scholarly journals Increase of efficiency of QSAR — the analysis of carcinogenic activity of halogeneted hydrocarbons

2005 ◽  
Vol 3 (2) ◽  
pp. 5-14
Author(s):  
Aleksey V Tarasov ◽  
Serikbay K Abilev ◽  
Ramis M Velibekov ◽  
Valentin A Tarasov
Keyword(s):  
Biological Activity ◽  
Computer Program ◽  
Chemical Compounds ◽  
Carcinogenic Activity ◽  
Structural Descriptors ◽  
Selection Of

The new principle of analysis of structureactivity of carcinogenic compounds is offered. It is basis on use a compound structural descriptors representing a combination untied among themselves of structural fragments of a molecule. The computer program is developed, allowing to generate every possible structural fragments of molecules of chemical compounds and their  combinations and to carry out selection of the compound descriptors statistically significantly influencing their biological activity. In work it is used the samples consisting of 89 halogeneted hydrocarbons for which their carcinogenic activity on rodents is investigated.

Robustness of Biological Activity Spectra Predicting by Computer Program PASS for Noncongeneric Sets of Chemical Compounds

2000 ◽  
Vol 40 (6) ◽  
pp. 1349-1355 ◽  
Author(s):  
V. V. Poroikov ◽  
D. A. Filimonov ◽  
Yu. V. Borodina ◽  
A. A. Lagunin ◽  
A. Kos
Keyword(s):  
Biological Activity ◽  
Computer Program ◽  
Chemical Compounds

scholarly journals Analysis of the effects of related fingerprints on molecular similarity using an eigenvalue entropy approach

2019 ◽  
Author(s):  
Hiroyuki Kuwahara ◽  
Xin Gao
Keyword(s):  
Biological Activity ◽  
Virtual Screening ◽  
Molecular Similarity ◽  
Chemical Compounds ◽  
Structural Similarity ◽  
Optimal Selection ◽  
Two Dimensional ◽  
Chemical Fingerprints ◽  
Selection Of ◽  
Similarity Scores

AbstractTwo-dimensional (2D) chemical fingerprints are widely used as numerical features for the quantification of structural similarity of chemical compounds, which is an important step in similarity-based virtual screening (VS). Here, using an eigenvalue-based entropy approach, we sought to identify 2D fingerprints with little to no contribution to shaping the eigenvalue distribution of the feature matrix as related fingerprints and examined the degree to which these related 2D fingerprints influence molecular similarity scores via Tanimoto coefficient. We found that there are many related fingerprints in publicly available fingerprint schemes and that their presence in the feature set tends to decrease the similarity scores. Our results have implication in the optimal selection of 2D fingerprints and the identification of potential hits for compounds with target biological activity in VS.

ChemInform Abstract: Robustness of Biological Activity Spectra Predicting by Computer Program PASS for Noncongeneric Sets of Chemical Compounds.

ChemInform ◽  
2001 ◽  
Vol 32 (5) ◽  
pp. no-no
Author(s):  
V. V. Poroikov ◽  
D. A. Filimonov ◽  
Yu. V. Borodina ◽  
A. A. Lagunin ◽  
A. Kos
Keyword(s):  
Biological Activity ◽  
Computer Program ◽  
Chemical Compounds

scholarly journals Computer programs for calculating pKa: A comparative study for 3-[3-(2-nitrophenyl)prop-2-enoyl]-2h-1-benzopyran-2-one

2010 ◽  
Vol 75 (2) ◽  
pp. 243-248 ◽  
Author(s):  
Selma Spirtovic-Halilovic ◽  
Davorka Zavrsnik
Keyword(s):  
Antimicrobial Activity ◽  
Computer Program ◽  
Dissociation Constant ◽  
Chemical Compounds ◽  
Computer Programs ◽  
Good Activity ◽  
Target Compound ◽  
Theoretical Approaches ◽  
Pka Value ◽  
Good Agreement

Coumarin-based compounds containing a chalcone moiety exhibit antimicrobial activity. These substances are potential drugs and it is important to determine their pKa values. However, they are almost insoluble in water. The dissociation constant was experimentally determined by potentiometric titration for 3-[3-(2-nitrophenyl)prop-2-enoyl]-2H-1-benzopyran-2-one because this compound shows good activity and solubility. A number of different computer programs for the calculation of the dissociation constant of chemical compounds have been developed. The pKa value of the target compound was calculated using three different computer programs, i.e., the ACD/pKa, CSpKaPredictor and ADME/ToxWEB programs, which are based on different theoretical approaches. The analysis demonstrated good agreement between the experimentally observed pKa value of 3-[3-(2-nitrophenyl)prop-2-enoyl]-2H-1-benzopyran- 2-one and the value calculated using the computer program CSpKa.

scholarly journals A Computational Approach on Acetaminophen Drug using Degree-Based Topological Indices and M-Polynomials

2021 ◽  
Vol 12 (6) ◽  
pp. 7249-7266
Keyword(s):  
Biological Activity ◽  
Physicochemical Properties ◽  
Chemical Structure ◽  
Topological Index ◽  
Chemical Reactivity ◽  
Chemical Compounds ◽  
Computational Approach ◽  
Topological Indices ◽  
Numerical Representation ◽  
Essential Drug

Topological index is a numerical representation of a chemical structure. Based on these indices, physicochemical properties, thermodynamic behavior, chemical reactivity, and biological activity of chemical compounds are calculated. Acetaminophen is an essential drug to prevent/treat various types of viral fever, including malaria, flu, dengue, SARS, and even COVID-19. This paper computes the sum and multiplicative version of various topological indices such as General Zagreb, General Randić, General OGA, AG, ISI, SDD, Forgotten indices M-polynomials of Acetaminophen. To the best of our knowledge, for the Acetaminophen drugs, these indices have not been computed previously.

scholarly journals Selection of the chemical composition of steels and their thermal hardening mode using a computer program

2021 ◽  
pp. 59-65
Author(s):  
D. M. Berdiev ◽  
M. A. Uмаrоvа ◽  
A. A. Yusupov
Keyword(s):  
Wear Resistance ◽  
Chemical Composition ◽  
Computer Program ◽  
Sliding Friction ◽  
Thermal Hardening ◽  
Abrasive Particles ◽  
Density Of Dislocations ◽  
Heat Treated ◽  
Final Tempering ◽  
Selection Of

The relationships between the parameters of the structure of heat‑treated steels and their abrasive wear resistance are established. At all temperatures of the final tempering of hardened steel, there is a direct relationship between its structure parameters (the number of elements in a solid solution, the density of dislocations, the size of cementite particles and the intercementite distance) and wear resistance when sliding friction against loose abrasive particles. A computer program has been developed to select the chemical composition of the steel grade and methods of thermal hardening in order to ensure the required wear resistance.

scholarly journals Predicting the inhibition efficiencies of magnesium dissolution modulators using sparse machine learning models

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Elisabeth J. Schiessler ◽  
Tim Würger ◽  
Sviatlana V. Lamaka ◽  
Robert H. Meißner ◽  
Christian J. Cyron ◽  
...  
Keyword(s):  
Corrosion Inhibition ◽  
Molecular Descriptors ◽  
Chemical Space ◽  
Chemical Compounds ◽  
Automatic Identification ◽  
Organic Additives ◽  
Statistical Tool ◽  
Degradation Behaviour ◽  
Corrosion Inhibition Efficiency ◽  
Selection Of

AbstractThe degradation behaviour of magnesium and its alloys can be tuned by small organic molecules. However, an automatic identification of effective organic additives within the vast chemical space of potential compounds needs sophisticated tools. Herein, we propose two systematic approaches of sparse feature selection for identifying molecular descriptors that are most relevant for the corrosion inhibition efficiency of chemical compounds. One is based on the classical statistical tool of analysis of variance, the other one based on random forests. We demonstrate how both can—when combined with deep neural networks—help to predict the corrosion inhibition efficiencies of chemical compounds for the magnesium alloy ZE41. In particular, we demonstrate that this framework outperforms predictions relying on a random selection of molecular descriptors. Finally, we point out how autoencoders could be used in the future to enable even more accurate automated predictions of corrosion inhibition efficiencies.

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