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QSPR designer – a program to design and evaluate QSPR models. Case study on pKa prediction
2011
Journal of Cheminformatics
The performance of the software is demonstrated by a case study on the prediction of pK a . ...
Using the QSPR Designer, we have successfully designed, evaluated, and compared 75 different QSPR models for the prediction of pK a from charges. ...
The performance of the software is demonstrated by a case study on the prediction of pK a . ...
doi:10.1186/1758-2946-3-s1-p16
pmcid:PMC3083570
fatcat:gtgkmcj54fgz7ieoz2bb6d56qq
APPLICATION OF MULTIVARIATE IMAGE ANALYSIS IN QSPR STUDY OF pKa OF VARIOUS ACIDS BY PRINCIPAL COMPONENTS-LEAST SQUARES SUPPORT VECTOR MACHINE
2015
Journal of the Chilean Chemical Society (Print)
Multivariate image analysis applied to QSPR modeling was done by means of principal component-least squares support vector machine (PC-LSSVM) methods. ...
A new implemented quantitative structure-property relationships (QSPR) method, whose descriptors achieved from bidimensional images, was suggested for the predicting of acidity constant (pK a ) of various ...
The results of this study clearly show the potential and versatility of PC-LSSVM modeling in QSPR study of pK a of different acids using multivariate image analysis, which could be applied to prediction ...
doi:10.4067/s0717-97072015000300001
fatcat:h6wbieh3drbtboisfpy3pwxz7u
Use of QSPR Modeling to Characterize In Vitro Binding of Drugs to a Gut-Restricted Polymer
2018
Pharmaceutical Research
Methods We selected 28 drugs to evaluate for binding to patiromer in vitro over a range of pH and ionic conditions intended to mimic the gut environment. ...
Using this in vitro data, we developed QSPR models using step-wise linear regression and analyzed over 100 physiochemical drug descriptors. ...
ACKNOWLEDGMENTS AND DISCLOSURES This study was sponsored by Relypsa, Inc., a Vifor Pharma Group Company, Redwood City, California. ...
doi:10.1007/s11095-018-2356-y
pmid:29520505
pmcid:PMC5843698
fatcat:pwa56ntsxrgy3mnnk3xfkllvse
How Does the Methodology of 3D Structure Preparation Influence the Quality of pKa Prediction?
2015
Journal of Chemical Information and Modeling
Our results confirmed that QSPR models based on partial atomic charges are able to predict pK a with high accuracy. ...
The acid dissociation constant is an important molecular property and it can be successfully predicted by Quantitative Structure-Property Relationship (QSPR) models, even for in silico designed molecules ...
Acknowledgments This work was also supported in part by NIH grants R01 GM071872, U01 GM094612, and U54 GM094618 to R.A.. ...
doi:10.1021/ci500758w
pmid:26010215
pmcid:PMC5098400
fatcat:yyfxfrsnsbe3xc6j5rmiiradya
Density functional theory based quantitative structure-property relationship studies on coumarin-based prodrugs
2012
BioScience Trends
We suggest that the QSPR models derived here, especially the PNN models, can be used to predict the release kinetics of coumarin-based prodrugs as well as design new derivatives of coumarin-based prodrug ...
The calculated structural parameters were taken as theoretical descriptors to establish five novel QSPR models. ...
PNN simulation of QSPR In this case a nonlinear PNN model of QSPR was developed with the same selected subset of 6 descriptors from those linear models. ...
doi:10.5582/bst.2012.v6.5.234
fatcat:hwylbsmlyfc4losh4yzgih4nae
QSPR Models for Prediction of Aqueous Solubility: Exploring the Potency of Randić-type Indices
2020
Croatica Chemica Acta
The development of QSPR models to predict aqueous solubility (logS) is presented. ...
A 2 (not final pg. №) J. SLUGA et al.: QSPR Models for Prediction of Aqueous Solubility ... Croat. Chem. Acta 2020, 93(4) ...
Supporting information to the paper is attached to the electronic version of the article at: https://doi.org/10.5562/cca3776. ...
doi:10.5562/cca3776
fatcat:zqfx4e2pv5gofjahxyfckjpwhu
Development of Quantitative Structure-Pharmacokinetic Relationships
1985
Environmental Health Perspectives
This prompted several researchers to focus attention to pharmacokinetic parameters as potential descriptors in quantitative drug design. ...
It is clear that quantitative approaches are of considerable interest to toxicologists, since these methods may contribute to the development of real predictive toxicology. ...
Bernard Testa for fruitful discussions and for drawing their attention to a number of references used in this review. ...
doi:10.2307/3430080
fatcat:nujuikoctvcg7buq4lowvm3vdq
Development of quantitative structure-pharmacokinetic relationships
1985
Environmental Health Perspectives
This prompted several researchers to focus attention to pharmacokinetic parameters as potential descriptors in quantitative drug design. ...
It is clear that quantitative approaches are of considerable interest to toxicologists, since these methods may contribute to the development of real predictive toxicology. ...
Bernard Testa for fruitful discussions and for drawing their attention to a number of references used in this review. ...
doi:10.1289/ehp.8561295
pmid:3905378
pmcid:PMC1568751
fatcat:hbjjlkokrnezfcna6pfwrwcjsy
ADMET PREDICTORS ARE THE TOOLS FOR THE ENHANCEMENT OF DRUG DESIGN AND DEVELOPMENT: A SYSTEMATIC REVIEW
2018
International journal of advances in pharmacy and biotechnology
The ADMET predictor tools can be better used to predict the properties of the drug in early and therefore time and money can be saved. ...
If a new candidate fails in ADME properties or if it produces abnormal toxicity in humans, we cannot release the drug into the market. The time and money spent on its development turns waste. ...
Moka[9][10] It is one of the new software useful for prediction of organic compounds pka value. It is based on QSPR approach. The training set contains 26,000 pka values. ...
doi:10.38111/ijapb.20180404002
fatcat:j2t2dnaqajcmjoilti5tkrbqbe
Prediction of coating thickness for polyelectrolyte multilayers via machine learning
2021
Zenodo
Next, a predictive model has been developed using aforementioned parameters and molecular descriptors of polymers from the DeepChem library. ...
Besides coating thickness, which was selected as an output value in this study, machine learning approach can be potentially used to predict functional properties of multilayer coatings, e.g. biocompatibility ...
Acknowledgements This project received funding from the European Union's Horizon 2020 PANBioRA research and innovation program under Grant Agreement No. 760921, from ANR TerminAnion and Bourse Frenchtech ...
doi:10.5281/zenodo.6043801
fatcat:fisi2tmunnasxbdjfb2tz3nbvi
Evaluation of log P, pKa, and log D predictions from the SAMPL7 blind challenge
2021
Journal of Computer-Aided Molecular Design
AbstractThe Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) challenges focuses the computational modeling community on areas in need of improvement for rational drug design. ...
these values (with methods often disagreeing even as to the sign of the free energy change associated with certain transitions), indicating far more work needs to be done on pKa prediction methods. ...
TDB acknowledges and appreciates support from the Association for Computing Machinery's Special Interest Group on High ...
doi:10.1007/s10822-021-00397-3
pmid:34169394
pmcid:PMC8224998
fatcat:foz35hwhzndmtmobdjkr7cdg6y
A Way towards Reliable Predictive Methods for the Prediction of Physicochemical Properties of Chemicals Using the Group Contribution and other Methods
2019
Applied Sciences
In summary, this review focuses on methodologies to obtain the required accuracies for the chemical practitioner and process technologist designing chemical processes. ...
modelling. ...
Formally, a definition of such descriptors was given by Todeschini and Consonni [9] . Descriptors can be evaluated by well-established procedures and available programs. ...
doi:10.3390/app9081700
fatcat:eboactp6hjdqrk5uicnio4sxma
Recent Advances on Aqueous Solubility Prediction
2011
Combinatorial chemistry & high throughput screening
Because of the importance of aqueous solubility, a lot of efforts have been spent on developing reliable models to predict this physiochemical property. ...
Although some progress has been made and a lot of models have been constructed, it is concluded that accurate and reliable aqueous models targeted to predict solubility of drug-like molecules, have not ...
In a recent study, Hewitt et al. concluded that the MLR was superior over more complex modeling methods in their solubility prediction study [23b]. ...
doi:10.2174/138620711795508331
pmid:21470182
fatcat:zbtiksj7obflxmvpghk642gjua
Examining the PM6 semiempirical method for pKa prediction across a wide range of oxyacids
2009
Nature Precedings
The pKa estimation ability of the semiempirical PM6 method was evaluated across a broad range of oxyacids and compared to results obtained using the SPARC software program. ...
SPARC outperforms PM6 on the peroxides, peroxyacids, phenols, and α-saturated acids and α-saturated alcohols. pKa values for boron, nitrogen, and sulfur oxyacids do not appear to be reliably estimated ...
Conclusion The pKa estimation ability of the semiempirical PM6 method was evaluated across a broad range of oxyacids and compared to results obtained using the SPARC software program. ...
doi:10.1038/npre.2009.2981.1
fatcat:gofzon7mzveptgh3jsp53zf534
Application of physiologically-based toxicokinetic modelling in oral-to-dermal extrapolation of threshold doses of cosmetic ingredients
2014
Toxicology Letters
In addition, the role of quantitative structure-property relationships (QSPRs) in predicting skin penetration is evaluated for the three substances with a view to incorporating QSPR-predicted penetration ...
This gives better model prediction results when compared to those of a PBTK model with a simpler structure of the absorption barrier. ...
to Optimize Safety) Project and by Cosmetics Europe. ...
doi:10.1016/j.toxlet.2014.03.013
pmid:24731971
fatcat:zef7lp5ktbavph7prckv44jo7y
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