability for diagnostic radiopharmaceuticals. Specifically, we explore the crucial determinants of target specificity, abundance, localization, and positivity rate and their respective implications. Through a detailed analysis of existing protein targets, we elucidate the significance of each factor. By carefully considering and balancing these factors during the selection of targets, more efficacious and targeted radiopharmaceuticals are expected to be designed for the diagnosis of a wide range of diseases in the future.
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Affiliation(s)
- Xinyu Wang
- NHC
Key Laboratory of Nuclear Medicine, Jiangsu Key Laboratory of Molecular
Nuclear Medicine, Jiangsu Institute of Nuclear
Medicine, Wuxi 214063, PR China
- School
of Pharmacy, Nanjing Medical University, Nanjing 211166, PR China
| | - Chongyang Chen
- NHC
Key Laboratory of Nuclear Medicine, Jiangsu Key Laboratory of Molecular
Nuclear Medicine, Jiangsu Institute of Nuclear
Medicine, Wuxi 214063, PR China
| | - Junjie Yan
- NHC
Key Laboratory of Nuclear Medicine, Jiangsu Key Laboratory of Molecular
Nuclear Medicine, Jiangsu Institute of Nuclear
Medicine, Wuxi 214063, PR China
- School
of Pharmacy, Nanjing Medical University, Nanjing 211166, PR China
| | - Yuping Xu
- NHC
Key Laboratory of Nuclear Medicine, Jiangsu Key Laboratory of Molecular
Nuclear Medicine, Jiangsu Institute of Nuclear
Medicine, Wuxi 214063, PR China
- School
of Pharmacy, Nanjing Medical University, Nanjing 211166, PR China
| | - Donghui Pan
- NHC
Key Laboratory of Nuclear Medicine, Jiangsu Key Laboratory of Molecular
Nuclear Medicine, Jiangsu Institute of Nuclear
Medicine, Wuxi 214063, PR China
| | - Lizhen Wang
- NHC
Key Laboratory of Nuclear Medicine, Jiangsu Key Laboratory of Molecular
Nuclear Medicine, Jiangsu Institute of Nuclear
Medicine, Wuxi 214063, PR China
| | - Min Yang
- NHC
Key Laboratory of Nuclear Medicine, Jiangsu Key Laboratory of Molecular
Nuclear Medicine, Jiangsu Institute of Nuclear
Medicine, Wuxi 214063, PR China
- School
of Pharmacy, Nanjing Medical University, Nanjing 211166, PR China
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15
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Park M, Kim D, Kim I, Im SH, Kim S. Drug approval prediction based on the discrepancy in gene perturbation effects between cells and humans. EBioMedicine 2023; 94:104705. [PMID: 37453362 PMCID: PMC10366401 DOI: 10.1016/j.ebiom.2023.104705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 06/15/2023] [Accepted: 06/27/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Poor translation between in vitro and clinical studies due to the cells/humans discrepancy in drug target perturbation effects leads to safety failures in clinical trials, thus increasing drug development costs and reducing patients' life quality. Therefore, developing a predictive model for drug approval considering the cells/humans discrepancy is needed to reduce drug attrition rates in clinical trials. METHODS Our machine learning framework predicts drug approval in clinical trials based on the cells/humans discrepancy in drug target perturbation effects. To evaluate the discrepancy to predict drug approval (1404 approved and 1070 unapproved drugs), we analysed CRISPR-Cas9 knockout and loss-of-function mutation rate-based gene perturbation effects on cells and humans, respectively. To validate the risk of drug targets with the cells/humans discrepancy, we examined the targets of failed and withdrawn drugs due to safety problems. FINDINGS Drug approvals in clinical trials were correlated with the cells/humans discrepancy in gene perturbation effects. Genes tolerant to perturbation effects on cells but intolerant to those on humans were associated with failed drug targets. Furthermore, genes with the cells/humans discrepancy were related to drugs withdrawn due to severe side effects. Motivated by previous studies assessing drug safety through chemical properties, we improved drug approval prediction by integrating chemical information with the cells/humans discrepancy. INTERPRETATION The cells/humans discrepancy in gene perturbation effects facilitates drug approval prediction and explains drug safety failures in clinical trials. FUNDING S.K. received grants from the Korean National Research Foundation (2021R1A2B5B01001903 and 2020R1A6A1A03047902) and IITP (2019-0-01906, Artificial Intelligence Graduate School Program, POSTECH).
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Affiliation(s)
- Minhyuk Park
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, South Korea
| | - Donghyo Kim
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, South Korea
| | - Inhae Kim
- ImmunoBiome Inc., Pohang, South Korea
| | - Sin-Hyeog Im
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, South Korea; ImmunoBiome Inc., Pohang, South Korea
| | - Sanguk Kim
- Department of Life Sciences, Pohang University of Science and Technology, Pohang, South Korea.
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16
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Khedkar HN, Chen LC, Kuo YC, Wu ATH, Huang HS. Multi-Omics Identification of Genetic Alterations in Head and Neck Squamous Cell Carcinoma and Therapeutic Efficacy of HNC018 as a Novel Multi-Target Agent for c-MET/STAT3/AKT Signaling Axis. Int J Mol Sci 2023; 24:10247. [PMID: 37373393 DOI: 10.3390/ijms241210247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 06/07/2023] [Accepted: 06/12/2023] [Indexed: 06/29/2023] Open
Abstract
Amongst the most prevalent malignancies worldwide, head and neck squamous cell carcinoma (HNSCC) is characterized by high morbidity and mortality. The failure of standard treatment modalities, such as surgery, radiotherapy, and chemotherapy, demands the need for in-depth understanding of the complex signaling networks involved in the development of treatment resistance. A tumor's invasive growth and high levels of intrinsic or acquired treatment resistance are the primary causes of treatment failure. This may be a result of the presence of HNSCC's cancer stem cells, which are known to have self-renewing capabilities that result in therapeutic resistance. Using bioinformatics methods, we discovered that elevated expressions of MET, STAT3, and AKT were associated with poor overall survival in HNSCC patients. We then evaluated the therapeutic potential of our newly synthesized small molecule HNC018 towards its potential as a novel anticancer drug. Our computer-aided structure characterization and target identification study predicted that HNC018 could target these oncogenic markers implicated in HNSCC. Subsequently, the HNC018 has demonstrated its anti-proliferative and anticancer activities towards the head and neck squamous cell carcinoma cell lines, along with displaying the stronger binding affinities towards the MET, STAT3, and AKT than the standard drug cisplatin. Reduction in the clonogenic and tumor-sphere-forming ability displays HNC018's role in decreasing the tumorigenicity. Importantly, an vivo study has shown a significant delay in tumor growth in HNC018 alone or in combination with cisplatin-treated xenograft mice model. Collectively with our findings, HNC018 highlights the desirable properties of a drug-like candidate and could be considered as a novel small molecule for treating head and neck squamous cell carcinoma.
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Affiliation(s)
- Harshita Nivrutti Khedkar
- Ph.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, and Academia Sinica, Taipei 11031, Taiwan
- Graduate Institute for Cancer Biology & Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Lung-Ching Chen
- Division of Cardiology, Department of Internal Medicine, Shin Kong Wu Ho-Su Memorial Hospital, Taipei 11101, Taiwan
- School of Medicine, Fu Jen Catholic University, New Taipei 24205, Taiwan
| | - Yu-Cheng Kuo
- Department of Pharmacology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- School of Post-Baccalaureate Chinese Medicine, College of Chinese Medicine, China Medical University, Taichung 40402, Taiwan
| | - Alexander T H Wu
- Ph.D. Program for Translational Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
- Taipei Heart Institute (THI), Taipei Medical University, Taipei 11031, Taiwan
- Clinical Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei 11031, Taiwan
- International Ph.D. Program for Translational Science, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
- Graduate Institute of Medical Sciences, National Defense Medical Centre, Taipei 11490, Taiwan
| | - Hsu-Shan Huang
- Ph.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, and Academia Sinica, Taipei 11031, Taiwan
- Graduate Institute for Cancer Biology & Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
- Graduate Institute of Medical Sciences, National Defense Medical Centre, Taipei 11490, Taiwan
- School of Pharmacy, National Defense Medical Centre, Taipei 11490, Taiwan
- Ph.D. Program in Drug Discovery and Development Industry, College of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan
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17
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Srinivasan R, Kamalanathan D, Rathinavel T, Iqbal MN, Shanmugam G. Anti-cancer potentials of aervine validated through in silico molecular docking, dynamics simulations, pharmacokinetic prediction and in vitro assessment of caspase – 3 in SW480 cell line. MOLECULAR SIMULATION 2023. [DOI: 10.1080/08927022.2023.2193646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/01/2023]
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18
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Pradeep SD, Gopalakrishnan AK, Manoharan DK, Soumya RS, Gopalan RK, Mohanan PV. Isatin derived novel Schiff bases: An efficient pharmacophore for versatile biological applications. J Mol Struct 2023. [DOI: 10.1016/j.molstruc.2022.134121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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19
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Aidhen IS, Srikanth S, Lal H. The Emerging Promise with O/C‐Glycosides of Important Dietary Phenolic Compounds. European J Org Chem 2022. [DOI: 10.1002/ejoc.202200758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Indrapal Singh Aidhen
- Indian Institute of Technology Madras Department of Chemistry Adyar 600036 Chennai INDIA
| | | | - Heera Lal
- Indian Institute of Technology Madras Chemistry 600036 Chennai INDIA
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20
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Tabti K, Baammi S, ElMchichi L, Sbai A, Maghat H, Bouachrine M, Lakhlifi T. Computational investigation of pyrrolidin derivatives as novel GPX4/MDM2–p53 inhibitors using 2D/3D-QSAR, ADME/toxicity, molecular docking, molecular dynamics simulations, and MM-GBSA free energy. Struct Chem 2022. [DOI: 10.1007/s11224-022-01903-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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21
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Charan J, Riyad P, Ram H, Purohit A, Ambwani S, Kashyap P, Singh G, Hashem A, Abd_Allah EF, Gupta VK, Kumar A, Panwar A. Ameliorations in dyslipidemia and atherosclerotic plaque by the inhibition of HMG-CoA reductase and antioxidant potential of phytoconstituents of an aqueous seed extract of Acacia senegal (L.) Willd in rabbits. PLoS One 2022; 17:e0264646. [PMID: 35239727 PMCID: PMC8893677 DOI: 10.1371/journal.pone.0264646] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 02/14/2022] [Indexed: 11/19/2022] Open
Abstract
The assigned work was aimed to examine the capability of phytoconstituents of an aqueous seed extract of Acacia senegal (L.) Willd to inhibit HMG-CoA reductase and regression of the atherosclerotic plaque. The chemical fingerprinting of the test extract was assessed by LC-MS/MS. Consequently, the analyses of in-vitro, in-vivo, and in-silico were executed by using the standard protocols. The in-vitro assessment of the test extract revealed 74.1% inhibition of HMG-CoA reductase. In-vivo assessments of the test extract indicated that treated hypercholesterolemic rabbits exhibited a significant (P≤0.001) amelioration in the biomarker indices of the dyslipidaemia i.e., atherogenic index, Castelli risk index(I&II), atherogenic coefficient along with lipid profile. Subsequently, significant reductions were observed in the atherosclerotic plaque and antioxidant levels. The in-silico study of molecular docking shown interactions capabilities of the leading phytoconstituents of the test extract i.e., eicosanoic acid, linoleic acid, and flavan-3-ol with target protein of HMG-CoA reductase. The values of RSMF and potential energy of top docked complexes were show significant interactions. Accordingly, the free energy of solvation, interaction angle, radius of gyration and SASA were shown significant stabilities of top docked complex. The cumulative data of results indicate phytoconstituents of an aqueous seed extract of Acacia senegal have capabilities to inhibit the HMG-CoA reductase and improve the levels of antioxidants.
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Affiliation(s)
- Jaykaran Charan
- Department of Pharmacology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | - Priyanka Riyad
- Department of Zoology, Jai Narain Vyas University, Jodhpur, Rajasthan, India
| | - Heera Ram
- Department of Zoology, Jai Narain Vyas University, Jodhpur, Rajasthan, India
| | - Ashok Purohit
- Department of Zoology, Jai Narain Vyas University, Jodhpur, Rajasthan, India
| | - Sneha Ambwani
- Department of Pharmacology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
| | - Priya Kashyap
- University School of Biotechnology, GGS Indraprastha University, New Delhi, India
| | - Garima Singh
- Department of Botany, Pachhunga University College, Aizawl, Mizoram, India
| | - Abeer Hashem
- Botany and Microbiology Department, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Elsayed Fathi Abd_Allah
- Plant Production Department, College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Vijai Kumar Gupta
- Center for Safe and Improved Food & Biorefining and Advanced Biomaterials Research Center, SRUC, Kings Buildings, Scotland, United Kingdom
| | - Ashok Kumar
- Centre for Systems biology and bioinformatics, Panjab University Chandigarh, Punjab, India
| | - Anil Panwar
- Centre for Systems biology and bioinformatics, Panjab University Chandigarh, Punjab, India
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22
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How fullerene derivatives (FDs) act on therapeutically important targets associated with diabetic diseases. Comput Struct Biotechnol J 2022; 20:913-924. [PMID: 35242284 PMCID: PMC8861571 DOI: 10.1016/j.csbj.2022.02.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 02/09/2022] [Accepted: 02/09/2022] [Indexed: 12/12/2022] Open
Abstract
Five proteins related to diabetic disease were selected from Protein Data Bank. Binding scores were calculated for five proteins with 169 fullerene derivatives. Correlation between drug-like descriptors and binding scores activity was examined. The contribution of descriptors to protein-ligand binding was demonstrated. The QSARs models for prediction of binding scores activity were built.
Fullerene derivatives (FDs) belong to a relatively new family of nano-sized organic compounds. They are widely applied in materials science, pharmaceutical industry, and (bio) medicine. This research focused on the study of FDs in terms of their potential inhibitory effect on therapeutic targets associated with diabetic disease, as well as analysis of protein–ligand binding in order to identify the key binding characteristics of FDs. Therapeutic drug compounds when entering the biological system usually inevitably encounter and interact with a vast variety of biomolecules that are responsible for many different functions in organisms. Protein biomolecules are the most important functional components and used in this study as target structures. The structures of proteins [(PDB ID: 1BMQ, 1FM6, 1GPB, 1H5U, 1US0)] belonging to the class of anti-diabetes targets were obtained from the Protein Data Bank (PDB). Protein binding activity data (binding scores) were calculated for the dataset of 169 FDs related to these five proteins. Subsequently, the resulting data were analyzed using various machine learning and cheminformatics methods, including artificial neural network algorithms for variable selection and property prediction. The Quantitative Structure-Activity Relationship (QSAR) models for prediction of binding scores activity were built up according to five Organization for Economic Co-operation and Development (OECD) principles. All the data obtained can provide important information for further potential use of FDs with different functional groups as promising medical antidiabetic agents. Binding scores activity can be used for ranking of FDs in terms of their inhibitory activity (pharmacological properties) and potential toxicity.
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23
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Polypharmacology: The science of multi-targeting molecules. Pharmacol Res 2022; 176:106055. [PMID: 34990865 DOI: 10.1016/j.phrs.2021.106055] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 12/23/2021] [Accepted: 12/31/2021] [Indexed: 12/28/2022]
Abstract
Polypharmacology is a concept where a molecule can interact with two or more targets simultaneously. It offers many advantages as compared to the conventional single-targeting molecules. A multi-targeting drug is much more efficacious due to its cumulative efficacy at all of its individual targets making it much more effective in complex and multifactorial diseases like cancer, where multiple proteins and pathways are involved in the onset and development of the disease. For a molecule to be polypharmacologic in nature, it needs to possess promiscuity which is the ability to interact with multiple targets; and at the same time avoid binding to antitargets which would otherwise result in off-target adverse effects. There are certain structural features and physicochemical properties which when present would help researchers to predict if the designed molecule would possess promiscuity or not. Promiscuity can also be identified via advanced state-of-the-art computational methods. In this review, we also elaborate on the methods by which one can intentionally incorporate promiscuity in their molecules and make them polypharmacologic. The polypharmacology paradigm of "one drug-multiple targets" has numerous applications especially in drug repurposing where an already established drug is redeveloped for a new indication. Though designing a polypharmacological drug is much more difficult than designing a single-targeting drug, with the current technologies and information regarding different diseases and chemical functional groups, it is plausible for researchers to intentionally design a polypharmacological drug and unlock its advantages.
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Hafsa U, Chuwdhury GS, Hasan MK, Ahsan T, Moni MA. An in silico approach towards identification of novel drug targets in Klebsiella oxytoca. INFORMATICS IN MEDICINE UNLOCKED 2022. [DOI: 10.1016/j.imu.2022.100998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
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25
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Yu L, Xue L, Liu F, Li Y, Jing R, Luo J. The applications of deep learning algorithms on in silico druggable proteins identification. J Adv Res 2022; 41:219-231. [PMID: 36328750 PMCID: PMC9637576 DOI: 10.1016/j.jare.2022.01.009] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 12/21/2021] [Accepted: 01/18/2022] [Indexed: 11/20/2022] Open
Abstract
We developed the first deep learning-based druggable protein classifier for fast and accurate identification of potential druggable proteins. Experimental results on a standard dataset demonstrate that the prediction performance of deep learning model is comparable to those of existing methods. We visualized the representations of druggable proteins learned by deep learning models, which helps us understand how they work. Our analysis reconfirms that the attention mechanism is especially useful for explaining deep learning models.
Introduction The top priority in drug development is to identify novel and effective drug targets. In vitro assays are frequently used for this purpose; however, traditional experimental approaches are insufficient for large-scale exploration of novel drug targets, as they are expensive, time-consuming and laborious. Therefore, computational methods have emerged in recent decades as an alternative to aid experimental drug discovery studies by developing sophisticated predictive models to estimate unknown drugs/compounds and their targets. The recent success of deep learning (DL) techniques in machine learning and artificial intelligence has further attracted a great deal of attention in the biomedicine field, including computational drug discovery. Objectives This study focuses on the practical applications of deep learning algorithms for predicting druggable proteins and proposes a powerful predictor for fast and accurate identification of potential drug targets. Methods Using a gold-standard dataset, we explored several typical protein features and different deep learning algorithms and evaluated their performance in a comprehensive way. We provide an overview of the entire experimental process, including protein features and descriptors, neural network architectures, libraries and toolkits for deep learning modelling, performance evaluation metrics, model interpretation and visualization. Results Experimental results show that the hybrid model (architecture: CNN-RNN (BiLSTM) + DNN; feature: dictionary encoding + DC_TC_CTD) performed better than the other models on the benchmark dataset. This hybrid model was able to achieve 90.0% accuracy and 0.800 MCC on the test dataset and 84.8% and 0.703 on a nonredundant independent test dataset, which is comparable to those of existing methods. Conclusion We developed the first deep learning-based classifier for fast and accurate identification of potential druggable proteins. We hope that this study will be helpful for future researchers who would like to use deep learning techniques to develop relevant predictive models.
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26
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Sahoo A, Fuloria S, Swain SS, Panda SK, Sekar M, Subramaniyan V, Panda M, Jena AK, Sathasivam KV, Fuloria NK. Potential of Marine Terpenoids against SARS-CoV-2: An In Silico Drug Development Approach. Biomedicines 2021; 9:biomedicines9111505. [PMID: 34829734 PMCID: PMC8614725 DOI: 10.3390/biomedicines9111505] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 10/17/2021] [Accepted: 10/17/2021] [Indexed: 12/11/2022] Open
Abstract
In an emergency, drug repurposing is the best alternative option against newly emerged severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. However, several bioactive natural products have shown potential against SARS-CoV-2 in recent studies. The present study selected sixty-eight broad-spectrum antiviral marine terpenoids and performed molecular docking against two novel SARS-CoV-2 enzymes (main protease or Mpro or 3CLpro) and RNA-dependent RNA polymerase (RdRp). In addition, the present study analysed the physiochemical-toxicity-pharmacokinetic profile, structural activity relationship, and phylogenetic tree with various computational tools to select the 'lead' candidate. The genomic diversity study with multiple sequence analyses and phylogenetic tree confirmed that the newly emerged SARS-CoV-2 strain was up to 96% structurally similar to existing CoV-strains. Furthermore, the anti-SARS-CoV-2 potency based on a protein-ligand docking score (kcal/mol) exposed that the marine terpenoid brevione F (-8.4) and stachyflin (-8.4) exhibited similar activity with the reference antiviral drugs lopinavir (-8.4) and darunavir (-7.5) against the target SARS-CoV-Mpro. Similarly, marine terpenoids such as xiamycin (-9.3), thyrsiferol (-9.2), liouvilloside B (-8.9), liouvilloside A (-8.8), and stachyflin (-8.7) exhibited comparatively higher docking scores than the referral drug remdesivir (-7.4), and favipiravir (-5.7) against the target SARS-CoV-2-RdRp. The above in silico investigations concluded that stachyflin is the most 'lead' candidate with the most potential against SARS-CoV-2. Previously, stachyflin also exhibited potential activity against HSV-1 and CoV-A59 within IC50, 0.16-0.82 µM. Therefore, some additional pharmacological studies are needed to develop 'stachyflin' as a drug against SARS-CoV-2.
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Affiliation(s)
- Alaka Sahoo
- Department of Skin & VD, Institute of Medical Sciences and SUM Hospital, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar 751003, Odisha, India; (A.S.); (M.P.); (A.K.J.)
| | - Shivkanya Fuloria
- Faculty of Pharmacy, Centre of Excellence for Biomaterials Engineering, AIMST University, Bedong 08100, Kedah, Malaysia
- Correspondence: (S.F.); (N.K.F.)
| | - Shasank S. Swain
- Division of Microbiology and NCDs, ICMR–Regional Medical Research Centre, Bhubaneswar 751023, Odisha, India;
| | - Sujogya K. Panda
- Center of Environment Climate Change and Public Health, Utkal University, Vani Vihar, Bhubaneswar 751004, Odisha, India;
| | - Mahendran Sekar
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy and Health Sciences, Universiti Kuala Lumpur Royal College of Medicine Perak, Ipoh 30450, Perak, Malaysia;
| | - Vetriselvan Subramaniyan
- Faculty of Medicine, Bioscience and Nursing, MAHSA University, Jalan SP 2, Bandar Saujana Putra, Jenjarom 42610, Selangor, Malaysia;
| | - Maitreyee Panda
- Department of Skin & VD, Institute of Medical Sciences and SUM Hospital, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar 751003, Odisha, India; (A.S.); (M.P.); (A.K.J.)
| | - Ajaya K. Jena
- Department of Skin & VD, Institute of Medical Sciences and SUM Hospital, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar 751003, Odisha, India; (A.S.); (M.P.); (A.K.J.)
| | - Kathiresan V. Sathasivam
- Faculty of Applied Science, Centre of Excellence for Biomaterials Engineering, AIMST University, Bedong 08100, Kedah, Malaysia;
| | - Neeraj Kumar Fuloria
- Faculty of Pharmacy, Centre of Excellence for Biomaterials Engineering, AIMST University, Bedong 08100, Kedah, Malaysia
- Correspondence: (S.F.); (N.K.F.)
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Tucker AN, Carlson TJ, Sarkar A. Challenges in Drug Discovery for Intracellular Bacteria. Pathogens 2021; 10:pathogens10091172. [PMID: 34578204 PMCID: PMC8468363 DOI: 10.3390/pathogens10091172] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 08/26/2021] [Accepted: 09/04/2021] [Indexed: 01/04/2023] Open
Abstract
Novel drugs are needed to treat a variety of persistent diseases caused by intracellular bacterial pathogens. Virulence pathways enable many functions required for the survival of these pathogens, including invasion, nutrient acquisition, and immune evasion. Inhibition of virulence pathways is an established route for drug discovery; however, many challenges remain. Here, we propose the biggest problems that must be solved to advance the field meaningfully. While it is established that we do not yet understand the nature of chemicals capable of permeating into the bacterial cell, this problem is compounded when targeting intracellular bacteria because we are limited to only those chemicals that can permeate through both human and bacterial outer envelopes. Unfortunately, many chemicals that permeate through the outer layers of mammalian cells fail to penetrate the bacterial cytoplasm. Another challenge is the lack of publicly available information on virulence factors. It is virtually impossible to know which virulence factors are clinically relevant and have broad cross-species and cross-strain distribution. In other words, we have yet to identify the best drug targets. Yes, standard genomics databases have much of the information necessary for short-term studies, but the connections with patient outcomes are yet to be established. Without comprehensive data on matters such as these, it is difficult to devise broad-spectrum, effective anti-virulence agents. Furthermore, anti-virulence drug discovery is hindered by the current state of technologies available for experimental investigation. Antimicrobial drug discovery was greatly advanced by the establishment and standardization of broth microdilution assays to measure the effectiveness of antimicrobials. However, the currently available models used for anti-virulence drug discovery are too broad, as they must address varied phenotypes, and too expensive to be generally adopted by many research groups. Therefore, we believe drug discovery against intracellular bacterial pathogens can be advanced significantly by overcoming the above hurdles.
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Dutta M, Tareq AM, Rakib A, Mahmud S, Sami SA, Mallick J, Islam MN, Majumder M, Uddin MZ, Alsubaie A, Almalki ASA, Khandaker MU, Bradley D, Rana MS, Emran TB. Phytochemicals from Leucas zeylanica Targeting Main Protease of SARS-CoV-2: Chemical Profiles, Molecular Docking, and Molecular Dynamics Simulations. BIOLOGY 2021; 10:789. [PMID: 34440024 PMCID: PMC8389631 DOI: 10.3390/biology10080789] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 08/05/2021] [Accepted: 08/15/2021] [Indexed: 02/07/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a contemporary coronavirus, has impacted global economic activity and has a high transmission rate. As a result of the virus's severe medical effects, developing effective vaccinations is vital. Plant-derived metabolites have been discovered as potential SARS-CoV-2 inhibitors. The SARS-CoV-2 main protease (Mpro) is a target for therapeutic research because of its highly conserved protein sequence. Gas chromatography-mass spectrometry (GC-MS) and molecular docking were used to screen 34 compounds identified from Leucas zeylanica for potential inhibitory activity against the SARS-CoV-2 Mpro. In addition, prime molecular mechanics-generalized Born surface area (MM-GBSA) was used to screen the compound dataset using a molecular dynamics simulation. From molecular docking analysis, 26 compounds were capable of interaction with the SARS-CoV-2 Mpro, while three compounds, namely 11-oxa-dispiro[4.0.4.1]undecan-1-ol (-5.755 kcal/mol), azetidin-2-one 3,3-dimethyl-4-(1-aminoethyl) (-5.39 kcal/mol), and lorazepam, 2TMS derivative (-5.246 kcal/mol), exhibited the highest docking scores. These three ligands were assessed by MM-GBSA, which revealed that they bind with the necessary Mpro amino acids in the catalytic groove to cause protein inhibition, including Ser144, Cys145, and His41. The molecular dynamics simulation confirmed the complex rigidity and stability of the docked ligand-Mpro complexes based on the analysis of mean radical variations, root-mean-square fluctuations, solvent-accessible surface area, radius of gyration, and hydrogen bond formation. The study of the postmolecular dynamics confirmation also confirmed that lorazepam, 11-oxa-dispiro[4.0.4.1]undecan-1-ol, and azetidin-2-one-3, 3-dimethyl-4-(1-aminoethyl) interact with similar Mpro binding pockets. The results of our computerized drug design approach may assist in the fight against SARS-CoV-2.
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Affiliation(s)
- Mycal Dutta
- Department of Pharmacy, BGC Trust University Bangladesh, Chittagong 4381, Bangladesh; (M.D.); (J.M.); (M.Z.U.)
- Department of Pharmacy, Jahangirnagar University, Savar, Dhaka 1342, Bangladesh
| | - Abu Montakim Tareq
- Department of Pharmacy, International Islamic University Chittagong, Chittagong 4318, Bangladesh; (A.M.T.); (M.N.I.)
| | - Ahmed Rakib
- Department of Pharmacy, Faculty of Biological Sciences, University of Chittagong, Chittagong 4331, Bangladesh; (A.R.); (S.A.S.)
| | - Shafi Mahmud
- Microbiology Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi 6205, Bangladesh;
| | - Saad Ahmed Sami
- Department of Pharmacy, Faculty of Biological Sciences, University of Chittagong, Chittagong 4331, Bangladesh; (A.R.); (S.A.S.)
| | - Jewel Mallick
- Department of Pharmacy, BGC Trust University Bangladesh, Chittagong 4381, Bangladesh; (M.D.); (J.M.); (M.Z.U.)
- Department of Pharmacy, Jahangirnagar University, Savar, Dhaka 1342, Bangladesh
| | - Mohammad Nazmul Islam
- Department of Pharmacy, International Islamic University Chittagong, Chittagong 4318, Bangladesh; (A.M.T.); (M.N.I.)
| | - Mohuya Majumder
- Drug Discovery, GUSTO A Research Group, Chittagong 4203, Bangladesh;
| | - Md. Zia Uddin
- Department of Pharmacy, BGC Trust University Bangladesh, Chittagong 4381, Bangladesh; (M.D.); (J.M.); (M.Z.U.)
- Department of Pharmacy, Jahangirnagar University, Savar, Dhaka 1342, Bangladesh
| | - Abdullah Alsubaie
- Department of Physics, College of Khurma, Taif University, Taif 21944, Saudi Arabia;
| | | | - Mayeen Uddin Khandaker
- Centre for Applied Physics and Radiation Technologies, School of Engineering and Technology, Sunway University, Bandar Sunway 47500, Malaysia; (M.U.K.); (D.A.B.)
| | - D.A. Bradley
- Centre for Applied Physics and Radiation Technologies, School of Engineering and Technology, Sunway University, Bandar Sunway 47500, Malaysia; (M.U.K.); (D.A.B.)
- Department of Physics, University of Surrey, Guilford GU2 7XH, UK
| | - Md. Sohel Rana
- Department of Pharmacy, Jahangirnagar University, Savar, Dhaka 1342, Bangladesh
| | - Talha Bin Emran
- Department of Pharmacy, BGC Trust University Bangladesh, Chittagong 4381, Bangladesh; (M.D.); (J.M.); (M.Z.U.)
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Quest for Novel Preventive and Therapeutic Options Against Multidrug-Resistant Pseudomonas aeruginosa. Int J Pept Res Ther 2021; 27:2313-2331. [PMID: 34393689 PMCID: PMC8351238 DOI: 10.1007/s10989-021-10255-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/09/2021] [Indexed: 11/20/2022]
Abstract
Pseudomonas aeruginosa (P. aeruginosa) is a critical healthcare challenge due to its ability to cause persistent infections and the acquisition of antibiotic resistance mechanisms. Lack of preventive vaccines and rampant drug resistance phenomenon has rendered patients vulnerable. As new antimicrobials are in the preclinical stages of development, mining for the unexploited drug targets is also crucial. In the present study, we designed a B- and T-cell multi-epitope vaccine against P. aeruginosa using a subtractive proteomics and immunoinformatics approach. A total of five proteins were shortlisted based on essentiality, extracellular localization, virulence, antigenicity, pathway association, hydrophilicity, and low molecular weight. These include two outer membrane porins; OprF (P13794) and OprD (P32722), a protein activator precursor pra (G3XDA9), a probable outer membrane protein precursor PA1288 (Q9I456), and a conserved hypothetical protein PA4874 (Q9HUT9). These shortlisted proteins were further analyzed to identify immunogenic and antigenic B- and T-cell epitopes. The best scoring epitopes were then further subjected to the construction of a polypeptide multi-epitope vaccine and joined with cholera toxin B subunit adjuvant. The final chimeric construct was docked with TLR4 and confirmed by normal mode simulation studies. The designed B- and T-cell multi-epitope vaccine candidate is predicted immunogenic in nature and has shown strong interactions with TLR-4. Immune simulation predicted high-level production of B- and T-cell population and maximal expression was ensured in E. coli strain K12. The identified drug targets qualifying the screening criteria were: UDP-2-acetamido-2-deoxy-d-glucuronic acid 3-dehydrogenase WbpB (G3XD23), aspartate semialdehyde dehydrogenase (Q51344), 2-amino-4-hydroxy-6-hydroxymethyldihydropteridine pyrophosphokinase (Q9HV71), 3-deoxy-D-manno-octulosonic-acid transferase (Q9HUH7), glycyl-tRNA synthetase alpha chain (Q9I7B7), riboflavin kinase/FAD synthase (Q9HVM3), aconitate hydratase 2 (Q9I2V5), probable glycosyltransferase WbpH (G3XD85) and UDP-3-O-[3-hydroxylauroyl] glucosamine N-acyltransferase (Q9HXY6). For druggability and pocketome analysis crystal and homology structures of these proteins were retrieved and developed. A sequence-based search was performed in different databases (ChEMBL, Drug Bank, PubChem and Pseudomonas database) for the availability of reported ligands and tested drugs for the screened targets. These predicted targets may provide a basis for the development of reliable antibacterial preventive and therapeutic options against P. aeruginosa.
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Khedkar HN, Wang YC, Yadav VK, Srivastava P, Lawal B, Mokgautsi N, Sumitra MR, Wu ATH, Huang HS. In-Silico Evaluation of Genetic Alterations in Ovarian Carcinoma and Therapeutic Efficacy of NSC777201, as a Novel Multi-Target Agent for TTK, NEK2, and CDK1. Int J Mol Sci 2021; 22:ijms22115895. [PMID: 34072728 PMCID: PMC8198179 DOI: 10.3390/ijms22115895] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 05/26/2021] [Accepted: 05/27/2021] [Indexed: 02/06/2023] Open
Abstract
Ovarian cancer is often detected at the advanced stages at the time of initial diagnosis. Early-stage diagnosis is difficult due to its asymptomatic nature, where less than 30% of 5-year survival has been noticed. The underlying molecular events associated with the disease’s pathogenesis have yet to be fully elucidated. Thus, the identification of prognostic biomarkers as well as developing novel therapeutic agents for targeting these markers become relevant. Herein, we identified 264 differentially expressed genes (DEGs) common in four ovarian cancer datasets (GSE14407, GSE18520, GSE26712, GSE54388), respectively. We constructed a protein-protein interaction (PPI) interaction network with the overexpressed genes (72 genes) and performed gene enrichment analysis. In the PPI networks, three proteins; TTK Protein Kinase (TTK), NIMA Related Kinase 2 (NEK2), and cyclin-dependent kinase (CDK1) with higher node degrees were further evaluated as therapeutic targets for our novel multi-target small molecule NSC777201. We found that the upregulated DEGs were enriched in KEGG and gene ontologies associated with ovarian cancer progression, female gamete association, otic vesicle development, regulation of chromosome segregation, and therapeutic failure. In addition to the PPI network, ingenuity pathway analysis also implicate TTK, NEK2, and CDK1 in the elevated salvage pyrimidine and pyridoxal pathways in ovarian cancer. The TTK, NEK2, and CDK1 are over-expressed, demonstrating a high frequency of genetic alterations, and are associated with poor prognosis of ovarian cancer cohorts. Interestingly, NSC777201 demonstrated anti-proliferative and cytotoxic activities (GI50 = 1.6 µM~1.82 µM and TGI50 = 3.5 µM~3.63 µM) against the NCI panels of ovarian cancer cell lines and exhibited a robust interaction with stronger affinities for TTK, NEK2, and CDK1, than do the standard drug, paclitaxel. NSC777201 displayed desirable properties of a drug-like candidate and thus could be considered as a novel small molecule for treating ovarian carcinoma.
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Affiliation(s)
- Harshita Nivrutti Khedkar
- PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Academia Sinica, Taipei 11031, Taiwan; (H.N.K.); (B.L.); (N.M.); (M.R.S.)
- Graduate Institute for Cancer Biology & Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Yu-Chi Wang
- Department of Obstetrics and Gynecology, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan;
| | - Vijesh Kumar Yadav
- The Program for Translational Medicine, Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan; (V.K.Y.); (P.S.)
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Shuang Ho Hospital, New Taipei City 23561, Taiwan
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan
| | - Prateeti Srivastava
- The Program for Translational Medicine, Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan; (V.K.Y.); (P.S.)
| | - Bashir Lawal
- PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Academia Sinica, Taipei 11031, Taiwan; (H.N.K.); (B.L.); (N.M.); (M.R.S.)
- Graduate Institute for Cancer Biology & Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Ntlotlang Mokgautsi
- PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Academia Sinica, Taipei 11031, Taiwan; (H.N.K.); (B.L.); (N.M.); (M.R.S.)
- Graduate Institute for Cancer Biology & Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Maryam Rachmawati Sumitra
- PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Academia Sinica, Taipei 11031, Taiwan; (H.N.K.); (B.L.); (N.M.); (M.R.S.)
- Graduate Institute for Cancer Biology & Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Alexander T. H. Wu
- The Program for Translational Medicine, Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan; (V.K.Y.); (P.S.)
- The PhD Program for Translational Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
- TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei 11031, Taiwan
- Clinical Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei 11031, Taiwan
- Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei 11490, Taiwan
- Correspondence: (A.T.H.W.); (H.-S.H.)
| | - Hsu-Shan Huang
- PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Academia Sinica, Taipei 11031, Taiwan; (H.N.K.); (B.L.); (N.M.); (M.R.S.)
- Graduate Institute for Cancer Biology & Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
- Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei 11490, Taiwan
- National Defense Medical Center, School of Pharmacy, Taipei 11490, Taiwan
- PhD Program in Drug Discovery and Development Industry, College of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan
- Correspondence: (A.T.H.W.); (H.-S.H.)
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Network Pharmacological Analysis through a Bioinformatics Approach of Novel NSC765600 and NSC765691 Compounds as Potential Inhibitors of CCND1/ CDK4/ PLK1/ CD44 in Cancer Types. Cancers (Basel) 2021; 13:cancers13112523. [PMID: 34063946 PMCID: PMC8196568 DOI: 10.3390/cancers13112523] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 04/26/2021] [Accepted: 05/18/2021] [Indexed: 12/11/2022] Open
Abstract
Simple Summary Around 14 million new cancer cases, rate are reported annually, with high mortality worldswide, several mechanisms are associated with complexities in cancer, which leads to resistance to current therapeutic interventions in cancer patients. The aim of this study was to identify molecular genes responsible for cancer development, progression and resistances to therapeutic intervention, and also evaluate the potency of our novel compounds NSC7565600 and NSC765691 as potential target for these oncogenes. Using bioinformatics, we successfully identified CCND1/CDK4/PLK1/CD44 as oncogenic signatures, which drives cancer progression and resistance to treatment, and as potential druggable candidates for both NSC7565600 and NSC765691 small molecules. We also showed the antiproliferative and cytotoxic effects of these compounds against a panel of NCI-60 cancer cell lines. This suggests the potential of NSC765600 and NSC765691 compounds to inhibit CCND1/CDK4/PLK1/CD44 expressions in cancer. Abstract Cyclin D1 (CCND1) and cyclin-dependent kinase 4 (CDK4) both play significant roles in regulating cell cycle progression, while polo-like kinase 1 (PLK1) regulates cell differentiation and tumor progression, and activates cancer stem cells (CSCs), with the cluster of differentiation 44 (CD44) surface marker mostly being expressed. These oncogenes have emerged as promoters of metastasis in a variety of cancer types. In this study, we employed comprehensive computational and bioinformatics analyses to predict drug targets of our novel small molecules, NSC765600 and NSC765691, respectively derived from diflunisal and fostamatinib. The target prediction tools identified CCND1/CDK4/PLK1/CD44 as target genes for NSC765600 and NSC765691 compounds. Additionally, the results of our in silico molecular docking analysis showed unique ligand–protein interactions with putative binding affinities of NSC765600 and NSC765691 with CCND1/CDK4/PLK1/CD44 oncogenic signaling pathways. Moreover, we used drug-likeness precepts as our guidelines for drug design and development, and found that both compounds passed the drug-likeness criteria of molecular weight, polarity, solubility, saturation, flexibility, and lipophilicity, and also exhibited acceptable pharmacokinetic properties. Furthermore, we used development therapeutics program (DTP) algorithms and identified similar fingerprints and mechanisms of NSC765600 and NSC765691 with synthetic compounds and standard anticancer agents in the NCI database. We found that NSC765600 and NSC765691 displayed antiproliferative and cytotoxic effects against a panel of NCI-60 cancer cell lines. Based on these finding, NSC765600 and NSC765691 exhibited satisfactory levels of safety with regard to toxicity, and met all of the required criteria for drug-likeness precepts. Currently, further in vitro and in vivo investigations in tumor-bearing mice are in progress to study the potential treatment efficacies of the novel NSC765600 and NSC765691 small molecules.
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Abbas Manthiri A, Ramalingam S, George G, Aarthi R. Molecular structure analysis and biological properties investigation on antiseptic drug; 2-amino-1-phenyl-1-propanol using spectroscopic and computational research analysis. Heliyon 2021; 7:e06699. [PMID: 33898825 PMCID: PMC8056422 DOI: 10.1016/j.heliyon.2021.e06699] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 10/17/2020] [Accepted: 04/01/2021] [Indexed: 11/28/2022] Open
Abstract
The inducement of physical, chemical, structural and biological properties to entice of pharmaceutical property was analyzed by Vibrational spectroscopic, biological and theoretical tools. The structural arrangement for describing structure activity was investigated by injecting ligand groups in internal coordinate system by molecular tools (FT adopted IR, Raman, and NMR). Bond length and bond angle strain was pronounced much due to the chemical equivalent forces extension due to the injection of substitutional groups on base compound and thus non-Centro symmetry was processed. The molecular charge depletion profile was thoroughly studied to persuade protonic and electronic delocalization setup for arranging the drug potential. The chemi-equivalent potential exchange was monitored among different parts of the molecule for obtaining drug mechanism. The biological profile was keenly observed to look at the biological ambiance of the present molecule to fabricate advanced drug. The Lipinski five rule parameters; MV = 137.18, LogP = 0.27, HBD = 2, HBA = 2 and TPSA = 46.2 A2 showed the enhancement of additive drug quality. The exchange of oscillating chemical energy in the core and allied carbons of the base skeleton was keenly noted to find the prearranged chemical environment for successful drug mechanism. The non bonded transitions between Lewis acid and base of bonded molecular system were observed to determine the restoring potential to customize drug potential. The drug assistance for enantiomer characteristics of chirality sequence was displayed to expose the toxicity effect of the molecule. The active molecular bondings on different sites of molecule were measured by estimating polarizability and associated biological inhibition was validated.
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Affiliation(s)
- A. Abbas Manthiri
- Department of Physics, Jamal Mohamed College, Tiruchirappalli, Tamilnadu, India
| | - S. Ramalingam
- Department of Physics, A.V.C. College, Mayiladuthurai, Tamilnadu, India
| | - Gene George
- Department of Physics, T.B.M.L. College, Porayar, Tamilnadu, India
| | - R. Aarthi
- Department of Physics, ST. Theresa's Arts and Science College, Tharangambadi, Tamilnadu, India
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Koikov L, Starner RJ, Swope VB, Upadhyay P, Hashimoto Y, Freeman KT, Knittel JJ, Haskell-Luevano C, Abdel-Malek ZA. Development of hMC1R Selective Small Agonists for Sunless Tanning and Prevention of Genotoxicity of UV in Melanocytes. J Invest Dermatol 2021; 141:1819-1829. [PMID: 33609553 DOI: 10.1016/j.jid.2020.11.034] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 11/12/2020] [Accepted: 11/19/2020] [Indexed: 12/30/2022]
Abstract
Activation of the human melanocortin 1 receptor (hMC1R) expressed on melanocytes by α-melanocortin plays a central role in regulating human pigmentation and reducing the genotoxicity of UV by activating DNA repair and antioxidant defenses. For the development of a hMC1R-targeted photoprotection strategy, we designed tetra- and tripeptide agonists with modifications that provide the necessary lipophilicity and hMC1R selectivity to be effective drugs. These peptides proved to be superior to most of the existing analogs of the physiological tridecapeptide α-melanocortin because of their small size and high hMC1R selectivity. Testing on primary cultures of human melanocytes showed that these peptides are highly potent with prolonged stimulation of melanogenesis, enhanced repair of UV-induced DNA photoproducts, and reduced apoptosis. One of the tripeptides, designated as LK-514 (5), with a molecular weight of 660 Da, has unprecedented (>100,000) hMC1R selectivity when compared with the other melanocortin receptors hMC3R, hMC4R, and hMC5R, and increases pigmentation (sunless tanning) in a cultured, three-dimensional skin model. These new analogs should be efficacious in preventing skin cancer, including melanoma, and treatment of skin disorders, such as vitiligo and polymorphic light eruptions.
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Affiliation(s)
- Leonid Koikov
- Department of Dermatology, University of Cincinnati, Cincinnati, Ohio, USA
| | - Renny J Starner
- Department of Dermatology, University of Cincinnati, Cincinnati, Ohio, USA
| | - Viki B Swope
- Department of Dermatology, University of Cincinnati, Cincinnati, Ohio, USA
| | - Parth Upadhyay
- Department of Dermatology, University of Cincinnati, Cincinnati, Ohio, USA
| | - Yuki Hashimoto
- Department of Dermatology, Toho University, Tokyo, Japan
| | - Katie T Freeman
- Department of Medicinal Chemistry, University of Minnesota, Minneapolis, Minnesota, USA
| | - James J Knittel
- Department of Pharmaceutical and Administrative Sciences, Western New England University, Springfield, Massachusetts, USA
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Molecular Structure, In Vitro Anticancer Study and Molecular Docking of New Phosphate Derivatives of Betulin. Molecules 2021; 26:molecules26030737. [PMID: 33572631 PMCID: PMC7866984 DOI: 10.3390/molecules26030737] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 01/25/2021] [Accepted: 01/28/2021] [Indexed: 12/21/2022] Open
Abstract
A series of 30-diethylphosphate derivatives of betulin were synthesized and evaluated for their in vitro cytotoxic activity against human cancer cell lines, such as amelanotic melanoma (C-32), glioblastoma (SNB-19), and two lines of breast cancer (T47D, MDA-MB-231). The molecular structure and activities of the new compounds were also compared with their 29-phosphonate analogs. Compounds 7a and 7b showed the highest activity against C-32 and SNB-19 cell lines. The IC50 values for 7a were 2.15 and 0.91 μM, and, for 7b, they were 0.76 and 0.8 μM for the C-32 and SNB-19 lines, respectively. The most potent compounds, 7a and 7b, were tested for their effects on markers of apoptosis, such as H3, TP53, BAX, and BCL-2. For the whole series of phosphate derivatives, a lipophilicity study was performed, and the ADME parameters were calculated. The most active products were docked to the active site of the EGFR protein. The relative binding affinity of selected phosphate betulin derivatives toward EGFR was compared with standard erlotinib on the basis of ChemScore and KDEEP score. Positively, all derivatives docked inside the cavity and showed significant interactions. Moreover, a molecular dynamics study also reveals that ligands 7a,b form stable complexes and the plateau phase started after 7 ns.
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Chakraborty C, Bhattacharya M, Mallick B, Sharma AR, Lee SS, Agoramoorthy G. SARS-CoV-2 protein drug targets landscape: a potential pharmacological insight view for the new drug development. Expert Rev Clin Pharmacol 2021; 14:225-238. [PMID: 33423554 DOI: 10.1080/17512433.2021.1874348] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Introduction: Protein drug targets play a significant choice in different stages of the drug discovery process. There is an urgent need to understand the drug discovery approaches and protein drug targets (PDT) of SARS-CoV-2, with structural insights for the development of SARS-CoV-2 drugs through targeted therapeutic approach.Areas covered: We have described the protein as a drug target class and also discussed various drug discovery approaches for SARS-CoV-2 involving the protein drug targets such as drug repurposing study, designing of viral entry inhibitors, viral replication inhibitors, and different enzymes of the virus. We have performed comprehensive literature search from the popular databases such as PubMed Google scholar, Web of Science, and Scopus. Finally, we have illustrated the structural landscape of different significant viral proteins (3 CLpro or Mpro, PLpro, RdRp, helicase, S protein) and host proteins as drug targets (cathepsin L, furin, TMPRSS2, ACE2).Expert opinion: The structural landscape of PDT with their binding pockets, and significant residues involved in binding has been discussed further to better understand the PDT and the structure-based drug discovery for SARS-CoV-2. This attempt will increase more therapeutic options, and combination therapies with a multi-target strategy.
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Affiliation(s)
- Chiranjib Chakraborty
- Department of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata, West Bengal India.,Institute for Skeletal Aging & Orthopedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Gangwon-do, Republic of Korea
| | | | - Bidyut Mallick
- Department of Applied Science, Galgotias College of Engineering and Technology, Greater Noida, Uttar Pradesh, India
| | - Ashish Ranjan Sharma
- Institute for Skeletal Aging & Orthopedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Gangwon-do, Republic of Korea
| | - Sang-Soo Lee
- Institute for Skeletal Aging & Orthopedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Gangwon-do, Republic of Korea
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Lawal B, Liu YL, Mokgautsi N, Khedkar H, Sumitra MR, Wu ATH, Huang HS. Pharmacoinformatics and Preclinical Studies of NSC765690 and NSC765599, Potential STAT3/CDK2/4/6 Inhibitors with Antitumor Activities against NCI60 Human Tumor Cell Lines. Biomedicines 2021; 9:biomedicines9010092. [PMID: 33477856 PMCID: PMC7832910 DOI: 10.3390/biomedicines9010092] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Revised: 01/16/2021] [Accepted: 01/18/2021] [Indexed: 12/11/2022] Open
Abstract
Signal transducer and activator of transcription 3 (STAT3) is a transcriptional regulator of a number of biological processes including cell differentiation, proliferation, survival, and angiogenesis, while cyclin-dependent kinases (CDKs) are a critical regulator of cell cycle progression. These proteins appear to play central roles in angiogenesis and cell survival and are widely implicated in tumor progression. In this study, we used the well-characterized US National Cancer Institute 60 (NCI60) human tumor cell lines to screen the in vitro anti-cancer activities of our novel small molecule derivatives (NSC765690 and NSC765599) of salicylanilide. Furthermore, we used the DTP-COMPARE algorithm and in silico drug target prediction to identify the potential molecular targets, and finally, we used molecular docking to assess the interaction between the compounds and prominent potential targets. We found that NSC765690 and NSC765599 exhibited an anti-proliferative effect against the 60 panels of NCI human cancer cell lines, and dose-dependent cytotoxic preference for NSCLC, melanoma, renal, and breast cancer cell lines. Protein–ligand interactions studies revealed that NSC765690 and NSC765599 were favored ligands for STAT3/CDK2/4/6. Moreover, cyclization of the salicylanilide core scaffold of NSC765690 mediated its higher anti-cancer activities and had greater potential to interact with STAT3/CDK2/4/6 than did NSC765599 with an open-ring structure. NSC765690 and NSC765599 met the required safety and criteria of a good drug candidate, and are thus worthy of further in-vitro and in-vivo investigations in tumor-bearing mice to assess their full therapeutic efficacy.
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Affiliation(s)
- Bashir Lawal
- PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan; (B.L.); (N.M.); (H.K.); (M.R.S.)
- Graduate Institute for Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Yen-Lin Liu
- Department of Pediatrics, Taipei Medical University Hospital, Taipei 11031, Taiwan;
- Taipei Cancer Center, Taipei Medical University, Taipei 11031, Taiwan
- Department of Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei 11031, Taiwan
| | - Ntlotlang Mokgautsi
- PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan; (B.L.); (N.M.); (H.K.); (M.R.S.)
- Graduate Institute for Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Harshita Khedkar
- PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan; (B.L.); (N.M.); (H.K.); (M.R.S.)
- Graduate Institute for Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Maryam Rachmawati Sumitra
- PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan; (B.L.); (N.M.); (H.K.); (M.R.S.)
- Graduate Institute for Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Alexander T. H. Wu
- TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei 11031, Taiwan
- The PhD Program of Translational Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
- Clinical Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei 11031, Taiwan
- Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei 11490, Taiwan
- Correspondence: (A.T.H.W.); (H.-S.H.)
| | - Hsu-Shan Huang
- PhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan; (B.L.); (N.M.); (H.K.); (M.R.S.)
- Graduate Institute for Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
- Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei 11490, Taiwan
- School of Pharmacy, National Defense Medical Center, Taipei 11490, Taiwan
- PhD Program in Biotechnology Research and Development, College of Pharmacy, Taipei Medical University, Taipei 11031, Taiwan
- Correspondence: (A.T.H.W.); (H.-S.H.)
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Ligand-Based Virtual Screening, Molecular Docking, Molecular Dynamics, and MM-PBSA Calculations towards the Identification of Potential Novel Ricin Inhibitors. Toxins (Basel) 2020; 12:toxins12120746. [PMID: 33256167 PMCID: PMC7761309 DOI: 10.3390/toxins12120746] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Revised: 11/20/2020] [Accepted: 11/24/2020] [Indexed: 02/06/2023] Open
Abstract
Ricin is a toxin found in the castor seeds and listed as a chemical weapon by the Chemical Weapons Convention (CWC) due to its high toxicity combined with the easiness of obtention and lack of available antidotes. The relatively frequent episodes of usage or attempting to use ricin in terrorist attacks reinforce the urge to develop an antidote for this toxin. In this sense, we selected in this work the current RTA (ricin catalytic subunit) inhibitor with the best experimental performance, as a reference molecule for virtual screening in the PubChem database. The selected molecules were then evaluated through docking studies, followed by drug-likeness investigation, molecular dynamics simulations and Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) calculations. In every step, the selection of molecules was mainly based on their ability to occupy both the active and secondary sites of RTA, which are located right next to each other, but are not simultaneously occupied by the current RTA inhibitors. Results show that the three PubChem compounds 18309602, 18498053, and 136023163 presented better overall results than the reference molecule itself, showing up as new hits for the RTA inhibition, and encouraging further experimental evaluation.
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Kumar S, Mandal RS, Bulone V, Srivastava V. Identification of Growth Inhibitors of the Fish Pathogen Saprolegnia parasitica Using in silico Subtractive Proteomics, Computational Modeling, and Biochemical Validation. Front Microbiol 2020; 11:571093. [PMID: 33178154 PMCID: PMC7596660 DOI: 10.3389/fmicb.2020.571093] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 09/22/2020] [Indexed: 12/18/2022] Open
Abstract
Many Stramenopile species belonging to oomycetes from the genus Saprolegnia infect fish, amphibians, and crustaceans in aquaculture farms and natural ecosystems. Saprolegnia parasitica is one of the most severe fish pathogens, responsible for high losses in the aquaculture industry worldwide. Most of the molecules reported to date for the control of Saprolegnia infections either are inefficient or have negative impacts on the health of the fish hosts or the environment resulting in substantial economic losses. Until now, the whole proteome of S. parasitica has not been explored for a systematic screening of novel inhibitors against the pathogen. The present study was designed to develop a consensus computational framework for the identification of potential target proteins and their inhibitors and subsequent experimental validation of selected compounds. Comparative analysis between the proteomes of Saprolegnia, humans and fish species identified proteins that are specific and essential for the survival of the pathogen. The DrugBank database was exploited to select food and drug administration (FDA)-approved inhibitors whose high binding affinity to their respective protein targets was confirmed by computational modeling. At least six of the identified compounds significantly inhibited the growth of S. parasitica in vitro. Triclosan was found to be most effective with a minimum inhibitory concentration (MIC100) of 4 μg/ml. Optical microscopy showed that the inhibitors affect the morphology of hyphal cells, with hyper-branching being commonly observed. The inhibitory effects of the compounds identified in this study on Saprolegnia’s mycelial growth indicate that they are potentially usable for disease control against this class of oomycete pathogens. Similar approaches can be easily adopted for the identification of potential inhibitors against other plant and animal pathogenic oomycete infections.
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Affiliation(s)
- Sanjiv Kumar
- Division of Glycoscience, Department of Chemistry, School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), AlbaNova University Centre, Stockholm, Sweden
| | - Rahul Shubhra Mandal
- Department of Cancer Biology, Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Vincent Bulone
- Division of Glycoscience, Department of Chemistry, School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), AlbaNova University Centre, Stockholm, Sweden.,School of Agriculture, Food and Wine, The University of Adelaide, Adelaide, SA, Australia
| | - Vaibhav Srivastava
- Division of Glycoscience, Department of Chemistry, School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), AlbaNova University Centre, Stockholm, Sweden
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40
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Favero LM, Chideroli RT, Ferrari NA, Azevedo VADC, Tiwari S, Lopera-Barrero NM, Pereira UDP. In silico Prediction of New Drug Candidates Against the Multidrug-Resistant and Potentially Zoonotic Fish Pathogen Serotype III Streptococcus agalactiae. Front Genet 2020; 11:1024. [PMID: 33005185 PMCID: PMC7484375 DOI: 10.3389/fgene.2020.01024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 08/11/2020] [Indexed: 12/02/2022] Open
Abstract
Streptococcus agalactiae is an invasive multi-host pathogen that causes invasive diseases mainly in newborns, elderly, and individuals with underlying health complications. In fish, S. agalactiae causes streptococcosis, which is characterized by septicemia and neurological signs, and leads to great economic losses to the fish farming industry worldwide. These bacteria can be classified into different serotypes based on capsular antigens, and into different sequence types (ST) based on multilocus sequence typing (MLST). In 2015, serotype III ST283 was identified to be associated with a foodborne invasive disease in non-pregnant immunocompetent humans in Singapore, and the infection was related to raw fish consumption. In addition, a serotype III strain isolated from tilapia in Brazil has been reported to be resistant to five antibiotic classes. This specific serotype can serve as a reservoir of resistance genes and pose a serious threat to public health. Thus, new approaches for the control and treatment of S. agalactiae infections are needed. In the present study, 24 S. agalactiae serotype III complete genomes, isolated from human and fish hosts, were compared. The core genome was identified, and, using bioinformatics tools and subtractive criteria, five proteins were identified as potential drug targets. Furthermore, 5,008 drug-like natural compounds were virtually screened against the identified targets. The ligands with the best binding properties are suggested for further in vitro and in vivo analysis.
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Affiliation(s)
- Leonardo Mantovani Favero
- Laboratory of Fish Bacteriology, Department of Preventive Veterinary Medicine, State University of Londrina, Londrina, Brazil
| | - Roberta Torres Chideroli
- Laboratory of Fish Bacteriology, Department of Preventive Veterinary Medicine, State University of Londrina, Londrina, Brazil
| | - Natália Amoroso Ferrari
- Laboratory of Fish Bacteriology, Department of Preventive Veterinary Medicine, State University of Londrina, Londrina, Brazil
| | - Vasco Ariston De Carvalho Azevedo
- Institute of Biological Sciences, Department of Genetic, Ecology, and Evolution, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Sandeep Tiwari
- Institute of Biological Sciences, Department of Genetic, Ecology, and Evolution, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | | | - Ulisses de Pádua Pereira
- Laboratory of Fish Bacteriology, Department of Preventive Veterinary Medicine, State University of Londrina, Londrina, Brazil
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Ghaleb A, Aouidate A, Ayouchia HBE, Aarjane M, Anane H, Stiriba SE. In silico molecular investigations of pyridine N-Oxide compounds as potential inhibitors of SARS-CoV-2: 3D QSAR, molecular docking modeling, and ADMET screening. J Biomol Struct Dyn 2020; 40:143-153. [PMID: 32799761 DOI: 10.1080/07391102.2020.1808530] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
The new coronavirus SARS-CoV-2 virus is causing a severe pneumonia in human, provoking the serious outbreak epidemic CoV-2. Since its appearance in Wuhan, China on December 2019, CoV-2 becomes the biggest challenge the world is facing today, including the discovery of antiviral drug for SARS-CoV-2. In this study, the potential inhibitory of a class of human SARS inhibitors, namely pyridine N-oxide derivatives, against CoV-2 was addressed by quantitative structure-activity relationship 3 D-QSAR. The reliable CoMSIA developed model of 110 pyridine N-oxide based-antiviral compounds, showed Q2= 0.54 and rext2=0.71. The molecular surflex-docking was applied to identify the crystal structure of CoV-2 main protease 3CLpro (PDB: 6LU7) and two potentially and largely used antiviral molecules, namely chloroquine, hydroxychloroquine. The obtained free energy affinity and ADMET properties indicate that among the series of model antiviral compounds examined, the new antiviral compound A5 could be an excellent antiviral drug inhibitor against COVID-19. The inhibition activity of pyridine N-oxyde compounds against CoV-2 was compared with the activity of two common antiviral drug, namely chloroquine (CQ) and hydroxychloroquine (HCQ). DFT method was also used to define the sites of reactivity of pyridine N-oxyde derivatives as well as CQ and HCQ.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Adib Ghaleb
- Laboratoire de Chimie Analytique et Moléculaire/LCAM, Faculté Polydisciplinaire de Safi, Université Cadi Ayyad, Safi, Morocco
| | - Adnane Aouidate
- MCNSL, School of Sciences, Moulay Ismail University, Meknes, Morocco
| | - Hicham Ben El Ayouchia
- Laboratoire de Chimie Analytique et Moléculaire/LCAM, Faculté Polydisciplinaire de Safi, Université Cadi Ayyad, Safi, Morocco
| | - Mohammed Aarjane
- LCBAE, Equipe Chimie Moléculaire et Molécules Bioactives, Université Moulay Ismail, Faculté des Sciences, Meknès, Morocco
| | - Hafid Anane
- Laboratoire de Chimie Analytique et Moléculaire/LCAM, Faculté Polydisciplinaire de Safi, Université Cadi Ayyad, Safi, Morocco
| | - Salah-Eddine Stiriba
- Laboratoire de Chimie Analytique et Moléculaire/LCAM, Faculté Polydisciplinaire de Safi, Université Cadi Ayyad, Safi, Morocco.,Instituto de Ciencia Molecular/ICMol, Universidad de Valencia, Valencia, Spain
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Hannan MA, Dash R, Haque MN, Mohibbullah M, Sohag AAM, Rahman MA, Uddin MJ, Alam M, Moon IS. Neuroprotective Potentials of Marine Algae and Their Bioactive Metabolites: Pharmacological Insights and Therapeutic Advances. Mar Drugs 2020; 18:E347. [PMID: 32630301 PMCID: PMC7401253 DOI: 10.3390/md18070347] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 06/19/2020] [Accepted: 06/25/2020] [Indexed: 12/14/2022] Open
Abstract
Beyond their significant contribution to the dietary and industrial supplies, marine algae are considered to be a potential source of some unique metabolites with diverse health benefits. The pharmacological properties, such as antioxidant, anti-inflammatory, cholesterol homeostasis, protein clearance and anti-amyloidogenic potentials of algal metabolites endorse their protective efficacy against oxidative stress, neuroinflammation, mitochondrial dysfunction, and impaired proteostasis which are known to be implicated in the pathophysiology of neurodegenerative disorders and the associated complications after cerebral ischemia and brain injuries. As was evident in various preclinical studies, algal compounds conferred neuroprotection against a wide range of neurotoxic stressors, such as oxygen/glucose deprivation, hydrogen peroxide, glutamate, amyloid β, or 1-methyl-4-phenylpyridinium (MPP+) and, therefore, hold therapeutic promise for brain disorders. While a significant number of algal compounds with promising neuroprotective capacity have been identified over the last decades, a few of them have had access to clinical trials. However, the recent approval of an algal oligosaccharide, sodium oligomannate, for the treatment of Alzheimer's disease enlightened the future of marine algae-based drug discovery. In this review, we briefly outline the pathophysiology of neurodegenerative diseases and brain injuries for identifying the targets of pharmacological intervention, and then review the literature on the neuroprotective potentials of algal compounds along with the underlying pharmacological mechanism, and present an appraisal on the recent therapeutic advances. We also propose a rational strategy to facilitate algal metabolites-based drug development.
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Affiliation(s)
- Md. Abdul Hannan
- Department of Anatomy, Dongguk University College of Medicine, Gyeongju 38066, Korea; (M.A.H.); (R.D.); (M.A.)
- Department of Biochemistry and Molecular Biology, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh;
| | - Raju Dash
- Department of Anatomy, Dongguk University College of Medicine, Gyeongju 38066, Korea; (M.A.H.); (R.D.); (M.A.)
| | - Md. Nazmul Haque
- Department of Fisheries Biology and Genetics, Patuakhali Science and Technology University, Patuakhali 8602, Bangladesh;
| | - Md. Mohibbullah
- Department of Fishing and Post Harvest Technology, Sher-e-Bangla Agricultural University, Sher-e-Bangla Nagar, Dhaka 1207, Bangladesh;
| | - Abdullah Al Mamun Sohag
- Department of Biochemistry and Molecular Biology, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh;
| | - Md. Ataur Rahman
- Center for Neuroscience, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea;
| | - Md Jamal Uddin
- Graduate School of Pharmaceutical Sciences, College of Pharmacy, Ewha Womans University, Seoul 03760, Korea;
- ABEx Bio-Research Center, East Azampur, Dhaka 1230, Bangladesh
| | - Mahboob Alam
- Department of Anatomy, Dongguk University College of Medicine, Gyeongju 38066, Korea; (M.A.H.); (R.D.); (M.A.)
- Division of Chemistry and Biotechnology, Dongguk University, Gyeongju 780-714, Korea
| | - Il Soo Moon
- Department of Anatomy, Dongguk University College of Medicine, Gyeongju 38066, Korea; (M.A.H.); (R.D.); (M.A.)
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Huang MH, Kong B, Meng JY, Lv YB, Peng YF, Chen YP, Tan XD. Discovery of novel N-aryl pyrrothine derivatives as bacterial RNA polymerase inhibitors. Chem Biol Drug Des 2020; 96:1262-1271. [PMID: 32491252 DOI: 10.1111/cbdd.13736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 05/17/2020] [Accepted: 05/22/2020] [Indexed: 11/29/2022]
Abstract
Bacterial RNA polymerase (RNAP) is a validated drug target for broad-spectrum antibiotics, and its "switch region" is considered as the promising binding site for novel antibiotics. Based on the core scaffold of dithiolopyrrolone, a series of N-aryl pyrrothine derivatives was designed, synthesized, and evaluated for their antibacterial activity. Compounds generally displayed more active against Gram-positive bacteria, but less against Gram-negative bacteria. Among them, compound 6e exhibited moderate antibacterial activity against clinical isolates of rifampin-resistant Staphylococcus aureus with minimum inhibition concentration value of 1-2 μg/ml and inhibited Escherichia coli RNAP with IC50 value of 12.0 ± 0.9 μM. In addition, compound 6e showed certain degree of cytotoxicity against HepG2 and LO2 cells. Furthermore, molecular docking studies suggested that compound 6e might interact with the switch region of bacterial RNAP in a similar conformation to myxopyronin A. Together, the N-aryl pyrrothine scaffold is a promising lead for discovery of antibacterial drugs acting against bacterial RNAP.
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Affiliation(s)
- Mo-Han Huang
- College of Pharmacy, Guilin Medical University, Guilin, China.,Department of Pharmacy, Liuzhou People's Hospital, Liuzhou, China
| | - Bo Kong
- School of Life Sciences, Guangzhou University, Guangzhou, China
| | - Jie-Yun Meng
- College of Pharmacy, Guilin Medical University, Guilin, China
| | - Yu-Bin Lv
- College of Pharmacy, Guilin Medical University, Guilin, China
| | - Yan-Fen Peng
- College of Pharmacy, Guilin Medical University, Guilin, China
| | - Yi-Ping Chen
- School of Pharmaceutical Sciences, Guangxi University of Chinese Medicine, Nanning, China.,Guangxi Key Laboratory of Translational Medicine for Treating High-Incidence Infectious Diseases with Integrative Medicine, Nanning, China
| | - Xiang-Duan Tan
- College of Pharmacy, Guilin Medical University, Guilin, China
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Shahid F, Ashfaq UA, Saeed S, Munir S, Almatroudi A, Khurshid M. In Silico Subtractive Proteomics Approach for Identification of Potential Drug Targets in Staphylococcus saprophyticus. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17103644. [PMID: 32455889 PMCID: PMC7277342 DOI: 10.3390/ijerph17103644] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 05/12/2020] [Accepted: 05/13/2020] [Indexed: 11/16/2022]
Abstract
Staphylococcus saprophyticus is a uropathogenic bacteria responsible for acute urinary tract infections (UTIs) mainly in young female patients. Patients suffering from urinary catheterization, pregnant patients, the elderly as well as those with nosocomial UTIs are at greater risk of the colonizing S. saprophyticus infection. The causative factors include benign prostatic hyperplasia, indwelling catheter, neurogenic bladder, pregnancy, and history of frequent UTIs. Recent findings have exhibited that S. saprophyticus is resistant to several antimicrobial agents. Moreover, there is a global concern regarding the increasing level of antimicrobial resistance, which leads to treatment failure and reduced effectiveness of broad-spectrum antimicrobials. Therefore, a novel approach is being utilized to combat resistant microbes since the past few years. Subtractive proteome analysis has been performed with the entire proteome of S. saprophyticus strain American Type Culture Collection (ATCC) 15305 using several bioinformatics servers and software. The proteins that were non-homologous to humans and bacteria were identified for metabolic pathway analysis. Only four cytoplasmic proteins were found possessing the potential of novel drug target candidates. The development of innovative therapeutic agents by targeting the inhibition of any essential proteins may disrupt the metabolic pathways specific to the pathogen, thus causing destruction as well as eradication of the pathogen from a particular host. The identified targets can facilitate in designing novel and potent drugs against S. saprophyticus strain ATCC 15305.
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Affiliation(s)
- Farah Shahid
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Punjab 38000, Pakistan; (F.S.); (S.S.); (S.M.)
| | - Usman Ali Ashfaq
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Punjab 38000, Pakistan; (F.S.); (S.S.); (S.M.)
- Correspondence:
| | - Sania Saeed
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Punjab 38000, Pakistan; (F.S.); (S.S.); (S.M.)
| | - Samman Munir
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Punjab 38000, Pakistan; (F.S.); (S.S.); (S.M.)
| | - Ahmad Almatroudi
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 52571, Saudi Arabia;
| | - Mohsin Khurshid
- Department of Microbiology, Government College University, Faisalabad, Punjab 38000, Pakistan;
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Newman DJ, Cragg GM. Natural Products as Sources of New Drugs over the Nearly Four Decades from 01/1981 to 09/2019. JOURNAL OF NATURAL PRODUCTS 2020; 83:770-803. [PMID: 32162523 DOI: 10.1021/acs.jnatprod.9b01285] [Citation(s) in RCA: 2885] [Impact Index Per Article: 721.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
This review is an updated and expanded version of the five prior reviews that were published in this journal in 1997, 2003, 2007, 2012, and 2016. For all approved therapeutic agents, the time frame has been extended to cover the almost 39 years from the first of January 1981 to the 30th of September 2019 for all diseases worldwide and from ∼1946 (earliest so far identified) to the 30th of September 2019 for all approved antitumor drugs worldwide. As in earlier reviews, only the first approval of any drug is counted, irrespective of how many "biosimilars" or added approvals were subsequently identified. As in the 2012 and 2016 reviews, we have continued to utilize our secondary subdivision of a "natural product mimic", or "NM", to join the original primary divisions, and the designation "natural product botanical", or "NB", to cover those botanical "defined mixtures" now recognized as drug entities by the FDA (and similar organizations). From the data presented in this review, the utilization of natural products and/or synthetic variations using their novel structures, in order to discover and develop the final drug entity, is still alive and well. For example, in the area of cancer, over the time frame from 1946 to 1980, of the 75 small molecules, 40, or 53.3%, are N or ND. In the 1981 to date time frame the equivalent figures for the N* compounds of the 185 small molecules are 62, or 33.5%, though to these can be added the 58 S* and S*/NMs, bringing the figure to 64.9%. In other areas, the influence of natural product structures is quite marked with, as expected from prior information, the anti-infective area being dependent on natural products and their structures, though as can be seen in the review there are still disease areas (shown in Table 2) for which there are no drugs derived from natural products. Although combinatorial chemistry techniques have succeeded as methods of optimizing structures and have been used very successfully in the optimization of many recently approved agents, we are still able to identify only two de novo combinatorial compounds (one of which is a little speculative) approved as drugs in this 39-year time frame, though there is also one drug that was developed using the "fragment-binding methodology" and approved in 2012. We have also added a discussion of candidate drug entities currently in clinical trials as "warheads" and some very interesting preliminary reports on sources of novel antibiotics from Nature due to the absolute requirement for new agents to combat plasmid-borne resistance genes now in the general populace. We continue to draw the attention of readers to the recognition that a significant number of natural product drugs/leads are actually produced by microbes and/or microbial interactions with the "host from whence it was isolated"; thus we consider that this area of natural product research should be expanded significantly.
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Affiliation(s)
- David J Newman
- NIH Special Volunteer, Wayne, Pennsylvania 19087, United States
| | - Gordon M Cragg
- NIH Special Volunteer, Gaithersburg, Maryland 20877, United States
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Yuan JH, Han SB, Richter S, Wade RC, Kokh DB. Druggability Assessment in TRAPP Using Machine Learning Approaches. J Chem Inf Model 2020; 60:1685-1699. [DOI: 10.1021/acs.jcim.9b01185] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Jui-Hung Yuan
- Molecular and Cellular Modeling Group, Heidelberg Institute of Theoretical Studies (HITS), 69118 Heidelberg, Germany
- Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, 69120 Heidelberg, Germany
| | - Sungho Bosco Han
- Molecular and Cellular Modeling Group, Heidelberg Institute of Theoretical Studies (HITS), 69118 Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, 69120 Heidelberg, Germany
| | - Stefan Richter
- Molecular and Cellular Modeling Group, Heidelberg Institute of Theoretical Studies (HITS), 69118 Heidelberg, Germany
| | - Rebecca C. Wade
- Molecular and Cellular Modeling Group, Heidelberg Institute of Theoretical Studies (HITS), 69118 Heidelberg, Germany
- Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, 69120 Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, 69120 Heidelberg, Germany
- Zentrum für Molekulare Biologie (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, 69120 Heidelberg, Germany
| | - Daria B. Kokh
- Molecular and Cellular Modeling Group, Heidelberg Institute of Theoretical Studies (HITS), 69118 Heidelberg, Germany
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Kolawole AO, Kolawole AN, Olofinsan KA, Elekofehinti OO. Kolaflavanone of kolaviron selectively binds to subdomain 1B of human serum albumin: spectroscopic and molecular docking evidences. ACTA ACUST UNITED AC 2020. [DOI: 10.1016/j.comtox.2020.100118] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Yang ZY, He JH, Lu AP, Hou TJ, Cao DS. Application of Negative Design To Design a More Desirable Virtual Screening Library. J Med Chem 2020; 63:4411-4429. [DOI: 10.1021/acs.jmedchem.9b01476] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Zi-Yi Yang
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, Hunan, P. R. China
| | - Jun-Hong He
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, Hunan, P. R. China
| | - Ai-Ping Lu
- Institute for Advancing Translational Medicine in Bone and Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, SAR, P. R. China
| | - Ting-Jun Hou
- Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, P. R. China
| | - Dong-Sheng Cao
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, Hunan, P. R. China
- Institute for Advancing Translational Medicine in Bone and Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, SAR, P. R. China
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Fjodorova N, Novič M, Venko K, Rasulev B. A Comprehensive Cheminformatics Analysis of Structural Features Affecting the Binding Activity of Fullerene Derivatives. NANOMATERIALS (BASEL, SWITZERLAND) 2020; 10:E90. [PMID: 31906497 PMCID: PMC7023229 DOI: 10.3390/nano10010090] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 12/24/2019] [Accepted: 12/27/2019] [Indexed: 01/08/2023]
Abstract
Nanostructures like fullerene derivatives (FDs) belong to a new family of nano-sized organic compounds. Fullerenes have found a widespread application in material science, pharmaceutical, biomedical, and medical fields. This fact caused the importance of the study of pharmacological as well as toxicological properties of this relatively new family of chemicals. In this work, a large set of 169 FDs and their binding activity to 1117 proteins was investigated. The structure-based descriptors widely used in drug design (so-called drug-like descriptors) were applied to understand cheminformatics characteristics related to the binding activity of fullerene nanostructures. Investigation of applied descriptors demonstrated that polarizability, topological diameter, and rotatable bonds play the most significant role in the binding activity of FDs. Various cheminformatics methods, including the counter propagation artificial neural network (CPANN) and Kohonen network as visualization tool, were applied. The results of this study can be applied to compose the priority list for testing in risk assessment related to the toxicological properties of FDs. The pharmacologist can filter the data from the heat map to view all possible side effects for selected FDs.
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Affiliation(s)
- Natalja Fjodorova
- National Institute of Chemistry, SI-1000 Ljubljana, Slovenia; (M.N.); (K.V.)
| | - Marjana Novič
- National Institute of Chemistry, SI-1000 Ljubljana, Slovenia; (M.N.); (K.V.)
| | - Katja Venko
- National Institute of Chemistry, SI-1000 Ljubljana, Slovenia; (M.N.); (K.V.)
| | - Bakhtiyor Rasulev
- Department of Coatings and Polymeric Materials, North Dakota State University, Fargo, ND 58102, USA;
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Hu Y, Zhao T, Zhang N, Zhang Y, Cheng L. A Review of Recent Advances and Research on Drug Target Identification Methods. Curr Drug Metab 2019; 20:209-216. [PMID: 30251599 DOI: 10.2174/1389200219666180925091851] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2017] [Revised: 01/01/2018] [Accepted: 08/02/2018] [Indexed: 12/14/2022]
Abstract
BACKGROUND From a therapeutic viewpoint, understanding how drugs bind and regulate the functions of their target proteins to protect against disease is crucial. The identification of drug targets plays a significant role in drug discovery and studying the mechanisms of diseases. Therefore the development of methods to identify drug targets has become a popular issue. METHODS We systematically review the recent work on identifying drug targets from the view of data and method. We compiled several databases that collect data more comprehensively and introduced several commonly used databases. Then divided the methods into two categories: biological experiments and machine learning, each of which is subdivided into different subclasses and described in detail. RESULTS Machine learning algorithms are the majority of new methods. Generally, an optimal set of features is chosen to predict successful new drug targets with similar properties. The most widely used features include sequence properties, network topological features, structural properties, and subcellular locations. Since various machine learning methods exist, improving their performance requires combining a better subset of features and choosing the appropriate model for the various datasets involved. CONCLUSION The application of experimental and computational methods in protein drug target identification has become increasingly popular in recent years. Current biological and computational methods still have many limitations due to unbalanced and incomplete datasets or imperfect feature selection methods.
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Affiliation(s)
- Yang Hu
- School of Life Science and Technology, Department of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Tianyi Zhao
- School of Life Science and Technology, Department of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Ningyi Zhang
- School of Life Science and Technology, Department of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Ying Zhang
- Department of Pharmacy, Heilongjiang Province Land Reclamation Headquarters General Hospital, Harbin 150088, China
| | - Liang Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
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