Dissociation constant prediction software tools | Drug discovery data analysis
The biopharmaceutical profile of a compound depends directly on the dissociation constants of its acidic and basic groups, commonly expressed as the negative decadic logarithm pKa of the acid dissociation constant (Ka).
Predicts pK(a) values for drug-like molecules. Epik can use this capability in combination with technology for tautomerization to adjust the protonation state of small drug-like molecules to automatically generate one or more of the most probable forms for use in further molecular modeling studies. Epik can process large databases of drug-like molecules to provide information on protonation states. Extensions to the well-established Hammett and Taft approaches are used for pK(a) prediction, namely, mesomer standardization, charge cancellation, and charge spreading to make the predicted results reflect the nature of the molecule itself rather just for the particular Lewis structure used on input. In addition, an iterative technology for generating, ranking and culling the generated protonation states is employed.
Provides accurate and fast calculations for in-silico computation of pKa values. MoKa implements this approach using an algorithm based on descriptors derived from GRID molecular interaction fields. MoKa was trained using a very diverse set of more than 25000 pKa values. This package provides a graphical interface for predictions, containing tautomer check, batch mode for multi-structure files, integrated structure editor and cut and paste from ISIS/Draw (for Windows version). MoKa also proposes command line tools for advanced users.
Predicts pH-dependent aqueous solubility of druglike molecules. pHSol is based on artificial neural networks trained on a druglike PHYSPROP subset of 4548 compounds. It uses significantly fewer descriptors compared to other models. The tool can be used for evaluating existing commercial and in-house libraries. It can also compose new libraries of a desired solubility distribution at specific pH levels.
Specializes in fast electronic structure predictions for molecular systems of medium and large size. Jaguar is an ab initio quantum chemical program that focuses on computational methods with reasonable computational scaling with the size of the system, such as density functional theory (DFT) and local second-order Moller-Plesset perturbation theory. The favorable scaling of the methods and the high efficiency of the program make it possible to conduct routine computations involving several thousand molecular orbitals. The speed advantages are beneficial for applying Jaguar in biomolecular computational modeling. Additionally, owing to its superior wave function guess for transition-metal-containing systems, Jaguar finds applications in inorganic and bioinorganic chemistry. The emphasis on larger systems and transition metal elements paves the way toward developing Jaguar for its use in materials science modeling.
Computes and studies atomic charges which respond to changes in molecular conformation and chemical environment. ACC is based on the electronegativity equalization method (EEM). It implements interactive 3D visualization of the molecules based on atomic charges. This tool is useful for statistical analysis and comparison of the results. It can handle any type of molecular system, regardless of size and chemical complexity.
Uses computational algorithms based on fundamental chemical structure theory to estimate a wide variety of reactivity parameters strictly from molecular structure. This SPARC capability crosses chemical family boundaries to cover a broad range of organic compounds. The SPARC chemical modeling system is relatively mature and is used widely in academic, government and industrial laboratories.
Calculates the accurate acidic and basic pKa values (negative logarithms of acid-base ionization constants) for organic compounds, in most cases, within an error of 0.25 pKa units. pKalc calculation can be performed for any organic compound, including aromatics, mono and polyheteroaromatics, and small peptides. The applied logarithm, adapted after Hammett and Taft takes into account all necessary electronic, steric and other effects and relies on an extended database of almost a thousand equations. pKalc predicts acidic and basic pKa values before synthesis, such as in diversity calculations for combinatorial chemistry, in quantitative structure-activity relationship (QSAR), in evaluating the synthesis possibilities, or in characterizing substance libraries. It is also helpful in situations when compounds are poorly soluble or may decompose in a water solution, as well as in the case of pKa values which are too high or too low.