Name
Title | ||
|---|---|---|
A Triangle Framework among Subgraph Isomorphism, Pharmacophore and Structure-function Relationship |
Abstract | ||
|---|---|---|
BSTRACTCoronavirus disease 2019 (COVID-19) has gained utmost attention in the current time from academic research and industrial practices because it continues to rage in many countries. Pharmacophore models exploit molecule topological similarity as well as functional compound similarity so that they can be reliable via the application of the concept of bioisosterism. In this work, we analyze the targets for coronavirus protein and the structure of RNA virus variation, thereby complete the safety and pharmacodynamic action evaluation of small-molecule anti-coronavirus oral drugs. Common pharmacophore identifications could be converted into subgraph querying problems, due to chemical structures can also be converted to graphs, which is a knotty problem pressing for a solution. We adopt simplified representation pharmacophore graphs by reducing complete molecular structures to abstracts to detect isomorphic topological patterns and further to improve the substructure retrieval efficiency. Our threefold architecture subgraph isomorphism-based method retrieves query subgraphs over large graphs. First, by means of extracting a sequence of subgraphs to be matched and then comparing the number of vertex and edge between the potential isomorphic subgraphs and the query graph, we lower the computational scaling markedly. Afterwards, the directed vertex and edge matrix recording vertex and edge positional relation, directional relation and distance relation has been created. Then, on the basis of permutation theorem, we calculate the row sum of vertex and edge adjacency matrix of query graph and potential sample. Finally, according to equinumerosity theorem, we check the eigenvalues of the vertex and edge adjacency matrices of the two graphs are equinumerous. The topological distance could be calculated based on the graph isomorphism and the subgraph isomorphism can be implemented after the combination of the subgraph. The proposed quantitative structure–function relationships (QSFR) approach can be effectively applied for pharmacophoric abstract patterns identification. The framework of new drug development for covid-19 has been established based on this triangle. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3487553.3524724 | International World Wide Web Conference |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mengjiao Guo | 1 | 0 | 0.34 |
| Hui Zheng | 2 | 73 | 15.94 |
| Tengfei Ji | 3 | 0 | 0.34 |
| Hu Fa | 4 | 0 | 0.34 |
| Jing He | 5 | 362 | 48.04 |