Modeling of noncovalent inhibitors of the papain-like protease (PLpro) from SARS-CoV-2 considering the protein flexibility by using molecular dynamics and cross-docking

The papain-like protease (PLpro) found in coronaviruses that can be transmitted from animals to humans is a critical target in respiratory diseases linked to Severe Acute Respiratory Syndrome (SARS-CoV). Researchers have proposed designing PLpro inhibitors. In this study, a set of 89 compounds, including recently reported 2-phenylthiophenes with nanomolar inhibitory potency, were investigated as PLpro noncovalent inhibitors using advanced molecular modeling techniques. To develop the work with these inhibitors, multiple structures of the SARS-CoV-2 PLpro binding site were generated using a molecular sampling method. These structures were then clustered to select a group that represents the flexibility of the site. Subsequently, models of the protein-ligand complexes were created for the set of inhibitors within the chosen conformations. The quality of the complex models was assessed using LigRMSD software to verify similarities in the orientations of the congeneric series and interaction fingerprints to determine the recurrence of chemical interactions. With the multiple models constructed, a protocol was established to choose one per ligand, optimizing the correlation between the calculated docking energy values and the biological activities while incorporating the effect of the binding site's flexibility. A strong correlation (R2 = 0.922) was found when employing this flexible docking protocol.

Elucidating binding mechanisms of naringenin by alpha-chymotrypsin: Insights into non-binding interactions and complex formation

As an inevitable parameter in the description of enzyme properties, the investigation of enzyme-ligand interactions has attracted a lot of attention. Alpha-Chymotrypsin (α-Chy) is essential for protein digestion and plays an important role in human health. Naringenin (NAG) as a potent antioxidant has recently been applied in the pharmaceutical industry. Using multispectral methods and computational simulation techniques, the binding strength of NAG to α-Chy was investigated in this research. UV-vis and fluorescence quenching data showed significant spectral changes upon binding of NAG to α-Chy. As demonstrated by fluorescence techniques, NAG could employ a static quenching process to decrease the intrinsic fluorescence of α-Chy. Both circular dichroism (CD) and FTIR spectroscopic analyses revealed that binding of NAG to α-Chy caused more flexible conformation. The slight increases in RMSD (0.06 nm) were observed for the NAG-(α-Chy) compound was supported by the results of thermal stability data. Docking computation confirmed that hydrogen and Van der Waals interactions are the important forces, which is in exact agreement with thermodynamics studies. Kinetic analysis of the enzyme showed an increase in activity, which was consistent, with the MD simulation results. The findings from the in-silico studies were in complete agreement with the experimental results.

Computational study of the binding orientation and affinity of noncovalent inhibitors of the papain-like protease (PLpro) from SARS-CoV-1 considering the protein flexibility by using molecular dynamics and cross-docking

The papain-like protease (PLpro) from zoonotic coronaviruses (CoVs) has been identified as a target with an essential role in viral respiratory diseases caused by Severe Acute Respiratory Syndrome-associated coronaviruses (SARS-CoVs). The design of PLpro inhibitors has been proposed as an alternative to developing potential drugs against this disease. In this work, 67 naphthalene-derived compounds as noncovalent PLpro inhibitors were studied using molecular modeling methods. Structural characteristics of the bioactive conformations of these inhibitors and their interactions at the SARS-CoV-1 PLpro binding site were reported here in detail, taking into account the flexibility of the protein residues. Firstly, a molecular docking protocol was used to obtain the orientations of the inhibitors. After this, the orientations were compared, and the recurrent interactions between the PLpro residues and ligand chemical groups were described (with LigRMSD and interaction fingerprints methods). In addition, efforts were made to find correlations between docking energy values and experimentally determined binding affinities. For this, the PLpro was sampled by using Gaussian Accelerated Molecular Dynamics (GaMD), generating multiple conformations of the binding site. Diverse protein conformations were selected and a cross-docking experiment was performed, yielding models of the 67 naphthalene-derived compounds adopting different binding modes. Representative complexes for each ligand were selected to obtain the highest correlation between docking energies and activities. A good correlation (R ² = 0.948) was found when this flexible docking protocol was performed.

Comparative study on the interaction between flavonoids with different core structures and hyaluronidase

Hyaluronidase (HAase) is an important enzyme involved in a promoting inflammation pathway. Flavonoids are a group of major polyphenols including flavonols (such as myricetin and rutin), dihydroflavones (such as naringin and hesperidin), and isoflavones (such as genistein and puerarin), which have been proved to possess anti-inflammatory effects. In this study, the binding of the six flavonoids to HAase was investigated by steady state and time-resolved fluorescence, circular dichroism (CD) spectroscopy and molecular docking methods. Fluorescence data reveal that the fluorescence quenching mechanism of HAase by flavonoids is all static quenching procedure regardless of their core structure. The binding affinity is strongest for rutin and ranks in the order rutin > hesperidin > myricetin > puerarin > genistein > naringin. The thermodynamic analysis implies that hydrophobic interaction, electrostatic force and hydrogen bonding are the main interaction forces. Synchronous fluorescence spectroscopy and CD spectroscopy indicate that flavonoids have the same core structure and have similar effects on the microenvironment around Trp and Tyr residues and the secondary structure of HAase. The results of molecular docking show that the binding of flavonoids with the catalytic amino acid residues of HAase may lead to the decrease of enzyme activity.

Exploring the interactions of naringenin and naringin with trypsin and pepsin: Experimental and computational modeling approaches

Naringenin and naringin are two natural compounds with important health benefits, whether as food or drug. It is necessary to study the interactions between naringenin/naringin and digestive proteases, such as trypsin and pepsin. In this study, the bindings of naringenin and naringin to trypsin and pepsin were investigated using multi-spectroscopy analysis and computational modeling approaches. Fluorescence experiments indicate that both naringenin and naringin can quench the intrinsic fluorescence of trypsin/pepsin via static quenching mechanism. Naringin binds trypsin/pepsin in a more firmly way than naringenin. Thermodynamic analysis reveals that the interactions of naringenin/naringin and trypsin/pepsin are synergistically driven by enthalpy and entropy, and the major driving forces are hydrophobic, electrostatic interactions and hydrogen bonding. Synchronous fluorescence spectroscopy, circular dichroism spectroscopy and FT-IR show that naringenin/naringin may induce microenvironmental and conformational changes of trypsin and pepsin. Molecular docking reveals that naringenin binds in the close vicinity of the active site (Ser-195) of trypsin and Asp-32 (the catalytic activity of pepsin) appears in naringin-pepsin system. The direct interactions between naringenin or naringin and catalytic amino acid residues will inhibit the catalytic activity of trypsin and pepsin, respectively. The results of molecular dynamic simulation validate the reliability of the docking results.

Designing of the N-ethyl-4-(pyridin-4-yl)benzamide based potent ROCK1 inhibitors using docking, molecular dynamics, and 3D-QSAR

Rho-associated kinase-1 (ROCK1) has been recognized for its pivotal role in heart diseases, different types of malignancy, and many neurological disorders. Hyperactivity of ROCK phosphorylates the protein kinase-C (PKC), which ultimately induces smooth muscle cell contraction in the vascular system. Inhibition of ROCK1 has been shown to be a promising therapy for patients with cardiovascular disease. In this study, we have conducted molecular modeling techniques such as docking, molecular dynamics (MD), and 3-Dimensional structure-activity relationship (3D-QSAR) on a series of N-ethyl-4-(pyridin-4-yl)benzamide-based compounds. Docking and MD showed critical interactions and binding affinities between ROCK1 and its inhibitors. To establish the structure-activity relationship (SAR) of the compounds, 3D-QSAR techniques such as Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were used. The CoMFA (q ² = 0.774, r ² = 0.965, ONC = 6, and r p r e d 2 = 0.703) and CoMSIA (q ² = 0.676, r ² = 0.949, ONC = 6, and r p r e d 2 = 0.548) both models have shown reasonable external predictive activity, and contour maps revealed favorable and unfavorable substitutions for chemical group modifications. Based on the contour maps, we have designed forty new compounds, among which, seven compounds exhibited higher predictive activity (pIC₅₀). Further, we conducted the MD study, ADME/Tox, and SA score prediction using the seven newly designed compounds. The combination of docking, MD, and 3D-QSAR studies helps to understand the coherence modification of existing molecules. Our study may provide valuable insight into the development of more potent ROCK1 inhibitors.

Design and identification of two novel resveratrol derivatives as potential LSD1 inhibitors

Background: Overexpression of LSD1 is associated with the occurrence of many diseases, including cancers, which makes LSD1 a significant target for anticancer drug research. Methodology & Results: With the aid of 3D quantitative structure-activity relationship models established with 34 reported resveratrol derivative LSD1 inhibitors, derivatives 35-40 were designed. Absorption, distribution, metabolism and excretion calculations showed that they may have good bioavailability and drug likeness. Additionally, 35 and 37 presented good antitumor effects in an in vitro antiproliferative assay. Molecular docking and molecular dynamics simulation results indicated that 35 and 37 can establish extensive interactions with LSD1. Conclusion: The results of computational prediction and experimental validation suggest that 35 and 37 are effective antitumor inhibitors, which provides some ideas and directions for the development of new anticancer LSD1 inhibitors.

Computational Modeling to Explain Why 5,5-Diarylpentadienamides are TRPV1 Antagonists

Several years ago, the crystallographic structures of the transient receptor potential vanilloid 1 (TRPV1) in the presence of agonists and antagonists were reported, providing structural information about its chemical activation and inactivation. TRPV1’s activation increases the transport of calcium and sodium ions, leading to the excitation of sensory neurons and the perception of pain. On the other hand, its antagonistic inactivation has been explored to design analgesic drugs. The interactions between the antagonists 5,5-diarylpentadienamides (DPDAs) and TRPV1 were studied here to explain why they inactivate TRPV1. The present work identified the structural features of TRPV1–DPDA complexes, starting with a consideration of the orientations of the ligands inside the TRPV1 binding site by using molecular docking. After this, a chemometrics analysis was performed (i) to compare the orientations of the antagonists (by using LigRMSD), (ii) to describe the recurrent interactions between the protein residues and ligand groups in the complexes (by using interaction fingerprints), and (iii) to describe the relationship between topological features of the ligands and their differential antagonistic activities (by using a quantitative structure–activity relationship (QSAR) with 2D autocorrelation descriptors). The interactions between the DPDA groups and the residues Y511, S512, T550, R557, and E570 (with a recognized role in the binding of classic ligands), and the occupancy of isoquinoline or 3-hydroxy-3,4-dihydroquinolin-2(1H)-one groups of the DPDAs in the vanilloid pocket of TRPV1 were clearly described. Based on the results, the structural features that explain why DPDAs inactivate TRPV1 were clearly exposed. These features can be considered for the design of novel TRPV1 antagonists.

The latest automated docking technologies for novel drug discovery

INTRODUCTION

Molecular docking has been consolidated as one of the most important methods in the molecular modeling field. It has been recognized as a prominent tool in the study of protein-ligand complexes, to describe intermolecular interactions, to accurately predict poses of multiple ligands, to discover novel promising bioactive compounds. Molecular docking methods have evolved in terms of their accuracy and reliability; but there are pending issues to solve for improving the connection between the docking results and the experimental evidence.

AREAS COVERED

In this article, the author reviews very recent innovative molecular docking applications with special emphasis on reverse docking, treatment of protein flexibility, the use of experimental data to guide the selection of docking poses, the application of Quantum mechanics(QM) in docking, and covalent docking.

EXPERT OPINION

There are several issues being worked on in recent years that will lead to important breakthroughs in molecular docking methods in the near future These developments are related to more efficient exploration of large datasets and receptor conformations, advances in electronic description, and the use of structural information for guiding the selection of results.

Critical Insight into the Design of PPAR-γ Agonists by Virtual Screening Techniques

BACKGROUND

Design of novel PPAR-γ modulators with better binding efficiency and fewer side effects to treat type 2 diabetes is still a challenge for medicinal chemists. Cost and time efficient computational methods have presently become an integral part of research in nuclear receptors and their ligands, enabling hit to lead identification and lead optimization. This review will focus on cutting-edge technologies used in most recent studies on the design of PPAR- γ agonists and will discuss the chemistry of few molecules which emerged successful.

METHODS

Literature review was carried out in google scholar using customized search from 2011- 2017. Computer-aided design methods presented in this article were used as search terms to retrieve corresponding literature.

RESULTS

Virtual screening of natural product libraries is an effective strategy to harness nature as the source of ligands for PPARs. Rigid and induced fit docking and core hopping approach in docking are rapid screening methods to predict the PPAR- γ and PPAR-α/ γ dual agonistic activity. Onedimensional drug profile matching is one of the recent virtual screening methods by which an antiprotozoal drug, Nitazoxanide was identified as a PPAR- γ agonist.

CONCLUSION

It is concluded that to achieve a convincing and reliable design of PPAR-γ agonist by virtual screening techniques, customized workflow comprising of appropriate models is essential in which methods may be applied either sequentially or simultaneously.

3D-QSAR, molecular docking, and molecular dynamics simulation study of thieno[3,2-b]pyrrole-5-carboxamide derivatives as LSD1 inhibitors

Histone Lysine Specific Demethylase 1 (LSD1) is overexpressed in many cancers and becomes a new target for anticancer drugs. In recent years, small molecule inhibitors with various structures targeting LSD1 have been reported. Here we report the binding interaction modes of a series of thieno[3,2-b]pyrrole-5-carboxamide LSD1 inhibitors using molecular docking, and three-dimensional quantitative structure-activity relationships (3D-QSAR). Comparative molecular field analysis (CoMFA q 2 = 0.783, r 2 = 0.944, r pred 2 = 0.851) and comparative molecular similarity indices analysis (CoMSIA q 2 = 0.728, r 2 = 0.982, r pred 2 = 0.814) were used to establish 3D-QSAR models, which had good verification and prediction capabilities. Based on the contour maps and the information of molecular docking, 8 novel small molecules were designed in silico, among which compounds D4, D5 and D8 with high predictive activity were subjected to further molecular dynamics simulations (MD), and their possible binding modes were explored. It was found that Asn535 plays a crucial role in stabilizing the inhibitors. Furthermore, ADME and bioavailability prediction for D4, D5 and D8 were carried out. The results would provide valuable guidance for designing new reversible LSD1 inhibitors in the future.

Considerations for Docking of Selective Angiotensin-Converting Enzyme Inhibitors

The angiotensin-converting enzyme (ACE) is a two-domain dipeptidylcarboxypeptidase, which has a direct involvement in the control of blood pressure by performing the hydrolysis of angiotensin I to produce angiotensin II. At the same time, ACE hydrolyzes other substrates such as the vasodilator peptide bradykinin and the anti-inflammatory peptide N-acetyl-SDKP. In this sense, ACE inhibitors are bioactive substances with potential use as medicinal products for treatment or prevention of hypertension, heart failures, myocardial infarction, and other important diseases. This review examined the most recent literature reporting ACE inhibitors with the help of molecular modeling. The examples exposed here demonstrate that molecular modeling methods, including docking, molecular dynamics (MD) simulations, quantitative structure-activity relationship (QSAR), etc, are essential for a complete structural picture of the mode of action of ACE inhibitors, where molecular docking has a key role. Examples show that too many works identified ACE inhibitory activities of natural peptides and peptides obtained from hydrolysates. In addition, other works report non-peptide compounds extracted from natural sources and synthetic compounds. In all these cases, molecular docking was used to provide explanation of the chemical interactions between inhibitors and the ACE binding sites. For docking applications, most of the examples exposed here do not consider that: (i) ACE has two domains (nACE and cACE) with available X-ray structures, which are relevant for the design of selective inhibitors, and (ii) nACE and cACE binding sites have large dimensions, which leads to non-reliable solutions during docking calculations. In support of the solution of these problems, the structural information found in Protein Data Bank (PDB) was used to perform an interaction fingerprints (IFPs) analysis applied on both nACE and cACE domains. This analysis provides plots that identify the chemical interactions between ligands and both ACE binding sites, which can be used to guide docking experiments in the search of selective natural components or novel drugs. In addition, the use of hydrogen bond constraints in the S₂ and S₂′ subsites of nACE and cACE are suggested to guarantee that docking solutions are reliable.

Tetrahydroquinoline-Isoxazole/Isoxazoline Hybrid Compounds as Potential Cholinesterases Inhibitors: Synthesis, Enzyme Inhibition Assays, and Molecular Modeling Studies

A series of 44 hybrid compounds that included in their structure tetrahydroquinoline (THQ) and isoxazole/isoxazoline moieties were synthesized through the 1,3-dipolar cycloaddition reaction (1,3-DC) from the corresponding N-allyl/propargyl THQs, previously obtained via cationic Povarov reaction. In vitro cholinergic enzymes inhibition potential of all compounds was tested. Enzyme inhibition assays showed that some hybrids exhibited significant potency to inhibit acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). Especially, the hybrid compound 5n presented the more effective inhibition against AChE (4.24 µM) with an acceptable selectivity index versus BChE (SI: 5.19), while compound 6aa exhibited the greatest inhibition activity on BChE (3.97 µM) and a significant selectivity index against AChE (SI: 0.04). Kinetic studies were carried out for compounds with greater inhibitory activity of cholinesterases. Structure–activity relationships of the molecular hybrids were analyzed, through computational models using a molecular cross-docking algorithm and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) binding free energy approach, which indicated a good correlation between the experimental inhibition values and the predicted free binding energy.

Structural Requirements of N-alpha-Mercaptoacetyl Dipeptide (NAMdP) Inhibitors of Pseudomonas Aeruginosa Virulence Factor LasB: 3D-QSAR, Molecular Docking, and Interaction Fingerprint Studies

The zinc metallopeptidase Pseudomonas elastase (LasB) is a virulence factor of Pseudomonas aeruginosa (P. aeruginosa), a pathogenic bacterium that can cause nosocomial infections. The present study relates the structural analysis of 118 N-alpha-mercaptoacetyl dipeptides (NAMdPs) as LasB inhibitors. Field-based 3D-QSAR and molecular docking methods were employed to describe the essential interactions between NAMdPs and LasB binding sites, and the chemical features that determine their differential activities. We report a predictive 3D-QSAR model that was developed according to the internal and external validation tests. The best model, including steric, electrostatic, hydrogen bond donor, hydrogen bond acceptor, and hydrophobic fields, was found to depict a three-dimensional map with the local positive and negative effects of these chemotypes on the LasB inhibitory activities. Furthermore, molecular docking experiments yielded bioactive conformations of NAMdPs inside the LasB binding site. The series of NAMdPs adopted a similar orientation with respect to phosphoramidon within the LasB binding site (crystallographic reference), where the backbone atoms of NAMdPs are hydrogen-bonded to the LasB residues N112, A113, and R198, similarly to phosphoramidon. Our study also included a deep description of the residues involved in the protein-ligand interaction patterns for the whole set of NAMdPs, through the use of interaction fingerprints (IFPs).

Docking, Interaction Fingerprint, and Three-Dimensional Quantitative Structure-Activity Relationship (3D-QSAR) of Sigma1 Receptor Ligands, Analogs of the Neuroprotective Agent RC-33

The human Sigma1 receptor (S1R), which has been identified as a target with an important role in neuropsychological disorders, was first crystallized 3 years ago. Since S1R structure has no relation with another previous crystallized structures, the presence of the new crystal is an important hallmark for the design of agonists and antagonists against this important target. Some years ago, our group identified RC-33, a potent and selective S1R agonist, endowed with neuroprotective properties. In this work, drawing on new structural information, we studied the interactions of RC-33 and its analogs with the S1R binding site by using computational methods such as docking, interaction fingerprints, and receptor-guided alignment three dimensional quantitative structure–activity relationship (3D-QSAR). We found that RC-33 and its analogs adopted similar orientations within S1R binding site, with high similitude with orientations of the crystallized ligands; such information was used for identifying the residues involved in chemical interactions with ligands. Furthermore, the structure-activity relationship of the studied ligands was adequately described considering classical QSAR tests. All relevant aspects of the interactions between the studied compounds and S1R were covered here, through descriptions of orientations, binding interactions, and features that influence differential affinities. In this sense, the present results could be useful in the future design of novel S1R modulators.

Mycobacterium tuberculosis serine/threonine protein kinases: structural information for the design of their specific ATP-competitive inhibitors

In the last decades, human protein kinases (PKs) have been relevant as targets in the development of novel therapies against many diseases, but the study of Mycobacterium tuberculosis PKs (MTPKs) involved in tuberculosis pathogenesis began much later and has not yet reached an advanced stage of development. To increase knowledge of these enzymes, in this work we studied the structural features of MTPKs, with focus on their ATP-binding sites and their interactions with inhibitors. PknA, PknB, and PknG are the most studied MTPKs, which were previously crystallized; ATP-competitive inhibitors have been designed against them in the last decade. In the current work, reported PknA, PknB, and PknG inhibitors were extracted from literature and their orientations inside the ATP-binding site were proposed by using docking method. With this information, interaction fingerprints were elaborated, which reveal the more relevant residues for establishing chemical interactions with inhibitors. The non-crystallized MTPKs PknD, PknF, PknH, PknJ, PknK, and PknL were also studied; their three-dimensional structural models were developed by using homology modeling. The main characteristics of MTPK ATP-binding sites (the non-crystallized and crystallized MTPKs, including PknE and PknI) were accounted; schemes of the main polar and nonpolar groups inside their ATP-binding sites were constructed, which are suitable for a major understanding of these proteins as antituberculotic targets. These schemes could be used for establishing comparisons between MTPKs and human PKs in order to increase selectivity of MTPK inhibitors. As a key tool for guiding medicinal chemists interested in the design of novel MTPK inhibitors, our work provides a map of the structural elements relevant for the design of more selective ATP-competitive MTPK inhibitors.

Insights into the Structural Requirements of 2(S)-Amino-6-Boronohexanoic Acid Derivatives as Arginase I Inhibitors: 3D-QSAR, Docking, and Interaction Fingerprint Studies

Human arginase I (hARGI) is an important enzyme involved in the urea cycle; its overexpression has been associated to cardiovascular and cerebrovascular diseases. In the last years, several congeneric sets of hARGI inhibitors have been reported with possible beneficial roles for the cardiovascular system. At the same time, crystallographic data have been reported including hARGI–inhibitor complexes, which can be considered for the design of novel inhibitors. In this work, the structure–activity relationship (SAR) of Cα substituted 2(S)-amino-6-boronohexanoic acid (ABH) derivatives as hARGI inhibitors was studied by using a three-dimensional quantitative structure–activity relationships (3D-QSAR) method. The predictivity of the obtained 3D-QSAR model was demonstrated by using internal and external validation experiments. The best model revealed that the differential hARGI inhibitory activities of the ABH derivatives can be described by using steric and electrostatic fields; the local effects of these fields in the activity are presented. In addition, binding modes of the above-mentioned compounds inside the hARGI binding site were obtained by using molecular docking. It was found that ABH derivatives adopted the same orientation reported for ABH within the hARGI active site, with the substituents at Cα exposed to the solvent with interactions with residues at the entrance of the binding site. The hARGI residues involved in chemical interactions with inhibitors were identified by using an interaction fingerprints (IFPs) analysis.

Is It Reliable to Take the Molecular Docking Top Scoring Position as the Best Solution without Considering Available Structural Data?

Molecular docking is the most frequently used computational method for studying the interactions between organic molecules and biological macromolecules. In this context, docking allows predicting the preferred pose of a ligand inside a receptor binding site. However, the selection of the “best” solution is not a trivial task, despite the widely accepted selection criterion that the best pose corresponds to the best energy score. Here, several rigid-target docking methods were evaluated on the same dataset with respect to their ability to reproduce crystallographic binding orientations, to test if the best energy score is a reliable criterion for selecting the best solution. For this, two experiments were performed: (A) to reconstruct the ligand-receptor complex by performing docking of the ligand in its own crystal structure receptor (defined as self-docking), and (B) to reconstruct the ligand-receptor complex by performing docking of the ligand in a crystal structure receptor that contains other ligand (defined as cross-docking). Root-mean square deviation (RMSD) was used to evaluate how different the obtained docking orientation is from the corresponding co-crystallized pose of the same ligand molecule. We found that docking score function is capable of predicting crystallographic binding orientations, but the best ranked solution according to the docking energy is not always the pose that reproduces the experimental binding orientation. This happened when self-docking was achieved, but it was critical in cross-docking. Taking into account that docking is typically used with predictive purposes, during cross-docking experiments, our results indicate that the best energy score is not a reliable criterion to select the best solution in common docking applications. It is strongly recommended to choose the best docking solution according to the scoring function along with additional structural criteria described for analogue ligands to assure the selection of a correct docking solution.

Energetic differences between non-domain-swapped and domain-swapped chain connectivities in the K2P potassium channel TRAAK

Two-pore domain (K2P) channels are twofold symmetric K⁺ channels which control cell excitability by enabling the leak of potassium ions from cells in response to physicochemical stimuli. Crystallization of K2P channels revealed the presence of several structural features, which include an external cap. In the available crystallographic structures, the cap is present as non-domain-swapped (NDS) and domain-swapped (DS) chain conformations, where DS chain conformation exchanges two opposing outer helices 180° around the channel. In this work, energy differences between the residues located at the highest point of the cap in NDS and DS conformations were evaluated for TRAAK, a K2P channel that was crystallized in both conformations. Results indicated a preference for DS conformation, but this result is not extensible to TASK K2P channels.

In the available crystallographic structures of K2P channels, the cap is present as non-domain-swapped (NDS) and domain-swapped (DS) chain conformations.

Docking and quantitative structure-activity relationship of bi-cyclic heteroaromatic pyridazinone and pyrazolone derivatives as phosphodiesterase 3A (PDE3A) inhibitors

PDE3s belong to the phosphodiesterases family, where the PDE3A isoform is the major subtype in platelets involved in the cAMP regulation pathway of platelet aggregation. PDE3A inhibitors have been designed as potential antiplatelet agents. In this work, a homology model of PDE3A was developed and used to obtain the binding modes of bicyclic heteroaromatic pyridazinones and pyrazolones. Most of the studied compounds adopted similar orientations within the PDE3A active site, establishing hydrogen bonds with catalytic amino acids. Besides, the structure-activity relationship of the studied inhibitors was described by using a field-based 3D-QSAR method. Different structure alignment strategies were employed, including template-based and docking-based alignments. Adequate correlation models were obtained according to internal and external validations. In general, QSAR models revealed that steric and hydrophobic fields describe the different inhibitory activities of the compounds, where the hydrogen bond donor and acceptor fields have minor contributions. It should be stressed that structural elements of PDE3A inhibitors are reported here, through descriptions of their binding interactions and their differential affinities. In this sense, the present results could be useful in the future design of more specific and potent PDE3A inhibitors that may be used for the treatment of cardiovascular diseases.

Study of the interactions between Edaglitazone and Ciglitazone with PPARγ and their antiplatelet profile

Peroxisome proliferator-activated receptor γ (PPARγ) is a ligand-activated transcription factor with an important role in lipid metabolism, inflammation and cardiovascular diseases. PPARγ ligands have inhibitory effects on platelet aggregation via the cAMP pathway, which may confer them a protective cardioprotective role. Edaglitazone and Ciglitazone are two chemically-similar thiazolidinedione (TZD) drugs that have been described as potent PPARγ agonists; however, Edaglitazone is over 100 times more potent than Ciglitazone. Here, we report a computational study to describe the ligand binding and the experimental antiplatelet profiles of Edaglitazone and Ciglitazone. Both ligands presented similar orientations within the PPARγ binding site. Their polar heads exhibit complex hydrogen bond networks with the residues at arm I pocket, while their hydrophobic tails are oriented inside arm II or the entrance pocket. The bulkier and longer tail of Edaglitazone exhibited additional hydrophobic interactions, explaining its stronger binding to PPARγ supported by binding affinity calculations. On the other hand, both Edaglitazone and Ciglitazone displayed an antiplatelet activity, but only Edaglitazone retained such effect at low concentrations. Furthermore, we evidenced that Edaglitazone increases intraplatelet cAMP levels and prevents PPARγ secretion, explaining its greater antiplatelet activity. Altogether, the more potent PPARγ agonist Edaglitazone seems to be a potent antiplatelet agent.