Molecular modeling of purinergic receptor P2Y12 and interaction with its antagonists

Zhan, Changhong; Yang, Jie; Dong, Xiao; Wang, Yuelan

doi:10.1016/j.jmgm.2006.09.006

Cited by 23 publications

(24 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The computations involving the scoring matrix methods are a substantial test of such an approach, with explicit models built that cover roughly 90% of approved GPCRs in test sets. Our focus in previous work was methodological for prediction of active sites using the scoring matrix [40] while this approach showed that the scoring matrix methodology quantitatively outperformed molecular modeling methods for prediction target proteins. In the present work, the scoring matrix methods are used to predict potential proteins as well as prediction of active sites at a level of genome or amino acid sequences.…”

Section: Discussionmentioning

confidence: 99%

“…According to our previous methods [40,43], we defined the coding sequence (CDS) of GPCRs' each TM as TM-CDS unit composed of nucleotides. At first, the TM-CDS units are obtained using the sliding window method one by one from 5'-terminal of GPCRs' CDS to 3'-teminal: A sequence of l nucleotides gives rise to m 1 l m   TM-CDS units.…”

Section: Test Setsmentioning

confidence: 99%

“…Early structural models, such as HIV-1 co-receptor CCR5 (chemokine receptors) [37,38], and human thromboxane receptor [39], are based on the atomic coordinates of the brh structure; some models, e.g. human ADP receptor (Purinergic Receptor P2Y12) [40], are constructed by homology modeling using bovine rhodopsin as a template. All of these modeling studies combined with bioinformatics and chemoinformatics become amenable to the rational design of novel drugs targeting GPCRs in the human genome [28].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Discovery and validation of potential drug targets based on the phylogenetic evolution of GPCRs

Yang¹,

Li²,

Zhu³

et al. 2012

Self Cite

View full text Add to dashboard Cite

Target identification is a critical step following the discovery of small molecules that elicit a biological phenotype. G-protein coupled recaptors (GPCRs) are among the most important drug targets for the pharmaceutical industry. The present work seeks to provide an in silico model of known GPCR protein fishing technologies in order to rapidly fish out potential drug targets on the basis of amino acid sequences and seven transmembrane regions (TMs) of GPCRs. Some scoring matrices were trained on 22 groups of GPCRs in the GPCRDB database. These models were employed to predict the GPCR proteins in two groups of test sets. On average, the mean correct rate of each TM of 38 GPCRs from two test sets ( and ) was found 62% and 57.5%, respectively, using training set 18 ( ); the mean hit rate of each TM of 38 GPCRs from and S 24 was found 68.1% and 64.7%, respectively. Based on the scoring matrices of PreMod, the mean correct rate of each TM of GPCRs from and was found 62% and 62.04%, respectively; the mean hit rate of each TM of GPCRs from and was found 67.7% and 68.0%, respectively. The means of GPCRs in based on is close to those based on PreMod; whereas the means of GPCRs in 24 based on D S 18 is less than those based on PreMod. Moreover, the accuracy ("2") and validity ("2 + 1") rates of prediction all seven TMs of 38 GPCRs by the scoring matrices of PreMod are more than those by ,

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Test Setsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Discovery and validation of potential drug targets based on the phylogenetic evolution of GPCRs

Yang¹,

Li²,

Zhu³

et al. 2012

Self Cite

View full text Add to dashboard Cite

show abstract

“…And it helps for the following statistic analysis and further matrix comparison. According to our methods [17,18], the accumulative times ( k c ) and the percentage ( k P ) of each herbal medicine in 233…”

Section: Database Of Diabetes Mellitus Proved Recipes and Statistic Amentioning

confidence: 99%

“…Simple score matrix method On the basis of our methods [18], according to the order of 241 kinds of CMMs, the matching direction of medicinal herbs, and the character of drug pairs (mated herbs), choose 18 kinds of CMM from eight DMPRs ( Table 2) for a 1×18 unitary score matrix consisting of zero for scoring mismatches and a series of positive scores namely (7 7 3 3 3 3 3 3 3 …”

Section: Score Matrixmentioning

confidence: 99%

Systematical Analysis of the Application of Chinese Traditional Medicine Informatics to Diabetes Proved Recipesw

Yang¹

2012

J Diab Res Clin Met

Self Cite

View full text Add to dashboard Cite

Chinese medicinal materials that originate from animal, mineral and plant have thousands years for diabetes therapy and accumulate a great deal of valuable clinical experience. The rapidly increasing diabetes mellitus is becoming a serious threat to mankind health in all parts of the world. Currently, bioinformatics has already impenetrate biology, medicine, genomics, clinical pharmacology, botany, and other subjects. This paper mainly expatiates the actual application of information technology to traditional Chinese medicinal materials, especially build a database of diabetes mellitus proved recipe (DMPR) by Microsoft Access 2000; analyze and find complexity information of DMPR viz matrix alignment. Our research results reveal that there is not linearity relationship between P value and clinical activities of DMPR that show diversity and complexity; and t-test results show that P1 value of simple score matrix and P2 value of complex score matrix present significantly difference and the latter is more rational than the former because the secondary score matrix plays a complementary role to the first score matrix so that enhance the reliability and the veracity of prediction. Therefore, bioinformatics at many scales and many levels should be spread for Chinese traditional medicine proved recipe possessing complexity, diversity, and non-linearity. This will greatly change the research actuality of Chinese traditional medicine, improve the research level of Chinese traditional medicine informatics, and accelerate the research step of modernization of Chinese traditional medicine.

show abstract

Receptors for Purines and Pyrimidines

Ralevic

Burnstock

2012

Purinergic Signalling and the Nervous System

1,017

View full text Add to dashboard Cite

Molecular modeling of purinergic receptor P2Y12 and interaction with its antagonists

Cited by 23 publications

References 41 publications

Discovery and validation of potential drug targets based on the phylogenetic evolution of GPCRs

Discovery and validation of potential drug targets based on the phylogenetic evolution of GPCRs

Systematical Analysis of the Application of Chinese Traditional Medicine Informatics to Diabetes Proved Recipesw

Receptors for Purines and Pyrimidines

Contact Info

Product

Resources

About