Drug-likeness of Phytic Acid and Its Analogues

Inositol hexakisphosphate is known to be the phosphorous reserve in plants particularly in the seeds. Though it has been known for its antinutrient properties for many years, recent research shed light to reveal it as a novel anticancer agent. Hence the present study investigates the drug-likeness of phytic acid and its analogues through bioinformatics methods. Two potential cancer drug targets such as mitogen activated kinase and inositol 1,4,5-triphosphate receptor are included in the study. Out of 50 selected analogues of phytic acid, 42 structures interact well with the chosen drug targets. The best interacting structures are 1-diphosinositol pentakisphosphate and 2,3,4,5,6-pentaphosphonooxycyclohexyl dihydrogen phosphate. For both of these structures, the negative binding energy obtained was -49.5 KJ/mol; this affirms the stability of the complex. ADME properties are also predicted to assess the drug-like properties of the compounds. The structure activity relationship model is generated for 12 compounds with experimental IC50 values.

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Abstract C159: Identification of potential cancer drug targets using HT RNAi screening with pooled shRNA libraries.

10.1158/1535-7163.targ-11-c159 ◽

2011 ◽

Author(s):

Donato Tedesco ◽

Kyle Bonneau ◽

Mikhail Makhanov ◽

Costas G. Frangou ◽

Alex Chenchik

Keyword(s):

Drug Targets ◽

Cancer Drug ◽

Rnai Screening ◽

Potential Cancer

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Integration of Cancer Gene Co-expression Network and Metabolic Network To Uncover Potential Cancer Drug Targets

Journal of Proteome Research ◽

10.1021/pr400162t ◽

2013 ◽

Vol 12 (6) ◽

pp. 2354-2364 ◽

Cited By ~ 13

Author(s):

Jingqi Chen ◽

Ming Ma ◽

Ning Shen ◽

Jianzhong Jeff Xi ◽

Weidong Tian

Keyword(s):

Metabolic Network ◽

Drug Targets ◽

Cancer Drug ◽

Cancer Gene ◽

Potential Cancer

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New cancer drug targets identified in adrenocortical carcinoma through gene expression profiling

Endocrine Abstracts ◽

10.1530/endoabs.56.p115 ◽

2018 ◽

Author(s):

Raimunde Liang ◽

Isabel Weigand ◽

Barbara Altieri ◽

Stefan Kircher ◽

Sonja Steinhauer ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Profiling ◽

Adrenocortical Carcinoma ◽

Expression Profiling ◽

Drug Targets ◽

Cancer Drug

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A Survey on Computational Methods for Essential Proteins and Genes Prediction

Current Bioinformatics ◽

10.2174/1574893613666181112150422 ◽

2019 ◽

Vol 14 (3) ◽

pp. 211-225 ◽

Cited By ~ 2

Author(s):

Ming Fang ◽

Xiujuan Lei ◽

Ling Guo

Keyword(s):

Computational Methods ◽

Drug Targets ◽

Disease Genes ◽

Essential Proteins ◽

Experimental Identification ◽

Cellular Life ◽

Different Types ◽

The Stability ◽

Human Disease Genes ◽

Biology Research

Background: Essential proteins play important roles in the survival or reproduction of an organism and support the stability of the system. Essential proteins are the minimum set of proteins absolutely required to maintain a living cell. The identification of essential proteins is a very important topic not only for a better comprehension of the minimal requirements for cellular life, but also for a more efficient discovery of the human disease genes and drug targets. Traditionally, as the experimental identification of essential proteins is complex, it usually requires great time and expense. With the cumulation of high-throughput experimental data, many computational methods that make useful complements to experimental methods have been proposed to identify essential proteins. In addition, the ability to rapidly and precisely identify essential proteins is of great significance for discovering disease genes and drug design, and has great potential for applications in basic and synthetic biology research. Objective: The aim of this paper is to provide a review on the identification of essential proteins and genes focusing on the current developments of different types of computational methods, point out some progress and limitations of existing methods, and the challenges and directions for further research are discussed.

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Advances in Cancer Drug Targets

10.2174/97816080593861140201 ◽

2014 ◽

Keyword(s):

Drug Targets ◽

Cancer Drug

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Advances in Cancer Drug Targets

10.2174/97816810823321160301 ◽

2016 ◽

Keyword(s):

Drug Targets ◽

Cancer Drug

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Cellular Fitness Phenotypes of Cancer Target Genes from Oncobiology to Cancer Therapeutics

Cells ◽

10.3390/cells10020433 ◽

2021 ◽

Vol 10 (2) ◽

pp. 433

Author(s):

Bijesh George ◽

P. Mukundan Pillai ◽

Aswathy Mary Paul ◽

Revikumar Amjesh ◽

Kim Leitzel ◽

...

Keyword(s):

Drug Targets ◽

Target Genes ◽

Human Cancer ◽

Cancer Therapeutics ◽

Survival Duration ◽

Cancer Drug ◽

Targeted Therapeutics ◽

Cellular Targets ◽

Human Cancer Cells ◽

Cancer Types

To define the growing significance of cellular targets and/or effectors of cancer drugs, we examined the fitness dependency of cellular targets and effectors of cancer drug targets across human cancer cells from 19 cancer types. We observed that the deletion of 35 out of 47 cellular effectors and/or targets of oncology drugs did not result in the expected loss of cell fitness in appropriate cancer types for which drugs targeting or utilizing these molecules for their actions were approved. Additionally, our analysis recognized 43 cellular molecules as fitness genes in several cancer types in which these drugs were not approved, and thus, providing clues for repurposing certain approved oncology drugs in such cancer types. For example, we found a widespread upregulation and fitness dependency of several components of the mevalonate and purine biosynthesis pathways (currently targeted by bisphosphonates, statins, and pemetrexed in certain cancers) and an association between the overexpression of these molecules and reduction in the overall survival duration of patients with breast and other hard-to-treat cancers, for which such drugs are not approved. In brief, the present analysis raised cautions about off-target and undesirable effects of certain oncology drugs in a subset of cancers where the intended cellular effectors of drug might not be good fitness genes and that this study offers a potential rationale for repurposing certain approved oncology drugs for targeted therapeutics in additional cancer types.

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Forward Rate Bias in Developed and Developing Countries: More Risky Not Less Rational

Econometrics ◽

10.3390/econometrics8040043 ◽

2020 ◽

Vol 8 (4) ◽

pp. 43

Author(s):

Michael D. Goldberg ◽

Olesia Kozlova ◽

Deniz Ozabaci

Keyword(s):

Developing Countries ◽

Forward Rate ◽

Currency Markets ◽

Developed Country ◽

Slope Coefficient ◽

Break Points ◽

Time Periods ◽

The Stability ◽

Widespread View ◽

Shed Light

This paper examines the stability of the Bilson–Fama regression for a panel of 55 developed and developing countries. We find multiple break points for nearly every country in our panel. Subperiod estimates of the slope coefficient show a negative bias during some time periods and a positive bias during other time periods in nearly every country. The subperiod biases display two key patterns that shed light on the literature’s linear regression findings. The results point toward the importance of risk in currency markets. We find that risk is greater for developed country markets. The evidence undercuts the widespread view that currency returns are predictable or that developed country markets are less rational.

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