Feasibility of Using Molecular Docking-Based Virtual Screening for Searching Dual Target Kinase Inhibitors

Structure-Based Discovery of Dual-Target Hits for Acetylcholinesterase and the α7 Nicotinic Acetylcholine Receptors: In Silico Studies and In Vitro Confirmation

Despite extensive efforts in the development of drugs for complex neurodegenerative diseases, treatment often remains challenging or ineffective, and hence new treatment strategies are necessary. One approach is the design of multi-target drugs, which can potentially address the complex nature of disorders such as Alzheimer's disease. We report a method for high throughput virtual screening aimed at identifying new dual target hit molecules. One of the identified hits, N,N-dimethyl-1-(4-(3-methyl-[1,2,4]triazolo[4,3-a]pyrimidin-6-yl)phenyl)ethan-1-amine (Ý;mir-2), has dual-activity as an acetylcholinesterase (AChE) inhibitor and as an α7 nicotinic acetylcholine receptor (α7 nAChR) agonist. Using computational chemistry methods, parallel and independent screening of a virtual compound library consisting of 3,848,234 drug-like and commercially available molecules from the ZINC15 database, resulted in an intersecting set of 57 compounds, that potentially possess activity at both of the two protein targets. Based on ligand efficiency as well as scaffold and molecular diversity, 16 of these compounds were purchased for in vitro validation by Ellman's method and two-electrode voltage-clamp electrophysiology. Ý;mir-2 was shown to exhibit the desired activity profile (AChE IC₅₀ = 2.58 ± 0.96 µM; α7 nAChR activation = 7.0 ± 0.9% at 200 µM) making it the first reported compound with this particular profile and providing further evidence of the feasibility of in silico methods for the identification of novel multi-target hit molecules.

Structural insights and influence of V599 mutations on the overall dynamics of BRAF protein against its kinase domains

Mutations in the BRAF gene are well known for their oncogenic effects. Point mutations in V599 are particularly oncogenic and are considered important for therapeutic purposes. Along with wild type, other V599 mutated BRAF variants viz. V599E, V599D and V599R are reported and crystals of the former two with inhibitor (BAY43-9006) are further detailed. Both wild-type and mutated BRAF forms show similar interaction patterns with BAY43-9006, but the 599th residue did not show any involvement in the interactions. Upon BAY43-9006 binding, kinase domains of both forms were found adopting essentially identical conformations. However, BAY43-9006 shows a varied activity profile in the case of the wild and V599E variant of the BRAF protein. Furthermore, MMGBSA binding energy results for all four BRAF variants, further revealed the importance of the 599th residue. In-depth analysis viz. molecular dynamics, residue correlation studies and residue interaction network (RIN) analyses were conducted, providing a deep insight into the 599th residue and its impact on the overall dynamics of BRAF protein. Our findings reveal that the mutated residue at the 599th position not only changed the BAY43-9006-BRAF binding behaviour but also produced a massive impact on the overall dynamic behaviour of the protein. The insights obtained herein could be of great relevance for designing new BRAF inhibitors aimed at getting ideal activity against all BRAF forms.

Novel Approach for the Search for Chemical Scaffolds with Dual Activity with Acetylcholinesterase and the α7 Nicotinic Acetylcholine Receptor-A Perspective for the Treatment of Neurodegenerative Disorders

Neurodegenerative disorders, including Alzheimer’s disease, belong to the group of the most difficult and challenging conditions with very limited treatment options. Attempts to find new drugs in most cases fail at the clinical stage. New tactics to develop better drug candidates to manage these diseases are urgently needed. It is evident that better understanding of the neurodegeneration process is required and targeting multiple receptors may be essential. Herein, we present a novel approach, searching for dual active compounds interacting with acetylcholinesterase (AChE) and the α7 nicotinic acetylcholine receptor (nAChR) using computational chemistry methods including homology modelling and high throughput virtual screening. Activities of identified hits were evaluated at the two targets using the colorimetric method of Ellman and two-electrode voltage-clamp electrophysiology, respectively. Out of 87,250 compounds from a ZINC database of natural products and their derivatives, we identified two compounds, 8 and 9, with dual activity and balanced IC₅₀ values of 10 and 5 µM at AChE, and 34 and 14 µM at α7 nAChR, respectively. This is the first report presenting successful use of virtual screening in finding compounds with dual mode of action inhibiting both the AChE enzyme and the α7 nAChR and shows that computational methods can be a valuable tool in the early lead discovery process.

Selection of protein conformations for structure-based polypharmacology studies

Several drugs exert their therapeutic effect through the modulation of multiple targets. Structure-based approaches hold great promise for identifying compounds with the desired polypharmacological profiles. These methods use knowledge of the protein binding sites to identify stereoelectronically complementary ligands. The selection of the most suitable protein conformations to be used in the design process is vital, especially for multitarget drug design in which the same ligand has to be accommodated in multiple binding pockets. Herein, we focus on currently available techniques for the selection of the most suitable protein conformations for multitarget drug design, compare the potential advantages and limitations of each method, and comment on how their combination could help in polypharmacology drug design.

Flavonoids as potent allosteric inhibitors of protein tyrosine phosphatase 1B: molecular dynamics simulation and free energy calculation

Protein tyrosine phosphatase 1B (PTP1B) is a member of the PTP superfamily which is considered to be a negative regulator of insulin receptor (IR) signaling pathway. PTP1B is a promising drug target for the treatment of type 2 diabetes, obesity, and cancer. The existence of allosteric site in PTP1B has turned the researcher's attention to an alternate strategy for inhibition of this enzyme. Herein, the molecular interactions between the allosteric site of PTP1B with three non-competitive flavonoids, (MOR), (MOK), and (DPO) have been investigated. Three ligands were docked into allosteric site of the enzyme. The resulting protein-ligand complexes were used for molecular dynamics studies. Principal component and free-energy landscape (FEL) as well as cluster analyses were used to investigate the conformational and dynamical properties of the protein and identify representative enzyme substrates bounded to the inhibitors. Per residue energy decomposition analysis attributed dissimilar affinities of three inhibitors to the several hydrogen bonds and non-bonded interactions. In conclusion, our results exhibited an inhibitory pattern of the ligands against PTP1B.

Dual or multi-targeting inhibitors: The next generation anticancer agents

Dual-targeting/Multi-targeting of oncoproteins by a single drug molecule represents an efficient, logical and alternative approach to drug combinations. An increasing interest in this approach is indicated by a steady upsurge in the number of articles on targeting dual/multi proteins published in the last 5 years. Combining different inhibitors that destiny specific single target is the standard treatment for cancer. A new generation of dual or multi-targeting drugs is emerging, where a single chemical entity can act on multiple molecular targets. Dual/Multi-targeting agents are beneficial for solving limited efficiencies, poor safety and resistant profiles of an individual target. Designing dual/multi-target inhibitors with predefined biological profiles present a challenge. The latest advances in bioinformatic tools and the availability of detailed structural information of target proteins have shown a way of discovering multi-targeting molecules. This neoteric artifice that amalgamates the molecular docking of small molecules with protein-based common pharmacophore to design multi-targeting inhibitors is gaining great importance in anticancer drug discovery. Current review focus on the discoveries of dual targeting agents in cancer therapy using rational, computational, proteomic, bioinformatics and polypharmacological approach that enables the discovery and rational design of effective and safe multi-target anticancer agents.

Computational and experimental prediction of molecules involved in the anti-melanoma action of berberine

ETHNOPHARMACOLOGIC RELEVANCE

Berberine (BBR) is a naturally occurring alkaloid compound that can be found in Chinese medicinal herbs such as Rhizoma Coptidis and Phellodendri Cortex. These BBR containing herbs are commonly used by Chinese medicine doctors to treat cancers including melanoma. In this study, we explored proteins potentially involved in the anti-melanoma effects of BBR using computational and experimental approaches.

MATERIALS AND METHODS

Target proteins of BBR were predicted using the reverse pharmacophore screening, molecular docking and molecular dynamics. Anti-melanoma activities of BBR in melanoma cells were examined by MTT and EdU proliferation assays. Effects of BBR on activities of target proteins in melanoma cells were examined by Western blotting or fluorescence assay.

RESULTS

Ten proteins implicated in cancer and with high fit-score in the reverse pharmacophore screening were selected as potential targets of BBR. Molecular docking and molecular dynamics revealed that BBR could stably bind to four of the ten proteins, namely 3-phosphoinositide-dependent protein kinase 1 (PDK1), glucocorticoid receptor (GR), p38 mitogen-activated protein kinase (p38) and dihydroorotate dehydrogenase (DHODH). Cellular experiments showed that BBR inhibited cell proliferation, increased the phosphorylation of GR and p38, and inhibited the activity of DHODH in A375 human melanoma cells.

CONCLUSIONS

These findings suggest that p38, GR and DHODH are potentially involved in the anti-melanoma action of BBR. This study provided a chemical and pharmacological justification for the clinical use of BBR-containing herbs in melanoma treatment.

Side Chains of Parabens Modulate Antiandrogenic Activity: In Vitro and Molecular Docking Studies

Parabens have been widely used in packaged foods, pharmaceuticals, and personal-care products. Considering their potential hydrolysis, we herein investigated structural features leading to the disruption of human androgen receptor (AR) and whether hydrolysis could alleviate such effects using the recombinant yeast two-hybrid assay. Parabens with an aryloxy side chain such as benzyl paraben and phenyl paraben have the strongest antiandrogenic activity. The antiandrogenic activity of parabens with alkyloxyl side chains decreases as the side chain length increases from 1 to 4, and no antiandrogenic effect occurred for heptyl, octyl, and dodecyl parabens with the number of alkoxyl carbon atoms longer than 7. The antiandrogenic activity of parabens correlates significantly with their binding energies (R² = 0.84, p = 0.01) and were completely diminished after the hydrolysis, particularly for parabens with aryloxy side chains. The K_m for the hydrolysis of parabens with aromatic moiety side chain is 1 order of magnitude higher than that of the parabens with alkyl side chains. Both in vitro and in silico data, for the first time, suggest parabens with aromatic side chains are less prone to hydrolysis. Our results provide an insight into risk of various paraben and considerations for design of new paraben-related substitutes.

Discovery of Novel and Selective Adenosine A2A Receptor Antagonists for Treating Parkinson's Disease through Comparative Structure-Based Virtual Screening

Among non-dopaminergic strategies for combating Parkinson's disease (PD), antagonism of the A_2A adenosine receptor (AR) has emerged to show great potential. In this study, on the basis of two crystal structures of the A_2A AR with the best capability to distinguish known antagonists from decoys, docking-based virtual screening (VS) was conducted to identify novel A_2A AR antagonists. A total of 63 structurally diverse compounds identified by VS were submitted to experimental testing, and 11 of them exhibited substantial activity against the A_2A AR (K_i < 10 μM), including two compounds with K_i below 1 μM (compound 43, 0.42 μM; compound 51, 0.27 μM) and good A_2A/A₁ selectivity (fold < 0.1). Compounds 43 and 51 demonstrated antagonistic activity according to the results of cAMP measurements (cAMP IC₅₀ = 1.67 and 1.80 μM, respectively) and showed good efficacy in the haloperidol-induced catalepsy (HIC) rat model for PD at doses of up to 30 mg/kg. Further lead optimization based on a substructure searching strategy led to the discovery of compound 84 as an excellent A_2A AR antagonist (A_2A K_i = 54 nM, A_2A/A₁ fold < 0.1, cAMP IC₅₀ = 0.3 μM) that exhibited significant improvement in anti-PD efficacy in the HIC rat model.

Target specific proteochemometric model development for BACE1 – protein flexibility and structural water are critical in virtual screening

Structural water and protein plasticity are important factors for BACE1 targeted ligand virtual screening.

Importance of protein flexibility in ranking inhibitor affinities: modeling the binding mechanisms of piperidine carboxamides as Type I1/2 ALK inhibitors

Anaplastic lymphoma kinase (ALK) has gained increased attention as an attractive therapeutic target for the treatment of various cancers, especially non-small-cell lung cancer (NSCLC).

Structure-based computational approaches for small-molecule modulation of protein-protein interactions

Three-dimensional structures of proteins offer an opportunity for the rational design of small molecules to modulate protein-protein interactions. The presence of a well-defined binding pocket on the surface of protein complexes, particularly at their interface, can be used for docking-based virtual screening of chemical libraries. Several approaches have been developed to identify binding pockets that are implemented in programs such as SiteMap, fpocket, and FTSite. These programs enable the scoring of these pockets to determine whether they are suitable to accommodate high-affinity small molecules. Virtual screening of commercial or combinatorial libraries can be carried out to enrich these libraries and select compounds for further experimental validation. In virtual screening, a compound library is docked to the target protein. The resulting structures are scored and ranked for the selection and experimental validation of top candidates. Molecular docking has been implemented in a number of computer programs such as AutoDock Vina. We select a set of protein-protein interactions that have been successfully inhibited with small molecules in the past. Several computer programs are applied to identify pockets on the surface, and molecular docking is conducted in an attempt to reproduce the binding pose of the inhibitors. The results highlight the strengths and limitations of computational methods for the design of PPI inhibitors.

Assessing an ensemble docking-based virtual screening strategy for kinase targets by considering protein flexibility

In this study, to accommodate receptor flexibility, based on multiple receptor conformations, a novel ensemble docking protocol was developed by using the naïve Bayesian classification technique, and it was evaluated in terms of the prediction accuracy of docking-based virtual screening (VS) of three important targets in the kinase family: ALK, CDK2, and VEGFR2. First, for each target, the representative crystal structures were selected by structural clustering, and the capability of molecular docking based on each representative structure to discriminate inhibitors from non-inhibitors was examined. Then, for each target, 50 ns molecular dynamics (MD) simulations were carried out to generate an ensemble of the conformations, and multiple representative structures/snapshots were extracted from each MD trajectory by structural clustering. On average, the representative crystal structures outperform the representative structures extracted from MD simulations in terms of the capabilities to separate inhibitors from non-inhibitors. Finally, by using the naïve Bayesian classification technique, an integrated VS strategy was developed to combine the prediction results of molecular docking based on different representative conformations chosen from crystal structures and MD trajectories. It was encouraging to observe that the integrated VS strategy yields better performance than the docking-based VS based on any single rigid conformation. This novel protocol may provide an improvement over existing strategies to search for more diverse and promising active compounds for a target of interest.

Search for β2 adrenergic receptor ligands by virtual screening via grid computing and investigation of binding modes by docking and molecular dynamics simulations

We designed a program called MolGridCal that can be used to screen small molecule database in grid computing on basis of JPPF grid environment. Based on MolGridCal program, we proposed an integrated strategy for virtual screening and binding mode investigation by combining molecular docking, molecular dynamics (MD) simulations and free energy calculations. To test the effectiveness of MolGridCal, we screened potential ligands for β2 adrenergic receptor (β2AR) from a database containing 50,000 small molecules. MolGridCal can not only send tasks to the grid server automatically, but also can distribute tasks using the screensaver function. As for the results of virtual screening, the known agonist BI-167107 of β2AR is ranked among the top 2% of the screened candidates, indicating MolGridCal program can give reasonable results. To further study the binding mode and refine the results of MolGridCal, more accurate docking and scoring methods are used to estimate the binding affinity for the top three molecules (agonist BI-167107, neutral antagonist alprenolol and inverse agonist ICI 118,551). The results indicate agonist BI-167107 has the best binding affinity. MD simulation and free energy calculation are employed to investigate the dynamic interaction mechanism between the ligands and β2AR. The results show that the agonist BI-167107 also has the lowest binding free energy. This study can provide a new way to perform virtual screening effectively through integrating molecular docking based on grid computing, MD simulations and free energy calculations. The source codes of MolGridCal are freely available at http://molgridcal.codeplex.com.

Enrichment of chemical libraries docked to protein conformational ensembles and application to aldehyde dehydrogenase 2

Molecular recognition is a complex process that involves a large ensemble of structures of the receptor and ligand. Yet, most structure-based virtual screening is carried out on a single structure typically from X-ray crystallography. Explicit-solvent molecular dynamics (MD) simulations offer an opportunity to sample multiple conformational states of a protein. Here we evaluate our recently developed scoring method SVMSP in its ability to enrich chemical libraries docked to MD structures of seven proteins from the Directory of Useful Decoys (DUD). SVMSP is a target-specific rescoring method that combines machine learning with statistical potentials. We find that enrichment power as measured by the area under the ROC curve (ROC-AUC) is not affected by increasing the number of MD structures. Among individual MD snapshots, many exhibited enrichment that was significantly better than the crystal structure, but no correlation between enrichment and structural deviation from crystal structure was found. We followed an innovative approach by training SVMSP scoring models using MD structures (SVMSPMD). The resulting models were applied to two difficult cases (p38 and CDK2) for which enrichment was not better than random. We found remarkable increase in enrichment power, particularly for p38, where the ROC-AUC increased by 0.30 to 0.85. Finally, we explored approaches for a priori identification of MD snapshots with high enrichment power from an MD simulation in the absence of active compounds. We found that the use of randomly selected compounds docked to the target of interest using SVMSP led to notable enrichment for EGFR and Src MD snapshots. SVMSP rescoring of protein-compound MD structures was applied for the search of small-molecule inhibitors of the mitochondrial enzyme aldehyde dehydrogenase 2 (ALDH2). Rank-ordering of a commercial library of 50 000 compounds docked to MD structures of ALDH2 led to five small-molecule inhibitors. Four compounds had IC50s below 5 μM. These compounds serve as leads for the design and synthesis of more potent and selective ALDH2 inhibitors.

Autogrid-based clustering of kinases: selection of representative conformations for docking purposes

The selection of the most appropriate protein conformation is a crucial aspect in molecular docking experiments. In order to reduce the errors arising from the use of a single protein conformation, several authors suggest the use of several tridimensional structures for the target. However, the selection of the most appropriate protein conformations still remains a challenging goal. The protein 3D-structures selection is mainly performed based on pairwise root-mean-square-deviation (RMSD) values computation, followed by hierarchical clustering. Herein we report an alternative strategy, based on the computation of only two atom affinity map for each protein conformation, followed by multivariate analysis and hierarchical clustering. This methodology was applied on seven different kinases of pharmaceutical interest. The comparison with the classical RMSD-based strategy was based on cross-docking of co-crystallized ligands. In the case of epidermal growth factor receptor kinase, also the docking performance on 220 known ligands were evaluated, followed by 3D-QSAR studies. In all the cases, the herein proposed methodology outperformed the RMSD-based one.