Computational prediction

To identify the main methods and tools available for the computer prediction of spectra from the molecular structure, and for automatic structure elucidation from spectral data... 

Gavezzotti A and G Filippini 1996. Computer Prediction of Organic Crystal Structures Using Partial X-ray Diffraction Data, journal of the American Chemical Society 118 7153-7157. 

Although the Arrhenius equation does not predict rate constants without parameters obtained from another source, it does predict the temperature dependence of reaction rates. The Arrhenius parameters are often obtained from experimental kinetics results since these are an easy way to compare reaction kinetics. The Arrhenius equation is also often used to describe chemical kinetics in computational fluid dynamics programs for the purposes of designing chemical manufacturing equipment, such as flow reactors. Many computational predictions are based on computing the Arrhenius parameters. 

QSPR and QSAR are useful techniques for predicting properties that would be very dilficult to predict by any other method. This is a somewhat empirical or indirect calculation that ultimately limits the accuracy and amount of information which can be obtained. When other means of computational prediction are not available, these techniques are recommended for use. There are a variety of algorithms in use that are not equivalent. An examination of published results and tests of several techniques are recommended. 

After the completion of the balanced acceleration and deceleration runs, the unbalance weight must be placed at the predetermined location and the acceleration and deceleration test repeated using the same recording instrumentation. The results should be compared to the appropriate computer predictions and the API acceptance criteria applied. Acceptance criteria were added in the API 617 sixth edition. 

Ekins S, Andreyev S, Ryabov A, Kirilov E, Rakhmatulin EA, Bugrim A, et al. Computational prediction of human drug metabolism. Exp Opin Drug Metab Toxicol 2005 1 303-24. 

Even as the computational prediction error rate is reduced to acceptable levels, many cases will be encountered in which the predictions are indistinguishable to within error. In a scenario in which several different in silico designs are given equivalent but favorable activity predictions, the end user s medicinal experience may help decide which to promote to synthesis. The quality of that decision at this point will be strongly influenced by how easy it is to understand the different contributions to the computational predictions. Interpretability is thus critical for synergistically utilizing the experience of the end user. 

In the context of drug discovery, computational methods do not add value unless they can achieve practical results. Results must be produced quickly enough so that they can influence decision making in chemical synthesis. Most importantly, computational methods must be accurate enough to maintain the trust of the medicinal chemist. Without this trust, computational predictions will rarely be tested in the laboratory, which will then prevent the generation of critical data useful for improving the original predictions. 

Helguera AM, Perez MAC, Gonzalez MP, Ruiz RM, Dfaz HG. A topological substructural approach applied to the computational prediction of rodent carcinogenicity. Bioorg Med them 2005 13 2477-88. 

Barratt MD, Rodford RA. The computational prediction of toxicity. Curr Opin Chem Biol 2001,5 383-8. 

Yamazaki K and Kanaoka M. Computational prediction of the plasma proteinbinding percent of diverse pharmaceutical compounds. J Pharm Sci 2004 93 1480-94. 

The agreement between calculated and measured adsorption energies and barrier energies is sufficiently good that computational predictions can be quite reliable. Such studies are now providing a lot of detailed insight into reaction mechanisms. 

Barratt, M.D. Rodford, R.A. (2001) The Computational Prediction of Toxicity. Current Opinion in Chemistry and Biology, 5, 383-388. 

The difficulties and low-throughput nature of the experimental dual determination, especially in alkane-water systems, the development of other techniques more amenable to automation, as well as more refined computational approaches for octanol-water systems, aU have contributed to Umit the use of the alkane-water system as a second bulk-phase system. However, efforts have been devoted to the development of log (alkane) computational prediction methods by Rekker et al. [13] as well as Caron and Ermondi [14]. 

Compare the computer predictions with the Rayleigh equation prediction, where ... 

The computational prediction of vibrational spectra is among the important areas of application for modem quantum chemical methods because it allows the interpretation of experimental spectra and can be very instrumental for the identification of unknown species. A vibrational spectrum consists of two characteristics, the frequency of the incident light at which the absorption occurs and how much of the radiation is absorbed. The first quantity can be obtained computationally by calculating the harmonic vibrational frequencies of a molecule. As outlined in Chapter 8 density functional methods do a rather good job in that area. To complete the picture, one must also consider the second quantity, i. e., accurate computational predictions of the corresponding intensities have to be provided. 

The computational prediction of not the ligand but the metal, particularly transition-metal chemical shifts poses an even more severe challenge to any method. Electron corre-... 

The challenge for the drug discovery organization is how to handle the resource issues for multiple screening data feedback. Often a combination of experimental screens and computational prediction approaches will be used. Rapid data feedback to the medicinal chemist is essential, whether the data is experimental or computational. Data delayed is data with greatly reduced value. 

The figures that follow provide examples of some ways in which in vitro clearance data for two series can be compared and assessed to identify key questions, trends, or hypotheses. While the data presented here are for clearance in a human liver microsomal (HLM) incubation, the analysis could be applied in the same way to other data sets - including other experimental ADME or safety end points, or computationally predicted end points. 

---