Ismail Erol

Computational insights into the protonation states of catalytic dyad in BACE1-acyl guanidine based inhibitor complex.

Developing small compound based drugs targeting the β-secretase (BACE) enzyme is one of the most promising strategies in treatment of the Alzheimers disease. As the enzyme shows the activity based on the acid-base reaction at a very narrow pH range, the protonation state of aspartic acids with the residue number 32 and 228 (Asp32 and Asp228), which forms the active site dyad, along with the protonation state of the ligand (substrate or inhibitor) play very critical role in interactions between the ligand and enzyme. Thus, understanding the nature of the protonation state of both enzymes active site dyad and ligand is crucial for drug design in Alzheimers disease field. Here we have investigated the protonation state of the Asp32 and Asp228 residues in the presence of a highly potent beta secretase inhibitor, containing acyl guanidine warhead that have recently been devised but not extensively studied. Our Quantum Mechanical, Molecular Dynamics and Docking studies on all the possible protonation states have suggested that the dyad residues are in di-deprotonated states in the presence of protonated inhibitor.

Structure-based design of hERG-neutral antihypertensive oxazalone and imidazolone derivatives

Angiotensin II receptor type 1 (AT1) antagonists are the most recent drug class against hypertension. Recently first crystal structure of AT1 receptor is deposited to the protein data bank (PDB ID: 4YAY). In this work, several molecular screening methods such as molecular docking and de novo design studies were performed and it is found that oxazolone and imidazolone derivatives reveal similar/better interaction energy profiles compared to the FDA approved sartan molecules at the binding site of the AT1 receptor. A database consisting of 3500-fragments were used to enumerate de novo designed imidazolone and oxazolone derivatives and hereby more than 50000 novel small molecules were generated. These derivatives were then used in high throughput virtual screening simulations (Glide/HTVS) to find potent hit molecules. In addition, virtual screening of around 18 million small drug-like compounds from ZINC database were screened at the binding pocket of the AT1 receptor via Glide/HTVS method. Filtered structures were then used in more sophisticated molecular docking simulations protocols (i.e., Glide/SP; Glide/XP; Glide/IFD; Glide/QPLD, and GOLD). However, the K+ ion channel/drug interactions should also be considered in studies implemented in molecular level against their cardiovascular risks. Thus, selected compounds with high docking scores via all diverse docking algorithms are also screened at the pore domain regions of human ether-a-go-go-related gene (hERG1) K+ channel to remove the high affinity hERG1 blocking compounds. High docking scored compounds at the AT1 with low hERG1 affinity is considered for long molecular dynamics (MD) simulations. Post-processing analysis of MD simulations assisted for better understanding of molecular mechanism of studied compounds at the binding cavity of AT1 receptor. Results of this study can be useful for designing of novel and safe AT1 inhibitors.

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.

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.

Integration of multi-scale molecular modeling approaches with experiments for the in silico guided design and discovery of novel hERG-Neutral antihypertensive oxazalone and imidazolone derivatives and analysis of their potential restrictive effects on cell proliferation

AT1 antagonists is the most recent drug class of molecules against hypertension and they mediate their actions through blocking detrimental effects of angiotensin II (A-II) when acts on type I (AT1) A-II receptor. The effects of AT1 antagonists are not limited to cardiovascular diseases. AT1 receptor blockers may be used as potential anti-cancer agents - due to the inhibition of cell proliferation stimulated by A-II. Therefore, AT1 receptors and the A-II biosynthesis mechanisms are targets for the development of new synthetic drugs and therapeutic treatment of various cardiovascular and other diseases. In this work, multi-scale molecular modeling approaches were performed and it is found that oxazolone and imidazolone derivatives reveal similar/better interaction energy profiles compared to the FDA approved sartan molecules at the binding site of the AT1 receptor. In silico-guided designed hit molecules were then synthesized and tested for their binding affinities to human AT1 receptor in radioligand binding studies, using [125I-Sar1-Ile8] AngII. Among the compounds tested, 19d and 9j molecules bound to receptor in a dose response manner and with relatively high affinities. Next, cytotoxicity and wound healing assays were performed for these hit molecules. Since hit molecule 19d led to deceleration of cell motility in all three cell lines (NIH3T3, A549, and H358) tested in this study, this molecule is investigated in further tests. In two cell lines (HUVEC and MCF-7) tested, 19d induced G2/M cell cycle arrest in a concentration dependent manner. Adherent cells detached from the plates and underwent cell death possibly due to apoptosis at 19d concentrations that induced cell cycle arrest.

Application of Multiscale Simulation Tools on GPCRs. An Example with Angiotensin II Type 1 Receptor

G protein-coupled receptors (GPCRs) represent the biggest class of membrane proteins included in signal transduction cascade across the biological lipid bilayers. They are essential target structures for cell signaling and are of great commercial interest to the pharmaceutical industry (~50% of marketed drugs and ~25% of top-selling drugs targeting this receptor family). Recent advances made in molecular biology and computational chemistry open new avenues for the design of new therapeutic compounds. Molecular biology has recently provided the crystal structures of a few ligand-bound GPCRs in active and inactive states, which can be used as accurate templates in modeling studies. Computational chemistry offers a range of simulation, multiscale modeling with ligand- and structure-based approaches, and virtual screening tools for definition and analysis of protein-ligand, protein-protein, and protein-DNA interactions. Development of new approaches and algorithms on statistical methods and free energy simulations help to predict novel optimal compounds. Integrated approach to drug discovery that combines quantum mechanics calculations, molecular docking, molecular dynamics (MD) simulations, quantitative structure-activity relationships (QSAR), and de novo design studies under a single umbrella can be used for decreasing the risk of false-positive results. Each method has its own pros and cons and, when used alone, is not likely to yield very useful results. However, when these methods are combined with positive feedback loops, they may enhance each other and successful drug leads may be obtained. Moreover, investigating the activation mechanisms and atomistic determinants of ligand binding to GPCR targets would allow greater safety in the human life.

Oligomerization and Cooperativity in GPCRs from the Perspective of the Angiotensin AT1 and Dopamine D2 Receptors

G Protein-Coupled Receptors (GPCRs) can form homo- and heterodimers or constitute higher oligomeric clusters with other heptahelical GPCRs. In this article, multiscale molecular modeling approaches as well as experimental techniques which are used to study oligomerization of GPCRs are reviewed. In particular, the effect of dimerization/oligomerization to the ligand binding affinity of individual protomers and also on the efficacy of the oligomer are discussed by including diverse examples from the literature. In addition, possible allosteric effects that may emerge upon interaction of GPCRs with membrane components, like cholesterol, is also discussed. Investigation of these above-mentioned interactions may greatly contribute to the candidate molecule screening studies and development of novel therapeutics with fewer adverse effects.

Targeting the NF-κB/IκBα complex via fragment-based E-Pharmacophore virtual screening and binary QSAR models

Nuclear factor-κB (NF-κB) transcription factors represent a conserved family of proteins that regulate not only immune cells, but also heart cells, glial cells and neurons, playing a fundamental role in various cellular processes. Due to its dysregulation in certain cancer types as well as in chronic inflammation and autoimmune diseases, it has recently been appreciated as an important therapeutic target. The aim of this study was to investigate the binding pocket of NF-κB (p50/p65) heterodimer complex in association with NF-κB inhibitor IκBα to identify potent ligands via fragment-based e-pharmacophore screening. The ZINC Clean Fragments (∼2 million) and the Schrodingers medically relevant Glide fragments library (∼670) were used to create the e-pharmacophore models at the potential binding site which was validated by site mapping. Glide/HTVS docking was conducted followed by re-docking of the top 20% fragments by Glide/SP and Glide/XP protocols. The top-85000 Glide XP-docked fragments were used to generate the e-pharmacophore hypotheses. The Otava small molecule library (∼260000 drug-like molecules) and 85 known NF-κB inhibitors were additionally screened against the derived e-pharmacophore models. The top-1000 high-scored molecules, which were well aligned to the e-pharmacophore models, from the Otava small molecule library, were then docked into the binding pocket. Finally, the selected 88 hit molecules and the 85 known inhibitors were analyzed by the MetaCore/MetaDrug™ platform, which uses developed binary QSAR models for therapeutic activity prediction as well as pharmacokinetic and toxicity profile predictions of screening molecules. Ligand selection criteria led to the refinement of 3 potent hit molecules using molecular dynamics (MD) simulations to better investigate their structural and dynamical profiles. The selected hit molecules had a low toxicity and a significant therapeutic potential for heart failure, antiviral activity, asthma and depression, all conditions in which NF-κB plays a critical role. These hit ligands were also structurally stable at the NF-κB/IκBα complex as per the MD simulations and MM/GBSA analysis. Two of these ligands (Otava IDs: 1426436 and 6248112) showed stronger binding and therefore are hypothesized to be more potent. The identification of new potent NF-κB/IκBα inhibitors may thus present a novel therapy for inflammation-mediated conditions as well as cancer, facilitating more efficient research, and leading the way to future drug development efforts.

Identification of novel serotonin reuptake inhibitors targeting central and allosteric binding sites: A virtual screening and molecular dynamics simulations study

The serotonin (5-hydroxytryptamine, 5HT) transporter (SERT) is a member of neurotransmitter sodium symporter (NSS) family, which maintains neurotransmitter by reuptaking 5HT into synapses. Decrease in serotonin concentrations in synaptic clefts have been reported to cause psychological and neurological disorders. Therefore, inhibition of SERT is a potent strategy for the treatment of related diseases such as depression. In this study, approximately 260,000 small molecules from an available chemical database have been virtually screened both at central and allosteric binding sites of SERT to identify potent novel candidate SERT inhibitors. A set of docking algorithms were used to predict binding modes and energies of compounds. Screening analyses led three top-ranked hit compounds (160234, Otava ID: 7118020138; 159166, Otava ID: 7117171303; and 69419, Otava ID: 118671819) for central binding site (S1) and one compound (93507, Otava ID: 6248262) for allosteric binding site (S2). These promising compounds are then subjected to long multiple molecular dynamics (MD) simulations to elucidate their structural and dynamical profiles at the binding cavities of SERT. Higher predicted binding affinities of identified compounds were also confirmed with binding free energy calculations (MM/GBSA) in comparison with the reference central and allosteric binding site inhibitors, paroxetine (8PR) and escitalopram (68P), respectively. To the best of our knowledge, the present work is the first structure-based high throughput virtual screening study reported using recently revealed crystal structure of SERT for screening inhibitors from chemical databases on S1 and S2 binding sites. Small molecule library screening study yielded candidate compounds both at central and allosteric binding site of SERT, and further experimentation may pave the way for developing novel strong inhibitors.

First universal pharmacophore model for hERG1 K+ channel activators: acthER

The intra-cavitary drug blockade of hERG1 channel has been extensively studied, both experimentally and theoretically. Structurally diverse ligands inadvertently block the hERG1 K+ channel currents lead to drug induced Long QT Syndrome (LQTS). Accordingly, designing either hERG1 channel openers or current activators, with the potential to target other binding pockets of the channel, has been introduced as a viable approach in modern anti-arrhythmia drug development. However, reports and investigations on the molecular mechanisms underlying activators binding to the hERG1 channel remain sparse and the overall molecular design principles are largely unknown. Most of the hERG1 activators were discovered during mandatory screening for hERG1 blockade. To fill this apparent deficit, the first universal pharmacophore model for hERG1 K+ channel activators was developed using PHASE. 3D structures of 18 hERG1 K+ channel activators and their corresponding measured binding affinity values were used in the development of pharmacophore models. These compounds spanned a range of structurally different chemotypes with moderate variation in binding affinity. A five sites AAHRR (A, hydrogen-bond accepting, H, hydrophobic, R, aromatic) pharmacophore model has shown reasonable high statistical results compared to the other developed more than 1000 hypotheses. This model was used to construct steric and electrostatic contour maps. The predictive power of the model was tested with 3 external test set compounds as true unknowns. Finally, the pharmacophore model was combined with the previously developed receptor-based model of hERG1 K+ channel to develop and screen novel activators. The results are quite striking and it suggests a greater future role for pharmacophore modeling and virtual drug screening simulations in deciphering complex patterns of molecular mechanisms of hERG1 channel openers at the target sites. The developed model is available upon request and it may serve as basis for the synthesis of novel therapeutic hERG1 activators.