Leveraging computational tools to combat malaria: assessment and development of new therapeutics.

As the world grapples with the relentless challenges posed by diseases like malaria, the advent of sophisticated computational tools has emerged as a beacon of hope in the quest for effective treatments. In this study we delve into the strategies behind computational tools encompassing virtual screening, molecular docking, artificial intelligence (AI), and machine learning (ML). We assess their effectiveness and contribution to the progress of malaria treatment. The convergence of these computational strategies, coupled with the ever-increasing power of computing systems, has ushered in a new era of drug discovery, holding immense promise for the eradication of malaria. SCIENTIFIC CONTRIBUTION: Computational tools remain pivotal in drug design and development. They provide a platform for researchers to explore various treatment options and save both time and money in the drug development pipeline. It is imperative to assess computational techniques and monitor their effectiveness in disease control. In this study we examine renown computational tools that have been employed in the battle against malaria, the benefits and challenges these tools have presented, and the potential they hold in the future eradication of the disease.

Molecular docking, molecular dynamics simulations and binding free energy studies of interactions between Mycobacterium tuberculosis Pks13, PknG and bioactive constituents of extremophilic bacteria.

Mycobacterial pathogens present a significant challenge to disease control efforts globally due to their inherent resistance to multiple antibiotics. The rise of drug-resistant strains of Mycobacterium tuberculosis has prompted an urgent need for innovative therapeutic solutions. One promising way to discover new tuberculosis drugs is by utilizing natural products from the vast biochemical space. Multidisciplinary methods can used to harness the bioactivity of these natural products. This study aimed to evaluate the antimycobacterial efficacy of functional crude extracts from bacteria isolated from gold mine tailings in South Africa. Bacterial strains were identified using 16S rRNA sequencing. The crude extracts obtained from the bacteria were tested against Mycobacterium tuberculosis H37Rv, Mycobacterium smegmatis mc2155, and Mycobacterium aurum A+. Untargeted HPLC-qTOF and molecular networking were used to identify the functional constituents present in extracts that exhibited inhibitory activity. A virtual screening workflow (VSW) was used to filter compounds that were strong binders to Mycobacterium tuberculosis Pks13 and PknG. The ligands returned from the VSW were subjected to optimization using density functional theory (DFT) at M06-2X/6-311++ (d,p) level of theory and basis set implemented in Gaussian16 Rev.C01. The optimized ligands were re-docked against Mycobacterium tuberculosis Pks13 and PknG. Molecular dynamics simulation and molecular mechanics generalized born surface area were used to evaluate the stability of the protein-ligand complexes formed by the identified hits. The hit that showed promising binding characteristics was virtually modified through multiple synthetic routes using reaction-driven enumeration. Three bacterial isolates showed significant activity against the two strains of Mycobacterium, while only two, Bacillus subtilis and Bacillus licheniformis, exhibited activity against both Mycobacterium tuberculosis H37Rv, Mycobacterium smegmatis mc2155, and Mycobacterium aurum A+. The tentatively identified compounds from the bacterial crude extracts belonged to various classes of natural compounds associated with antimicrobial activity. Two compounds, cyclo-(L-Pro-4-OH-L-Leu) and vazabitide A, showed strong binding against PknG and Pks13, with pre-MD MM-GBSA values of - 42.8 kcal/mol and - 47.6 kcal/mol, respectively. The DFT-optimized compounds exhibited the same docking scores as the ligands optimized using the OPSL-4 force field. After modifying vazabitide A, its affinity to the Pks13 binding site increased to - 85.8 kcal/mol, as revealed by the post-MD MM-GBSA analysis. This study highlights the potential of bacteria isolates from gold mine tailings as a source of new scaffolds for designing and optimizing anti-Mycobacterium agents. These agents synthesized in-silico can be further tested in-vitro to evaluate their efficacy.

In-silico and in-vitro assessments of some fabaceae, rhamnaceae, apocynaceae, and anacardiaceae species against Mycobacterium tuberculosis H37Rv and triple-negative breast cancer cells.

Medicinal plants play a huge role in the treatment of various diseases in the Limpopo province (South Africa). Traditionally, concoctions used for treating tuberculosis and cancer are sometimes prepared from plant parts naturally occurring in the region, these include (but not limited to) Schotia brachypetala, Rauvolfia caffra, Schinus molle, Ziziphus mucronate, and Senna petersiana. In this study, the aim was to evaluate the potential antimycobacterial activity of the five medicinal plants against Mycobacterium smegmatis mc2155, Mycobacterium aurum A + , and Mycobacterium tuberculosis H37Rv, and cytotoxic activity against MDA-MB 231 triple-negative breast cancer cells. Phytochemical constituents present in R. caffra and S. molle were tentatively identified by LC-QTOF-MS/MS as these extracts showed antimycobacterial and cytotoxic activity. A rigorous Virtual Screening Workflow (VSW) of the tentatively identified phytocompounds was then employed to identify potential inhibitor/s of M. tuberculosis pantothenate kinase (PanK). Molecular dynamics simulations and post-MM-GBSA free energy calculations were used to determine the potential mode of action and selectivity of selected phytocompounds. The results showed that plant crude extracts generally exhibited poor antimycobacterial activity, except for R. caffra and S. molle which exhibited average efficacy against M. tuberculosis H37Rv with minimum inhibitory concentrations between 0.25-0.125 mg/mL. Only one compound with a favourable ADME profile, namely, norajmaline was returned from the VSW. Norajmaline exhibited a docking score of -7.47 kcal/mol, while, pre-MM-GBSA calculation revealed binding free energy to be -37.64 kcal/mol. All plant extracts exhibited a 50% inhibitory concentration (IC50) of < 30 µg/mL against MDA-MB 231 cells. Flow cytometry analysis of treated MDA-MB 231 cells showed that the dichloromethane extracts from S. petersiana, Z. mucronate, and ethyl acetate extracts from R. caffra and S. molle induced higher levels of apoptosis than cisplatin. It was concluded that norajmaline could emerge as a potential antimycobacterial lead compound. Validation of the antimycobacterial activity of norajmaline will need to be performed in vitro and in vivo before chemical modifications to enhance potency and efficacy are done. S. petersiana, Z. mucronate, R.caffra and S. molle possess strong potential as key contributors in developing new and effective treatments for triple-negative breast cancer in light of the urgent requirement for innovative therapeutic solutions.

A colorimetric chemosensor for distinct color change with (E)-2-(1-(3-aminophenyl)ethylideneamino)benzenethiol to detect Cu2+ in real water samples.

The study reports the synthesis of chemosensor (E)-2-(1-(3-aminophenyl)ethylideneamino)benzenethiol (C1), a highly sensitive, colorimetric metal probe that shows distinct selectivity for the detection of Cu2+ ion in various real water samples. Upon complexation with Cu2+ in CH3OH/H2O (60:40 v/v) (aqueous methanol), the C1 demonstrate significant enhancement in the absorption at 250 nm and 300 nm with a color change from light yellow to brown which was visualized using naked-eye. Therefore, these properties make C1 as an effective candidate for on-site Cu2+ ions detection. The emission spectrum of C1 illustrated "TURN-ON" recognition of Cu2+ with a limit of detection (LOD) of 46 nM. Furthermore, Density Functional Theory (DFT) calculations were performed to better understand the interactions between C1 and Cu2+. The obtained results suggested that the electron clouds present around the -NH2 in nitrogen and sulfur in -SH play a pivotal role in the formation of a stable complex. The computational results were in good agreement with the experimental UV-visible spectrometry results.

Molecular Dynamics Study on Selected Bioactive Phytochemicals as Potential Inhibitors of HIV-1 Subtype C Protease.

Acquired immunodeficiency syndrome (AIDS), one of the deadliest global diseases, is caused by the Human Immunodeficiency Virus (HIV). To date, there are no known conventional drugs that can cure HIV/AIDS, and this has prompted continuous scientific efforts in the search for novel and potent anti-HIV therapies. In this study, molecular dynamics simulation (MDS) and computational techniques were employed to investigate the inhibitory potential of bioactive compounds from selected South African indigenous plants against HIV-1 subtype C protease (HIVpro). Of the eight compounds (CMG, MA, UA, CA, BA, UAA, OAA and OA) evaluated, only six (CMG (-9.9 kcal/mol), MA (-9.3 kcal/mol), CA (-9.0 kcal/mol), BA (-8.3 kcal/mol), UAA (-8.5 kcal/mol), and OA (-8.6 kcal/mol)) showed favourable activities against HIVpro and binding landscapes like the reference FDA-approved drugs, Lopinavir (LPV) and Darunavir (DRV), with CMG and MA having the highest binding affinities. Using the structural analysis (root-mean-square deviation (RMSD), fluctuation (RMSF), and radius of gyration (RoG) of the bound complexes with HIVpro after 350 ns, structural evidence was observed, indicating that the six compounds are potential lead candidates for inhibiting HIVpro. This finding was further corroborated by the structural analysis of the enzyme-ligand complexe systems, where structural mechanisms of stability, flexibility, and compactness of the study metabolites were established following binding with HIVpro. Furthermore, the ligand interaction plots revealed that the metabolites interacted hydrophobically with the active site amino residues, with identification of other key residues implicated in HIVpro inhibition for drug design. Overall, this is the first computational report on the anti-HIV-1 activities of CMG and MA, with efforts on their in vitro and in vivo evaluations underway. Judging by the binding affinity, the degree of stability, and compactness of the lead metabolites (CMG, MA, CA, BA, OA, and UAA), they could be concomitantly explored with conventional HIVpro inhibitors in enhancing their therapeutic activities against the HIV-1 serotype.

Exploring the bioactivity of pentacyclic triterpenoids as potential antimycobacterial nutraceutics: Insights through comparative biomolecular modelling.

A group of bioactive compounds known as triterpenoids, which are often found in plant materials, have been tested to possess nutritional and pharmaceutical activity. These plant components are referred to as nutraceuticals, and are used as therapeutic agents. In this study, we explore the interactions of betulinic acid (BA), oleanolic acid (OA), ursolic acid (UA), and maslinic acid (MA) against FadA5. Studies have identified FadA5, a trifunctional enzyme-like thiolase, as a target towards Mycobacterium tuberculosis inhibition. The investigation involves molecular dynamics (MD) and hybrid quantum mechanics/molecular mechanics (QM/MM) applications. Analyses of the four pentacyclic triterpenoids binding to FadA5 showed appreciable bioactivity against FadA5. The application of two or more theoretical models to unravel ligand-enzyme binding energies can pave the way for accurate binding affinity prediction and validation.

Computational development and validation of a representative MDI-BDO-based polyurethane hard segment model.

Segmented polyurethanes show extraordinary physicochemical properties, mainly owing to the nature and the chemistry of the hard segment domains. There are yet many inexplicable physiochemical properties of MDI-BDO-based hard polyurethane segments such as the geometry, cis-trans isomerism, electronic structure, chemical reactivity, the inter-hard-segment interactions, and the photo-response. In the present study, it was attempted to develop and validate a model system that would facilitate further research on the structural and chemical properties of the MDI-BDO hard segments. It was found that the trans isomer of urethane bond is more stable than the cis isomer, and it is argued here that thermal transformation from trans to cis not possible due to the high rotational energy barrier. The differences between the calculated IR spectra of the cis and trans isomers are proposed as a powerful differentiation tool. The calculated Fukui indices show that cis and trans isomers are different in their chemical reactivity. The findings of the present study suggest intermolecular and intramolecular pi-stacking and highly plausible two significant types of hydrogen bond types between hard segments. In the present study, a model system for MDI-BDO hard segment was developed and successfully validated via computational experiments. Further calculations done with the new model provided an indispensable understanding of the structure, cis-trans isomerism, reactivity, and intermolecular interactions of the MDI-BDO hard segments. The proposed model can be further improved in the future by incorporating suitable soft segments. In summary, the model system developed and validated in the present study has provided new opportunities to understand and further study the structural and chemical features of the hard segments of the MDI-BDO-based polyurethane.

Ligand-based pharmacophore modelling and virtual screening for the identification of amyloid-beta diagnostic molecules.

Currently, only three molecules, flutemetamol, florbetaben and florbetapir, have been approved for clinical use towards the definitive diagnosis of Alzheimer's disease (AD). Despite the clinically approved drugs' advantages, there still exists a need for new diagnostic molecules with improved properties (physicochemical and pharmacokinetic) in comparison to the current molecules in clinical use and research. In this work, we report a pharmacophore model and a quantitative structure activity relationship (QSAR) model, constructed from a series of 166 amyloid beta diagnostic compounds (targeting Alzheimer's disease) with the purpose of identifying functional groups influencing and predicting bioactivity. Subsequently, pharmacophore based virtual screening and QSAR predictions were used to identify new amyloid beta diagnostic molecules. In addition, docking and molecular dynamics simulations were conducted to explore the type and nature of interactions required for ligands to bind effectively in the binding regions of amyloid beta fibrils (PDB 2MXU). In our findings, the highest-ranked 4 feature pharmacophore model possessed one hydrogen bond acceptor, one hydrophobic feature and two ring features (AHRR). Systematically, the same dataset of molecules used for pharmacophore modelling was used to generate an atom-based 3D QSAR hypothesis to illustrate the activity relationship of amyloid-beta diagnostic molecules. The partial least squares (PLS) 3D QSAR model obtained showed good correlation as indicated by respective statistical parameters, R^2, Q^2 and Pearson values of 0.76, 0.72 and 0.86 respectively. Virtual screening against ZINC15 database and the ChemBridge CNS-Set yielded 7 molecules, 4 of which had satisfactory ADME properties. Docking and molecular dynamics simulations showed that hydrogen bonding, hydrophobic and π-π interactions are crucial towards the binding of ligands (as predicted by our pharmacophore and QSAR models) to amyloid beta fibrils. In conclusion, the findings of this work present a wealth of information that can be useful in future research towards identifying and design of new amyloid diagnostic molecules. The pharmacophore presented here can be used to filter independent databases to identify new structurally related molecules with improved activity whereas the QSAR model can be useful in predicting bioactivities of the predicted hits.

Computational investigation of the binding characteristics of ß-amyloid fibrils.

Timely and accurate diagnosis of Alzheimer's disease (AD) remains a major challenge in the medical arena. ß-amyloid (Aß) imaging techniques such as positron emission tomography and single photon emission computed tomography require the use of an imaging probe. To date, only flutemetamol, florbetaben and florbetapir have been approved for clinical use as imaging probes. Design of imaging probes requires a detailed understanding of disease mechanism(s) and receptor-ligand interaction. In this study, molecular docking, molecular dynamics and binding free energies were used to investigate the multiple binding sites exhibited by ß-amyloid fibrils. Protein atomic models 2BEG, 5KK3, 2M4J, 2LMN, 5OQV, 2NAO, 2MVX and 2MXU (protein databank codes) were used to investigate the nature and location of binding sites and binding profiles of selected molecules with known affinities. Although amyloid fibrils are known to have multiple binding sites, we demonstrated that model 2MXU possesses one site which is druggable and can bind with common scaffolds currently being used in the imaging of amyloid fibrils. Models 2NAO, 5KK3 and 2M4J revealed that even though multiple sites may be available in some fibrils, the entire protein may not have a druggable site. Molecular dynamics revealed atomic models 2MXU and 2MVX to be the least flexible among the list. The outcomes of this investigation can be translated to assist in designing novel molecules that can be used for brain imaging in Alzheimer's disease.

The effects of two-dimensional TiSe2 on the thermoelectric, electronic and optical response of Yb14MnSb11/AlSb9Yb11 heterostructures - A theoretical study.

Two-dimensional TiSe2, with Yb14MnSb11 and AlSb9Yb11 thermoelectric materials, were used to generate heterostructures. The electronic and optical calculations were done using the Materials Studio 2018 modelling software package, employing the Cambridge Serial Total Energy Package code and using the generalised gradient approximation with Perdew-Burke-Ernzerhof exchange-correlation functionals. However, the electronic results obtained revealed a reduction in the calculated band gap and an increase in the slope of the density of state at the Femi level, as well as the energy bands of the generated heterostructures was reported. Partial density of states showed that various orbitals were present in the thermoelectric materials. The thermal transport and electronic properties are compared using the Boltzmann transport theory and Mott derived equations, which were expressed in the maximum attainable figure of merit. A variation in the electric potential of the layers is observed. The dielectric function is found to decrease in both thermoelectric layers generated and far more than the Yb14MnSb11-TiSe2 layer, which was more negative. The reduction in reflectivity of AlSb9Yb11TiSe2 layer and elevation of the Yb14MnSb11-TiSe2 layer is observed. Upon forming heterostructures with TiSe2, the conductivity reduced in the high frequency, due to the generated complex multicomponent compounds.

Charge transport, interfacial interactions and synergistic mechanisms in BiNbO4/MWO4 (M = Zn and Cd) heterostructures for hydrogen production: insights from a DFT+U study.

In the 21st century, the growing demand of global energy is one of the key challenges. The photocatalytic generation of hydrogen has attracted extensive attention to discuss the increasing global demand for sustainable and clean energy. However, hydrogen evolution reactions normally use the economically expensive rare noble metals and the processes remain a challenge. Herein, low-cost BiNbO4/MWO4(010) heterostructures are studied for the first time to check their suitability towards photocatalytic hydrogen production. A theoretical study with the aid of density functional theory (DFT) is used to investigate the synergistic effect, ionisation energy, electron affinities, charge transfer, electronic properties and the underlying mechanism for hydrogen generation of BiNbO4/MWO4(010) heterostructures. The experimental band gaps of bulk ZnWO4, CdWO4 and BiNbO4 are well reproduced using the DFT+U method. The calculated band edge position shows a type-II staggered band alignment and the charge transfer between BiNbO4 and MWO4 monolayers results in a large interfacial built-in potential, which will favour the separation of charge carriers in the heterostructures. The effective mass of the photoinduced holes is higher compared to the electrons, making the heterostructures useful in hydrogen production. The relatively low ionisation energy and electron affinity for the heterostructures compared to the monolayers make them ideal for photocatalysis applications due to their small energy barrier for the injection of electrons and creation of holes. The BiNbO4/MWO4(010) heterostructures are more suitable for photocatalytic hydrogen production due to their strong reducing power relative to the H+/H2O potential. This study sheds light on the less known BiNbO4/ZnWO4(010) heterostructures and the fully explored electronic and optical properties will pave way for future photocatalytic water splitting applications.

Evaluating AM1/d-CB1 for Chemical Glycobiology QM/MM Simulations.

The newly parametrized AM1/d-CB1 is evaluated for its performance in modeling monosaccharide structure, carbohydrate ring pucker, amino acid proton transfer, DNA base pair interactions, carbohydrate-aromatic π interactions, and phosphates that are prominent in glycosyltransferases. The accuracy of the method in these computations is compared to a comprehensive range of NDDO methods commonly used to study glycan structure and reactivity in chemical biology. AM1/d-CB1 shows significant improvement over existing NDDO type methods in the computation of five and six membered carbohydrate ring pucker free energy surfaces. Moreover, the computation of carbohydrate amino acid interactions commonly present in catalytic domains and binding sites are improved over existing NDDO methods. AM1/d-CB1 shows slight improvement for carbohydrate-aromatic π interactions compared to a commonly used NDDO method (AM1). The method is applied to a glycosyltransferase reaction, where it is the only NDDO method able to achieve an optimized reaction profile. Moreover, a comparison of the geometry optimized computations of the reaction scheme give a transition state energy barrier that best compares with DFT (MPW1K). Overall, AM1/d-CB1 is shown to significantly improve on existing NDDO methods in modeling chemical glycobiological events.

AM1/d-CB1: A Semiempirical Model for QM/MM Simulations of Chemical Glycobiology Systems.

A semiempirical method based on the AM1/d Hamiltonian is introduced to model chemical glycobiological systems. We included in the parameter training set glycans and the chemical environment often found about them in glycoenzymes. Starting with RM1 and AM1/d-PhoT models we optimized H, C, N, O, and P atomic parameters targeting the best performing molecular properties that contribute to enzyme catalyzed glycan reaction mechanisms. The training set comprising glycans, amino acids, phosphates and small organic model systems was used to derive parameters that reproduce experimental data or high-level density functional results for carbohydrate, phosphate and amino acid heats of formation, amino acid proton affinities, amino acid and monosaccharide dipole moments, amino acid ionization potentials, water-phosphate interaction energies, and carbohydrate ring pucker relaxation times. The result is the AM1/d-Chemical Biology 1 or AM1/d-CB1 model that is considerably more accurate than existing NDDO methods modeling carbohydrates and the amino acids often present in the catalytic domains of glycoenzymes as well as the binding sites of lectins. Moreover, AM1/d-CB1 computed proton affinities, dipole moments, ionization potentials and heats of formation for transition state puckered carbohydrate ring conformations, observed along glycoenzyme catalyzed reaction paths, are close to values computed using DFT M06-2X. AM1/d-CB1 provides a platform from which to accurately model reactions important in chemical glycobiology.

QTAIM and ETS-NOCV analyses of intramolecular CH···HC interactions in metal complexes.

The topological analysis, based on the quantum theory of atoms in molecules (QTAIM) of Bader and the ETS-NOCV charge and energy decomposition method have been used to characterize coordination bonds, chelating rings, and additional intramolecular interactions in the ZnNTA and ZnNTPA complexes in solvent. The QTAIM and ETS-NOCV studies have conclusively demonstrated that the H-clashes (they are observed only in the ZnNTPA complex and classically are interpreted as steric hindrance destabilizing a complex) are characterized by (i) the electron flow channel between the H-atoms involved, as discovered by the ETS-NOCV analysis (on average, ΔE(orb) = -1.35 kcal mol(-1)) and (ii) QTAIM-defined a bond path that indicates the presence of a preferred quantum-mechanical exchange channel, hence, they should be seen as H-H intramolecular bonding interactions. The main reason for the formation of a weaker ZnNTPA complex was attributed to the strain energy (from both QTAIM and ETS-NOCV techniques) and the larger Pauli repulsion contribution found from the ETS-NOCV analysis. An excellent agreement between physical properties controlling the stability of the two complexes was found from the two techniques, QTAIM and ETS-NOCV.

A density functional theory- and atoms in molecules-based study of NiNTA and NiNTPA complexes toward physical properties controlling their stability. A new method of computing a formation constant.

The log K(1) value of analytical quality was obtained for the NiNTPA complex using the density functional theory (DFT)-computed (at the B3LYP/6-311++G(d,p) level of theory in solvent, CPCM/UAKS) G(aq) values of the lowest-energy conformers of the ligands, nitrilotriacetic acid (NTA) and nitrilotri-3-propanoic acid (NTPA), and the Ni(II) complexes (NiNTA and NiNTPA). The described mathematical protocol is of a general nature. The topological analysis, based on the quantum theory of atoms in molecules (QTAIM) of Bader, was used to characterize coordination bonds, chelating rings, and additional intramolecular interactions in the complexes. The topological data, but not the structural analysis, explained the observed difference in stability of the NiNTA and NiNTPA complexes. It was found that the structural H...H contacts (classically regarded H-clashes, a steric hindrance destabilizing the complex) are in fact the H-H bonds contributing to the overall stability of NiNTPA. Also a CH-O bond was found in NiNTPA. The absence of intramolecular bonds between the atoms that fulfill a distance criterion in NiNTPA is explained by the formation of adjacent intramolecular rings that have larger electron density at the ring critical points when compared with the rings containing these atoms. It is postulated that the strength of a chelating ring (a chelating effect) can be measured by the electron density at the ring critical point. It was found that the strain energy, E(s), in the as-in-complex NTPA ligand (E(s) is significantly lowered by the presence of the intramolecular bonded interactions found by QTAIM) is responsible for the decrease in strength of NiNTPA; the E(s) ratio (NTPA/NTA) of 1.9 correlates well with the experimental log K(1) ratio (NTA/NTPA) of 1.98.

Density functional theory and isodesmic reaction based prediction of four stepwise protonation constants, as log KH(n), for nitrilotriacetic acid. The importance of a kind and protonated form of a reference molecule used.

An explicit application of isodesmic reaction (a proton exchange between the studied and structurally similar reference molecule), where the free energy change of the protonation reaction in water was obtained using the free energies in solution from a single continuum model, was used to predict stepwise protonation constants of nitrilotriacetic acid. Calculations were performed at the RB3LYP/6-311+G(d,p) level of theory in conjunction with the PCM-UA0 solvation model. Five reference molecules were investigated. It has been established that one must pay special attention to structural similarities between the studied and reference molecules and selection of a protonated form of the reference molecule. The protonation reactions in which the studied and reference molecule are involved in must be (if possible) of the same order; e.g., the first (or generally nth) protonation reaction of the reference molecule must be used to compute the first (or nth) protonation constant of the studied molecule. The lowest energy conformer must always be used. The first, second, third, and fourth computed protonation constants differed, on average, from experimental values by 3.3, 0.8, 0.2, and 0.2 log units, respectively. It appears that the charge on the reference molecule has more decisive influence on the accuracy of computed protonation constants than its structural differences when compared with the studied molecule. Results reported can be used as a guide in constructing isodesmic reactions useful for the theoretical prediction of protonation constants by use of methodology described in this work.

Density functional theory in prediction of four stepwise protonation constants for nitrilotripropanoic acid (NTPA).

It has been demonstrated for the first time that prediction of several consecutive protonation constants for the highly and negatively charged molecules, such as nitrilotripropanoic acid (NTPA), is possible with acceptable accuracy when isodesmic reaction (IRn) methodology, instead of commonly employed thermodynamic cycle (TC), is employed. Four stepwise protonation constants of NTPA were computed (RB3LYP/6-311+G(d,p) level of theory employing PCM/UA0 solvation model) to within +/-1 log unit of experimental data with an average error in the protonation constant of about 0.5 log unit. This good agreement was achieved for minimum energy structures of NTPA (studied ligand) and iminodiacetic acid (reference molecule). Results obtained strongly support the view that full conformational analysis should be seen as prerequisite for computing protonation/dissociation constants from IRn and possibly also from TC. Methodology proposed here broadens up, in our opinion, a scope of studying protonation constants computationally and opens up a new field of applications for poly charged ligands. TC did not work here at all as proton on N-atom was not preserved in gas-optimized structures; this proton always protonated available COO(-) group instead.