Integrated Binary QSAR-Driven Virtual Screening and In Vitro Studies for Finding Novel hMAO-B-Selective Inhibitors.

The increased activity of monoamine oxidase (MAO) enzymes may lead to serious consequences since they reduce the level of neurotransmitters and are associated with severe neurodegenerative diseases. The inhibition of this enzyme, especially the B isoform, plays a vital role in the treatment of Parkinson's disease (PD). This study is aimed to find novel human MAO-B (hMAO-B) selective inhibitors. A total of 256.750 compounds from the Otava small molecules database were virtually screened gradually by employing several screening techniques for this purpose. Initially, a high-throughput virtual screening (HTVS) method was employed, and 10% of the molecules having high docking scores were subjected to binary QSAR models for further screening of their therapeutic activities against PD, Alzheimer's disease (AD), and depression as well as for their toxicity and pharmacokinetic properties. Then, enzyme selectivity of the ligands towards the A and B forms that passed through all the filters were studied using the induced-fit docking method and molecular dynamics simulations. At the end of this exhaustive research, we identified two hit molecules ligand 3 (Otava ID: 7131545) and ligand 4 (Otava ID: 7566820). Based on the in vitro results, these two compounds (ligands 3 and 4) together with ligands 1 and 2 found in our previous study showed activity at the nanomolar (nM) level, and the results indicated that these four ligands inhibit hMAO-B better than the FDA-approved drug selegiline.

Discovering novel carbonic anhydrase type IX (CA IX) inhibitors from seven million compounds using virtual screening and in vitro analysis.

Carbonic anhydrase type IX (CA IX) enzyme is mostly over expressed in different cancer cell lines and tumor tissues. Potent CA IX inhibitors can be effective for adjusting the pH imbalance in tumor cells. In the present work, we represented the successful application of high throughput virtual screening (HTVS) of large dataset from ZINC database included of ∼7 million compounds to discover novel inhibitors of CA IX. HTVS and molecular docking were performed using consequence Glide/standard precision (SP), extra precision (XP) and induced fit docking (IFD) molecular docking protocols. For each compound, docking code calculates a set of low-energy poses and then exhaustively scans the binding pocket of the target with small compounds. Novel CA IX inhibitor candidates were suggested based on molecular modeling studies and a few of them were tested using in vitro analysis. These compounds were determined as good inhibitors against human CA IX target with Ki in the range of 0.85-1.58 µM. In order to predict the pharmaceutical properties of the selected compounds, ADME (absorption, distribution, metabolism and excretion) analysis was also carried out.

In silico investigation of PARP-1 catalytic domains in holo and apo states for the design of high-affinity PARP-1 inhibitors.

The rational design of high-affinity inhibitors of poly-ADP-ribose polymerase-1 (PARP-1) is at the heart of modern anti-cancer drug design. While relevance of enzyme to DNA repair processes in cellular environment is firmly established, the structural and functional understanding of the main determinants for high-affinity ligands controlling PARP-1 activity is still lacking. The conserved active site of PARP-1 represents an ideal target for inhibitors and may offer a novel target at the treatment of breast cancer. To fill the gap in the structural knowledge, we report on the combination of molecular dynamics (MD) simulations, principal component analysis (PCA), and conformational analysis that analyzes in great details novel binding mode for a number of inhibitors at the PARP-1. While optimization of the binding affinity for original target is an important goal in the drug design, many of the promising molecules for treatment of the breast cancer are plagued by significant cardiotoxicity. One of the most common side-effects reported for a number of polymerase inhibitors is its off-target interactions with cardiac ion channels and hERG1 channel, in particular. Thus, selected candidate PARP-1 inhibitors were also screened in silico at the central cavities of hERG1 potassium ion channel.

Molecular Simulations of Solved Co-crystallized X-Ray Structures Identify Action Mechanisms of PDEδ Inhibitors.

PDEδ is a small protein that binds and controls the trafficking of RAS subfamily proteins. Its inhibition protects initiation of RAS signaling, and it is one of the common targets considered for oncological drug development. In this study, we used solved x-ray structures of inhibitor-bound PDEδ targets to investigate mechanisms of action of six independent all-atom MD simulations. An analysis of atomic simulations combined with the molecular mechanic-Poisson-Boltzmann solvent accessible surface area/generalized Born solvent accessible surface area calculations led to the identification of action mechanisms for a panel of novel PDEδ inhibitors. To the best of our knowledge, this study is one of the first in silico investigations on co-crystallized PDEδ protein. A detailed atomic-scale understanding of the molecular mechanism of PDEδ inhibition may assist in the design of novel PDEδ inhibitors. One of the most common side effects for diverse small molecules/kinase inhibitors is their off-target interactions with cardiac ion channels and human-ether-a-go-go channel specifically. Thus, all of the studied PDEδ inhibitors are also screened in silico at the central cavities of hERG1 potassium channels.

Modeling and protein engineering studies of active and inactive states of human dopamine D2 receptor (D2R) and investigation of drug/receptor interactions.

Homology model structures of the dopamine D2 receptor (D2R) were generated starting from the active and inactive states of ß2-adrenergic crystal structure templates. To the best of our knowledge, the active conformation of D2R was modeled for the first time in this study. The homology models are built and refined using MODELLER and ROSETTA programs. Top-ranked models have been validated with ligand docking simulations and in silico Alanine-scanning mutagenesis studies. The derived extra-cellular loop region of the protein models is directed toward the binding site cavity which is often involved in ligand binding. The binding sites of protein models were refined using induced fit docking to enable the side-chain refinement during ligand docking simulations. The derived models were then tested using molecular modeling techniques on several marketed drugs for schizophrenia. Alanine-scanning mutagenesis and molecular docking studies gave similar results for marketed drugs tested. We believe that these new D2 receptor models will be very useful for a better understanding of the mechanisms of action of drugs to be targeted to the binding sites of D2Rs and they will contribute significantly to drug design studies involving G-protein-coupled receptors in the future.

Elucidation of conformational states, dynamics, and mechanism of binding in human κ-opioid receptor complexes.

Opioid G protein-coupled receptors (GPCRs) have been implicated in modulating pain, addiction, psychotomimesis, mood and memory, among other functions. We have employed the recently reported crystal structure of the human κ-opioid receptor (κ-OR) and performed molecular dynamics (MD), free energy, and ab initio calculations to elucidate the binding mechanism in complexes with antagonist JDTic and agonist SalA. The two systems were modeled in water and in DPPC lipid bilayers, in order to investigate the effect of the membrane upon conformational dynamics. MD and Atoms in Molecules (AIM) ab initio calculations for the complexes in water showed that each ligand was stabilized inside the binding site of the receptor through hydrogen bond interactions that involved residues Asp138 (with JDTic) and Gln115, His291, Leu212 (with SalA). The static description offered by the crystal structure was overcome to reveal a structural rearrangement of the binding pocket, which facilitated additional interactions between JDTic and Glu209/Tyr139. The role of Glu209 was emphasized, since it belongs to an extracellular loop that covers the binding site of the receptor and is crucial for ligand entrapment. The above interactions were retained in membrane complexes (SalA forms additional hydrogen bonds with Tyr139/312), except the Tyr139 interaction, which is abolished in the JDTic complex. For the first time, we report that JDTic alternates between a "V-shape" (stabilized via a water-mediated intramolecular interaction) and a more extended conformation, a feature that offers enough suppleness for effective binding. Moreover, MM-PBSA calculations showed that the more efficient JDTic binding to κ-OR compared to SalA (ΔGJDTic = -31.6 kcal mol(-1), ΔGSalA = -9.8 kcal mol(-1)) is attributed mostly to differences in electrostatic contributions. Importantly, our results are in qualitative agreement with the experiments (ΔGJDTic,exp = -14.4 kcal mol(-1), ΔGSalA,exp = -10.8 kcal mol(-1)). This study provides previously unattainable information on the dynamics of human κ-OR and insight on the rational design of drugs with improved pharmacological properties.

Elucidation of DNA-Eltrombopag Binding: Electrochemical, Spectroscopic and Molecular Docking Techniques.

Eltrombopag is a powerful adjuvant anticancer drug used in treating MS (myelodysplastic syndrome) and AML (acute myeloid leukemia) diseases. In this study, the interaction mechanism between eltrombopag and DNA was studied by voltammetry, spectroscopic techniques, and viscosity measurements. We developed a DNA-based biosensor and nano-biosensor using reduced graphene oxide-modified glassy carbon electrode to detect DNA-eltrombopag binding. The reduction of desoxyguanosine (dGuo) and desoxyadenosine (dAdo) oxidation signals in the presence of the drug demonstrated that a strong interaction could be established between the eltrombopag and dsDNA. The eltrombopag-DNA interaction was further investigated by UV absorption and fluorescence emission spectroscopy to gain more quantitative insight on binding. Viscosity measurements were utilized to characterize the binding mode of the drug. To shed light on the noncovalent interactions and binding mechanism of eltrombopag molecular docking and molecular dynamics (MD), simulations were performed. Through simultaneously carried out experimental and in silico studies, it was established that the eltrombopag binds onto the DNA via intercalation.

Deciphering the mechanism and binding interactions of Pemetrexed with dsDNA with DNA-targeted chemotherapeutics via spectroscopic, analytical, and simulation studies.

Pemetrexed is a well-known and widely used antineoplastic drug under the category of cytotoxic, folate anti-metabolites that is used in chemotherapeutic treatments, especially in malignant mesothelioma and non-small cell lung carcinoma. Here, the binding mechanism and interactions of Pemetrexed with double strain fish sperm deoxyribonucleic acid (dsDNA) were studied thoroughly both experimentally and theoretically, using multi-spectroscopic techniques and molecular docking simulations. Our ultimate goal is to understand better the potential of such antineoplastic drugs and, hence, to design drugs with high dsDNA binding affinities and fewer adverse effects. We employed several techniques yielding different but complementary results such as UV, fluorescence, thermal denaturation, electrochemical and viscosity, and molecular docking studies under physiological conditions. Our results revealed that the Pemetrexed binds fairly strongly to dsDNA's minor groove through hydrogen bond interactions with the mostly adenine and guanine bases via its p-carbamide and p-carboxylic groups. MD simulations of the drug-dsDNA complex were followed for 50 ns to confirm that interaction is stable and robust electrostatic interactions were due to hydrogen bonding mostly with the adenine and guanine nucleotides in the minor groove.

Detection of Axitinib Using Multiwalled Carbon Nanotube-Fe2O3/Chitosan Nanocomposite-Based Electrochemical Sensor and Modeling with Density Functional Theory.

In this study, axitinib (AXI), a potent and selective inhibitor of vascular endothelial growth factor receptor (VEGFR) tyrosine kinase and used as a second-generation targeted drug, was investigated electrochemically under optimized conditions using multiwalled carbon nanotubes/iron(III) oxide nanoparticle-chitosan nanocomposite (MWCNT/Fe2O3@chitosan NC) modified on the glassy carbon electrode (GCE) surface. Characterization of the modified electrode was performed using scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS). The adsorptive stripping differential pulse voltammetric (AdSDPV) technique was used for the sensitive, rapid, and precise detection of AXI. The current peak obtained with the MWCNT/Fe2O3@chitosan NC modified electrode was 23 times higher compared to the bare electrode. The developed modified electrode showed excellent electrocatalytic activity in AXI oxidation. Under optimized conditions, the effect of supporting electrolyte and pH was investigated, and 0.1 M H2SO4 was chosen as the electrolyte with the highest peak current for the target analyte. In the concentration range of MWCNT/Fe2O3@chitosan NC/GCE, 6 × 10-9 and 1 × 10-6 M, the limit of detection (LOD) and limit of quantification (LOQ) values were calculated to be 0.904 and 0.0301 pM, respectively. Tablet and serum samples were used for the applicability of the developed sensor, relative standard deviation (RSD) values for all samples were below 2%, and the recovery results were 99.23 and 101.84%, respectively. The MWCNT/Fe2O3@chitosan NC/GCE designed to determine AXI demonstrated the applicability, selectivity, precision, and accuracy of the sensor. The mechanism of electron transfer from the modified GCE surface to the analyte solution is studied via modeling the modified GCE surface by the density functional theory (DFT) method at B3LYP/6-311+g(d,p) and M062X/6-31g(d,p) levels. We observed that the iron oxide nanoparticles play an important role in channeling electron flow from the analyte solution to the MWCNT-coated GCE electrode surface. Adsorption of the nanocomposite material onto the GCE surface occurs via strong electrostatic interactions, including ionic and hydrogen bond formations. During the adsorption-controlled oxidation process of the axitinib, the electrons are transferred via the highest occupied molecular orbital (HOMO) localized on the iron oxide moiety to the lowest unoccupied molecular orbital (LUMO) of the MWCNT/GCE surface.

Elucidation of interaction mechanism of hERG1 potassium channel with scorpion toxins BeKm-1 and BmTx3b.

The human ether-a-go-go related gene 1 (hERG1) K+ channels play crucial role in the heart, different regions of brain, endocrine cells, smooth muscle cells, and numerous tumor cells. It is known that the inherited mutations of hERG1 gene may lead to the disorder of cardiac repolarization (i.e., long QT syndrome (LQTS)), which may result in sudden cardiac death. It is known that K+ ion channels involved in signaling pathways lead to cell proliferation or apoptosis and some specific toxins were investigated for diverse therapeutic applications on targeting the hERG1 K+ channel. Thus, investigation of channel/toxin interactions mechanisms in atomic level is an important topic for the development of toxin-based therapeutics. Thus, in this work, the interaction mechanisms of two toxins named as BeKm-1 and BmTx3b with the closed-state hERG1 channel have been studied by using different molecular modeling techniques including protein-protein docking and molecular dynamics (MD) simulations. The crucial residues of toxins in channel interactions have been elucidated. It is found that R1, K6, K18, R20, K23 and R27 residues in BeKm-1 and F1, K7, K19, K20 and K28 in BmTx3b are the important residues involved in the strong interactions with the closed-state hERG1 K+ channel. The results of this study can be used by medicinal chemists in the designing of diverse therapeutic applications of natural or synthetic peptides targeting the closed state hERG1 K+ channels.

Proposing novel MDM2 inhibitors: Combined physics-driven high-throughput virtual screening and in vitro studies.

The mouse double minute 2 (MDM2) protein acts as a negative regulator of the p53 tumor suppressor. It directly binds to the N terminus of p53 and promotes p53 ubiquitination and degradation. Since the most common p53-suppressing mechanisms involve the MDM2, proposing novel inhibitors has been the focus of many in silico and also experimental studies. Thus, here we screened around 500,000 small organic molecules from Enamine database at the binding pocket of this oncogenic target. The screening was achieved systematically with starting from the high-throughput virtual screening method followed by more sophisticated docking approaches. The initial high number of screened molecules was reduced to 100 hits which then were studied extensively for their therapeutic activity and pharmacokinetic properties using binary QSAR models. The structural and dynamical profiles of the selected molecules at the binding pocket of the target were studied thoroughly by all-atom molecular dynamics simulations. The free energy of the binding of the hit molecules was estimated by the MM/GBSA method. Based on docking simulations, binary QSAR model results, and free energy calculations, 11 compounds (E1-E11) were selected for in vitro studies. HUVEC vascular endothelium, colon cancer, and breast cancer cell lines were used for testing the binding affinities of the identified hits and for further cellular effects on human cancer cell. Based on in vitro studies, six compounds (E1, E2, E5, E6, E9, and E11) in breast cancer cell lines and six compounds (E1, E2, E5, E6, E8, and E10) in colon cancer cell lines were found as active. Our results showed that these compounds inhibit proliferation and lead to apoptosis.

Elucidation of binding interactions and mechanism of Fludarabine with dsDNA via multispectroscopic and molecular docking studies.

Fludarabine is a purine derivative, anti-neoplastic drug and is still being used in the treatments of chronic lymphocytic leukemia, small lymphocytic lymphoma, acute myeloid leukemia, Non-Hodgkin's lymphoma. It achieves its function by interacting with DNA. Therefore, the binding interactions of such drugs with deoxyribonucleic acid (DNA) is an important subject for pharmaceutical and biochemical studies aiming at designing better DNA binding drugs. Although DNA binding mode of some of the anti-neoplastic drugs has been studied, DNA interaction of Fludarabine has not been explored yet. For this reason, this work has been dedicated to deciphering the experimental and theoretical investigation of Fludarabine binding mechanism via multispectroscopic techniques including UV absorption spectroscopy, thermal denaturation, fluorescence and FTIR spectroscopy, electrochemical and viscosity measurement methods as well as with molecular docking studies under physiological conditions. We observed in the lowest energy docking poses that Fludarabine binds to DNA via major groove binding mode. The nonplanar and extended structure and hydrogen bonding interactions of Fludarabine with the Adenine-Thymine base-pair played a very decisive role in the binding mode as supported by the experimental results.

Molecular dynamics simulation of water diffusion in MFI-type zeolites.

Molecular dynamics simulation using COMPASS force field has been employed to understand the dynamics of water diffusion and structuring in silicalite-1 and Na-ZSM-5 (Si/Al = 95 and 191) samples at three different temperatures, 297, 354, and 393 K, at a water loading of 8 molecules per unit cell, in canonical ensemble. Diffusion coefficients were significantly reduced upon the introduction of aluminum atoms into the framework, together with charge balancing cations placed in their vicinity, since the ion-dipole interactions dominant in ZSM-5 samples are stronger than the H-bond interactions in silicalite-1. The activation energy of diffusion increased with decreasing Si/Al ratio. In the silicalite-1 and ZSM-5 samples, straight channels were observed to be preferred than the sinusoidal ones and the channel preference was not observed to be a strong function of either temperature or the Si/Al ratio. The ordered structures of the water molecules, forming clusters in the channels of silicalite-1 at low temperature was observed to be broken to some extent by increased temperatures, and decreased Si/Al ratio, resulting in less ordered structures. The positions of the water molecules in the straight and sinusoidal channels for the ZSM-5 samples were mainly determined by the location of the charge compensating cation(s) in the structure, as was shown by the concentration profiles.

Proposing Novel MAO-B Hit Inhibitors Using Multidimensional Molecular Modeling Approaches and Application of Binary QSAR Models for Prediction of Their Therapeutic Activity, Pharmacokinetic and Toxicity Properties.

Monoamine oxidase (MAO) enzymes MAO-A and MAO-B play a critical role in the metabolism of monoamine neurotransmitters. Hence, MAO inhibitors are very important for the treatment of several neurodegenerative diseases such as Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS). In this study, 256 750 molecules from Otava Green Chemical Collection were virtually screened for their binding activities as MAO-B inhibitors. Two hit molecules were identified after applying different filters such as high docking scores and selectivity to MAO-B, desired pharmacokinetic profile predictions with binary quantitative structure-activity relationship (QSAR) models. Therapeutic activity prediction as well as pharmacokinetic and toxicity profiles were investigated using MetaCore/MetaDrug platform which is based on a manually curated database of molecular interactions, molecular pathways, gene-disease associations, chemical metabolism, and toxicity information. Particular therapeutic activity and toxic effect predictions are based on the ChemTree ability to correlate structural descriptors to that property using recursive partitioning algorithm. Molecular dynamics (MD) simulations were also performed to make more detailed assessments beyond docking studies. All these calculations were made not only to determine if studied molecules possess the potential to be a MAO-B inhibitor but also to find out whether they carry MAO-B selectivity versus MAO-A. The evaluation of docking results and pharmacokinetic profile predictions together with the MD simulations enabled us to identify one hit molecule (ligand 1, Otava ID: 3463218) which displayed higher selectivity toward MAO-B than a positive control selegiline which is a commercially used drug for PD therapeutic purposes.

A QM protein-ligand investigation of antipsychotic drugs with the dopamine D2 Receptor (D2R).

The dopamine D2 Receptor (D2R) is a member of the G-Protein-Coupled Receptor family and plays a critical role in neurotransmission activities in the human brain. Dysfunction in dopamine receptor signaling may lead to mental health illnesses such as schizophrenia and Parkinson's disease. D2R is the target protein of the commonly used antipsychotic drugs such as risperidone, clozapine, aripiprazole, olanzapine, ziprasidone, and quetiapine. Due to their significant side effects and non-selective profiles, the discovery of novel drugs has become a challenge for researchers working in this field. Recently, our group has focused on the interactions of these drug molecules in the active site of the D2R using different in silico approaches. We here compare the performances of different approaches in estimating the drug binding affinities using quantum chemical approaches. Conformations of drug molecules (ligands) at the binding site of the D2R taken from the preliminary docking studies and molecular dynamics simulations were used to generate protein-ligand interaction models. In a first approach, the BSSE-corrected interaction energies of the ligands with the most critical amino acid Asp114 and with the other amino acids closest to ligands in the binding cavity were calculated separately by density functional theory method in implicit water environment at the M06-2X/6-31 g(d,p) level of the theory. In a second approach, ligand binding affinities were calculated by taking into consideration not only the interaction energies but also deformation and desolvation energies of ligands with surrounding amino acid residues, in a radius of 5 Å of the protein-bound ligand. The quantum mechanically obtained results were compared with the experimentally obtained binding affinity values. We concluded that although H-bond interactions of ligands with Asp114 are the most dominant interaction in the binding site, if van der Waals and steric interactions of ligands which have cumulative effect on the ligand binding are not included in the calculations, the interaction energies are overestimated.

Adsorption of dihalogen molecules on pristine graphene surface: Monte Carlo and molecular dynamics simulation studies.

Weak interactions of graphene surface with reactive molecular impurities are the subject of many studies since noncovalent functionalization of surface via molecular doping is a powerful tool for tuning the electronic properties of graphene layers. In this work, the adsorption of diatomic halogen gas molecules, F2, Cl2, Br2, I2 onto bilayer and multilayer pristine graphene surfaces were studied comparatively by Monte Carlo (MC) and molecular dynamics (MD) simulation techniques in canonical ensemble. The adsorption sites, adsorption capacity, coverage factors, adsorption isotherms, and adsorption kinetics were investigated and the adsorption energies were calculated for all adsorbates. Graphene was modeled as a two-dimensional layer of 200 carbon atoms in a honeycomb arrangement. The COMPASS force field was used in the simulations. The adsorption isotherms were obtained and fitted to Langmuir model. The kinetics of adsorption was studied and found to be first order. Both the monolayer and the multilayer adsorption of halogen molecules showed that van der Waals volumes of halogen molecules and also their polarizabilities display a competitive role in the saturation capacity and the strength of surface interactions.

Atomistic molecular dynamics simulations of typical and atypical antipsychotic drugs at the dopamine D2 receptor (D2R) elucidates their inhibition mechanism.

Dopamine D2 receptor (D2R) plays a pivotal role in nervous systems. Its dysfunction leads to the schizophrenia, Parkinson's diseases and drug addiction. Since the crystal structure of the D2R was not solved yet, discovering of potent and highly selective anti-psychotic drugs carry challenges for different neurodegenerative diseases. In the current study, we modeled the three-dimensional (3D) structure of the D2R based on a recently crystallized structure of the dopamine D3 receptor. These two receptors share a high amino acid sequence homology (>70%). The interaction of the modeled receptor with well-known atypical and typical anti-psychotic drugs and the inhibition mechanisms of drugs at the catalytic domain were studied via atomistic molecular dynamics simulations. Our results revealed that, class-I and class-II forms of atypical and typical D2R antagonists follow different pathways in the inhibition of the D2Rs.

Analysis of the Glutamate Agonist LY404,039 Binding to Nonstatic Dopamine Receptor D2 Dimer Structures and Consensus Docking.

Dopamine receptor D2 (D2R) plays an important role in the human central nervous system and is a focal target of antipsychotic agents. The D2HighR and D2LowR dimeric models previously developed by our group are used to investigate the prediction of binding affinity of the LY404,039 ligand and its binding mechanism within the catalytic domain. The computational data obtained using molecular dynamics simulations fit well with the experimental results. The calculated binding affinities of LY404,039 using MM/PBSA for the D2HighR and D2LowR targets were -12.04 and -9.11 kcal/mol, respectively. The experimental results suggest that LY404,039 binds to D2HighR and D2LowR with binding affinities (Ki) of 8.2 and 1640 nM, respectively. The high binding affinity of LY404,039 in terms of binding to [3H]domperidone was inhibited by the presence of a guanine nucleotide, indicating an agonist action of the drug at D2HighR. The interaction analysis demonstrated that while Asp114 was among the most critical amino acids for D2HighR binding, residues Ser193 and Ser197 were significantly more important within the binding cavity of D2LowR. Molecular modeling analyses are extended to ensemble docking as well as structure-based pharmacophore model (E-pharmacophore) development using the bioactive conformation of LY404,039 at the binding pocket as a template and screening of small-molecule databases with derived pharmacophore models.

Virtual screening of small molecules databases for discovery of novel PARP-1 inhibitors: combination of in silico and in vitro studies.

Poly(ADP-ribose) polymerase-1 (PARP-1) enzyme has critical roles in DNA replication repair and recombination. Thus, PARP-1 inhibitors play an important role in the cancer therapy. In the current study, we have performed combination of in silico and in vitro studies in order to discover novel inhibitors against PARP-1 target. Structure-based virtual screening was carried out for an available small molecules database. A total of 257,951 ligands from Otava database were screened at the binding pocket of PARP-1 using high-throughput virtual screening techniques. Filtered structures based on predicted binding energy results were then used in more sophisticated molecular docking simulations (i.e. Glide/standard precision, Glide/XP, induced fit docking - IFD, and quantum mechanics polarized ligand docking - QPLD). Potential high binding affinity compounds that are predicted by molecular simulations were then tested by in vitro methods. Computationally proposed compounds as PARP-1 inhibitors (Otava Compound Codes: 7111620047 and 7119980926) were confirmed by in vitro studies. In vitro results showed that compounds 7111620047 and 7119980926 have IC50 values of 0.56 and 63 µM against PARP-1 target, respectively. The molecular mechanism analysis, free energy perturbation calculations using long multiple molecular dynamics simulations for the discovered compounds which showed high binding affinity against PARP-1 enzyme, as well as structure-based pharmacophore development (E-pharmacophore) studies were also studied.

The signaling pathway of dopamine D2 receptor (D2R) activation using normal mode analysis (NMA) and the construction of pharmacophore models for D2R ligands.

G-protein-coupled receptors (GPCRs) are targets of more than 30% of marketed drugs. Investigation on the GPCRs may shed light on upcoming drug design studies. In the present study, we performed a combination of receptor- and ligand-based analysis targeting the dopamine D2 receptor (D2R). The signaling pathway of D2R activation and the construction of universal pharmacophore models for D2R ligands were also studied. The key amino acids, which contributed to the regular activation of the D2R, were in detail investigated by means of normal mode analysis (NMA). A derived cross-correlation matrix provided us an understanding of the degree of pair residue correlations. Although negative correlations were not observed in the case of the inactive D2R state, a high degree of correlation appeared between the residues in the active state. NMA results showed that the cytoplasmic side of the TM5 plays a significant role in promoting of residue-residue correlations in the active state of D2R. Tracing motions of the amino acids Arg219, Arg220, Val223, Asn224, Lys226, and Ser228 in the position of the TM5 are found to be critical in signal transduction. Complementing the receptor-based modeling, ligand-based modeling was also performed using known D2R ligands. The top-scored pharmacophore models were found as 5-sited (AADPR.671, AADRR.1398, AAPRR.3900, and ADHRR.2864) hypotheses from PHASE modeling from a pool consisting of more than 100 initial candidates. The constructed models using 38 D2R ligands (in the training set) were validated with 15 additional test set compounds. The resulting model correctly predicted the pIC50 values of an additional test set compounds as true unknowns.