Using a novel computational drug-repositioning approach (DrugPredict) to rapidly identify potent drug candidates for cancer treatment

This study for drug repositioning has been performed for the drugs which are in the market since more than a decade and they are approved with their well-established efficacy and safety in human being. Objective of this study was to reposition the existing non-cancer drug therapy for cancer treatment, which is having well characterized pharmacologic profile with more efficacy and least toxicity as anti-neoplastic agent. We have retrieved the source data from FDA Adverse Event Reporting System (FAERS) for the last 13 years covering duration from 2004 to 2016 and analysed those using pharmacovigilance approach â€˜a proposed future novel pharmaceutical tool for drug repositionâ€™. Signal management activity was performed for statistical analysis. Result of statistical analysis derived that propranolol; metformin; pioglitazone; dabigatran and nitroglycerin are the existing non-cancer drugs which deserved for their direct / indirect reposition for cancer treatment and anti-neoplastic activity. Further studies retrieving the source data from other regulatory database (e.g. Eudravigilance of EMA and VigiFlow of WHO) and post-marketing surveillance study with the same objective may adjuvant our results for the reposition of existing drugs by pharmacovigilance approach.

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PS4DR: A multimodal workflow for identification and prioritization of drugs based on pathway signatures

10.21203/rs.2.12791/v4 ◽

2020 ◽

Author(s):

Mhammad Asif Emon ◽

Daniel Domingo-Fernández ◽

Charles Tapley Hoyt ◽

Martin Hofmann-Apitius

Keyword(s):

Gene Expression ◽

Genome Wide Association Study ◽

Drug Repositioning ◽

Heterogeneous Data ◽

New Drugs ◽

Gwas Data ◽

Drug Candidates ◽

Gene Expression Signatures ◽

Approved Drugs ◽

Fda Approved Drugs

Abstract Background: During the last decade, there has been a surge towards computational drug repositioning owing to constantly increasing -omics data in the biomedical research field. While numerous existing methods focus on the integration of heterogeneous data to propose candidate drugs, it is still challenging to substantiate their results with mechanistic insights of these candidate drugs. Therefore, there is a need for more innovative and efficient methods which can enable better integration of data and knowledge for drug repositioning. Results: Here, we present a customizable workflow ( PS4DR) which not only integrates high-throughput data such as genome-wide association study (GWAS) data and gene expression signatures from disease and drug perturbations but also takes pathway knowledge into consideration to predict drug candidates for repositioning. We have collected and integrated publicly available GWAS data and gene expression signatures for several diseases and hundreds of FDA-approved drugs or those under clinical trial in this study. Additionally, different pathway databases were used for mechanistic knowledge integration in the workflow. Using this systematic consolidation of data and knowledge, the workflow computes pathway signatures that assist in the prediction of new indications for approved and investigational drugs. Conclusion: We showcase PS4DR with applications demonstrating how this tool can be used for repositioning and identifying new drugs as well as proposing drugs that can simulate disease dysregulations. We were able to validate our workflow by demonstrating its capability to predict FDA-approved drugs for their known indications for several diseases. Further, PS4DR returned many potential drug candidates for repositioning that were backed up by epidemiological evidence extracted from scientific literature. Source code is freely available at https://github.com/ps4dr/ps4dr .

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Screening of FDA Approved Drugs Against COVID-19 Main Protease: Coronavirus Disease

10.20944/preprints202004.0062.v1 ◽

2020 ◽

Cited By ~ 4

Author(s):

Vijayakumar Balakrishnan ◽

Karthik Lakshminarayanan

Keyword(s):

Vaccine Development ◽

New Drugs ◽

World Health ◽

Wuhan City ◽

Drug Candidates ◽

Human Contact ◽

Main Protease ◽

Potent Drug ◽

Approved Drugs ◽

Fda Approved Drugs

In the end of December 2019, a new strain of coronavirus was identified in the Wuhan city of Hubei province in China. Within a shorter period of time, an unprecedented outbreak of this strain was witnessed over the entire Wuhan city. This novel coronavirus strain was later officially renamed as COVID-19 (Coronavirus disease 2019) by the World Health Organization. The mode of transmission had been found to be human-to-human contact and hence resulted in a rapid surge across the globe where more than 1,100,000 people have been infected with COVID-19. In the current scenario, finding potent drug candidates for the treatment of COVID-19 has emerged as the most challenging task for clinicians and researchers worldwide. Identification of new drugs and vaccine development may take from a few months to years based on the clinical trial processes. To overcome the several limitations involved in identifying and bringing out potent drug candidates for treating COVID-19, in the present study attempts were made to screen the FDA approved drugs using High Throughput Virtual Screening (HTVS). The COVID-19 main protease (COVID-19 Mpro) was chosen as the drug target for which the FDA approved drugs were initially screened with HTVS. The drug candidates that exhibited favorable docking score, energy and emodel calculations were further taken for performing Induced Fit Docking (IFD) using Schrodinger’s GLIDE. From the flexible docking results, the following four FDA approved drugs Sincalide, Pentagastrin, Ritonavir and Phytonadione were identified. In particular, Sincalide and Pentagastrin can be considered potential key players for the treatment of COVID-19 disease.

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Differential Interactome Based Drug Repositioning Unraveled Abacavir, Exemestane, Nortriptyline Hydrochloride, and Tolcapone as Potential Therapeutics for Colorectal Cancers

Frontiers in Bioinformatics ◽

10.3389/fbinf.2021.710591 ◽

2021 ◽

Vol 1 ◽

Author(s):

Hande Beklen ◽

Sema Arslan ◽

Gizem Gulfidan ◽

Beste Turanli ◽

Pemra Ozbek ◽

...

Keyword(s):

Drug Repositioning ◽

Positive Control ◽

Drug Candidates ◽

Novel Biomarkers ◽

Critical Requirement ◽

Nortriptyline Hydrochloride ◽

In Silico Molecular Docking ◽

Prognostic Power ◽

Potential Therapeutics

There is a critical requirement for alternative strategies to provide the better treatment in colorectal cancer (CRC). Hence, our goal was to propose novel biomarkers as well as drug candidates for its treatment through differential interactome based drug repositioning. Differentially interacting proteins and their modules were identified, and their prognostic power were estimated through survival analyses. Drug repositioning was carried out for significant target proteins, and candidate drugs were analyzed via in silico molecular docking prior to in vitro cell viability assays in CRC cell lines. Six modules (mAPEX1, mCCT7, mHSD17B10, mMYC, mPSMB5, mRAN) were highlighted considering their prognostic performance. Drug repositioning resulted in eight drugs (abacavir, ribociclib, exemestane, voriconazole, nortriptyline hydrochloride, theophylline, bromocriptine mesylate, and tolcapone). Moreover, significant in vitro inhibition profiles were obtained in abacavir, nortriptyline hydrochloride, exemestane, tolcapone, and theophylline (positive control). Our findings may provide new and complementary strategies for the treatment of CRC.

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Homology Modeling and Virtual Screening Studies of Antigen MLAA-42 Protein: Identification of Novel Drug Candidates against Leukemia—An In Silico Approach

Computational and Mathematical Methods in Medicine ◽

10.1155/2020/8196147 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Ihsan A. Shehadi ◽

Huda R. M. Rashdan ◽

Aboubakr H. Abdelmonsef

Keyword(s):

Virtual Screening ◽

Homology Modeling ◽

Protein Identification ◽

Binding Affinities ◽

Monocytic Leukemia ◽

Drug Candidates ◽

Promising Target ◽

Leukemia Treatment ◽

Potent Drug ◽

Novel Drug

Monocytic leukemia-associated antigen-42 (MLAA-42) is associated with excessive cell division and progression of leukemia. Thus, human MLAA-42 is considered as a promising target for designing of new lead molecules for leukemia treatment. Herein, the 3D model of the target was generated by homology modeling technique. The model was then evaluated using various cheminformatics servers. Moreover, the virtual screening studies were performed to explore the possible binding patterns of ligand molecules to MLAA’s active site pocket. Thirteen ligand molecules from the ChemBank™ database were identified as they showed good binding affinities, scaffold diversity, and preferential ADME properties which may act as potent drug candidates against leukemia. The study provides the way to identify novel therapeutics with optimal efficacy, targeting MLAA-42.

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Natural Products as Modulators of Sirtuins

Molecules ◽

10.3390/molecules25143287 ◽

2020 ◽

Vol 25 (14) ◽

pp. 3287 ◽

Cited By ~ 2

Author(s):

Berin Karaman Mayack ◽

Wolfgang Sippl ◽

Fidele Ntie-Kang

Keyword(s):

Natural Products ◽

Drug Discovery ◽

Histone Deacetylases ◽

High Throughput Screening ◽

Chemical Space ◽

Class Iii ◽

Drug Candidates ◽

Starting Point ◽

Recent Developments ◽

Potent Drug

Natural products have been used for the treatment of human diseases since ancient history. Over time, due to the lack of precise tools and techniques for the separation, purification, and structural elucidation of active constituents in natural resources there has been a decline in financial support and efforts in characterization of natural products. Advances in the design of chemical compounds and the understanding of their functions is of pharmacological importance for the biomedical field. However, natural products regained attention as sources of novel drug candidates upon recent developments and progress in technology. Natural compounds were shown to bear an inherent ability to bind to biomacromolecules and cover an unparalleled chemical space in comparison to most libraries used for high-throughput screening. Thus, natural products hold a great potential for the drug discovery of new scaffolds for therapeutic targets such as sirtuins. Sirtuins are Class III histone deacetylases that have been linked to many diseases such as Parkinson`s disease, Alzheimer’s disease, type II diabetes, and cancer linked to aging. In this review, we examine the revitalization of interest in natural products for drug discovery and discuss natural product modulators of sirtuins that could serve as a starting point for the development of isoform selective and highly potent drug-like compounds, as well as the potential application of naturally occurring sirtuin inhibitors in human health and those in clinical trials.

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Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace

Briefings in Bioinformatics ◽

10.1093/bib/bbaa034 ◽

2020 ◽

Cited By ~ 8

Author(s):

Natesh Singh ◽

Ludovic Chaput ◽

Bruno O Villoutreix

Keyword(s):

Virtual Screening ◽

Drug Repositioning ◽

Pharmaceutical Research ◽

Bioactive Molecules ◽

Screening Methods ◽

Web Servers ◽

Web Based ◽

Drug Candidates ◽

Screening Experiments ◽

Molecule Docking

Abstract The interplay between life sciences and advancing technology drives a continuous cycle of chemical data growth; these data are most often stored in open or partially open databases. In parallel, many different types of algorithms are being developed to manipulate these chemical objects and associated bioactivity data. Virtual screening methods are among the most popular computational approaches in pharmaceutical research. Today, user-friendly web-based tools are available to help scientists perform virtual screening experiments. This article provides an overview of internet resources enabling and supporting chemical biology and early drug discovery with a main emphasis on web servers dedicated to virtual ligand screening and small-molecule docking. This survey first introduces some key concepts and then presents recent and easily accessible virtual screening and related target-fishing tools as well as briefly discusses case studies enabled by some of these web services. Notwithstanding further improvements, already available web-based tools not only contribute to the design of bioactive molecules and assist drug repositioning but also help to generate new ideas and explore different hypotheses in a timely fashion while contributing to teaching in the field of drug development.

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Identification of Prognostic Biomarker Signatures and Candidate Drugs in Colorectal Cancer: Insights from Systems Biology Analysis

Medicina ◽

10.3390/medicina55010020 ◽

2019 ◽

Vol 55 (1) ◽

pp. 20 ◽

Cited By ~ 21

Author(s):

Md. Rezanur Rahman ◽

Tania Islam ◽

Esra Gov ◽

Beste Turanli ◽

Gizem Gulfidan ◽

...

Keyword(s):

Colorectal Cancer ◽

Regulatory Networks ◽

Prognostic Biomarker ◽

Drug Repositioning ◽

Gene Expression Omnibus ◽

Transcriptional Regulatory Networks ◽

Survival Analyses ◽

Drug Candidates ◽

Protein Protein Interaction ◽

Kaplan Meier

Colorectal cancer (CRC) is the second most common cause of cancer-related death in the world, but early diagnosis ameliorates the survival of CRC. This report aimed to identify molecular biomarker signatures in CRC. We analyzed two microarray datasets (GSE35279 and GSE21815) from the Gene Expression Omnibus (GEO) to identify mutual differentially expressed genes (DEGs). We integrated DEGs with protein–protein interaction and transcriptional/post-transcriptional regulatory networks to identify reporter signaling and regulatory molecules; utilized functional overrepresentation and pathway enrichment analyses to elucidate their roles in biological processes and molecular pathways; performed survival analyses to evaluate their prognostic performance; and applied drug repositioning analyses through Connectivity Map (CMap) and geneXpharma tools to hypothesize possible drug candidates targeting reporter molecules. A total of 727 upregulated and 99 downregulated DEGs were detected. The PI3K/Akt signaling, Wnt signaling, extracellular matrix (ECM) interaction, and cell cycle were identified as significantly enriched pathways. Ten hub proteins (ADNP, CCND1, CD44, CDK4, CEBPB, CENPA, CENPH, CENPN, MYC, and RFC2), 10 transcription factors (ETS1, ESR1, GATA1, GATA2, GATA3, AR, YBX1, FOXP3, E2F4, and PRDM14) and two microRNAs (miRNAs) (miR-193b-3p and miR-615-3p) were detected as reporter molecules. The survival analyses through Kaplan–Meier curves indicated remarkable performance of reporter molecules in the estimation of survival probability in CRC patients. In addition, several drug candidates including anti-neoplastic and immunomodulating agents were repositioned. This study presents biomarker signatures at protein and RNA levels with prognostic capability in CRC. We think that the molecular signatures and candidate drugs presented in this study might be useful in future studies indenting the development of accurate diagnostic and/or prognostic biomarker screens and efficient therapeutic strategies in CRC.

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Combining Human Genetics of Multiple Sclerosis with Oxidative Stress Phenotype for Drug Repositioning

Pharmaceutics ◽

10.3390/pharmaceutics13122064 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2064

Author(s):

Stefania Olla ◽

Maristella Steri ◽

Alessia Formato ◽

Michael B. Whalen ◽

Silvia Corbisiero ◽

...

Keyword(s):

Oxidative Stress ◽

Multiple Sclerosis ◽

Human Genetics ◽

Drug Repositioning ◽

Neuronal Loss ◽

Arginine Methyltransferase ◽

Drug Candidates ◽

Genome Wide ◽

Brain Expression ◽

Oxidative Homeostasis

In multiple sclerosis (MS), oxidative stress (OS) is implicated in the neurodegenerative processes that occur from the beginning of the disease. Unchecked OS initiates a vicious circle caused by its crosstalk with inflammation, leading to demyelination, axonal damage and neuronal loss. The failure of MS antioxidant therapies relying on the use of endogenous and natural compounds drives the application of novel approaches to assess target relevance to the disease prior to preclinical testing of new drug candidates. To identify drugs that can act as regulators of intracellular oxidative homeostasis, we applied an in silico approach that links genome-wide MS associations and molecular quantitative trait loci (QTLs) to proteins of the OS pathway. We found 10 drugs with both central nervous system and oral bioavailability, targeting five out of the 21 top-scoring hits, including arginine methyltransferase (CARM1), which was first linked to MS. In particular, the direction of brain expression QTLs for CARM1 and protein kinase MAPK1 enabled us to select BIIB021 and PEITC drugs with the required target modulation. Our study highlights OS-related molecules regulated by functional MS variants that could be targeted by existing drugs as a supplement to the approved disease-modifying treatments.

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Dynamic Collaborations for the Development of Immune Checkpoint Blockade Agents

Journal of Personalized Medicine ◽

10.3390/jpm11060460 ◽

2021 ◽

Vol 11 (6) ◽

pp. 460

Author(s):

Arisa Djurian ◽

Tomohiro Makino ◽

Yeongjoo Lim ◽

Shintaro Sengoku ◽

Kota Kodama

Keyword(s):

Cancer Treatment ◽

Immune Checkpoint ◽

Success Factors ◽

Interorganizational Collaboration ◽

Immune Checkpoint Blockade ◽

Checkpoint Blockade ◽

Drug Candidates ◽

Innovative Drugs ◽

Product Sales ◽

Checkpoint Blockade Agents

We studied the overview of drug discovery and development to understand the recent trends and potential success factors of interorganizational collaboration by reviewing 1204 transactions performed until 2019 for 107 anticancer drugs approved by the US Food and Drug Administration (FDA) from 1999 to 2018. Immune checkpoint blockade was found to be a significantly active area in interorganizational transactions, especially the number of alliances, compared with other mechanisms of action of small molecules and biologics for cancer treatment. Furthermore, the analysis of pembrolizumab and nivolumab showed that the number of approved indications for these two drugs has been rapidly expanding since their first approval in 2014. Examination of the acquisitions and alliances regarding pembrolizumab and nivolumab showed that many combination partners were developed by US-based biotechnology or start-up companies, the majority of which were biologics. These findings suggest that immune checkpoint blockade is a paradigm for cancer treatment, resulting in huge product sales and continuous indication expansion. Additionally, interorganizational collaboration, especially trial collaboration, is a strategic approach for the development of immune checkpoint blockade agents. The translation of these empirical practices to new drug candidates is expected for the research and development of innovative drugs in the future.

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