Epik: a software program for pK _a prediction and protonation state generation for drug-like molecules

Abstract

Epik is a computer program for predicting 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. Many medicinal chemicals can exchange protons with their environment, resulting in various ionization and tautomeric states, collectively known as protonation states. The protonation state of a drug can affect its solubility and membrane permeability. In modeling, the protonation state of a ligand will also affect which conformations are predicted for the molecule, as well as predictions for binding modes and ligand affinities based upon protein–ligand interactions. Despite the importance of the protonation state, many databases of candidate molecules used in drug development do not store reliable information on the most probable protonation states. Epik is sufficiently rapid and accurate to process large databases of drug-like molecules to provide this information. Several new technologies are employed. 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, a new iterative technology for generating, ranking and culling the generated protonation states is employed.

Appendix: Prioritizing SMARTS patterns for ABGs

All SMARTS patterns for ABGs are assigned numeric priorites. The pattern with the highest priority that matches a particular ABG is selected and the parameters (e.g. pKa⁰ and ρ) associated with that pattern are used in the HT calculations. These priorities are assigned in one of three ways:

• 1. The ABG was manually assigned a negative priority and thus are matched only if a more specific pattern is not found. This was only done for very general patterns (e.g. primary, secondary or tertiary amines) which would match many functionalities, most of which are better described by more specific patterns (e.g. amides and anilines). Roughly 5% of the patterns in the database are assigned negative priorities.

• 2. The priority for the ABG was calculated from the SMARTS pattern.

• 3. In a couple of cases the priority was calculated as described in the last item (2) except that a manually assigned shift was added to distinguish very closely related patterns.

The procedure for calculating the priority from the SMARTS pattern will be outlined in detail below.

All SMARTS patterns for ABGs are recorded in the acidic form and begin with the acidic hydrogen followed immediately by the atom to with the acidic hydrogen is bound. We will refer that atom as the first heavy atom.

The SMARTS pattern is translated into a list of atoms and a list of bonds. The type of bond is noted or inferred from the SMARTS pattern consistent with the SMARTS standard. Each atom is classified SP3-like unless it meets one of two conditions:

• 1. If any of the bonds involving this atom are double, triple or aromatic

• 2. If it is a O, S or N and bonded to an aromatic atom

The priority, P, of a SMARTS pattern for an ABG is calculated using the equation:

$$ P=2^\ast a_2 +\sum\limits_{i > 2} {p_i^\ast a_i } $$

(16)

where: a _i is the weighting for atom i in the SMARTS pattern and p _i is an attenuation factor that depends on the shortest topological path from atom 2, the first heavy atom, to atom i. All atoms in the SMARTS pattern are included in the sum except the acidic hydrogen atom (atom 1). The a _i values were determined by trial and error and are given in Table 3. The p _i values were calculated using the equation:

$$ p_i =\prod\limits_j s_j $$

(17)

where s _j is a attenuation factor corresponding to a portion of the shortest path from atom 2 to atom i. Each non-aromatic bond has a separate propagation factor while each set of consecutive aromatic bonds gets a single factor. Aromatic bonds are treated differently because the influence of atoms in aromatic systems does not monotonically decrease with the number of bonds. The attenuation factors for non-aromatic bonds are given in Table 4 while those for aromatic bonds are given in Table 5.

Table 3 Atom weighting factors used in prioritizing SMARTS matches for ABGs

Table 4 Attenuation factors, s _j , for different non-aromatic bond types

Table 5 Attenuation factors, s _j , as a function of aromatic path length