Journal Articles

Protonate 3D:
Assignment of Macromolecular Protonation
State and Geometry

Paul Labute
July 2007
Chemical Computing Group Inc.
 

Introduction

The rapid growth of available macromolecular structure data from X-ray crystallography in the Protein Data Bank [Bernstein 1977] has had a large impact on computer-aided drug design and other computational life science methodology. This structural data coupled with the development of all-atom forcefields such as AMBER [Weiner 1986] OPLS-AA [Jorgensen 1996] and MMFF94 [Halgren 1996] provides means to conduct simulations of macromolecular structures such as Energy Minimization, Molecular Dynamics and Ligand-Receptor Docking. Explicit hydrogen atoms are required for all-atom molecular mechanics, dynamics, docking and electrostatic calculations, and the initial state of the hydrogen bond network and ionization state of titratable groups can have a dramatic effect on simulations results. Unfortunately, most macromolecular crystal structures contain little or no hydrogen coordinate data due to limited resolution or disorder in the crystal.

Scientists that attempt to make use crystal structure data of macromolecules for detailed simulations must spend a great deal of effort to prepare the initial structure. Since the hydrogen data is missing in PDB files most software programs assign default protonation states to the amino acid, or nucleic acid residues as well as counter ions and other solvent. Such assignments, at best, take only local structural details into account; e.g., ensuring that a protonated nitrogen in the histidine sidechain does not point at a ligated metal). Starting with such a default structure (leaving aside the problem of missing atoms and disorder) the protonation uncertainties must be dealt with; commonly, one must determine

  1. the rotamers of -SH -OH -CH3 and -NH3 groups in CYS, SER, TYR, THR, MET, LYS, etc.;
  2. the ionization states of acids and bases in ARG, ASP, GLU, LYS, HIS, etc.;
  3. the tautomers of imidazoles (HIS) and carboxylic acids (ASP,GLU);
  4. the protonation state of metal ligand atoms in CYS, HIS, ASP, GLU, etc.;
  5. the ionization state of metals.

The addition of hydrogen atoms to a macromolecule is a non-trivial task. In many cases, unambiguous assignments can be made (when backbone atoms are involved) but the complexity of many hydrogen bond networks and ionic interaction networks often makes protonation state determination very difficult. Compounding the problem is the unfortunate fact that even the heavy atoms of some chemical groups have uncertain identities; for example, terminal amides in GLN and ASN and even the element identities of the imidazole ring in HIS are often in question.

Consequently, one must add to the above list the determination of such element identities. This is commonly referred to as flipping terminal groups: the terminal amide groups in GLN, ASN and HIS can be left as read from the PDB file (black) or "flipped" (blue). Possible mis-assignments of element identities must also be considered in ligands and additional groups must be examined (such as terminal sulfonamides -SO2NH2).

The protonation state problem exists not only with low resolution X-ray structures, but also with high resolution structures. Hydrogen coordinates are not always given for all atoms, and in some cases the protonation assignment is questionable. For example, in the PDB entry for a photoactive yellow protein (3PYP, 0.82 Å) one sees that the deposited coordinates have a questionable proton assignment: the phenol oxygen is deprotonated and the nearby carboxylate is neutral and has an unusual conformation (see figure to the right).

In other high resolution structures, one can see -CO2 groups near ligands with no deposited hydrogen coordinates. In the α-lytic protease structure (2H5C, 0.82 Å) such a -CO2 group is adjacent to a glycerol molecule that has no hydrogen atoms. In such a case, one cannot be certain that the -CO2 is negatively charged, or neutral but with missing hydrogen coordinates.

In general, the presence of a hydrogen atom in a PDB entry is clearly a statement on the part of a crystallographer that a hydrogen was visible; however, the absence of a hydrogen atom does not necessarily mean that a hydrogen is definitely not there, merely that nothing was "visible". Even if hydrogen coordinates are given for high resolution structures, artifacts and phase errors of the electron density can lead to questionable hydrogen coordinate assignments.

Computational attempts to deal with the macromolecular protonation state assignment problem largely divide into two broad categories:

  1. Geometric Methods attempt to place protons often based upon local hydrogen bonding environments or based upon optimization of hydrogen bond networks. Crystallographic software often includes such procedures (e.g., WHATIF)[Vriend 1990].

  2. Electrostatic Methods attempt to place protons based upon electrostatic field considerations and often attempt the calculation of pKa shifts.

Geometric methods have the appealing feature that many proton assignments can be made unambiguously from local hydrogen bonding environments - sophisticated electrostatic treatment and dependence on partial charge models and implicit solvent models is avoided. The Reduce program [Word 1999] attempts to determine the hydrogen coordinates using steric considerations and geometric hydrogen bond network analysis; ionization and flipped states of HIS, GLU and ASP are assigned on geometric grounds alone and rotamers are assigned from a fixed discrete collection. In many cases, this program is effective; however, since longer range electrostatic effects are not taken into account, Reduce can fail to make some clear assignments and simply cannot properly assess complex ionic environments.

The electrostatic methods have appeal because of the more realistic treatment of the underlying physics and thermodynamics. Computational methods for calculating pKa values of residues often require sophisticated electrostatic treatment using multiple Poisson-Boltzmann calculations [Bashford 1992] followed by a search of the discrete ionization states for the lowest free energy state [Gilson 1993]. Often, these programs only assign the charge state and not the precise proton geometry. In all-atom electrostatic methods, the protonation state of the non-titratable groups is often taken to be some fixed default value, or assigned iteratively taking into account the results of the titration calculation.

In all-atom methods, the protonation geometry of the non-titratable groups depends on the ionization state of the titratable groups and vice versa. Hence, the two problems must be solved simultaneously. Were it not for the ionization state assignment (which changes the number of particles in the system), forcefield methods, such as energy minimization or molecular dynamics, could be used to determine flipped states and rotamers. Unfortunately, the large number of local minima requires good initial estimates of the hydrogen coordinates in order to properly search the conformational space. Constant pH simulations (molecular dynamics or Monte Carlo) are possible, but these methods require enormous computing time and resources to properly converge.

The protonation assignment problem is inherently discrete; that is, it is fundamentally a combinatorial search over a discrete set of states. Certainly, the ionization state and tautomeric state can easily be thought of as discrete. The rotamer problem can be made discrete by considering only a fixed collection of rotamers (e.g., -OH dihedrals sampled every 30 degrees). Thus, the rotamer, tautomer and ionization state calculation can be put into a single context based upon discrete states. A particular protonation state of a residue (or chemical group) consists of the 3D coordinates of all of its hydrogens - tautomer and ionization states as well as a rotamer state. For the amino acids, a reasonable collection of protonation states is depicted below:

Here, all polar hydrogens are considered titratable, and terminal hydroxyls and thiols are given discrete rotameric states (the number of which may depend on hybridization or conjugation). Histidine has multiple tautomers as well as "flipped" states, asparagine and glutamine are given "flipped" states. The remaining amino acid sidechains and the backbone can reasonably be assumed to exist in only one state with reliably predictable hydrogen geometry (e.g., staggered for terminal methyl in valine or isoleucine).

The foregoing discrete formulation of the protonation state assignment problem is as follows: given the 3D coordinates of the heavy atoms of a macromolecule, select a single protonation state (from the available states) for each chemical group that is somehow "best". The definition of "best" can be geometric or electrostatic depending on the particular methodology and a complete method must specify the definition of "best" as well as an algorithm for performing the combinatorial search over the discrete state space.

In this document, we present a method - Protonate 3D - that solves the discrete protonation state assignment problem. The method has been implemented and is an application in the Molecular Operating Environment in the 2007 release. In the following sections of this document, we present the underlying theory and algorithms of the method as well as some results when applied to PDB crystal structures. We summarize in the final section.

Methodology

Protonate 3D solves the macromolecular protonation state assignment problem by selecting a protonation state for each chemical group that minimizes the total free energy of the system (taking titration into account). The electrostatic interactions are approximated using the Generalized Born / Volume Integral methodology [Labute 2007] with a 15 Å cutoff. The discrete state search is performed using an algorithm that solves the Unary Quadratic Optimization problem. We now present the thermodynamic theory and algorithmic methodology that lies at the heart of the Protonate 3D application.

The Protonate 3D methodology for protonation state assignment proceeds as follows

  1. System Partition - The atoms of the system are partitioned into separate chemical groups according to the patterns in a rule file. Each chemical group will be given one or more topological states that include tautomer states and ionization states. Each such group will have associated with it a pKa and a strain energy used to penalize particular tautomeric states. Each protonation state for each chemical group will subjected to conformation generation to generate a collection of rotamers.

  2. Self Energy Calculation - The pKa values and strain energies along with interactions to fixed (single state) chemical groups will be calculated and stored in a vector, u.

  3. Interaction Matrix Calculation - The interaction energies between each pair of 3D protonation states (corresponding to different chemical groups) is calculated and stored in a matrix, U.

  4. Dead End Elimination - A provably correct criterion is applied in order to eliminate 3D protonation states that cannot appear in an optimal solution. This reduces the complexity of the optimization procedure in subsequent steps.

  5. System Optimization - A search for the particular configuration of protonation states of the chemical groups that minimizes the quadratic energy function E(x) = xT U x / 2 + uTx is performed. In this function x is a binary vector that encodes the particular configuration of selected protonation states (see below).

The discrete formulation of the protonation problem is very similar to the sidechain placement and protein design problems with the protonation states playing the role of the rotamer library popular in homology modeling [Bower 1997]. Consequently, the methods used to solve these problems can be applied to the protonation state problem [Looger 2001] [Desmet 2002] [Canutescu 2003]. In the sidechain placement methods, each residue state (rotamer) is assigned so that a pair-wise interaction function is optimized. Typically, a short range steric function is used, such as the SCWRL function [Bower 1997]. Unfortunately, such functions are not accurate enough for titration calculations since longer range electrostatic interactions, solvation effects and titration free energies are not taken into account. Once longer range effects are taken into account, the performance of algorithms used in sidechain placement deteriorate - these algorithms rely on very sparse pair-wise interactions. Nevertheless, the formalism is applicable to the protonation state assignment problem provided that the interaction function is suitable and that the search algorithm is capable of handling the more numerous longer range interactions common to electrostatics calculations.

The partition of the system proceeds by (implicitly) cutting bonds connecting sp3 carbons followed by the application of pattern matching of patterns specified in a rule file. The results of the partition are a collection of non-intersecting atom sets, each specifying a single chemical group. Each such atom set will have an associated collection of one or more ionization states, tautomeric strain energies, pKa values and 3D geometries (conformers). The groups with exactly one state are assigned that single state and collected into a single set of atoms P. Thus, the original system is divided into a set of atoms P with a fixed protonation state, and one or more chemical groups {A, B, C, ...} each of which has two or more protonation states (including 3D geometry).

A binary vector x is used to encode a particular selection of protonation states of {A, B, C, ...} as follows. The bits of x are arranged in blocks, one for each group with each block containing one bit for each particular configuration of a particular chemical group. For example, if A has 4 protonation states, B has 2 states and C has 3 states then the vector

x = [ 0 1 0 0 | 1 0 | 0 0 1 | ... ]

specifies the configuration of state 2 for A, state 1 for B and state 3 for C. In this representation, a value of 1 in the x vector selects a particular state and 0 de-selects a particular state. Admissible values of the x are those in which there is exactly one 1 bit in each block of bits that correspond to the states of a particular chemical group. This constraint on the values of x is called a unary constraint since the individual states of the chemical groups are encoded in base 1 or unary notation.

Suppose that the interaction matrix U and self energy vector u have been calculated as described above in the Self Energy and Interaction Matrix steps of the procedure. (We will describe the details of this matrix and vector below.) The optimization required in the System Optimization step of the procedure is an instance of Binary Quadratic Programming; the particular instance is called the Unary Quadratic Optimization (UQO) problem, which is to optimize a multi-dimensional quadratic function defined over binary vectors subject to the unary constraint (that of selecting exactly 1 alternative in each block of bits). More precisely, the UQO problem is

Here, the Ax = b condition enforces the unary constraint and the x in {0,1}n enforces that x must be an n-dimensional binary vector (n is the total number of protonation states of A, B, C, ... Protonate 3D uses the opt_UQO function in MOE to solve the UQO problem thereby determining the minimum energy protonation state of the system. The opt_UQO performs a very efficient recursive search through all of the binary vectors x satisfying the unary constraint to locate the vector x that minimizes the quadratic energy function E. For protein-sized problems, the search can be typically conducted in under one minute and often only a few seconds.

Prior to the recursive state search, an iterative procedure called Dead End Elimination is applied in order to reduce the complexity of the system. The Goldstein criterion [Goldstein 1994] is a condition that can decide if a particular protonation state cannot possibly appear in the optimal solution. Consider a particular chemical group A with two particular protonation states r and s; if the Goldstein criterion

holds then protonation state r cannot possibly be within cutoff energy units above the optimal solution. In the equation, ur and us denote the self energies of r and s respectively (elements of the u vector) and Uij denotes the (i,j) entry of the interaction matrix, U. The sum in the Goldstein criterion extends over all other chemical groups, B, different from A. The Protonate 3D application uses a cutoff of 0. In the Dead End Elimination step of the procedure, the Goldstein criterion is applied repeatedly to all pairs of protonation states for all chemical groups until no eliminations are detected. The Dead End Elimination step typically reduces the complexity of the optimization problem dramatically and rapidly eliminates protonation states that are obviously too high in energy (e.g., negatively charged tryptophan). Configuration spaces with 10200 or so states are often reduced to 1010 - hundreds of orders of magnitude.

It remains to describe the details of the interaction matrix U and self energy vector u which define the energy function that is optimized in the Protonate 3D calculation. Fundamentally, the energy function is a free energy function - the number of particles in a titration calculation changes and consequently, potential energy values of the different configurations cannot be compared. The quadratic energy function consists of the following terms:

  1. A van der Waals interaction energy;
  2. An electrostatic interaction energy;
  3. An implicit solvent interaction energy;
  4. A tautomeric strain energy;
  5. A rotamer strain energy;
  6. A titration free energy.

Each of these terms contributes (in some way) to the self energy vector, u, or the interaction matrix, U. The tautomeric and rotamer strain energies are inherent to each chemical group and contribute to the vector, u. The tautomeric strain energy is taken from a rule file which associates relative tautomer energies with the tautomers of each chemical group. The rotamer strain energy is calculated when the conformations of each chemical group are generated and is consistent with modern forcefields. [Halgren 1996].

The van der Waals interactions play a relatively small role in the Protonate 3D calculation; mostly they are used to distinguish flipped states of terminal imidazoles and terminal amides, but sometimes they may help distinguish correct protonation geometry [Word 1999]. The van der Waals interaction energies contribute both to the u vector and U matrix. For each protonation state of a chemical group the van der Waals interaction energy between the state and the fixed part of the protein P is added to the u vector. For each pair for protonation states of different chemical groups, the van der Waals interaction energy is added to the appropriate element of the U matrix. Protonate 3D uses an approximation to the Lennard-Jones 12-6 potential energy function that mimics the repulsive potential and not the attractive potential (which is more appropriate in implicit solvent model conditions). The van der Waals radii and well-depth parameters are those of the Engh-Huber forcefield [Engh 1991] commonly used in crystallographic refinement.

The electrostatic energy terms are Coulombic in nature and make similar contributions as the van der Waals interactions. The electrostatic interaction energies contribute both to the u vector and U matrix. For each protonation state of a chemical group the electrostatic interaction energy between the state and the fixed part of the protein P is added to the u vector. For each pair for protonation states of different chemical groups, the electrostatic interaction energy is added to the appropriate element of the U matrix. The electrostatic functional form is configurable, and may be Coulomb's law, a shifted-force Coulomb's law or a distance-dependent dielectric form of Coulomb's law. For implicit solvent interaction energies, the electrostatic energy used is always Coulomb's law. Partial charges are those of the MMFF94 [Halgren 1996] forcefield (so that ligands can be handled).

The implicit solvent interaction energy and the titration free energy form the basis of the titration calculation. Together with the pKa values of the chemical groups and an input pH, free energies of titrations are approximated with the following methodology. The fundamental implicit solvent model that is used by Protonate 3D is the Generalized Born / Volume Integral formalism [Labute 2007] with an additional salt term:

The GB/VI solvation free energy estimate consists of two parts, the "self", or VI, part which calculates self energies of atoms and the interaction, or GB, part, which estimates polarization interaction energies between atoms. The inputs are fixed parameters (e.g., the {Ri} and {γi}) and the partial charges {qi} of the atoms and the salt concentration (from which κ is derived).

Consider a titratable group AH in a protein environment P. In order to estimate the free energy of the reaction PAH deprotonating to PA- + H+ we introduce the thermodynamic cycle

In this cycle, the charges within the fixed protein P are removed (thermodynamically) and reintroduced along the vertical directions by using specific interaction terms of the electrostatic and GB/VI energy models. The symbol EXY denotes the interaction energy between two sets of atoms X and Y. The blue ΔG values on the horizontal paths denote unknown quantities. The top value is the required free energy and the bottom horizontal value arises from the pKa shift due to the protein cavity (without charges). This bottom ΔG value can be estimated with another thermodynamic cycle

In this cycle, the protein cavity is removed and reintroduced along the vertical directions. The vertical free energies are estimated, again, from the GB/VI model and correspond to GB/VI calculations with different Born factors (inversely proportional to the Born radii). Thus, the previously unknown ΔG value (on top) is estimated with the vertical free energy estimates and an experimental pKa value derived from the rule file and the pH.

For polyprotic species (such as histidine) the above considerations generalize to the following thermodynamic diagram.

in which the top horizontal ΔG values are the required titration free energies of a titratable group A in situ in a protein environment P. The bottom horizontal ΔG values are free energy differences derived from the pKa values and the pH (as above). The vertical ΔG values are those estimated from the GB/VI model (as in the previous thermodynamic diagrams). The blue G values are the free energies of the protonation states of the chemical group A and have the property that their differences are equal to the top horizontal ΔG values for the titration reactions; these values will be added to the corresponding elements of the self energy vector u required for the UQO formulation of the problem.

The interaction matrix, U is populated with the GB interaction energies between the various chemical group protonation states in a straightforward way. Collecting all of the electrostatic, implicit solvent and titration free energy values together, we arrive at the final UQO energy function formulation

These values, together with the van der Waals contributions, the tautomeric and rotamer strain energies form the complete free energy function E required to compare different protonation state configurations of the entire collection of chemical groups. This function E is optimized with the opt_UQO function to produce optimal protonation state.

Results and Discussion

In this section we present some results of the Protonate 3D methodology to certain PDB crystal structures.

The PDB entry 2H5C (α-lytic protease) is a 0.82 Å crystal structure with hydrogen atoms fit to the electron density. The single protein chain has 198 residues and there are 2 glycerol molecules and 11 SO4 ions. The System Partition step produced 502 individual protonation states leading to a U matrix of dimensions 502 by 502. Prior to the Dead End Elimination step there were 10**61.8 system states and after the Dead End Elimination step there were 10**6.1 states. The Protonate 3D application required 17 seconds total run-time on a 2 GHz Intel computer with 2 seconds spent in the UQO search. The output of Protonate 3D was compared to the crystal structure.

The figure to the right shows the results of the comparison. Residues without Protonate 3D protons that were in agreement with the crystal structure are shown in green; disagreements are in red. Agreement was designated if the ionization states were equal, the tautomer and/or flip state was in agreement and the hydrogen rotamer was within 60 degrees.

85% of all residues had their hydrogen rotamers within 15 degrees of the crystal structure and 90% were within 60 degrees. All of the disagreements were on the surface. Of the residues showing disagreement, 10 were deposited without hydrogens - 7 serines, 2 threonines and 1 leucine. There were two terminal amide disagreements, ASN60 and GLN223, both of which were on the surface and had very little contact with the rest of the protein.

Two interacting methionine residues showed more than 60 degrees difference between the prediction and the crystal structure (depicted below). The terminal methyls were allow free rotation (no rotamer strain energy was used and as a result they adopted eclipsed-like conformations. Perhaps the addition of a rotation penalty (to model the rotation barrier) would have resulted in staggered conformations. In any event, this disagreement is quite minor; indeed, almost insignificant.

The figure to the right of the interacting methionine residues is a close-up of GLU174 (mentioned in the introduction of this document). The terminal carboxylic acid is adjacent to a glycerol molecule and neither the carboxylic acid nor the glycerol showed hydrogen coordinates in the PDB entry. Protonate 3D assigned a neutral state to GLU174. While this is a formal disagreement we do not deem it serious.

The PDB entry 3PYP (photoactive yellow protein) is a 0.82 Å crystal structure with hydrogen atoms fit to the electron density. The single protein chain has 125 residues with a covalent ligand. The System Partition step produced 415 individual protonation states leading to a U matrix of dimensions 415 by 415. Prior to the Dead End Elimination step there were 10**46.1 system states and after the Dead End Elimination step there were 10**4.1 states. The Protonate 3D application required 5.2 seconds total run-time on a 2 GHz Intel computer with 1.6 seconds spent in the UQO search. The output of Protonate 3D was compared to the crystal structure.

The figure to the right shows the results of the comparison. Residues without Protonate 3D protons that were in agreement with the crystal structure are shown in green; disagreements are in red. Agreement was designated if the ionization states were equal, the tautomer and/or flip state was in agreement and the hydrogen rotamer was within 60 degrees.

The four active site residues showing disagreement were referred to in the introduction of this document. The deposited coordinates showed a deprotonated phenol in close proximity to a protonated GLU46 (see the leftmost figure below). Moreover, the conformation of the GLU46 is unusual with the hydrogen in a kind of trans conformation to the carbonyl oxygen. The nearby THR50 and TYR42 are donating hydrogen bonds to the (anionic?) phenol oxygen. The deposited protonation state is largely questionable because of the relative pKa difference between phenol and carboxylic acid; one would expect that given the close proximity, the carboxylic acid of GLU46 would be deprotonated and the phenol of the covalent ligand be protonated yet this is not the case in the crystal structure.

The rightmost figure below depicts the same residues with the protonation state assigned by the Protonate 3D procedure.

 

Protonate 3D protonated the phenol of the covalent ligand and deprotonated the carboxylic acid of GLU46. The nearby THR50 and TYR42 are able to form favorable polar interactions with the THR50 now donating its hydrogen to the GLU46.

The PDB entry 1YK4 (electron transport rubredoxin 24L/R5S) is a 0.69 Å crystal structure with hydrogen atoms stated to be "visible" in the PDB file header. The single protein chain has 53 residues and one iron atom. The System Partition step produced 189 individual protonation states leading to a U matrix of dimensions 189 by 189. Prior to the Dead End Elimination step there were 10**22 system states and after the Dead End Elimination step there were 10**0.1 states. The Protonate 3D application required 1.8 seconds total run-time on a 2 GHz Intel computer with 0.8 seconds spent in the UQO search. The output of Protonate 3D was compared to the crystal structure.

The figure to the right shows the results of the comparison. Residues without Protonate 3D protons that were in agreement with the crystal structure are shown in green; disagreements are in red. Agreement was designated if the ionization states were equal, the tautomer and/or flip state was in agreement and the hydrogen rotamer was within 60 degrees.

85% of the residues had hydrogen rotamers within 10 degrees of the crystal structure and 91% had hydrogen rotamers with 20 degrees of the crystal structure. Three residues with 60 degree differences were protonated lysines. All disagreements were on the surface. Only one residue showed more than a 60 degree rotamer disagreement, a serine on the surface.

The 1YK4 structure has an iron surrounded by four CYS sulfurs. In the, Protonate 3D procedure, the iron was allowed to adopt one of three ionization states: +1, +2 or +3 without any redox penalty; in other words, the remainder of the system determined the ionization state of the iron. The figure on the right shows the output of the Protonate 3D procedure at the iron center. The four CYS sulfurs are assigned anionic states and the iron is assigned a +2 state, giving an overall -2 charge for the environment. This assignment is quite reasonable, although one must keep in mind that only a simplistic treatment of metal ligation was conducted (entirely consisting of Coulombic and implicit solvent effects).

Generally, transition metals are treated in Protonate 3D in a disconnected ionic manner. For example, zinc atoms are disconnected from their (possibly) ligated atoms and their ionization states are selected from a fixed collection. The possible ligated atoms are titrated in the usual manner. For this reason, we allow histidine to adopt a negative charge state; this allows for possible metal ligation of the otherwise neutral histidine. For the most part, this (simplistic) metal treatment produces reasonable results which are good starting points for further analysis, possibly with a higher level of theory.

Summary

We have presented a method - Protonate 3D - for adding protons to macromolecules. Tautomerism, titration, metal ligation, steric and (implicit solvent) electrostatic interactions are addressed in a thermodynamically sound manner. The combinatorial optimization is conducted with an algorithm that solves the Unary Quadratic Optimization problem.

The method shows good agreement with (very) high resolution crystal structures subject to some key limitations. Metal centers are handled by overly-simple method (Coulombic). The method is sensitive (at times) to crystallographic coordinates. Borderline titration cases may be unreliable due to the static Generalized Born formalism in which calculation is conducted.

Protonate 3D has been implemented in the SVL programming language and is available as part of the Molecular Operating Environment (2007 version).

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