Displaying publications 1 - 20 of 35 in total

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  1. Babajide Mustapha I, Saeed F
    Molecules, 2016 Jul 28;21(8).
    PMID: 27483216 DOI: 10.3390/molecules21080983
    Following the explosive growth in chemical and biological data, the shift from traditional methods of drug discovery to computer-aided means has made data mining and machine learning methods integral parts of today's drug discovery process. In this paper, extreme gradient boosting (Xgboost), which is an ensemble of Classification and Regression Tree (CART) and a variant of the Gradient Boosting Machine, was investigated for the prediction of biological activity based on quantitative description of the compound's molecular structure. Seven datasets, well known in the literature were used in this paper and experimental results show that Xgboost can outperform machine learning algorithms like Random Forest (RF), Support Vector Machines (LSVM), Radial Basis Function Neural Network (RBFN) and Naïve Bayes (NB) for the prediction of biological activities. In addition to its ability to detect minority activity classes in highly imbalanced datasets, it showed remarkable performance on both high and low diversity datasets.
    Matched MeSH terms: Drug Discovery/methods*
  2. Shiammala PN, Duraimutharasan NKB, Vaseeharan B, Alothaim AS, Al-Malki ES, Snekaa B, et al.
    Methods, 2023 Nov;219:82-94.
    PMID: 37778659 DOI: 10.1016/j.ymeth.2023.09.010
    Artificial intelligence (AI), particularly deep learning as a subcategory of AI, provides opportunities to accelerate and improve the process of discovering and developing new drugs. The use of AI in drug discovery is still in its early stages, but it has the potential to revolutionize the way new drugs are discovered and developed. As AI technology continues to evolve, it is likely that AI will play an even greater role in the future of drug discovery. AI is used to identify new drug targets, design new molecules, and predict the efficacy and safety of potential drugs. The inclusion of AI in drug discovery can screen millions of compounds in a matter of hours, identifying potential drug candidates that would have taken years to find using traditional methods. AI is highly utilized in the pharmaceutical industry by optimizing processes, reducing waste, and ensuring quality control. This review covers much-needed topics, including the different types of machine-learning techniques, their applications in drug discovery, and the challenges and limitations of using machine learning in this field. The state-of-the-art of AI-assisted pharmaceutical discovery is described, covering applications in structure and ligand-based virtual screening, de novo drug creation, prediction of physicochemical and pharmacokinetic properties, drug repurposing, and related topics. Finally, many obstacles and limits of present approaches are outlined, with an eye on potential future avenues for AI-assisted drug discovery and design.
    Matched MeSH terms: Drug Discovery/methods
  3. Rostam MA, Piva TJ, Rezaei HB, Kamato D, Little PJ, Zheng W, et al.
    Clin Exp Pharmacol Physiol, 2015 Feb;42(2):117-24.
    PMID: 25377120 DOI: 10.1111/1440-1681.12335
    Peptidyl-prolyl cis/trans isomerases (PPIases) are a conserved group of enzymes that catalyse the conversion between cis and trans conformations of proline imidic peptide bonds. These enzymes play critical roles in regulatory mechanisms of cellular function and pathophysiology of disease. There are three different classes of PPIases and increasing interest in the development of specific PPIase inhibitors. Cyclosporine A, FK506, rapamycin and juglone are known PPIase inhibitors. Herein, we review recent advances in elucidating the role and regulation of the PPIase family in vascular disease. We focus on peptidyl-prolyl cis/trans isomerase NIMA-interacting 1 (Pin1), an important member of the PPIase family that plays a role in cell cycle progression, gene expression, cell signalling and cell proliferation. In addition, Pin1 may be involved in atherosclerosis. The unique role of Pin1 as a molecular switch that impacts on multiple downstream pathways necessitates the evaluation of a highly specific Pin1 inhibitor to aid in potential therapeutic drug discovery.
    Matched MeSH terms: Drug Discovery/methods
  4. Said NA, Gould CM, Lackovic K, Simpson KJ, Williams ED
    Assay Drug Dev Technol, 2014 Sep;12(7):385-94.
    PMID: 25181411 DOI: 10.1089/adt.2014.593
    Metastasis accounts for the poor prognosis of the majority of solid tumors. The phenotypic transition of nonmotile epithelial tumor cells to migratory and invasive "mesenchymal" cells (epithelial-to-mesenchymal transition [EMT]) enables the transit of cancer cells from the primary tumor to distant sites. There is no single marker of EMT; rather, multiple measures are required to define cell state. Thus, the multiparametric capability of high-content screening is ideally suited for the comprehensive analysis of EMT regulators. The aim of this study was to generate a platform to systematically identify functional modulators of tumor cell plasticity using the bladder cancer cell line TSU-Pr1-B1 as a model system. A platform enabling the quantification of key EMT characteristics, cell morphology and mesenchymal intermediate filament vimentin, was developed using the fluorescent whole-cell-tracking reagent CMFDA and a fluorescent promoter reporter construct, respectively. The functional effect of genome-wide modulation of protein-coding genes and miRNAs coupled with those of a collection of small-molecule kinase inhibitors on EMT was assessed using the Target Activation Bioapplication integrated in the Cellomics ArrayScan platform. Data from each of the three screens were integrated to identify a cohort of targets that were subsequently examined in a validation assay using siRNA duplexes. Identification of established regulators of EMT supports the utility of this screening approach and indicated capacity to identify novel regulators of this plasticity program. Pathway analysis coupled with interrogation of cancer-related expression profile databases and other EMT-related screens provided key evidence to prioritize further experimental investigation into the molecular regulators of EMT in cancer cells.
    Matched MeSH terms: Drug Discovery/methods*
  5. Sasidharan S, Chen Y, Saravanan D, Sundram KM, Yoga Latha L
    PMID: 22238476
    Natural products from medicinal plants, either as pure compounds or as standardized extracts, provide unlimited opportunities for new drug leads because of the unmatched availability of chemical diversity. Due to an increasing demand for chemical diversity in screening programs, seeking therapeutic drugs from natural products, interest particularly in edible plants has grown throughout the world. Botanicals and herbal preparations for medicinal usage contain various types of bioactive compounds. The focus of this paper is on the analytical methodologies, which include the extraction, isolation and characterization of active ingredients in botanicals and herbal preparations. The common problems and key challenges in the extraction, isolation and characterization of active ingredients in botanicals and herbal preparations are discussed. As extraction is the most important step in the analysis of constituents present in botanicals and herbal preparations, the strengths and weaknesses of different extraction techniques are discussed. The analysis of bioactive compounds present in the plant extracts involving the applications of common phytochemical screening assays, chromatographic techniques such as HPLC and, TLC as well as non-chromatographic techniques such as immunoassay and Fourier Transform Infra Red (FTIR) are discussed.
    Matched MeSH terms: Drug Discovery/methods*
  6. Tiekink ER
    Dalton Trans, 2012 Jun 7;41(21):6390-5.
    PMID: 22252404 DOI: 10.1039/c2dt12225a
    Despite being disparaged for their malodorous and toxic demeanour, compounds of selenium, a bio-essential element, and tellurium, offer possibilities as therapeutic agents. Herein, their potential use as drugs, for example, as anti-viral, anti-microbial, anti-inflammatory agents, etc., will be surveyed along with a summary of the established biological functions of selenium. The natural biological functions of tellurium remain to be discovered.
    Matched MeSH terms: Drug Discovery/methods*
  7. Okuda KS, Lee HM, Velaithan V, Ng MF, Patel V
    Microcirculation, 2016 08;23(6):389-405.
    PMID: 27177346 DOI: 10.1111/micc.12289
    Cancer metastasis which predominantly occurs through blood and lymphatic vessels, is the leading cause of death in cancer patients. Consequently, several anti-angiogenic agents have been approved as therapeutic agents for human cancers such as metastatic renal cell carcinoma. Also, anti-lymphangiogenic drugs such as monoclonal antibodies VGX-100 and IMC-3C5 have undergone phase I clinical trials for advanced and metastatic solid tumors. Although anti-tumor-associated angiogenesis has proven to be a promising therapeutic strategy for human cancers, this approach is fraught with toxicities and development of drug resistance. This emphasizes the need for alternative anti-(lymph)angiogenic drugs. The use of zebrafish has become accepted as an established model for high-throughput screening, vascular biology, and cancer research. Importantly, various zebrafish transgenic lines have now been generated that can readily discriminate different vascular compartments. This now enables detailed in vivo studies that are relevant to both human physiological and tumor (lymph)angiogenesis to be conducted in zebrafish. This review highlights recent advancements in the zebrafish anti-vascular screening platform and showcases promising new anti-(lymph)angiogenic compounds that have been derived from this model. In addition, this review discusses the promises and challenges of the zebrafish model in the context of anti-(lymph)angiogenic compound discovery for cancer treatment.
    Matched MeSH terms: Drug Discovery/methods
  8. Akbar N, Siddiqui R, Sagathevan KA, Khan NA
    Appl Microbiol Biotechnol, 2019 May;103(10):3955-3964.
    PMID: 30941460 DOI: 10.1007/s00253-019-09783-2
    The morbidity and mortality associated with bacterial infections have remained significant despite chemotherapeutic advances. With the emergence of drug-resistant bacterial strains, the situation has become a serious threat to the public health. Thus, there is an urgent need to identify novel antibacterials. The majority of antibiotics available in the market are produced by bacteria isolated from soil. However, the low-hanging fruit has been picked; hence, there is a need to mine bacteria from unusual sources. With this in mind, it is important to note that animals and pests such as cockroaches, snake, crocodiles, and water monitor lizard come across pathogenic bacteria regularly, yet flourish in contaminated environments. These species must have developed methods to defend themselves to counter pathogens. Although the immune system is known to possess antiinfective properties, gut bacteria of animals/pests may also offer a potential source of novel antibacterial agents, and it is the subject of this study. This paper discusses our current knowledge of bacteria isolated from land and marine animals with antibacterial properties and to propose untapped sources for the isolation of bacteria to mine potentially novel antibiotic molecules.
    Matched MeSH terms: Drug Discovery/methods
  9. Tan CS, Aqiludeen NA, Tan R, Gowbei A, Mijen AB, Santhana Raj L, et al.
    Med J Malaysia, 2020 03;75(2):110-116.
    PMID: 32281590
    INTRODUCTIONS: The emergence of multidrug-resistant bacteria such as Methicillin-Resistant Staphylococcus aureus (MRSA) complicates the treatment of the simplest infection. Although glycopeptides such as vancomycin still proves to be effective in treating MRSA infections, the emergence of vancomycin-resistant strains limits the long term use of this antibiotic. Bacteriophages are ubiquitous bacterial viruses which is capable of infecting and killing bacteria including its antibiotic-resistant strains. Bactericidal bacteriophages use mechanisms that is distinct from antibiotics and is not affected by the antibioticresistant phenotypes.

    OBJECTIVES: The study was undertaken to evaluate the possibility to isolate bacteriolytic bacteriophages against S.aureus from raw sewage water and examine their efficacy as antimicrobial agents in vitro.

    METHODS: Bacteriophages were isolated from the raw sewage using the agar overlay method. Isolated bacteriophages were plaque purified to obtain homogenous bacteriophage isolates. The host range of the bacteriophages was determined using the spot test assay against the 25 MRSA and 36 MSSA isolates obtained from the Sarawak General Hospital. Staphylococcus saprophyticus, Staphylococcus sciuri and Staphylococcus xylosus were included as non-SA controls. The identity of the bacteriophages was identified via Transmission Electron Microscopy and genomic size analysis. Their stability at different pH and temperature were elucidated.

    RESULTS: A total of 10 lytic bacteriophages infecting S.aureus were isolated and two of them namely ΦNUSA-1 and ΦNUSA-10 from the family of Myoviridae and Siphoviridae respectively exhibited exceptionally broad host range against >80% of MRSA and MSSA tested. Both bacteriophages were specific to S.aureus and stable at both physiologic pH and temperature.

    CONCLUSION: This study demonstrated the abundance of S.aureus specific bacteriophages in raw sewage. Their high virulence against both MSSA and MRSA is an excellent antimicrobial characteristic which can be exploited for bacteriophage therapy against MRSA.

    Matched MeSH terms: Drug Discovery/methods
  10. Al-Dabbagh MM, Salim N, Himmat M, Ahmed A, Saeed F
    J Comput Aided Mol Des, 2017 Apr;31(4):365-378.
    PMID: 28220440 DOI: 10.1007/s10822-016-0003-4
    Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.
    Matched MeSH terms: Drug Discovery/methods*
  11. Zainal-Abidin MH, Hayyan M, Ngoh GC, Wong WF, Looi CY
    J Control Release, 2019 12 28;316:168-195.
    PMID: 31669211 DOI: 10.1016/j.jconrel.2019.09.019
    The applications of eutectic systems, including deep eutectic solvents (DESs), in diverse sectors have drawn significant interest from researchers, academicians, engineers, medical scientists, and pharmacists. Eutecticity increases drug dissolution, improves drug penetration, and acts as a synthesis route for drug carriers. To date, DESs have been extensively explored as potential drug delivery systems on account of their unique properties such as tunability and chemical and thermal stability. This review discusses two major topics: first, the application of eutectic mixtures (before and after the introduction of DES) in the field of drug delivery systems, and second, the most promising examples of DES pharmaceutical activity. It also considers future prospects in the medical and biotechnological fields. In addition to the application of DESs in drug delivery systems, they show greatly promising pharmaceutical activities, including anti-fungal, anti-bacterial, anti-viral, and anti-cancer activities. Eutecticity is a valid strategy for overcoming many obstacles inherently associated with either introducing new drugs or enhancing drug delivery systems.
    Matched MeSH terms: Drug Discovery/methods
  12. Chung PY
    Curr Drug Targets, 2018;19(7):832-840.
    PMID: 28891454 DOI: 10.2174/1389450118666170911114604
    BACKGROUND: Bacterial resistance to antibiotics is one of the most serious challenge to global public health. The introduction of new antibiotics in clinical settings, i.e. agents that belong to a new class of antibacterials, act on new targets or has a novel mechanisms of action, may not be sufficient to cope with the emergence of multidrug-resistant pathogens such as Staphylococcus aureus, Streptococcus pneumoniae, Pseudomonas aeruginosa, Klebsiella pneumoniae, Acinetobacter baumannii and Escherichia coli, which are increasingly prevalent in healthcare settings in Europe, the USA and Asia. Hence, coordinated efforts in minimizing the risk of spread of resistant bacteria and renewing research efforts in the search for novel antibacterial agents are urgently needed to manage this global crisis.

    OBJECTIVE: This review highlights the challenges and potential in using current technologies in the discovery and development of novel antibacterial agents to keep up with the constantly evolving resistance in bacteria.

    CONCLUSION: With the explosion of bacterial genomic data and rapid development of new sequencing technologies, the understanding of bacterial pathogenesis and identification of novel antibiotic targets have significantly improved.

    Matched MeSH terms: Drug Discovery/methods
  13. Tan BH, Pan Y, Dong AN, Ong CE
    J Pharm Pharm Sci, 2017;20(1):319-328.
    PMID: 29145931 DOI: 10.18433/J3434R
    In vitro and in silico models of drug metabolism are utilized regularly in the drug research and development as tools for assessing pharmacokinetic variability and drug-drug interaction risk. The use of in vitro and in silico predictive approaches offers advantages including guiding rational design of clinical drug-drug interaction studies, minimization of human risk in the clinical trials, as well as cost and time savings due to lesser attrition during compound development process. This article gives a review of some of the current in vitro and in silico methods used to characterize cytochrome P450(CYP)-mediated drug metabolism for estimating pharmacokinetic variability and the magnitude of drug-drug interactions. Examples demonstrating the predictive applicability of specific in vitro and in silico approaches are described. Commonly encountered confounding factors and sources of bias and error in these approaches are presented. With the advent of technological advancement in high throughput screening and computer power, the in vitro and in silico methods are becoming more efficient and reliable and will continue to contribute to the process of drug discovery, development and ultimately safer and more effective pharmacotherapy. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
    Matched MeSH terms: Drug Discovery/methods*
  14. Anwar A, Khan NA, Siddiqui R
    Parasit Vectors, 2018 01 09;11(1):26.
    PMID: 29316961 DOI: 10.1186/s13071-017-2572-z
    Acanthamoeba spp. are protist pathogens and causative agents of serious infections including keratitis and granulomatous amoebic encephalitis. Its ability to convert into dormant and highly resistant cysts form limits effectiveness of available therapeutic agents and presents a pivotal challenge for drug development. During the cyst stage, Acanthamoeba is protected by the presence of hardy cyst walls, comprised primarily of carbohydrates and cyst-specific proteins, hence synthesis inhibition and/or degradation of cyst walls is of major interest. This review focuses on targeting of Acanthamoeba cysts by identifying viable therapeutic targets.
    Matched MeSH terms: Drug Discovery/methods*
  15. Kazi A, Chuah C, Majeed ABA, Leow CH, Lim BH, Leow CY
    Pathog Glob Health, 2018 05;112(3):123-131.
    PMID: 29528265 DOI: 10.1080/20477724.2018.1446773
    Immunoinformatics plays a pivotal role in vaccine design, immunodiagnostic development, and antibody production. In the past, antibody design and vaccine development depended exclusively on immunological experiments which are relatively expensive and time-consuming. However, recent advances in the field of immunological bioinformatics have provided feasible tools which can be used to lessen the time and cost required for vaccine and antibody development. This approach allows the selection of immunogenic regions from the pathogen genomes. The ideal regions could be developed as potential vaccine candidates to trigger protective immune responses in the hosts. At present, epitope-based vaccines are attractive concepts which have been successfully trailed to develop vaccines which target rapidly mutating pathogens. In this article, we provide an overview of the current progress of immunoinformatics and their applications in the vaccine design, immune system modeling and therapeutics.
    Matched MeSH terms: Drug Discovery/methods*
  16. Patra JK, Das G, Fraceto LF, Campos EVR, Rodriguez-Torres MDP, Acosta-Torres LS, et al.
    J Nanobiotechnology, 2018 Sep 19;16(1):71.
    PMID: 30231877 DOI: 10.1186/s12951-018-0392-8
    Nanomedicine and nano delivery systems are a relatively new but rapidly developing science where materials in the nanoscale range are employed to serve as means of diagnostic tools or to deliver therapeutic agents to specific targeted sites in a controlled manner. Nanotechnology offers multiple benefits in treating chronic human diseases by site-specific, and target-oriented delivery of precise medicines. Recently, there are a number of outstanding applications of the nanomedicine (chemotherapeutic agents, biological agents, immunotherapeutic agents etc.) in the treatment of various diseases. The current review, presents an updated summary of recent advances in the field of nanomedicines and nano based drug delivery systems through comprehensive scrutiny of the discovery and application of nanomaterials in improving both the efficacy of novel and old drugs (e.g., natural products) and selective diagnosis through disease marker molecules. The opportunities and challenges of nanomedicines in drug delivery from synthetic/natural sources to their clinical applications are also discussed. In addition, we have included information regarding the trends and perspectives in nanomedicine area.
    Matched MeSH terms: Drug Discovery/methods
  17. Baharuddin A, Hassan AA, Sheng GC, Nasir SB, Othman S, Yusof R, et al.
    Curr Pharm Des, 2014;20(21):3428-44.
    PMID: 24001228
    Viruses belonging to the Flaviviridae family primarily spread through arthropod vectors, and are the major causes of illness and death around the globe. The Flaviviridae family consists of 3 genera which include the Flavivirus genus (type species, yellow fever virus) as the largest genus, the Hepacivirus (type species, hepatitis C virus) and the Pestivirus (type species, bovine virus diarrhea). The flaviviruses (Flavivirus genus) are small RNA viruses transmitted by mosquitoes and ticks that take over host cell machinery in order to propagate. However, hepaciviruses and pestiviruses are not antropod-borne. Despite the extensive research and public health concern associated with flavivirus diseases, to date, there is no specific treatment available for any flavivirus infections, though commercially available vaccines for yellow fever, Japanese encephalitis and tick-born encephalitis exist. Due to the global threat of viral pandemics, there is an urgent need for new drugs. In many countries, patients with severe cases of flavivirus infections are treated only by supportive care, which includes intravenous fluids, hospitalization, respiratory support, and prevention of secondary infections. This review discusses the strategies used towards the discovery of antiviral drugs, focusing on rational drug design against Dengue virus (DENV), West Nile virus (WNV), Japanese encephalitis virus (JEV), Yellow Fever virus (YFV) and Hepatitis C virus (HCV). Only modified peptidic, nonpeptidic, natural compounds and fragment-based inhibitors (typically of mass less than 300 Da) against structural and non-structural proteins are discussed.
    Matched MeSH terms: Drug Discovery/methods*
  18. Othman M, Genapathy S, Liew PS, Ch'ng QT, Loh HS, Khoo TJ, et al.
    Nat Prod Res, 2011 Nov;25(19):1857-64.
    PMID: 21838540 DOI: 10.1080/14786419.2010.537274
    The world's rainforests hold untold potential for drug discovery. Rainforest plants are thought to contain evolved defensive active metabolites of greater diversity compared to plants from temperate regions. In recent years, the interest and overall output from pharmaceutical companies on novel antibacterial agents has diminished at a time when there is a critical need for them to fight the threat of resistance. In this study, we have investigated the antimicrobial properties of 21 flowering plants from 16 different families against six bacterial strains consisting of two Gram negative and four Gram positive. Using the pour plate disc diffusion technique, almost all extracts from these plants were found to be active against some of the bacterial strains tested. The most interesting and active plants with broad spectrum activities include Duabanga grandiflora, Acalypha wilkesiana and Pseuduvaria macrophylla where the minimum inhibitory concentration, minimum bactericidal concentration and phytochemical analysis were carried out. This is the first report describing the antimicrobial and phytochemical properties of D. grandiflora and P. macrophylla. Our findings support the utilisation of higher plant species in the search for new antimicrobial molecules to combat new emerging infective diseases and the problem of drug resistant pathogens.
    Matched MeSH terms: Drug Discovery/methods*
  19. Venkateskumar K, Parasuraman S, Chuen LY, Ravichandran V, Balamurgan S
    Curr Drug Discov Technol, 2020;17(4):507-514.
    PMID: 31424372 DOI: 10.2174/1570163816666190819141344
    About 95% of earth living space lies deep below the ocean's surface and it harbors extraordinary diversity of marine organisms. Marine biodiversity is an exceptional reservoir of natural products, bioactive compounds, nutraceuticals and other potential compounds of commercial value. Timeline for the development of the drug from a plant, synthetic and other alternative sources is too lengthy. Exploration of the marine environment for potential bioactive compounds has gained focus and huge opportunity lies ahead for the exploration of such vast resources in the ocean. Further, the evolution of superbugs with increasing resistance to the currently available drugs is alarming and it needs coordinated efforts to resolve them. World Health Organization recommends the need and necessity to develop effective bioactive compounds to combat problems associated with antimicrobial resistance. Based on these factors, it is imperative to shift the focus towards the marine environment for potential bioactive compounds that could be utilized to tackle antimicrobial resistance. Current research trends also indicate the huge strides in research involving marine environment for drug discovery. The objective of this review article is to provide an overview of marine resources, recently reported research from marine resources, challenges, future research prospects in the marine environment.
    Matched MeSH terms: Drug Discovery/methods*
  20. Ashraf MI, Ong SK, Mujawar S, Pawar S, More P, Paul S, et al.
    Sci Rep, 2018 04 27;8(1):6669.
    PMID: 29703908 DOI: 10.1038/s41598-018-25042-2
    Identifying effective drug targets, with little or no side effects, remains an ever challenging task. A potential pitfall of failing to uncover the correct drug targets, due to side effect of pleiotropic genes, might lead the potential drugs to be illicit and withdrawn. Simplifying disease complexity, for the investigation of the mechanistic aspects and identification of effective drug targets, have been done through several approaches of protein interactome analysis. Of these, centrality measures have always gained importance in identifying candidate drug targets. Here, we put forward an integrated method of analysing a complex network of cancer and depict the importance of k-core, functional connectivity and centrality (KFC) for identifying effective drug targets. Essentially, we have extracted the proteins involved in the pathways leading to cancer from the pathway databases which enlist real experimental datasets. The interactions between these proteins were mapped to build an interactome. Integrative analyses of the interactome enabled us to unearth plausible reasons for drugs being rendered withdrawn, thereby giving future scope to pharmaceutical industries to potentially avoid them (e.g. ESR1, HDAC2, F2, PLG, PPARA, RXRA, etc). Based upon our KFC criteria, we have shortlisted ten proteins (GRB2, FYN, PIK3R1, CBL, JAK2, LCK, LYN, SYK, JAK1 and SOCS3) as effective candidates for drug development.
    Matched MeSH terms: Drug Discovery/methods*
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