PREDICTION OF BIOLOGICAL ACTIVITY OF FLAVONOIDS ISOLATED FROM VERBASCUM ORIENTALE PLANT GROWING IN EASTERN KAZAKHSTAN REGION USING PASS PROGRAM

Chemogenomics is a new multidisciplinary field of science, the ultimate goal of which has been studied by various authors (Caron et al., 2001; Kubini, 2006; Rognan, 2007) to establish complete correspondence between all ligands in biological objects. Chemogenomics uses methods of establishing patterns based on computer analysis of information in chemical and biological databases. The goal of creating and developing the computer program PASS (Prediction of Activity Spectrum of Substances) is to predict all types of biological activity that a chemical substance can exhibit when interacting with biological objects. The forecast is made on the basis of the analysis of a large-scale learning model, which includes information about the structure of known biologically active substances and their interaction with biological objects. PASS is a virtual chemogenomics "tool" that allows in silico to identify the most likely ligands for known targets and, conversely, the most likely targets for known ligands, as well as to predict the effects of specific ligands interacting with specific targets. . It provides a brief description of PASS and examples of its practical application to identify ligands, their potential biological targets, and the effects caused by these interactions. Therefore, the help of special computer systems is needed to obtain an estimate of the possible types of biological activity for different classes of compounds. A real opportunity to comprehensively study the biological activity of substances can be provided by creating new computer prediction technologies and using them to evaluate the possible types of activity of chemical compounds, and then testing the studied substances according to the prediction. A fairly fast and effective method of searching for pharmacologically active compounds is the use of a database, based on which structural analogues with a given pharmacological activity can be predicted in advance. In this case ISIS/Draw, ChemDraw, ChemScetch, etc. Programs such as The computer program PASS (Prediction of Activity Spectra for Substances) for predicting the spectrum of biological activity of organic compounds works on this principle.

Authors

Publication Details

Journal
Yessenov Science Journal
Published
2024-12-10
DOI
https://doi.org/10.56525/oajb1571
Primary Topic
Phytochemistry and Biological Activities
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PREDICTION OF BIOLOGICAL ACTIVITY OF FLAVONOIDS ISOLATED FROM VERBASCUM ORIENTALE PLANT GROWING IN EASTERN KAZAKHSTAN REGION USING PASS PROGRAM

М. А. Ибраева, Zh. Mukazhanova, С. Ж. КЕҢЕСХАНОВА
Yessenov Science Journal
Phytochemistry and Biological Activities
article

PREDICTION OF BIOLOGICAL ACTIVITY OF FLAVONOIDS ISOLATED FROM VERBASCUM ORIENTALE PLANT GROWING IN EASTERN KAZAKHSTAN REGION USING PASS PROGRAM

М. А. Ибраева, Zh. Mukazhanova, С. Ж. КЕҢЕСХАНОВА
article en

Abstract

Chemogenomics is a new multidisciplinary field of science, the ultimate goal of which has been studied by various authors (Caron et al., 2001; Kubini, 2006; Rognan, 2007) to establish complete correspondence between all ligands in biological objects. Chemogenomics uses methods of establishing patterns based on computer analysis of information in chemical and biological databases. The goal of creating and developing the computer program PASS (Prediction of Activity Spectrum of Substances) is to predict all types of biological activity that a chemical substance can exhibit when interacting with biological objects. The forecast is made on the basis of the analysis of a large-scale learning model, which includes information about the structure of known biologically active substances and their interaction with biological objects. PASS is a virtual chemogenomics "tool" that allows in silico to identify the most likely ligands for known targets and, conversely, the most likely targets for known ligands, as well as to predict the effects of specific ligands interacting with specific targets. . It provides a brief description of PASS and examples of its practical application to identify ligands, their potential biological targets, and the effects caused by these interactions. Therefore, the help of special computer systems is needed to obtain an estimate of the possible types of biological activity for different classes of compounds. A real opportunity to comprehensively study the biological activity of substances can be provided by creating new computer prediction technologies and using them to evaluate the possible types of activity of chemical compounds, and then testing the studied substances according to the prediction. A fairly fast and effective method of searching for pharmacologically active compounds is the use of a database, based on which structural analogues with a given pharmacological activity can be predicted in advance. In this case ISIS/Draw, ChemDraw, ChemScetch, etc. Programs such as The computer program PASS (Prediction of Activity Spectra for Substances) for predicting the spectrum of biological activity of organic compounds works on this principle.

Yessenov Science JournalVol. 49(4)
Openalex Percentile: Top 85%
Phytochemistry and Biological Activities
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

PREDICTION OF BIOLOGICAL ACTIVITY OF FLAVONOIDS ISOLATED FROM VERBASCUM ORIENTALE PLANT GROWING IN EASTERN KAZAKHSTAN REGION USING PASS PROGRAM — М. А. Ибраева, Zh. Mukazhanova, et al. · Yessenov Science Journal (2024) | TGRS Research Map | TGRS