In Silico Binding Free Energy Predictability by Using the Linear Interaction Energy (LIE) Method: Bromobenzimidazole CK2 Inhibitors as a Case Study

In Silico 3D Modeling of Binding Activities

In silico three-dimensional (3D) molecular modeling tools based upon the receptor/enzyme-ligand docking simulation in protein crystal structures and/or homology modeling of receptors have been reliably used in pharmacological research and development for decades. Molecular docking methodologies are helpful for revealing facets of activation and inactivation, thus improving mechanistic understanding and predicting molecular ligand binding activity, and they can have a high level of accuracy, and have also been explored and applied in chemical risk assessment. This computational approach is, however, only applicable for chemical hazard identification situations where the specific target receptor for a given chemical is known and the crystal structure/homology model of the receptor is available.

A comparative study of binding affinities for 6,7-dimethoxy-4-pyrrolidylquinazolines as phosphodiesterase 10A inhibitors using the linear interaction energy method

The linear interaction energy (LIE) method was used to estimate the free energies of binding for a set of 27 pyrrolidylquinazoline derivatives as phosphodiesterase 10A inhibitors. Twenty-six X-ray crystal structures of phosphodiesterase 10A and two sampling methods, minimization and Hybrid Monte Carlo, were used to assess the affinity models based on the linear interaction energies. The best model was obtained based on the parameters α=0.16 and β=0.04, which represent non-polar and polar interactions, respectively, with a root mean square error (RMSE) of 0.42kcal/mol (R(2)=0.71) and 0.52kcal/mol (R(2)=0.86) for the training and test sets, respectively. In addition, the applicability domain of the model was investigated. After validation of the models, the best model was subsequently used in a virtual screening process, which resulted in a set of optimized compounds. The models developed in this study could be useful as filter for virtual screening and lead optimization processes for phosphodiesterase 10A drug developments.

Structural insights into flavones as protein kinase CK2 inhibitors derived from a combined computational study

Binding conformation of flavone inhibitors to protein kinase CK2.

Designing a ligand for pharmaceutical purposes

BACKGROUND

Drug approval applications to the FDA have shown a remarkably small increment compared with what was expected. In the last few years several efforts have been made to improve the results of rational drug design approaches and in particular to predict inhibitor-target structure and to evaluate the free energy of binding. Virtual database screening, combined with other computational methods, is one of the most promising methods to overcome this key issue.

OBJECTIVE

It is possible to understand how computational medicinal chemistry is changing, improving from its errors and moving towards becoming a more important tool for drug development.

METHODS

Some of the most recent modeling techniques have been presented and in particular the benefits of combining these techniques are highlighted.

RESULTS/CONCLUSION

At present computational chemists can understand the peculiar problems associated with the study of biological systems and on this basis they can choose the right collection of complementary in silico approaches to solve the medicinal chemistry problem in a better manner.

Molecular docking methodologies

Molecular docking represents an important technology for structure-based drug design. Docking is a computational technique aimed at the prediction of the most favorable ligand-target spatial configuration and an estimate of the corresponding complex free energy, although as stated at the beginning accurate scoring methods remain still elusive. In this chapter, the state of art of molecular docking methodologies and their applications in drug discovery is summarized.

Application of consensus scoring and principal component analysis for virtual screening against β-secretase (BACE-1)

Background

In order to identify novel chemical classes of β-secretase (BACE-1) inhibitors, an alternative scoring protocol, Principal Component Analysis (PCA), was proposed to summarize most of the information from the original scoring functions and re-rank the results from the virtual screening against BACE-1.

Method

Given a training set (50 BACE-1 inhibitors and 9950 inactive diverse compounds), three rank-based virtual screening methods, individual scoring, conventional consensus scoring and PCA, were judged by the hit number in the top 1% of the ranked list. The docking poses were generated by Surflex, five scoring functions (Surflex_Score, D_Score, G_Score, ChemScore, and PMF_Score) were used for pose extraction. For each pose group, twelve scoring functions (Surflex_Score, D_Score, G_Score, ChemScore, PMF_Score, LigScore1, LigScore2, PLP1, PLP2, jain, Ludi_1, and Ludi_2) were used for the pose rank. For a test set, 113,228 chemical compounds (Sigma-Aldrich® corporate chemical directory) were docked by Surflex, then ranked by the same three ranking methods motioned above to select the potential active compounds for experimental test.

Results

For the training set, the PCA approach yielded consistently superior rankings compared to conventional consensus scoring and single scoring. For the test set, the top 20 compounds according to conventional consensus scoring were experimentally tested, no inhibitor was found. Then, we relied on PCA scoring protocol to test another different top 20 compounds and two low micromolar inhibitors (S450588 and 276065) were emerged through the BACE-1 fluorescence resonance energy transfer (FRET) assay.

Conclusion

The PCA method extends the conventional consensus scoring in a quantitative statistical manner and would appear to have considerable potential for chemical screening applications.

How druggable is protein kinase CK2?

CK2 is a pleiotropic, ubiquitous, and constitutively active protein kinase (PK), with both cytosolic and nuclear localization in most mammalian cells. The holoenzyme is generally composed of two catalytic (alpha and/or alpha') and two regulatory (beta) subunits, but the free alpha/alpha' subunits are catalytically active by themselves and can be present in cells under some circumstances. CK2 catalyzes the phosphorylation of more than 300 substrates characterized by multiple acidic residues surrounding the phosphor-acceptor amino acid, and, consequently, it plays a key role in several physiological and pathological processes. But how can one kinase orchestrate all these tasks faithfully? How is it possible that one kinase can, despite all pleiotropic characteristics of PKs in general, be involved in so many different biochemical events? Is CK2 a druggable target? Several questions are still to be clearly answered, and this review is an occasion for a fruitful discussion.

Binding free energy calculations of N-sulphonyl-glutamic acid inhibitors of MurD ligase

The increasing incidence of bacterial resistance to most available antibiotics has underlined the urgent need for the discovery of novel efficacious antibacterial agents. The biosynthesis of bacterial peptidoglycan, where the MurD enzyme is involved in the intracellular phase of UDP-MurNAc-pentapeptide formation, represents a collection of highly selective targets for novel antibacterial drug design. Structural studies of N-sulfonyl-glutamic acid inhibitors of MurD have made possible the examination of binding modes of this class of compounds, providing valuable information for the lead optimization phase of the drug discovery cycle. Binding free energies were calculated for a series of MurD N-sulphonyl-Glu inhibitors using the linear interaction energy (LIE) method. Analysis of interaction energy during the 20-ns MD trajectories revealed non-polar van der Waals interactions as the main driving force for the binding of these inhibitors, and excellent agreement with the experimental free energies was obtained. Calculations of binding free energies for selected moieties of compounds in this structural class substantiated even deeper insight into the source of inhibitory activity. These results constitute new valuable information to further assist the lead optimization process.

Synthesis and quantitative structure-activity relationship of fatty acid amide hydrolase inhibitors: modulation at the N-portion of biphenyl-3-yl alkylcarbamates

Alkylcarbamic acid biphenyl-3-yl esters are a class of fatty acid amide hydrolase (FAAH) inhibitors that comprises cyclohexylcarbamic acid 3'-carbamoylbiphenyl-3-yl ester (URB597), a compound with analgesic, anxiolytic-like and antidepressant-like properties in rat and mouse models. Here, we extended the structure-activity relationships (SARs) for this class of compounds by replacing the cyclohexyl ring of the parent compound cyclohexylcarbamic acid biphenyl-3-yl ester (URB524) (FAAH IC50 = 63 nM) with a selected set of substituents of different size, shape, flexibility, and lipophilicity. Docking experiments and linear interaction energy (LIE) calculations indicated that the N-terminal group of O-arylcarbamates fits within the lipophilic region of the substrate-binding site, mimicking the arachidonoyl chain of anandamide. Significant potency improvements were observed for the beta-naphthylmethyl derivative 4q (IC50 = 5.3 nM) and its 3'-carbamoylbiphenyl-3-yl ester 4z (URB880, IC50 = 0.63 nM), indicating that shape complementarity and hydrogen bonds are crucial to obtain highly potent inhibitors.

Towards improving compound selection in structure-based virtual screening

Structure-based virtual screening is now an established technology for supporting hit finding and lead optimisation in drug discovery. Recent validation studies have highlighted the poor performance of currently used scoring functions in estimating binding affinity and hence in ranking large datasets of docked ligands. Progress in the analysis of large datasets can be made through the use of appropriate data mining techniques and the derivation of a broader range of descriptors relevant to receptor-ligand binding. In addition, simple scoring functions can be supplemented by simulation-based scoring protocols. Developments in workflow design allow the automation of repetitive tasks, and also encourage the routine use of simulation-based methods and the rapid prototyping of novel modelling and analysis procedures.

The ATP-binding site of protein kinase CK2 holds a positive electrostatic area and conserved water molecules

CK2 is a highly pleiotropic Ser/Thr protein kinase that is able to promote cell survival and enhance the tumour phenotype under specific circumstances. We have determined the crystal structure of three new complexes with tetrabromobenzimidazole derivatives that display K(i) values between 0.15 and 0.30 microM. A comparative analysis of these data with those of four other inhibitors of the same family revealed the presence of some highly conserved water molecules in the ATP-binding site. These waters reside near Lys68, in an area with a positive electrostatic potential that is able to attract and orient negatively charged ligands. The presence of this positive region and two unique bulky residues that are typical of CK2, Ile66 and Ile174, play a critical role in determining the ligand orientation and binding selectivity.