Dipole moments and tautomeric equilibria of some aroylacetanilides

1981 ◽  
Vol 78 ◽  
pp. 155-159 ◽  
Author(s):  
Magdi M. Naoum ◽  
Hakim G. Shinouda ◽  
Ahmed S. Shawali ◽  
Hanna A. Rizk
2019 ◽  
Author(s):  
Kateryna Goloviznina ◽  
José N. Canongia Lopes ◽  
Margarida Costa Gomes ◽  
Agilio Padua

A general, transferable polarisable force field for molecular simulation of ionic liquids and their mixtures with molecular compounds is developed. This polarisable model is derived from the widely used CL\&P fixed-charge force field that describes most families of ionic liquids, in a form compatible with OPLS-AA, one of the major force fields for organic compounds. Models for ionic liquids with fixed, integer ionic charges lead to pathologically slow dynamics, a problem that is corrected when polarisation effects are included explicitly. In the model proposed here, Drude induced dipoles are used with parameters determined from atomic polarisabilities. The CL\&P force field is modified upon inclusion of the Drude dipoles, to avoid double-counting of polarisation effects. This modification is based on first-principles calculations of the dispersion and induction contributions to the van der Waals interactions, using symmetry-adapted perturbation theory (SAPT) for a set of dimers composed of positive, negative and neutral fragments representative of a wide variety of ionic liquids. The fragment approach provides transferability, allowing the representation of a multitude of cation and anion families, including different functional groups, without need to re-parametrise. Because SAPT calculations are expensive an alternative predictive scheme was devised, requiring only molecular properties with a clear physical meaning, namely dipole moments and atomic polarisabilities. The new polarisable force field, CL\&Pol, describes a broad set set of ionic liquids and their mixtures with molecular compounds, and is validated by comparisons with experimental data on density, ion diffusion coefficients and viscosity. The approaches proposed here can also be applied to the conversion of other fixed-charged force fields into polarisable versions.<br>


Author(s):  
Arijit Bag

Background: IC50 is one of the most important parameters of a drug. But, it is very difficult to predict this value of a new compound without experiment. There are only a few QSAR based methods available for IC50 prediction which is also highly dependable on huge number of known data. Thus, there is an immense demand for a sophisticated computational method of IC50 prediction, in the field of in-silico drug designing. Objective: Recently developed quantum computation based method of IC50 prediction by Bag and Ghorai requires an affordable known data. In present research work further development of this method is carried out such that the requisite number of known data being minimal. Methods: To retrench the cardinal data span and shrink the effects of variant biological parameters on the computed value of IC50, a relative approach of IC50 computation is pursued in the present method. To predict an approximate value of IC50 of a small molecule, only the IC50 of a similar kind of molecule is required for this method. Results: The present method of IC50 computation is tested for both organic and organometallic compounds as HIV-1 capsid A inhibitor and cancer drugs. Computed results match very well with the experiment. Conclusion: This method is easily applicable to both organic and organometallic com- pounds with acceptable accuracy. Since this method requires only the dipole moments of an unknown compound and the reference compound, IC50 based drug search is possible with this method. An algorithm is proposed here for IC50 based drug search.


1968 ◽  
Vol 33 (7) ◽  
pp. 2019-2028 ◽  
Author(s):  
O. Exner ◽  
Z. Fidlerová ◽  
V. Jehlička
Keyword(s):  

1972 ◽  
Vol 37 (12) ◽  
pp. 3859-3860 ◽  
Author(s):  
V. Gregor ◽  
V. Jehlička ◽  
J. Stuchlík
Keyword(s):  

1968 ◽  
Vol 33 (9) ◽  
pp. 2862-2871 ◽  
Author(s):  
O. Exner ◽  
V. Jehlička ◽  
B. Uchytil
Keyword(s):  

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