Extra precision docking, free energy calculation and molecular dynamics simulation studies of CDK2 inhibitors

In silico design of small peptides antagonist against leptin receptor for the treatment of obesity and its associated immune-mediated diseases

Excess adiposity in obese inhibits negatively impacts immune function and host defence. Obesity is characterized by a state of low-grade, chronic inflammation in addition to disturbed levels of circulating nutrients and metabolic hormones. The impact of metabolic abnormalities on obesity-related co-morbidities has undergone intense scrutiny over the past decades. Thus, treatment of obesity and its associated immune-mediated diseases is challenging due to impaired function of leptin system. These disorders are managed through antibiotics and by cytokines replacement. However, the effectiveness of cytokines coupled to the complexity of the cytokine network leads to severe side-effects, which can still occur after careful preclinical evaluation. In addition, synthetic immunotherapeutics carry a degree of risk, time-consuming and expensive. Hence, the complexity of existing therapy and adverse effects emphasizes the need for an alternative approach for the management of immune dysfunction associated with obesity. Computer-aided small molecule antibody technology has been successful in the design of novel biologicals for the diagnosis of diseases and therapeutic interventions. In this study, the crystal structure of leptin receptor (LEPR) complex with monoclonal antibody (9F8 Fab) was explored to predict Ag-Ab interactions using bioinformatics tools. The LEPR of complementarity-determining region (CDR) loops were mutated with published positive control residues of Ser, Thr, Tyr, Trp, and Phe to design a set of 678 peptides which were evaluated through Ag-peptide docking, binding free-energies, and interaction energies. Thus, hypothesized novel peptides can be explored as clinically applicable antagonists for the treatment of obesity and associated immune-mediated diseases.

Exploration for novel inhibitors showing back-to-front approach against VEGFR-2 kinase domain (4AG8) employing molecular docking mechanism and molecular dynamics simulations

Background

Angiogenesis is a process of formation of new blood vessels and is an important criteria demonstrated by cancer cells. Over a period of time, these cancer cells infect the other parts of the healthy body by a process called progression. The objective of the present article is to identify a drug molecule that inhibits angiogenesis and progression.

Methods

In this pursuit, ligand based pharmacophore virtual screening was employed, generating a pharmacophore model, Hypo1 consisting of four features. Furthermore, this Hypo1 was validated recruiting, Fischer’s randomization, test set method and decoy set method. Later, Hypo1 was allowed to screen databases such as Maybridge, Chembridge, Asinex and NCI and were further filtered by ADMET filters and Lipinski’s Rule of Five. A total of 699 molecules that passed the above criteria, were challenged against 4AG8, an angiogenic drug target employing GOLD v5.2.2.

Results

The results rendered by molecular docking, DFT and the MD simulations showed only one molecule (Hit) obeyed the back-to-front approach. This molecule displayed a dock score of 89.77, involving the amino acids, Glu885 and Cys919, Asp1046, respectively and additionally formed several important hydrophobic interactions. Furthermore, the identified lead molecule showed interactions with key residues when challenged with CDK2 protein, 1URW.

Conclusion

The lead candidate showed several interactions with the crucial residues of both the targets. Furthermore, we speculate that the residues Cys919 and Leu83 are important in the development of dual inhibitor. Therefore, the identified lead molecule can act as a potential inhibitor for angiogenesis and progression.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4050-1) contains supplementary material, which is available to authorized users.

Exploration of cell cycle regulation and modulation of the DNA methylation mechanism of pelargonidin: Insights from the molecular modeling approach

Pelargonidin is an anthocyanidin isolated from plant resources. It shows strong cytotoxicity toward various cancer cell lines, even though the carcinogenesis-modulating pathway of pelargonidin is not yet known. One of our previous reports showed that pelargonidin arrests the cell cycle and induces apoptosis in HT29 cells. Flowcytometry and immunoblot analysis confirmed that pelargonidin specifically inhibits the activation of CDK1 and blocks the G2-M transition of the cell cycle. In addition, DNA fragmentation was observed along with induction of cytochrome c release-mediated apoptosis. Hence, the aim of the present study was to investigate the molecular mechanism of pelargonidin's action on cell cycle regulators CDK1, CDK4, and CDK6 as well as the substrate-binding domain of DNMT1 and DNMT3A, which regulate the epigenetic signals related to DNA methylation. The results of docking analysis, binding free energy calculation, and molecular dynamics simulation correlated with the experimental results, and pelargonidin showed a specific interaction with CDK1. In this context, pelargonidin may also inhibit the recognition of DNA and catalytic binding by DNMT1 and DNMT3A. The HOMO-LUMO analysis mapped the functional groups of pelargonidin. Prediction of pharmacological descriptors suggested that pelargonidin can serve as a multitarget inhibitor for cancer treatment.

Recent advances on CDK inhibitors: An insight by means of in silico methods

The cyclin dependent kinases (CDKs) are a small family of serine/threonine protein kinases that can act as a potential therapeutic target in several proliferative diseases, including cancer. This short review is a survey on the more recent research progresses in the field achieved by using in silico methods. All the "armamentarium" available to the medicinal chemists (docking protocols and molecular dynamics, fragment-based, de novo design, virtual screening, and QSAR) has been employed to the discovery of new, potent, and selective inhibitors of cyclin dependent kinases. The results cited herein can be useful to understand the nature of the inhibitor-target interactions, and furnish an insight on the structural/molecular requirements necessary to achieve the required selectivity against cyclin dependent kinases over other types of kinases.

Novel ligand-based docking; molecular dynamic simulations; and absorption, distribution, metabolism, and excretion approach to analyzing potential acetylcholinesterase inhibitors for Alzheimer's disease

Acetylcholinesterase (AChE) plays an important role in Alzheimer's disease (AD). The excessive activity of AChE causes various neuronal problems, particularly dementia and neuronal cell deaths. Generally, anti-AChE drugs induce some serious neuronal side effects in humans. Therefore, this study sought to identify alternative drug molecules from natural products with fewer side effects than those of conventional drugs for treating AD. To achieve this, we developed computational methods for predicting drug and target binding affinities using the Schrodinger suite. The target and ligand molecules were retrieved from established databases. The target enzyme has 539 amino acid residues in its sequence alignment. Ligand molecules of 20 bioactive molecules were obtained from different kinds of plants, after which we performed critical analyses such as molecular docking; molecular dynamic (MD) simulations; and absorption, distribution, metabolism, and excretion (ADME) analysis. In the docking studies, the natural compound rutin showed a superior docking score of −12.335 with a good binding energy value of −73.313 kcal/mol. Based on these findings, rutin and the target complex was used to perform MD simulations to analyze rutin stability at 30 ns. In conclusion, our study demonstrates that rutin is a superior drug candidate for AD. Therefore, we propose that this molecule is worth further investigation using in vitro studies.

An in silico high-throughput screen identifies potential selective inhibitors for the non-receptor tyrosine kinase Pyk2

The non-receptor tyrosine kinase proline-rich tyrosine kinase 2 (Pyk2) is a critical mediator of signaling from cell surface growth factor and adhesion receptors to cell migration, proliferation, and survival. Emerging evidence indicates that signaling by Pyk2 regulates hematopoietic cell response, bone density, neuronal degeneration, angiogenesis, and cancer. These physiological and pathological roles of Pyk2 warrant it as a valuable therapeutic target for invasive cancers, osteoporosis, Alzheimer’s disease, and inflammatory cellular response. Despite its potential as a therapeutic target, no potent and selective inhibitor of Pyk2 is available at present. As a first step toward discovering specific potential inhibitors of Pyk2, we used an in silico high-throughput screening approach. A virtual library of six million lead-like compounds was docked against four different high-resolution Pyk2 kinase domain crystal structures and further selected for predicted potency and ligand efficiency. Ligand selectivity for Pyk2 over focal adhesion kinase (FAK) was evaluated by comparative docking of ligands and measurement of binding free energy so as to obtain 40 potential candidates. Finally, the structural flexibility of a subset of the docking complexes was evaluated by molecular dynamics simulation, followed by intermolecular interaction analysis. These compounds may be considered as promising leads for further development of highly selective Pyk2 inhibitors.

Inhibitor Selectivity for Cyclin-Dependent Kinase 7: A Structural, Thermodynamic, and Modelling Study

Deregulation of the cell cycle by mechanisms that lead to elevated activities of cyclin-dependent kinases (CDK) is a feature of many human diseases, cancer in particular. We identified small-molecule inhibitors that selectively inhibit CDK7, the kinase that phosphorylates cell-cycle CDKs to promote their activities. To investigate the selectivity of these inhibitors we used a combination of structural, biophysical, and modelling approaches. We determined the crystal structures of the CDK7-selective compounds ICEC0942 and ICEC0943 bound to CDK2, and used these to build models of inhibitor binding to CDK7. Molecular dynamics (MD) simulations of inhibitors bound to CDK2 and CDK7 generated possible models of inhibitor binding. To experimentally validate these models, we gathered isothermal titration calorimetry (ITC) binding data for recombinant wild-type and binding site mutants of CDK7 and CDK2. We identified specific residues of CDK7, notably Asp155, that are involved in determining inhibitor selectivity. Our MD simulations also show that the flexibility of the G-rich and activation loops of CDK7 is likely an important determinant of inhibitor specificity similar to CDK2.

Docking Methodologies and Recent Advances

Docking, a molecular modelling method, has wide applications in identification and optimization in modern drug discovery. This chapter addresses the recent advances in the docking methodologies like fragment docking, covalent docking, inverse docking, post processing, hybrid techniques, homology modeling etc. and its protocol like searching and scoring functions. Advances in scoring functions for e.g. consensus scoring, quantum mechanics methods, clustering and entropy based methods, fingerprinting, etc. are used to overcome the limitations of the commonly used force-field, empirical and knowledge based scoring functions. It will cover crucial necessities and different algorithms of docking and scoring. Further different aspects like protein flexibility, ligand sampling and flexibility, and the performance of scoring function will be discussed.

CD4-gp120 interaction interface - a gateway for HIV-1 infection in human: molecular network, modeling and docking studies

The major causative agent for Acquired Immune Deficiency Syndrome (AIDS) is Human Immunodeficiency Virus-1 (HIV-1). HIV-1 is a predominant subtype of HIV which counts on human cellular mechanism virtually in every aspect of its life cycle. Binding of viral envelope glycoprotein-gp120 with human cell surface CD4 receptor triggers the early infection stage of HIV-1. This study focuses on the interaction interface between these two proteins that play a crucial role for viral infectivity. The CD4-gp120 interaction interface has been studied through a comprehensive protein-protein interaction network (PPIN) analysis and highlighted as a useful step towards identifying potential therapeutic drug targets against HIV-1 infection. We prioritized gp41, Nef and Tat proteins of HIV-1 as valuable drug targets at early stage of viral infection. Lack of crystal structure has made it difficult to understand the biological implication of these proteins during disease progression. Here, computational protein modeling techniques and molecular dynamics simulations were performed to generate three-dimensional models of these targets. Besides, molecular docking was initiated to determine the desirability of these target proteins for already available HIV-1 specific drugs which indicates the usefulness of these protein structures to identify an effective drug combination therapy against AIDS.

Viper venom hyaluronidase and its potential inhibitor analysis: a multipronged computational investigation

Viper venom hyaluronidase (VV-HYA) inhibitors have long been used as therapeutic agents for arresting the local and systemic effects caused during its envenomation. Henceforth, to understand its structural features and also to identify the best potential inhibitor against it the present computational study was undertaken. Structure-based homology modeling of VV-HYA followed by its docking and free energy-based ranking analysis of ligand, the MD simulations of the lead complex was also performed. The sequence analysis and homology modeling of VV-HYA revealed a distorted (β/α)₈ folding as in the case of hydrolases family of proteins. Molecular docking of the resultant 3D structure of VV-HYA with known inhibitors (compounds 1-25) revealed the importance of molecular recognition of hotspot residues (Tyr 75, Arg 288, and Trp 321) other than that of the active site residues. It also revealed that Trp 321 of VV-HYA is highly important for mediating π-π interactions with ligands. In addition, the molecular docking and comparative free energy binding analysis was investigated for the VV-HYA inhibitors (compounds 1-25). Both molecular docking and relative free energy binding analysis clearly confirmed the identification of sodium chromoglycate (compound 1) as the best potential inhibitor against VV-HYA. Molecular dynamics simulations additionally confirmed the stability of their binding interactions. Further, the information obtained from this work is believed to serve as an impetus for future rational designing of new novel VV-HYA inhibitors with improved activity and selectivity.

Understanding the molecular basis of agonist/antagonist mechanism of GPER1/GPR30 through structural and energetic analyses

The G-protein coupled receptors (GPCRs) represent the largest superfamily of membrane proteins in charge to pass the cell signaling after binding with their cognate ligands to the cell interior. In breast cancer, a GPCR named GPER1 plays a key role in the process of growth and the proliferation of cancer cells. In a previous study, theoretical methods were applied to construct a model of GPER1, which later was submitted to molecular dynamics (MD) simulations to perform a docking calculation. Based on this preceding work, it is known that GPER1 is sensitive to structural differences in its binding site. However, due to the nature of that past study, conformational changes linked to the ligand binding were not observed. Therefore, in this study, in order to explore the conformational changes coupled to the agonist/antagonist binding, MD simulations of about 0.25μs were performed for the free and bound states, summarizing 0.75μs of MD simulation in total. For the bound states, one agonist (G-1) and antagonist (G-15) were chosen since is widely known that these two molecules cause an impact on GPER1 mobility. Based on the conformational ensemble generated through MD simulations, we found that despite G-1 and G-15 being stabilized by similar map of residues, the structural differences between both ligands impact the hydrogen bond pattern not only at the GPER1 binding site but also along the seven-helix bundle, causing significant differences in the conformational mobility along the extracellular and cytoplasmic domain, and to a lesser degree in the curvatures of helix 2, helix 3 and helix 7 between the free and bound states, which is in agreement with reported literature, and might be linked to microscopic characteristics of the activated-inactivated transition. Furthermore, binding free energy calculations using the MM/GBSA method for the bound states, followed by an alanine scanning analysis allowed us to identify some important residues for the complex stabilization.

Inhibitor design against JNK1 through e-pharmacophore modeling docking and molecular dynamics simulations

c-Jun-NH2 terminal kinases (JNKs) come under a class of serine/threonine protein kinases and are encoded by three genes, namely JNK1, JNK2 and JNK3. Human JNK1 is a cytosolic kinase belonging to mitogen-activated protein kinase (MAPK) family, which plays a major role in intracrinal signal transduction cascade mechanism. Overexpressed human JNK1, a key kinase interacts with other kinases involved in the etiology of many cancers, such as skin cancer, liver cancer, breast cancer, brain tumors, leukemia, multiple myeloma and lymphoma. Thus, to unveil a novel human JNK1 antagonist, receptor-based pharmacophore modeling was performed with the available eighteen cocrystal structures of JNK1 in the protein data bank. Eighteen e-pharmacophores were generated from the 18 cocrystal structures. Four common e-pharmacophores were developed from the 18 e-pharmacophores, which were used as three-dimensional (3D) query for shape-based similarity screening against more than one million small molecules to generate a JNK1 ligand library. Rigid receptor docking (RRD) performed using GLIDE v6.3 for the 1683 compounds from in-house library and 18 cocrystal ligands with human JNK1 from lower stringency to higher stringency revealed 17 leads. Further to derive the best leads, dock complexes obtained from RRD were studied further with quantum-polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area (MM-GBSA). Four leads have showed lesser binding free energy and better binding affinity towards JNK1 compared to 18 cocrystal ligands. Additionally, JNK1-lead1 complex interaction stability was reasserted using 50 ns MD simulations run and also compared with the best resolute cocrystal structure using Desmond v3.8. Thus, the results obtained from RRD, QPLD, IFD and MD simulations indicated that lead1 might be used as a potent antagonist toward human JNK1 in cancer therapeutics.

Identification of potential transmembrane protease serine 4 inhibitors as anti-cancer agents by integrated computational approach

Transmembrane protease serine 4 is a well known cell surface protease facilitating the extracellular matrix degradation and epithelial mesenchymal transition in hepatocellular carcinoma. Henceforth targeting transmembrane protease serine 4 is strongly believed to provide therapeutic intervention against hepatocellular carcinoma. Owing to lack of crystal structure for human transmembrane protease serine 4, we predicted its three dimensional structure for the first time in this study. Experimentally proven inhibitor-Tyroserleutide (TSL) against hepatocellular carcinoma via transmembrane protease serine 4 was used as a benchmark to identify structurally similar candidates from PubChem database to create the TSL library. Virtual screening of TSL library against modeled transmembrane protease serine 4 revealed the top four potential inhibitors. Further binding free energy (ΔGbind) analysis of the potential inhibitors revealed the best potential lead compound against transmembrane protease serine 4. Drug likeliness nature of the top four potential hits were additionally analyzed in comparison to TSL to confirm on the best potential lead compound with the highest % of human oral absorption. Consequently, e-pharmacophore mapping of the best potential lead compound yielded a six point feature. It was observed to contain four hydrogen bond donor sites (D), one positively ionizable site (P) and one aromatic ring (R). Such e-pharmacophore insight obtained from structural determinants by integrated computational analysis could serve as a framework for further advancement of drug discovery process of new anti-cancer agents with less toxicity and high specificity targeting transmembrane protease serine 4 and hepatocellular carcinoma.

Molecular simulation studies on the binding selectivity of 2-anilino-4-(thiazol-5-yl)-pyrimidines in complexes with CDK2 and CDK7

Molecular modeling simulations were performed to explore the selectivity mechanism of inhibitors binding to CDK2 and CDK7.

Identification of an Inhibitor of the Aminoglycoside 6'-N-Acetyltransferase type Ib [AAC(6')-Ib] by Glide Molecular Docking

The aminoglycoside 6'-N-acetyltransferase type Ib, AAC(6')-Ib, confers resistance to clinically relevant aminoglycosides and is the most widely distributed enzyme among AAC(6')-I-producing Gram-negative pathogens. An alternative to counter the action of this enzyme is the development of inhibitors. Glide is a computational strategy for rapidly docking ligands to protein sites and estimating their binding affinities. We docked a collection of 280,000 compounds from 7 sub-libraries of the Chembridge library as ligands to the aminoglycoside binding site of AAC(6')-Ib. We identified a compound, 1-[3-(2-aminoethyl)benzyl]-3-(piperidin-1-ylmethyl)pyrrolidin-3-ol (compound 1), that inhibited the acetylation of aminoglycosides in vitro with IC50 values of 39.7 and 34.9 µM when the aminoglycoside substrates assayed were kanamycin A or amikacin, respectively. The growth of an amikacin-resistant Acinetobacter baumannii clinical strain was inhibited in the presence of a combination of amikacin and compound 1.

Insights on Structural Characteristics and Ligand Binding Mechanisms of CDK2

Cyclin-dependent kinase 2 (CDK2) is a crucial regulator of the eukaryotic cell cycle. However it is well established that monomeric CDK2 lacks regulatory activity, which needs to be aroused by its positive regulators, cyclins E and A, or be phosphorylated on the catalytic segment. Interestingly, these activation steps bring some dynamic changes on the 3D-structure of the kinase, especially the activation segment. Until now, in the monomeric CDK2 structure, three binding sites have been reported, including the adenosine triphosphate (ATP) binding site (Site I) and two non-competitive binding sites (Site II and III). In addition, when the kinase is subjected to the cyclin binding process, the resulting structural changes give rise to a variation of the ATP binding site, thus generating an allosteric binding site (Site IV). All the four sites are demonstrated as being targeted by corresponding inhibitors, as is illustrated by the allosteric binding one which is targeted by inhibitor ANS (fluorophore 8-anilino-1-naphthalene sulfonate). In the present work, the binding mechanisms and their fluctuations during the activation process attract our attention. Therefore, we carry out corresponding studies on the structural characterization of CDK2, which are expected to facilitate the understanding of the molecular mechanisms of kinase proteins. Besides, the binding mechanisms of CDK2 with its relevant inhibitors, as well as the changes of binding mechanisms following conformational variations of CDK2, are summarized and compared. The summary of the conformational characteristics and ligand binding mechanisms of CDK2 in the present work will improve our understanding of the molecular mechanisms regulating the bioactivities of CDK2.

Insights into the structural basis of 3,5-diaminoindazoles as CDK2 inhibitors: prediction of binding modes and potency by QM-MM interaction, MESP and MD simulation

The novel 3,5-diaminoindazole derivatives are well-known as potent and anti-proliferative cyclin-dependent kinase 2 inhibitors. We report a combined quantum mechanics/molecular mechanics study to determine the protein-ligand interaction energy, and some quantum chemical descriptors to successfully rank these inhibitors. The results in this work show that the QM-MM interaction energy is strongly correlated to the biological activity and can be used as a predictor, which was further validated by Spearman's rank correlation coefficient. An exhaustive analysis of the protein-ligand structures obtained from molecular dynamics simulations shows specific interactions within the active site. Furthermore, the docking study was supported by electronic property analysis using density functional theory at the B3LYP/3-21*G level. The results obtained from molecular docking and surface analysis shed some insight on steric and electronic complementarities of these molecules to CDK2. Aqueous solvation energy values give an indication of the solubility and can be used as a guide for the pharmacokinetic optimization of these molecules. Furthermore, ADME/T properties calculated are in the desirable range, so these compounds are predicted to be drug like with low toxicity potential. Overall, the approach was successful in the cases considered, and it could be useful for the design of inhibitors in the lead optimization phase of drug discovery against CDK2.

The impact of molecular dynamics on drug design: applications for the characterization of ligand-macromolecule complexes

Among all tools available to design new drugs, molecular dynamics (MD) simulations have become an essential technique. Initially developed to investigate molecular models with a limited number of atoms, computers now enable investigations of large macromolecular systems with a simulation time reaching the microsecond range. The reviewed articles cover four years of research to give an overview on the actual impact of MD on the current medicinal chemistry landscape with a particular emphasis on studies of ligand-protein interactions. With a special focus on studies combining computational approaches with data gained from other techniques, this review shows how deeply embedded MD simulations are in drug design strategies and articulates what the future of this technique could be.

Exploring molecular fingerprints of selective PPARδ agonists through comparative and validated chemometric techniques

Peroxysome proliferator-activated receptors (PPARs) have grown greatly in importance due to their role in the metabolic profile. Among three subtypes (α, γ and δ), we here consider the least investigated δ subtype to explore the molecular fingerprints of selective PPARδ agonists. Validated QSAR models (regression based 2D-QSAR, HQSAR and KPLS) and molecular docking with dynamics analyses support the inference of classification-based Bayesian and recursive models. Chemometric studies indicate that the presence of ether linkages and heterocyclic rings has optimum influence in imparting selective bioactivity. Pharmacophore models and docking with molecular dynamics analyses postulate the occurrence of aromatic rings, HB acceptor and a hydrophobic region as crucial molecular fragments for development of PPARδ modulators. Multi-chemometric studies suggest the essential structural requirements of a molecule for imparting potent and selective PPARδ modulation.

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

Binding conformation of flavone inhibitors to protein kinase CK2.

Hydrogen bonding plays a significant role in the binding of coomassie brilliant blue-R to hemoglobin: FT-IR, fluorescence and molecular dynamics studies

Coomassie brilliant blue-R (CBB-R) specifically binds to bovine hemoglobin with a stoichiometric ratio of 1 : 1.

Inhibition of acetylcholinesterase by two genistein derivatives: kinetic analysis, molecular docking and molecular dynamics simulation

In this study two genistein derivatives (G1 and G2) are reported as inhibitors of acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE), and differences in the inhibition of AChE are described. Although they differ in structure by a single methyl group, the inhibitory effect of G1 (IC₅₀=264 nmol/L) on AChE was 80 times stronger than that of G2 (IC₅₀=21,210 nmol/L). Enzyme-kinetic analysis, molecular docking and molecular dynamics (MD) simulations were conducted to better understand the molecular basis for this difference. The results obtained by kinetic analysis demonstrated that G1 can interact with both the catalytic active site and peripheral anionic site of AChE. The predicted binding free energies of two complexes calculated by the molecular mechanics/generalized born surface area (MM/GBSA) method were consistent with the experimental data. The analysis of the individual energy terms suggested that a difference between the net electrostatic contributions (ΔE_ele+ΔG_GB) was responsible for the binding affinities of these two inhibitors. Additionally, analysis of the molecular mechanics and MM/GBSA free energy decomposition revealed that the difference between G1 and G2 originated from interactions with Tyr124, Glu292, Val294 and Phe338 of AChE. In conclusion, the results reveal significant differences at the molecular level in the mechanism of inhibition of AChE by these structurally related compounds.

Computational studies on the binding mechanism between triazolone inhibitors and Chk1 by molecular docking and molecular dynamics

Chk1, a serine/threonine protein kinase that participates in transducing DNA damage signals, is an attractive target due to its involvement in tumor initiation and progression. As a novel Chk1 inhibitor, the triazolone's bioactivity mechanism is not clear. In this study, we carried out an integrated computational study that combines molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations to identify the key factors necessary for the bioactivities. With the aim of discerning the structural features that affect the inhibitory activity of triazolones, MK-8776, a Chk1 inhibitor that reached the clinical stage, was also used as a reference for simulations. A comparative analysis of the triazolone inhibitors at the molecular level offers valuable insight into the structural and energetic properties. A general feature is that all the studied inhibitors bind in the pocket characterized by residues Leu14, Val22, Ala35, Glu84, Tyr85, Cys86, and Leu136 of Chk1. Moreover, introducing hydrophobic groups into triazolone inhibitors is favorable for binding to Chk1, which is corroborated by residue Leu136 with a relatively large difference in the contribution between MK-8776 and five triazolones to the total binding free energies. A hydrogen bond between the polar hydrogen atoms at R1 and Cys86 can facilitate proper placement of the inhibitor in the binding pocket of Chk1 that favors binding. However, the introduction of hydrophilic groups into the R2 position diminishes binding affinity. The information provided by this research is of benefit for further rational design of novel promising inhibitors of Chk1.

A combined experimental and computational study of Vam3, a derivative of resveratrol, and Syk interaction

Spleen tyrosine kinase (Syk) plays an indispensable role through preliminary extracellular antigen-induced crosslinking of Fc receptor (FcR) in the pathogenesis of autoimmune disorders, such as rheumatoid arthritis. In this study, we identify Vam3, a dimeric derivative of resveratrol isolated from grapes, as an ATP-competitive inhibitor of Syk with an IC₅₀ of 62.95 nM in an in vitro kinase assay. Moreover, docking and molecular dynamics simulation approaches were performed to get more detailed information about the binding mode of Vam3 and Syk. The results show that 11b-OH on ring-C and 4b-OH on ring-D could form two hydrogen bonds with Glu449 and Phe382 of Syk, respectively. In addition, arene-cation interaction between ring-D of Vam3 and Lys402 of Syk was also observed. These results indicate that ring-C and D play an essential role in Vam3–Syk interaction. Our studies may be helpful in the structural optimization of Vam3, and also aid the design of novel Syk inhibitors in the future.

Targeting the cyclin-binding groove site to inhibit the catalytic activity of CDK2/cyclin A complex using p27(KIP1)-derived peptidomimetic inhibitors

Functionally activated cyclin-dependent kinase 2 (CDK2)/cyclin A complex has been validated as an interesting therapeutic target to develop the efficient antineoplastic drug based on the cell cycle arrest. Cyclin A binds to CDK2 and activates the kinases as well as recruits the substrate and inhibitors using a hydrophobic cyclin-binding groove (CBG). Blocking the cyclin substrate recruitment on CBG is an alternative approach to override the specificity hurdle of the currently available ATP site targeting CDK2 inhibitors. Greater understanding of the interaction of CDK2/cyclin A complex with p27 (negative regulator) reveals that the Leu-Phe-Gly (LFG) motif region of p27 binds with the CBG site of cyclin A to arrest the malignant cell proliferation that induces apoptosis. In the present study, Replacement with Partial Ligand Alternatives through Computational Enrichment (REPLACE) drug design strategies have been applied to acquire LFG peptide-derived peptidomimetics library. The peptidomimetics function is equivalent with respect to substrate p27 protein fashion but does not act as an ATP antagonist. The combined approach of molecular docking, molecular dynamics (MD), and molecular electrostatic potential and ADME/T prediction were carried out to evaluate the peptidomimetics. Resultant interaction and electrostatic potential maps suggested that smaller substituent is desirable at the position of phenyl ring to interact with Trp217, Arg250, and Gln254 residues in the active site. The best docked poses were refined by the MD simulations which resulted in conformational changes. After equilibration, the structure of the peptidomimetic and receptor complex was stable. The results revealed that the various substrate protein-derived peptidomimetics could serve as perfect leads against CDK2 protein.

Comparative analysis of various electrostatic potentials on docking precision against cyclin-dependent kinase 2 protein: a multiple docking approach

The fundamental of molecular modeling is the interaction and binding to form a complex, because it explains the action of most drugs to a receptor active site. In the present study, different semiempirical (RM1, AM1, PM3, MNDO) and ab initio (HF, DFT) charge models were investigated for their performance in prediction of docking pose against CDK2 proteins with their respective inhibitor. Further, multiple docking approaches and Prime/MM-GBSA calculations were applied to predict the binding mode with respective charge model against CDK2 inhibitors. A reliable docking result was obtained using RRD, which showed significance improvement on ligand binding poses and docking score accuracy to the IFD. The combined use of RRD and Prime/MM-GBSA method could give a high correlation between the predicted binding free energy and experimental biological activity. The preliminary results point out that AM1 could be a precious charge model for design of new drugs with enhanced success rate. As a very similar result was also found for a different system of the protein-ligand binding, the suggested scoring function based on AM1 method seems to be applicable in drug design. The results from this study can provide insights into highest success rate for design of potent and selective CDK2 inhibitors.

Drug design of cyclin-dependent kinase 2 inhibitor for melanoma from traditional Chinese medicine

One has found an important cell cycle controller. This guard can decide the cell cycle toward proliferation or quiescence. Cyclin-dependent kinase 2 (CDK2) is a unique target among the CDK family in melanoma therapy. We attempted to find out TCM compounds from TCM Database@Taiwan that have the ability to inhibit the activity of CDK2 by systems biology. We selected Tetrahydropalmatine, Reserpiline, and (+)-Corydaline as the candidates by docking and screening results for further survey. We utilized support vector machine (SVM), multiple linear regression (MLR) models and Bayesian network for validation of predicted activity. By overall analysis of docking results, predicted activity, and molecular dynamics (MD) simulation, we could conclude that Tetrahydropalmatine, Reserpiline, and (+)-Corydaline had better binding affinity than the control. All of them had the ability to inhibit the activity of CDK2 and might have the opportunity to be applied in melanoma therapy.

Performance of the MM/GBSA scoring using a binding site hydrogen bond network-based frame selection: the protein kinase case

Conformational clustering using hydrogen bond network analysis improved the MM/GBSA scoring for some protein-kinase–ligand systems used as case studies.