Enterocin DD14 can inhibit the infection of eukaryotic cells with enveloped viruses.

Bacteriocins are ribosomally synthesized bacterial peptides endowed with antibacterial, antiprotozoal, anticancer and antiviral activities. In the present study, we evaluated the antiviral activities of two bacteriocins, enterocin DD14 (EntDD14) and lacticaseicin 30, against herpes simplex virus type 1 (HSV-1), human coronavirus 229E (HCoV-229E) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Vero, Huh7 and Vero E6 cells, respectively. In addition, the interactions of these bacteriocins with the envelope glycoprotein D of HSV-1 and the receptor binding domains of HCoV-229E and SARS-CoV-2 have been computationally evaluated using protein-protein docking and molecular dynamics simulations. HSV-1 replication in Vero cells was inhibited by EntDD14 and, to a lesser extent, by lacticaseicin 30 added to cells after virus inoculation. EntDD14 and lacticaseicin 30 had no apparent antiviral activity against HCoV-229E; however, EntDD14 was able to inhibit SARS-CoV-2 in Vero E6 cells. Further studies are needed to elucidate the antiviral mechanism of these bacteriocins.

Utilizing Heteroatom Types and Numbers from Extensive Ligand Libraries to Develop Novel hERG Blocker QSAR Models Using Machine Learning-Based Classifiers.

The human ether-à-go-go-related gene (hERG) channel plays a crucial role in membrane repolarization. Any disruptions in its function can lead to severe cardiovascular disorders such as long QT syndrome (LQTS), which increases the risk of serious cardiovascular problems such as tachyarrhythmia and sudden cardiac death. Drug-induced LQTS is a significant concern and has resulted in drug withdrawals from the market in the past. The main objective of this study is to pinpoint crucial heteroatoms present in ligands that initiate interactions leading to the effective blocking of the hERG channel. To achieve this aim, ligand-based quantitative structure-activity relationships (QSAR) models were constructed using extensive ligand libraries, considering the heteroatom types and numbers, and their associated hERG channel blockage pIC50 values. Machine learning-assisted QSAR models were developed to analyze the key structural components influencing compound activity. Among the various methods, the KPLS method proved to be the most efficient, allowing the construction of models based on eight distinct fingerprints. The study delved into investigating the influence of heteroatoms on the activity of hERG blockers, revealing their significant role. Furthermore, by quantifying the effect of heteroatom types and numbers on ligand activity at the hERG channel, six compound pairs were selected for molecular docking. Subsequent molecular dynamics simulations and per residue MM/GBSA calculations were performed to comprehensively analyze the interactions of the selected pair compounds.

Exploring the binding capacity of lactic acid bacteria derived bacteriocins against RBD of SARS-CoV-2 Omicron variant by molecular simulations.

The changes in the SARS-CoV-2 genome have resulted in the emergence of new variants. Some of the variants have been classified as variants of concern (VOC). These strains have higher transmission rate and improved fitness. One of the prevalent were the Omicron variant. Unlike previous VOCs, the Omicron possesses fifteen mutations on the spike protein's receptor binding domain (RBD). The modifications of spike protein's key amino acid residues facilitate the virus' binding capability against ACE2, resulting in an increase in the infectiousness of Omicron variant. Consequently, investigating the prevention and treatment of the Omicron variant is crucial. In the present study, we aim to explore the binding capacity of twenty-two bacteriocins derived from Lactic Acid Bacteria (LAB) against the Omicron variant by using protein-peptidedocking and molecular dynamics (MD) simulations. The Omicron variant RBD was prepared by introducing fifteen mutations using PyMol. The protein-peptide complexes were obtained using HADDOCK v2.4 docking webserver. Top scoring complexes obtained from HADDOCK webserver were retrieved and submitted to the PRODIGY server for the prediction of binding energies. RBD-bacteriocin complexes were subjected to MD simulations. We discovered promising peptide-based therapeutic candidates for the inhibition of Omicron variant for example Salivaricin B, Pediocin PA 1, Plantaricin W, Lactococcin mmfii and Enterocin A. The lead bacteriocins, except Enterocin A, are biosynthesized by food-grade lactic acid bacteria. Our study puts forth a preliminary information regarding potential utilization of food-grade LAB-derived bacteriocins, particularly Salivaricin B and Pediocin PA 1, for Covid-19 treatment and prophylaxis.Communicated by Ramaswamy H. Sarma.

In Silico Analysis of Bacteriocins from Lactic Acid Bacteria Against SARS-CoV-2.

The COVID-19 pandemic caused by a novel coronavirus (SARS-CoV-2) is a serious health concern in the twenty-first century for scientists, health workers, and all humans. The absence of specific biotherapeutics requires new strategies to prevent the spread and prophylaxis of the novel virus and its variants. The SARS-CoV-2 virus shows pathogenesis by entering the host cells via spike protein and Angiotensin-Converting Enzyme 2 receptor protein. Thus, the present study aims to compute the binding energies between a wide range of bacteriocins with receptor-binding domain (RBD) on spike proteins of wild type (WT) and beta variant (lineage B.1.351). Molecular docking analyses were performed to evaluate binding energies. Upon achieving the best bio-peptides with the highest docking scores, further molecular dynamics (MD) simulations were performed to validate the structure and interaction stability. Protein-protein docking of the chosen 22 biopeptides with WT-RBD showed docking scores lower than -7.9 kcal/mol. Pediocin PA-1 and salivaricin P showed the lowest (best) docking scores of - 12 kcal/mol. Pediocin PA-1, salivaricin B, and salivaricin P showed a remarkable increase in the double mutant's predicted binding affinity with -13.8 kcal/mol, -13.0 kcal/mol, and -12.5 kcal/mol, respectively. Also, a better predicted binding affinity of pediocin PA-1 and salivaricin B against triple mutant was observed compared to the WT. Thus, pediocin PA-1 binds stronger to mutants of the RBD, particularly to double and triple mutants. Salivaricin B showed a better predicted binding affinity towards triple mutant compared to WT, showing that it might be another bacteriocin with potential activity against the SARS-CoV-2 beta variant. Overall, pediocin PA-1, salivaricin P, and salivaricin B are the most promising candidates for inhibiting SARS-CoV-2 (including lineage B.1.351) entrance into the human cells. These bacteriocins derived from lactic acid bacteria hold promising potential for paving an alternative way for treatment and prophylaxis of WT and beta variants.

Evolutionary association of receptor-wide amino acids with G protein-coupling selectivity in aminergic GPCRs.

G protein-coupled receptors (GPCRs) induce signal transduction pathways through coupling to four main subtypes of G proteins (Gs, Gi, Gq, and G12/13), selectively. However, G protein selective activation mechanisms and residual determinants in GPCRs have remained obscure. Herein, we performed extensive phylogenetic analysis and identified specifically conserved residues for the aminergic receptors having similar coupling profiles. By integrating our methodology of differential evolutionary conservation of G protein-specific amino acids with structural analyses, we identified specific activation networks for Gs, Gi1, Go, and Gq To validate that these networks could determine coupling selectivity we further analyzed Gs-specific activation network and its association with Gs selectivity. Through molecular dynamics simulations, we showed that previously uncharacterized Glycine at position 7x41 plays an important role in receptor activation and it may determine Gs coupling selectivity by facilitating a larger TM6 movement. Finally, we gathered our results into a comprehensive model of G protein selectivity called "sequential switches of activation" describing three main molecular switches controlling GPCR activation: ligand binding, G protein selective activation mechanisms, and G protein contact.

Near-physiological-temperature serial crystallography reveals conformations of SARS-CoV-2 main protease active site for improved drug repurposing.

The COVID-19 pandemic has resulted in 198 million reported infections and more than 4 million deaths as of July 2021 (covid19.who.int). Research to identify effective therapies for COVID-19 includes: (1) designing a vaccine as future protection; (2) de novo drug discovery; and (3) identifying existing drugs to repurpose them as effective and immediate treatments. To assist in drug repurposing and design, we determine two apo structures of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease at ambient temperature by serial femtosecond X-ray crystallography. We employ detailed molecular simulations of selected known main protease inhibitors with the structures and compare binding modes and energies. The combined structural and molecular modeling studies not only reveal the dynamics of small molecules targeting the main protease but also provide invaluable opportunities for drug repurposing and structure-based drug design strategies against SARS-CoV-2.

Toward Understanding the Impact of Dimerization Interfaces in Angiotensin II Type 1 Receptor.

Angiotensin II type 1 receptor (AT1R) is a prototypical class A G protein-coupled receptor (GPCR) that has an important role in cardiovascular pathologies and blood pressure regulation as well as in the central nervous system. GPCRs may exist and function as monomers; however, they can assemble to form higher order structures, and as a result of oligomerization, their function and signaling profiles can be altered. In the case of AT1R, the classical Gαq/11 pathway is initiated with endogenous agonist angiotensin II binding. A variety of cardiovascular pathologies such as heart failure, diabetic nephropathy, atherosclerosis, and hypertension are associated with this pathway. Recent findings reveal that AT1R can form homodimers and activate the noncanonical (ß-arrestin-mediated) pathway. Nevertheless, the exact dimerization interface and atomic details of AT1R homodimerization have not been still elucidated. Here, six different symmetrical dimer interfaces of AT1R are considered, and homodimers were constructed using other published GPCR crystal dimer interfaces as template structures. These AT1R homodimers were then inserted into the model membrane bilayers and subjected to all-atom molecular dynamics simulations. Our simulation results along with the principal component analysis and water pathway analysis suggest four different interfaces as the most plausible: symmetrical transmembrane (TM)1,2,8; TM5; TM4; and TM4,5 AT1R dimer interfaces that consist of one inactive and one active protomer. Moreover, we identified ILE2386.33 as a hub residue in the stabilization of the inactive state of AT1R.

Current status of multiscale simulations on GPCRs.

Membrane receptors couple signaling pathways using various mechanisms. G Protein-Coupled Receptors (GPCRs) represent the largest class of membrane proteins involved in signal transduction across the biological membranes. They are essential targets for cell signaling and are of great commercial interest to the pharmaceutical industry. Recent advances made in molecular biology and computational chemistry offer a range of simulation and multiscale modeling tools for the definition and analysis of protein-ligand, protein-protein, and protein-membrane interactions. The development of new techniques on statistical methods and free energy simulations help to predict novel optimal ligands, G protein specificity and oligomerization. The identification of the ligand-binding activation mechanisms and atomistic determinants as well as the interactions of intracellular binding partners that bind to GPCR targets in different coupling states will provide greater safety in human life. In this review, recent approaches and applications of multiscale simulations on GPCRs were highlighted.

Fast-dissolving electrospun gelatin nanofibers encapsulating ciprofloxacin/cyclodextrin inclusion complex.

Electrospun gelatin nanofibrous matrix encapsulating ciprofloxacin (CIP)/hydroxypropyl-beta-cyclodextrin (HPßCD)-inclusion complex (IC) was produced via electrospinning method. Computational modeling indicated that van der Waals forces are the most significant driving forces for the complexation and hydrophobic moiety (piperazinyl) of CIP, which was included in the cavity of HPßCD. The FTIR and XRD studies indicated the formation of CIP/HPßCD host/guest complexation, FTIR also suggested that hydrophobic moiety of CIP is in the HPßCD cavity in parallel with the computational modeling results. The phase solubility diagram demonstrated that the solubility of CIP was enhanced after complexation with HPßCD. SEM images showed that electrospun gelatin nanofibers encapsulating CIP/HPßCD-IC have bead-free morphology with a diameter of ˜90 nm. The gelatin nanofibrous mat loaded with CIP/HPßCD-IC has exhibited fast-dissolving character in water compared to gelatin/CIP nanofibrous mat due to the enhanced wettability of the nanofibrous mat by HPßCD and improvement achieved in the solubility of CIP.

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 Schrodinger's 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.

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.

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.

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.

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.

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.

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.

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.

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.

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

Developing small compound based drugs targeting the ß-secretase (BACE) enzyme is one of the most promising strategies in treatment of the Alzheimer's 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 enzyme's active site dyad and ligand is crucial for drug design in Alzheimer's 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.