Caspase-3 Inhibition Prediction of Pyrrolo[3,4-c] Quinoline-1,3-Diones Derivatives using Computational Tools (Record no. 15738)
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| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20211224104158.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 211224b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 15054 |
| Author | PANDEY, VANDANA |
| 245 ## - TITLE STATEMENT | |
| Title | Caspase-3 Inhibition Prediction of Pyrrolo[3,4-c] Quinoline-1,3-Diones Derivatives using Computational Tools |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.83(3), May-June |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Mumbai |
| Name of publisher, distributor, etc. | Indian Journal of Pharmaceutical Science |
| Year | 2021 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 504-514p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | In the present work, two dimensional quantitative structure activity relationship, molecular docking and absorption, distribution, metabolism, excretion and toxicity analyses were performed to pyrrolo[3,4-c] quinoline-1,3-diones derivatives, previously reported as caspase-3 inhibitors. A total of one hundred fifteen compounds were used to build linear multiple linear regression (multiple linear regression) and non-linear (artificial neural networks) quantitative structure activity relationship models, using genetic algorithm as a feature selection method. Both models were thoroughly validated following Organization for economic cooperation and development principles by internal and external validation as well as the domain of application (antiphase domain). Both Genetic algorithm-multiple linear regression (Rtrain=0.88, Rtest=0.94, mape test=5.3 and rmse test=0.41) and Genetic algorithm-artificial neural network (Rtrain=0.9, Rtest=0.93, mape test=4.5 and rmse test=0.4) models are statistically robust with high external predictive ability. Molecular docking simulations were performed on selected inhibitors revealed that binding energy values are in accordance with inhibitory activity values against caspase-3, which is modulated by hydrogen bondings, Pi stacking and hydrophobic interactions. The docking studies suggest that the inhibitors bind with an allosteric site of the enzyme formed by ARG207B, SER251B, PHE250 and PHE256 of the B chain. Besides, in silico, absorption, distribution, metabolism, excretion and toxicity profiles of selected inhibitors were checked to evaluate the key pharmacokinetic, physiochemical and druglikeness features. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4639 |
| Topical term or geographic name entry element | PHARMACEUTICS |
| 773 0# - HOST ITEM ENTRY | |
| Place, publisher, and date of publication | New Delhi |
| Title | Indian journal of pharmaceutical sciences |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://www.ijpsonline.com/articles/caspase3-inhibition-prediction-of-pyrrolo34c-quinoline13diones-derivatives-using-computational-tools.pdf |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Date acquired | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| School of Pharmacy | School of Pharmacy | Archieval Section | 2021-12-24 | 2021-2022558 | 2021-12-24 | 2021-12-24 | Articles Abstract Database |