Talk:Quantitative structure–activity relationship

Copyright notice and name dropping SPAM?

I would like to remove the text and all those copy right notices from Wikipedia of the q-pharm company. I see this rather as link SPAM than real added value. IMHO this is a kind of copyright notice SPAM and text SPAM for creating a new term 'post-QSAR'. Until this question is solved I will remove the text from the main page and enter it here.
And, this company or at least some people related to it, have added external link SPAM to e.g. the Cheminformatics page, and I do not like this.
Beside of this, the content of the text and its added value is really questionable. We do not need this text, there are tons of free text pieces for QSAR available. I really do not see any need to use their misleading and non-general text, which is a wild mix of terms and not really categorized. JKW 16:44, 6 May 2006 (UTC)[reply]

And dear contributers, please create a Wikipedia account.

And dear Wikipedia administrators, if you have a look at the history, I am wondering, if we should track some IP adresses, since there have been already several tries for adding link SPAM, e.g. 83.237.205.133, 83.237.126.150, 83.237.205.143

JKW 16:59, 6 May 2006 (UTC)[reply]

I completely agree. ~K 17:31, 6 May 2006 (UTC)[reply]

Text to be discussed

Post-QSAR technologies - The new paradigm in cheminformatics and molecular modelling – applying quantum and molecular physics instead of statistical scoring-function -like and QSAR-like methods, for many tasks, e.g. molecular docking. These novel techniques (demonstrate accurate affinity calculations due to fast quantum calculations, which take into account full flexibility of molecules, solvation effects, and entropy contribution. The first striking discrepancy between Post-QSAR and the QSAR based techniques is the method of calculation of Free Binding Energy. Post-QSAR apply “pure” physics models whereas other docking programs use scoring functions for energy evaluation. - Scoring functions evaluate free energy by substituting the exact physical model with simplified statistical methods. Such methods take into account the data of a training set – different parameters of intermolecular interaction for a set of protein-ligand complexes. As a result of such a statistical approach, the scoring function approximates only those ligands, which are similar to those in the training set with any level of accuracy and is not appropriate for analyzing novel molecules or for de novo drug design. Because of this shortcoming, docking programs based on scoring functions are typically used for docking molecules that are similar to the training set molecules; or as rough filters before wet chemistry screening to get rid of molecules with very low affinity. Moreover, and this is critically important for pharma and other industries, scoring functions can not predict inhibitors of novel classes, because the accuracy of all scoring functions depends greatly on the quality of training sets of known ligands belonging to known classes. That impacts patentability and increases the danger of infringement on the rights of third parties. The accuracy of binding calculations and docking performed using “pure” physics models is not effected by this and Post-QSAR approaches can generate truly novel inhibitors that are both strong and patentable. - As a rule, scoring functions are very simple mathematical functions, which require rather small computer resources and therefore calculate very quickly. Post-QSAR’s algorithms employ far more sophisticated mathematical models, which require a great deal of computer recourses. Post-QSAR's optimization algorithms are sophisticated tools for analyzing huge numbers of local minima of energy for protein-ligand complexes. The latest achievements of mathematics – modern Multigrid methods and so called Minima Hopping Methods - are implemented in Post-QSAR’s algorithms. Free energy calculations take from minutes to half an hour per complex depending on size of the ligand and the active site of the protein at the one node. - Scoring functions perform calculations quickly, but the quality is very poor. The configurational space in these calculations has fewer minima than a real complex would have. This means that scoring functions are not selective towards the ligand and all ligands have approximately the same predicted affinities. - QSAR-based technologies apply mostly very simplified solvation models like the Surface Area/Generalized Born. Quantum also uses this model, but only during the initial phases of screening. Some technologies ignore this subject entirely pretending that these effects are already taken into account in the scoring function. Obviously, this omission creates errors in predicting affinities. Post-QSAR uses the Poisson-Boltzmann Solvation Model, which requires solving partial differential equations. This takes time, but dramatically improves the results. - Protein Flexibility. Almost all chemoinformatics technologies treat ligands as flexible, but only few, has moved further and considered protein flexibility. Flexibility is one of the most important features because small changes in geometry of molecules lead to significant alterations in the free binding energy. There are two kinds of flexibility of proteins in Post-QSAR. The first accounts for small changes in the geometry of the protein by calculating corrections to entropy. In the second type, overall movements of the protein are taken into account; these movements are modeled by Normal Mode Analysis. - The result of technological advances is a dramatic difference in the accuracy of calculation between the post-QSAR and QSAR and scoring functions based programs. Post-QSAR techniques show an accuracy of only 15% error in free energy calculation. The majority of QSAR applications either try not to mention accuracy at all or indicate figures in the range of 40-50% error. Even those figures are doubtful because they can be obtained on complexes that are similar to those in the training sets and do not represent the general pattern. A fair estimate of errors of methods based on scoring functions should be near 100%. So these methods will have very limited application in future drug design. The application of Post-QSAR techniques does not demand the use of a training set. The comparison of the perfomance of the new technologies with the QSAR based and experimental tests can be found or made independently, e.g. here here.

Copyright (c) 2005-2006 Quantum Pharmaceuticals. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled "GNU Free Documentation License".

General

Quantum Pharmaceuticals (www.q-pharm.com) the copyright holder of the content is authorizing everyone to use this content for informational and educational purposes, including discussing it at Wikipedia. To check this authorization please contact Quantum Pharmaceuticals directly office ///at/// q-pharm.com.

Copyright (c) 2005-2006 Quantum Pharmaceuticals. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled "GNU Free Documentation License".

Kindest regards,

Quantum Pharmaceuticals legal department

Please review WP:GFDL. Only full agreement for the content to be released under that license will be adequate for the content to be placed on Wikipedia. JFW | T@lk 13:53, 17 January 2006 (UTC)[reply]

Hey Competitors of Quantum! You're urgently needed!

Should we place it inside the Wikipedia article or it is enough to place it here?

Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled "GNU Free Documentation License".