Finally, four distinct target proteins representing members of three families,
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Finally, four distinct target proteins representing members of three families,
92 and 1. 0. We observed the highest novelty ratio for CD and the lowest for RA. The high ratio of novel targets for all phenotypes to predicted tar gets suggests repositioning could have a large impact on clinical studies. Identification of novel therapeutics To identify novel [You must be registered and logged in to see this link.] drugs, we compared our phenotype of interest with indications associated with the drug. In total, we retrieved 7,252 drugs associated with human drug tar gets from all three drug databases. We found 2,192 unique drugs that target the 452 potential therapeutic targets. We retrieved the maximum number of drugs from DrugBank and the remainder from TTD and PharmGKB. In order to identify the novel drugs i. e. drugs not targeting our phenotype of interest, we fil tered the above list of 2,192 drugs to retrieve 2,130 novel therapeutics.
On a phenotype by phenotype basis, T1D and CAD had the maximum number of novel predicted therapeutics. Although CD had the highest number of novel targets, it had comparatively few novel therapeutics [You must be registered and logged in to see this link.] suggesting new drug development is needed for this phe notype. BD had the fewest therapeutics as expected based on the small number of predicted therapeutic targets. We found that the total percentage of drugs that may be repositioned towards identified novel targets was around 29% of the total number of extracted drugs. Table 2 shows the 24 replicated targets with examples of replicated drugs found in our study. For example, the drug Aleglitazar is in phase III clinical trial for the T2D target PPARA, a predicted candidate gene for T2D.
Rosiglita zone known to target PPARG as a therapeutic for diabetes mellitus, has a potential [You must be registered and logged in to see this link.] use in the related phenotype T1D. Examples of novel therapeutics for the seven phenotypes are shown in Table 3. For example, Pirenzepine, which acts upon the CHRM1 gene product, is approved as a therapeutic drug for peptic ulcers. Our study predicts CHRM1 is a predicted candidate gene and novel therapeu tic target for T2D, suggesting that the drug Pirenzepine may be repositioned as a novel therapeutic for T2D. Hence, the associated therapeutics for the novel therapeu tic targets may be repositioned against the phenotypes of interest, accelerating the drug discovery process. FDA approved and clinical targets Identification of therapeutic targets targeted by approved and clinical trial drugs can help us to prioritize drugs for repositioning against phenotypes of interest.
Both approved and clinical targets are potential drug targets, however, approved targets will undoubtedly be on the priority list for further experimental studies. We classi fied the predicted targets as FDA approved and clinical targets for the seven complex diseases. An example depicted in Figure 7 shows comparison between T2D tar gets from the TTD database and targets predicted by Gentrepid for T2D. Of the 84 targets predicted for T2D by Gentrepid, 28 are listed in TTD. Comparing these 28 targets with the 32 targets indicated for T2D in TTD, we found products of three genes are targeted by drugs cur rently in clinical trials for T2D. In addition, PPARA is already targeted by FDA approved drugs. Hence, we pre dicted 25 novel therapeutic targets from the TTD data base for T2D.
On a phenotype by phenotype basis, T1D and CAD had the maximum number of novel predicted therapeutics. Although CD had the highest number of novel targets, it had comparatively few novel therapeutics [You must be registered and logged in to see this link.] suggesting new drug development is needed for this phe notype. BD had the fewest therapeutics as expected based on the small number of predicted therapeutic targets. We found that the total percentage of drugs that may be repositioned towards identified novel targets was around 29% of the total number of extracted drugs. Table 2 shows the 24 replicated targets with examples of replicated drugs found in our study. For example, the drug Aleglitazar is in phase III clinical trial for the T2D target PPARA, a predicted candidate gene for T2D.
Rosiglita zone known to target PPARG as a therapeutic for diabetes mellitus, has a potential [You must be registered and logged in to see this link.] use in the related phenotype T1D. Examples of novel therapeutics for the seven phenotypes are shown in Table 3. For example, Pirenzepine, which acts upon the CHRM1 gene product, is approved as a therapeutic drug for peptic ulcers. Our study predicts CHRM1 is a predicted candidate gene and novel therapeu tic target for T2D, suggesting that the drug Pirenzepine may be repositioned as a novel therapeutic for T2D. Hence, the associated therapeutics for the novel therapeu tic targets may be repositioned against the phenotypes of interest, accelerating the drug discovery process. FDA approved and clinical targets Identification of therapeutic targets targeted by approved and clinical trial drugs can help us to prioritize drugs for repositioning against phenotypes of interest.
Both approved and clinical targets are potential drug targets, however, approved targets will undoubtedly be on the priority list for further experimental studies. We classi fied the predicted targets as FDA approved and clinical targets for the seven complex diseases. An example depicted in Figure 7 shows comparison between T2D tar gets from the TTD database and targets predicted by Gentrepid for T2D. Of the 84 targets predicted for T2D by Gentrepid, 28 are listed in TTD. Comparing these 28 targets with the 32 targets indicated for T2D in TTD, we found products of three genes are targeted by drugs cur rently in clinical trials for T2D. In addition, PPARA is already targeted by FDA approved drugs. Hence, we pre dicted 25 novel therapeutic targets from the TTD data base for T2D.
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