Ligand solvation in molecular docking

Interaction of systemic drugs causing ocular toxicity with organic cation transporter: an artificial intelligence prediction

Chronic disease patients (cancer, arthritis, cardiovascular diseases) undergo long-term systemic drug treatment. Membrane transporters in ocular barriers could falsely recognize these drugs and allow their trafficking into the eye from systemic circulation. Hence, despite their pharmacological activity, these drugs accumulate and cause toxicity at the non-target site, such as the eye. Since around 40% of clinically used drugs are organic cation in nature, it is essential to understand the role of organic cation transporter (OCT1) in ocular barriers to facilitate the entry of systemic drugs into the eye. We applied machine learning techniques and computer simulation models (molecular dynamics and metadynamics) in the current study to predict the potential OCT1 substrates. Artificial intelligence models were developed using a training dataset of a known substrates and non-substrates of OCT1 and predicted the potential OCT1 substrates from various systemic drugs causing ocular toxicity. Computer simulation studies was performed by developing the OCT1 homology model. Molecular dynamic simulations equilibrated the docked protein-ligand complex. And metadynamics revealed the movement of substrates across the transporter with minimum free energy near the binding pocket. The machine learning model showed an accuracy of about 80% and predicted the potential substrates for OCT1 among systemic drugs causing ocular toxicity - not known earlier, such as cyclophosphamide, bupivacaine, bortezomib, sulphanilamide, tosufloxacin, topiramate, and many more. However, further invitro and invivo studies are required to confirm these predictions.Communicated by Ramaswamy H. Sarma.

AlphaFold2 structures guide prospective ligand discovery

AlphaFold2 (AF2) models have had wide impact but mixed success in retrospective ligand recognition. We prospectively docked large libraries against unrefined AF2 models of the σ2 and serotonin 2A (5-HT2A) receptors, testing hundreds of new molecules and comparing results with those obtained from docking against the experimental structures. Hit rates were high and similar for the experimental and AF2 structures, as were affinities. Success in docking against the AF2 models was achieved despite differences between orthosteric residue conformations in the AF2 models and the experimental structures. Determination of the cryo-electron microscopy structure for one of the more potent 5-HT2A ligands from the AF2 docking revealed residue accommodations that resembled the AF2 prediction. AF2 models may sample conformations that differ from experimental structures but remain low energy and relevant for ligand discovery, extending the domain of structure-based drug design.

Novel meriolin derivatives potently inhibit cell cycle progression and transcription in leukemia and lymphoma cells via inhibition of cyclin-dependent kinases (CDKs)

A key feature of cancer is the disruption of cell cycle regulation, which is characterized by the selective and abnormal activation of cyclin-dependent kinases (CDKs). Consequently, targeting CDKs via meriolins represents an attractive therapeutic approach for cancer therapy. Meriolins represent a semisynthetic compound class derived from meridianins and variolins with a known CDK inhibitory potential. Here, we analyzed the two novel derivatives meriolin 16 and meriolin 36 in comparison to other potent CDK inhibitors and could show that they displayed a high cytotoxic potential in different lymphoma and leukemia cell lines as well as in primary patient-derived lymphoma and leukemia cells. In a kinome screen, we showed that meriolin 16 and 36 prevalently inhibited most of the CDKs (such as CDK1, 2, 3, 5, 7, 8, 9, 12, 13, 16, 17, 18, 19, 20). In drug-to-target modeling studies, we predicted a common binding mode of meriolin 16 and 36 to the ATP-pocket of CDK2 and an additional flipped binding for meriolin 36. We could show that cell cycle progression and proliferation were blocked by abolishing phosphorylation of retinoblastoma protein (a major target of CDK2) at Ser612 and Thr82. Moreover, meriolin 16 prevented the CDK9-mediated phosphorylation of RNA polymerase II at Ser2 which is crucial for transcription initiation. This renders both meriolin derivatives as valuable anticancer drugs as they target three different Achilles' heels of the tumor: (1) inhibition of cell cycle progression and proliferation, (2) prevention of transcription, and (3) induction of cell death.

Unveiling the Multifaceted Capabilities of Endophytic Aspergillus flavus Isolated from Annona squamosa Fruit Peels against Staphylococcus Isolates and HCoV 229E-In Vitro and In Silico Investigations

Recently, there has been a surge towards searching for primitive treatment strategies to discover novel therapeutic approaches against multi-drug-resistant pathogens. Endophytes are considered unexplored yet perpetual sources of several secondary metabolites with therapeutic significance. This study aims to isolate and identify the endophytic fungi from Annona squamosa L. fruit peels using morphological, microscopical, and transcribed spacer (ITS-rDNA) sequence analysis; extract the fungus's secondary metabolites by ethyl acetate; investigate the chemical profile using UPLC/MS; and evaluate the potential antibacterial, antibiofilm, and antiviral activities. An endophytic fungus was isolated and identified as Aspergillus flavus L. from the fruit peels. The UPLC/MS revealed seven compounds with various chemical classes. The antimicrobial activity of the fungal ethyl acetate extract (FEA) was investigated against different Gram-positive and Gram-negative standard strains, in addition to resistant clinical isolates using the agar diffusion method. The CPE-inhibition assay was used to identify the potential antiviral activity of the crude fungal extract against low pathogenic human coronavirus (HCoV 229E). Selective Gram-positive antibacterial and antibiofilm activities were evident, demonstrating pronounced efficacy against both methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-sensitive Staphylococcus aureus (MSSA). However, the extract exhibited very weak activity against Gram-negative bacterial strains. The ethyl acetate extract of Aspergillus flavus L exhibited an interesting antiviral activity with a half maximal inhibitory concentration (IC50) value of 27.2 µg/mL against HCoV 229E. Furthermore, in silico virtual molecular docking-coupled dynamics simulation highlighted the promising affinity of the identified metabolite, orienting towards three MRSA biotargets and HCoV 229E main protease as compared to reported reference inhibitors/substrates. Finally, ADME analysis was conducted to evaluate the potential oral bioavailability of the identified metabolites.

The Potential of Anti-coronavirus Plant Secondary Metabolites in COVID-19 Drug Discovery as an Alternative to Repurposed Drugs: A Review

In early 2020, a global pandemic was announced due to the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known to cause COVID-19. Despite worldwide efforts, there are only limited options regarding antiviral drug treatments for COVID-19. Although vaccines are now available, issues such as declining efficacy against different SARS-CoV-2 variants and the aging of vaccine-induced immunity highlight the importance of finding more antiviral drugs as a second line of defense against the disease. Drug repurposing has been used to rapidly find COVID-19 therapeutic options. Due to the lack of clinical evidence for the therapeutic benefits and certain serious side effects of repurposed antivirals, the search for an antiviral drug against SARS-CoV-2 with fewer side effects continues. In recent years, numerous studies have included antiviral chemicals from a variety of plant species. A better knowledge of the possible antiviral natural products and their mechanism against SARS-CoV-2 will help to develop stronger and more targeted direct-acting antiviral agents. The aim of the present study was to compile the current data on potential plant metabolites that can be investigated in COVID-19 drug discovery and development. This review represents a collection of plant secondary metabolites and their mode of action against SARS-CoV and SARS-CoV-2.

DOCK 6: Incorporating hierarchical traversal through precomputed ligand conformations to enable large-scale docking

To allow DOCK 6 access to unprecedented chemical space for screening billions of small molecules, we have implemented features from DOCK 3.7 into DOCK 6, including a search routine that traverses precomputed ligand conformations stored in a hierarchical database. We tested them on the DUDE-Z and SB2012 test sets. The hierarchical database search routine is 16 times faster than anchor-and-grow. However, the ability of hierarchical database search to reproduce the experimental pose is 16% worse than that of anchor-and-grow. The enrichment performance is on average similar, but DOCK 3.7 has better enrichment than DOCK 6, and DOCK 6 is on average 1.7 times slower. However, with post-docking torsion minimization, DOCK 6 surpasses DOCK 3.7. A large-scale virtual screen is performed with DOCK 6 on 23 million fragment molecules. We use current features in DOCK 6 to complement hierarchical database calculations, including torsion minimization, which is not available in DOCK 3.7.

Considerations Around Structure-Based Drug Discovery for KRAS Using DOCK

Molecular docking is a popular computational tool in drug discovery. Leveraging structural information, docking software predicts binding poses of small molecules to cavities on the surfaces of proteins. Virtual screening for ligand discovery is a useful application of docking software. In this chapter, using the enigmatic KRAS protein as an example system, we endeavor to teach the reader about best practices for performing molecular docking with UCSF DOCK. We discuss methods for virtual screening and docking molecules on KRAS. We present the following six points to optimize our docking setup for prosecuting a virtual screen: protein structure choice, pocket selection, optimization of the scoring function, modification of sampling spheres and sampling procedures, choosing an appropriate portion of chemical space to dock, and the choice of which top scoring molecules to pick for purchase.

Structure-Based Virtual Screening and De Novo Design to Identify Submicromolar Inhibitors of G2019S Mutant of Leucine-Rich Repeat Kinase 2

Missense mutations of leucine-rich repeat kinase 2 (LRRK2), including the G2019S mutant, are responsible for the pathogenesis of Parkinson's disease. In this work, structure-based virtual screening of a large chemical library was carried out to identify a number of novel inhibitors of the G2019S mutant of LRRK2, the biochemical potencies of which ranged from the low micromolar to the submicromolar level. The discovery of these potent inhibitors was made possible due to the modification of the original protein-ligand binding energy function in order to include an accurate ligand dehydration energy term. The results of extensive molecular docking simulations indicated that the newly identified inhibitors were bound to the ATP-binding site of the G2019S mutant of LRRK2 through the multiple hydrogen bonds with backbone amide groups in the hinge region as well as the hydrophobic interactions with the nonpolar residues in the P-loop, hinge region, and interdomain region. Among 18 inhibitors derived from virtual screening, 4-(2-amino-5-phenylpyrimidin-4-yl)benzene-1,3-diol (Inhibitor 2) is most likely to serve as a new molecular scaffold to optimize the biochemical potency, because it revealed submicromolar inhibitory activity in spite of its low molecular weight (279.3 amu). Indeed, a highly potent inhibitor (Inhibitor 2n) of the G2019S mutant was derived via the structure-based de novo design using the structure of Inhibitor 2 as the molecular core. The biochemical potency of Inhibitor 2n surged to the nanomolar level due to the strengthening of hydrophobic interactions in the ATP-binding site, which were presumably caused by the substitutions of small nonpolar moieties. Due to the high biochemical potency against the G2019S mutant of LRRK2 and the putatively good physicochemical properties, Inhibitor 2n is anticipated to serve as a new lead compound for the discovery of antiparkinsonian medicines.

Structure-based discovery of nonopioid analgesics acting through the α2A-adrenergic receptor

Because nonopioid analgesics are much sought after, we computationally docked more than 301 million virtual molecules against a validated pain target, the α2A-adrenergic receptor (α2AAR), seeking new α2AAR agonists chemotypes that lack the sedation conferred by known α2AAR drugs, such as dexmedetomidine. We identified 17 ligands with potencies as low as 12 nanomolar, many with partial agonism and preferential Gi and Go signaling. Experimental structures of α2AAR complexed with two of these agonists confirmed the docking predictions and templated further optimization. Several compounds, including the initial docking hit '9087 [mean effective concentration (EC50) of 52 nanomolar] and two analogs, '7075 and PS75 (EC50 4.1 and 4.8 nanomolar), exerted on-target analgesic activity in multiple in vivo pain models without sedation. These newly discovered agonists are interesting as therapeutic leads that lack the liabilities of opioids and the sedation of dexmedetomidine.

Two-Track Virtual Screening Approach to Identify the Dual Inhibitors of Wild Type and C481S Mutant of Bruton's Tyrosine Kinase

Bruton's tyrosine kinase (BTK) is responsible for the pathogenesis of various autoimmune diseases and chronic lymphocytic leukemia. However, the discovery of efficient medicines has seen limited success due to the constitutively active mutants that acquired the drug resistance. To disclose the dual inhibitors against the wild-type BTK and the problematic drug-resistant C481S mutant, a large chemical library was virtually screened with extensive molecular docking simulations using two target proteins. As a consequence of imposing the configurational restraint to make a hydrogen bond in the hinge region of BTK as well as modifying the ligand dehydration term in the scoring function, a total of 20 dual inhibitors were discovered with the range of the associated IC₅₀ values from 2.5 to 15 μM. All these dual inhibitors revealed the inhibitory activity against the C481S mutant to a comparable extent to that measured for the wild type. Among the new inhibitors, N-(3,5-dimethoxyphenyl)-6,7-dimethoxyquinazolin-4-amine (1) appeared to be most suitable as a starting point of the lead optimization due to the highest biochemical potency against the C481S mutant as well as the lowest molecular weight. To increase the potential of a drug candidate, 1 was modified into 6,7-dimethoxy-N-(pyridin-3-yl)quinazolin-4-amine (12) via chemical synthesis so as to possess better physicochemical properties without loss of the biochemical potency. 12 is suggested as a new effective molecular core from which numerous druggable dual inhibitors of the wild-type BTK and the C481S mutant would be derivatized.

Study of key amino acid residues of GH66 dextranase for producing high-degree polymerized isomaltooligosaccharides and improving of thermostability

Obtaining high-degree polymerized isomaltose is more difficult while achieving better prebiotic effects. We investigated the mutation specificity and enzymatic properties of SP5-Badex, a dextranase from the GH66 family of Bacillus aquimaris SP5, and determined its mutation sites through molecular docking to obtain five mutants, namely E454K, E454G, Y539F, N369F, and Y153N. Among them, Y539F and Y153N exhibited no enzymatic activity, but their hydrolysates included isomaltotetraose (IMO4). The enzymatic activity of E454G was 1.96 U/ml, which was 3.08 times higher than that before mutation. Moreover, 70% of the enzymatic activity could be retained after holding at 45°C for 180 min, which was 40% higher than that of SP5-Badex. Furthermore, its IMO4 content was 5.62% higher than that of SP5-Badex after hydrolysis at 30°C for 180 min. To investigate the effect of different amino acids on the same mutation site, saturation mutation was induced at site Y153, and the results showed that the enzyme activity of Y153W could be increased by 2 times, and some of the enzyme activity could still be retained at 50°C. Moreover, the enzyme activity increased by 50% compared with that of SP5-Badex after holding at 45°C for 180 min, and the IMO4 content of Y153W was approximately 64.97% after hydrolysis at 30°C for 180 min, which increased by approximately 12.47% compared with that of SP5-Badex. This site is hypothesized to rigidly bind to nonpolar (hydrophobic) amino acids to improve the stability of the protein structure, which in turn improves the thermal stability and simultaneously increases the IMO4 yield.

Drug Discovery of Plausible Lead Natural Compounds That Target the Insulin Signaling Pathway: Bioinformatics Approaches

The growing smooth talk in the field of natural compounds is due to the ancient and current interest in herbal medicine and their potentially positive effects on health. Dozens of antidiabetic natural compounds were reported and tested in vivo, in silico, and in vitro. The role of these natural compounds, their actions on the insulin signaling pathway, and the stimulation of the glucose transporter-4 (GLUT4) insulin-responsive translocation to the plasma membrane (PM) are all crucial in the treatment of diabetes and insulin resistance. In this review, we collected and summarized a group of available in vivo and in vitro studies which targeted isolated phytochemicals with possible antidiabetic activity. Moreover, the in silico docking of natural compounds with some of the insulin signaling cascade key proteins is also summarized based on the current literature. In this review, hundreds of recent studies on pure natural compounds that alleviate type II diabetes mellitus (type II DM) were revised. We focused on natural compounds that could potentially regulate blood glucose and stimulate GLUT4 translocation through the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) pathway. On attempt to point out potential new natural antidiabetic compounds, this review also focuses on natural ingredients that were shown to interact with proteins in the insulin signaling pathway in silico, regardless of their in vitro/in vivo antidiabetic activity. We invite interested researchers to test these compounds as potential novel type II DM drugs and explore their therapeutic mechanisms.

Structure based design, stability study and synthesis of the dinitrophenylhydrazone derivative of the oxidation product of lanosterol as a potential P. falciparum transketolase inhibitor and in-vivo antimalarial study

The growing resistance to the current antimalarial drugs in the absence of a vaccine can be effectively tackled by identifying new metabolic pathways that are essential to the survival of the malaria parasite and developing new drugs against them. Triterpenes and steroids are the most abundant group of natural products with a great variety of biological activities. However, lanosterol is not known to possess any significant biological activity. In this study the binding and interactions of a dinitrophenyl hydrazine (DNP) derivative of lanosterol, LAN (a derivative that incorporates a substantially polar moiety into the steroid) with P. falciparum transketolase was studied by molecular docking and MD simulation with the view to exploit the DNP derivative as a lead in antimalarial chemotherapy development considering that the P. falciparum transketolase (PfTk) is a novel target in antimalarial chemotherapy. The enzyme catalyses the production of ribose sugars needed for nucleic acid synthesis; it lacks a three-dimensional (3D) structure necessary for docking because it is difficult to obtain a crystalline form. A homology model of PfTk was constructed using Saccharomyces cerevisiae transketolase (protein data bank ID of 1TRK) as the template. The compound was observed to have Free Energy of Binding higher than that of the cofactor of the protein (Thiamine Pyrophosphate, TPP) and a synthetic analog (SUBTPP) used as reference compounds after MD Simulation. The compound was synthesized in a two-step, one-pot reaction, utilizing a non-acidic and mild oxidant to oxidize the lanosterol in order to avoid the rearrangement that accompanies the oxidation of sterols using acidic oxidants. The LAN was characterized using IR spectroscopy and NMR experiments and tested in-vivo for its antimalarial chemo suppression using a murine model with Chloroquine as a standard. The LAN at a concentration of 25 mg/kg was found to have a comparable activity with Chloroquine at 10 mg/kg and no mortality was observed among the test animals 24 days post drug administration showing that the compound indeed has potential as an antimalarial agent and a likely inhibitor of PfTk considering that there is a strong agreement between the in-silico results and biological study.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40203-021-00097-8.

Structure-Based Virtual Screening and De Novo Design of PIM1 Inhibitors with Anticancer Activity from Natural Products

BACKGROUND

the proviral insertion site of Moloney murine leukemia (PIM) 1 kinase has served as a therapeutic target for various human cancers due to the enhancement of cell proliferation and the inhibition of apoptosis.

METHODS

to identify effective PIM1 kinase inhibitors, structure-based virtual screening of natural products of plant origin and de novo design were carried out using the protein-ligand binding free energy function improved by introducing an adequate dehydration energy term.

RESULTS

as a consequence of subsequent enzyme inhibition assays, four classes of PIM1 kinase inhibitors were discovered, with the biochemical potency ranging from low-micromolar to sub-micromolar levels. The results of extensive docking simulations showed that the inhibitory activity stemmed from the formation of multiple hydrogen bonds in combination with hydrophobic interactions in the ATP-binding site. Optimization of the biochemical potency by chemical modifications of the 2-benzylidenebenzofuran-3(2H)-one scaffold led to the discovery of several nanomolar inhibitors with antiproliferative activities against human breast cancer cell lines.

CONCLUSIONS

these new PIM1 kinase inhibitors are anticipated to serve as a new starting point for the development of anticancer medicine.

Analyzing Kinase Similarity in Small Molecule and Protein Structural Space to Explore the Limits of Multi-Target Screening

While selective inhibition is one of the key assets for a small molecule drug, many diseases can only be tackled by simultaneous inhibition of several proteins. An example where achieving selectivity is especially challenging are ligands targeting human kinases. This difficulty arises from the high structural conservation of the kinase ATP binding sites, the area targeted by most inhibitors. We investigated the possibility to identify novel small molecule ligands with pre-defined binding profiles for a series of kinase targets and anti-targets by in silico docking. The candidate ligands originating from these calculations were assayed to determine their experimental binding profiles. Compared to previous studies, the acquired hit rates were low in this specific setup, which aimed at not only selecting multi-target kinase ligands, but also designing out binding to anti-targets. Specifically, only a single profiled substance could be verified as a sub-micromolar, dual-specific EGFR/ErbB2 ligand that indeed avoided its selected anti-target BRAF. We subsequently re-analyzed our target choice and in silico strategy based on these findings, with a particular emphasis on the hit rates that can be expected from a given target combination. To that end, we supplemented the structure-based docking calculations with bioinformatic considerations of binding pocket sequence and structure similarity as well as ligand-centric comparisons of kinases. Taken together, our results provide a multi-faceted picture of how pocket space can determine the success of docking in multi-target drug discovery efforts.

Rational Computational Design of Fourth-Generation EGFR Inhibitors to Combat Drug-Resistant Non-Small Cell Lung Cancer

Although the inhibitors of singly mutated epidermal growth factor receptor (EGFR) kinase are effective for the treatment of non-small cell lung cancer (NSCLC), their clinical efficacy has been limited due to the emergence of various double and triple EGFR mutants with drug resistance. It has thus become urgent to identify potent and selective inhibitors of triple mutant EGFRs resistant to first-, second-, and third-generation EGFR inhibitors. Herein, we report the discovery of potent and highly selective inhibitors of EGFR exon 19 p.E746_A750del/EGFR exon 20 p.T790M/EGFR exon 20 p.C797S (d746-750/T790M/C797S) mutant, which were derived via two-track virtual screening and de novo design. This two-track approach was performed so as to maximize and minimize the inhibitory activity against the triple mutant and the wild type, respectively. Extensive chemical modifications of the initial hit compounds led to the identification of several low-nanomolar inhibitors of the d746-750/T790M/C797S mutant. Among them, two compounds exhibited more than 10⁴-fold selectivity in the inhibition of EGFR^{d746-750/T790M/C797S} over the wild type. The formations of a hydrogen bond with the mutated residue Ser797 and the van der Waals contact with the mutated residue Met790 were found to be a common feature in the interactions between EGFR^{d746-750/T790M/C797S} and the fourth-generation inhibitors. Such an exceptionally high selectivity could also be attributed to the formation of the hydrophobic contact with a Gly loop residue or the hydrogen bond with Asp855 in the activation loop. The discovery of the potent and selective EGFR^{d746-750/T790M/C797S} inhibitors were actually made possible by virtue of the modified protein-ligand binding free energy function involving a new hydration free energy term with enhanced accuracy. The fourth-generation EGFR inhibitors found in this work are anticipated to serve as a new starting point for the discovery of anti-NSCLC medicines to overcome the problematic drug resistance.

Structure-Based Discovery of Novel Ligands for the Orexin 2 Receptor

The orexin receptors are peptide-sensing G protein-coupled receptors that are intimately linked with regulation of the sleep/wake cycle. We used a recently solved X-ray structure of the orexin receptor subtype 2 in computational docking calculations with the aim to identify additional ligands with unprecedented chemotypes. We found validated ligands with a high hit rate of 29% out of those tested, none of them showing selectivity with respect to the orexin receptor subtype 1. Furthermore, of the higher-affinity compounds examined, none showed any agonist activity. While novel chemical structures can thus be found, selectivity is a challenge owing to the largely identical binding pockets.

SAMPL7 TrimerTrip host-guest binding poses and binding affinities from spherical-coordinates-biased simulations

Host-guest binding remains a major challenge in modern computational modelling. The newest 7th statistical assessment of the modeling of proteins and ligands (SAMPL) challenge contains a new series of host-guest systems. The TrimerTrip host binds to 16 structurally diverse guests. Previously, we have successfully employed the spherical coordinates as the collective variables coupled with the enhanced sampling technique metadynamics to enhance the sampling of the binding/unbinding event, search for possible binding poses and calculate the binding affinities in all three host-guest binding cases of the 6th SAMPL challenge. In this work, we report a retrospective study on the TrimerTrip host-guest systems by employing the same protocol to investigate the TrimerTrip host in the SAMPL7 challenge. As no binding pose is provided by the SAMPL7 host, our simulations initiate from randomly selected configurations and are proceeded long enough to obtain converged free energy estimates and search for possible binding poses. The calculated binding affinities are in good agreement with the experimental reference, and the obtained binding poses serve as a nice starting point for end-point or alchemical free energy calculations. Note that as the work is performed after the close of the SAMPL7 challenge, we do not participate in the challenge and the results are not formally submitted to the SAMPL7 challenge.

A Focus on Unusual ECL2 Interactions Yields β2 -Adrenergic Receptor Antagonists with Unprecedented Scaffolds

The binding pockets of aminergic G protein-coupled receptors are often targeted by drugs and virtual screening campaigns. In order to find ligands with unprecedented scaffolds for one of the best-investigated receptors of this subfamily, the β2 -adrenergic receptor, we conducted a docking-based screen insisting that molecules would address previously untargeted residues in extracellular loop 2. We here report the discovery of ligands with a previously undescribed coumaran-based scaffold. Furthermore, we provide an analysis of the added value that X-ray structures in different conformations deliver for such docking screens.

Rational drug repurposing for cancer by inclusion of the unbiased molecular dynamics simulation in the structure-based virtual screening approach: Challenges and breakthroughs

Managing cancer is now one of the biggest concerns of health organizations. Many strategies have been developed in drug discovery pipelines to help rectify this problem and two of the best ones are drug repurposing and computational methods. The combination of these approaches can have immense impact on the course of drug discovery. In silico drug repurposing can significantly reduce the time, the cost and the effort of drug development. Computational methods such as structure-based drug design (SBDD) and virtual screening can predict the potentials of small molecule binders, such as drugs, for having favorable effect on a particular molecular target. However, the demand for accuracy and efficiency of SBDD requires more sophisticated and complicated approaches such as unbiased molecular dynamics (UMD) simulation that has been recently introduced. As a complementary strategy, the knowledge acquired from UMD simulations can increase the chance of finding the right candidates and the pipeline of its administration is introduced and discussed in this review. An elaboration of this pipeline is also made by detailing an example, the binding and unbinding pathways of dasatinib-c-Src kinase complex, which shows that how influential this method can be in rational drug repurposing in cancer treatment.

A computer-based approach for developing linamarase inhibitory agents

Cassava is a strategic crop, especially for developing countries. However, the presence of cyanogenic compounds in cassava products limits the proper nutrients utilization. Due to the poor availability of structure discovery and elucidation in the Protein Data Bank is limiting the full understanding of the enzyme, how to inhibit it and applications in different fields. There is a need to solve the three-dimensional structure (3-D) of linamarase from cassava. The structural elucidation will allow the development of a competitive inhibitor and various industrial applications of the enzyme. The goal of this review is to summarize and present the available 3-D modeling structure of linamarase enzyme using different computational strategies. This approach could help in determining the structure of linamarase and later guide the structure elucidationin silicoand experimentally.

SAMPL6 host-guest binding affinities and binding poses from spherical-coordinates-biased simulations

Host-guest binding is a challenging problem in computer simulation. The prediction of binding affinities between hosts and guests is an important part of the statistical assessment of the modeling of proteins and ligands (SAMPL) challenges. In this work, the volume-based variant of well-tempered metadynamics is employed to calculate the binding affinities of the host-guest systems in the SAMPL6 challenge. By biasing the spherical coordinates describing the relative position of the host and the guest, the initial-configuration-induced bias vanishes and all possible binding poses are explored. The agreement between the predictions and the experimental results and the observation of new binding poses indicate that the volume-based technique serves as a nice candidate for the calculation of binding free energies and the search of the binding poses.

Kinase and GPCR polypharmacological approach for the identification of efficient anticancer medicines

Discovery of an anticancer medicine using a single target protein has often been unsuccessful due to the complexity of pathogenic mechanisms as well as the presence of redundant signaling pathways. In this work, we attempted to find promising anticancer drug candidates by simultaneously targeting casein kinase 1 delta (CK1δ) and muscarinic acetylcholine receptor M3 (M3R). Through the structure-based virtual screening and de novo design with the modified potential function for protein-ligand binding, a series of benzo[4,5]imidazo[1,2-a][1,3,5]triazine-2-amine (BITA) derivatives were identified as CK1δ inhibitors and also as M3R antagonists. The biochemical potencies of these bifunctional molecules reached the nanomolar and low-micromolar levels with respect to CK1δ and M3R, respectively. A common interaction feature in the calculated CK1δ-inhibitor and M3R-antagonist complexes is that the BITA moiety is well-stabilized in the orthosteric site of M3R and the hinge region of CK1δ through the establishment of the three hydrogen bonds and the hydrophobic contacts in the vicinity. The computational and experimental results found in this work exemplify the efficiency of kinase and GPCR polypharmacology in developing anticancer medicines.

Discovery of Potent, Reversible, and Competitive Cruzain Inhibitors with Trypanocidal Activity: A Structure-Based Drug Design Approach

A virtual screening conducted with nearly 4 000 000 compounds from lead-like and fragment-like subsets enabled the identification of a small-molecule inhibitor (1) of the Trypanosoma cruzi cruzain enzyme, a validated drug target for Chagas disease. Subsequent comprehensive structure-based drug design and structure-activity relationship studies led to the discovery of carbamoyl imidazoles as potent, reversible, and competitive cruzain inhibitors. The most potent carbamoyl imidazole inhibitor (45) exhibited high affinity with a K_i value of 20 nM, presenting both in vitro and in vivo activity against T. cruzi. Furthermore, the most promising compounds reduced parasite burden in vivo and showed no toxicity at a dose of 100 mg/kg. These carbamoyl imidazoles are structurally attractive, nonpeptidic, and easy to prepare and synthetically modify. Finally, these results further advance our understanding of the noncovalent mode of inhibition of this pharmaceutically relevant enzyme, building strong foundations for drug discovery efforts.

Comparative Docking to Distinct G Protein-Coupled Receptor Conformations Exclusively Yields Ligands with Agonist Efficacy

G protein-coupled receptors exist in a whole spectrum of conformations that are stabilized by the binding of ligands with different efficacy or intracellular effector proteins. Here, we investigate whether three-dimensional structures of receptor conformations in different states of activation can be used to enrich ligands with agonist behavior in prospective docking calculations. We focused on the β ₂-adrenergic receptor, as it is currently the receptor with the highest number of active-state crystal structures. Comparative docking calculations to distinct conformations of the receptor were used for the in silico prediction of ligands with agonist efficacy. The pharmacology of molecules selected based on these predictions was characterized experimentally, resulting in a hit rate of 37% ligands, all of which were agonists. The ligands furthermore contain a pyrazole moiety that has previously not been described for β ₂-adrenergic receptor ligands, and one of them shows an intrinsic efficacy comparable to salbutamol. SIGNIFICANCE STATEMENT: Structure-based ligand design for G protein-coupled receptors crucially depends on receptor conformation and, hence, their activation state. We explored the influence of using multiple active-conformation X-ray structures on the hit rate of docking calculations to find novel agonists, and how to predict the most fruitful strategy to apply. The results suggest that aggregating the ranks of molecules across docking calculations to more than one active-state structure exclusively yields agonists.

Differential long-term regulation of TAS2R14 by structurally distinct agonists

Bitter taste receptor-14 (TAS2R14) is a GPCR also expressed on human airway smooth muscle cells, which signals to intracellular [Ca²⁺], resulting in relaxation of the airway, and is a novel target for bronchodilators. Here, we examine long-term, agonist-promoted down-regulation of TAS2R14 expression because tachyphylaxis would be an undesirable therapeutic characteristic. Five TAS2R structurally distinct full agonists were studied to ascertain biasing away from down-regulation. Agonist exposure for 18 h caused minimal desensitization by diphenhydramine (DPD) compared with ∼50% desensitization with all other agonists. Agonists evoked β-arrestin recruitment to TAS2R14, which was not seen with a phosphoacceptor-deficient mutant, TAS2R14-10A. All agonists except for DPD also caused subsequent TAS2R14 internalization and trafficking via early and late endosomes to down-regulation. TAS2R14-10A failed to undergo these events with any agonist. Molecular docking showed that DPD has specific interactions deep within a binding pocket that are not observed with the other agonists, which may lock the receptor in a conformation that does not internalize and therefore does not undergo down-regulation. Thus, TAS2R14 is subject to β-arrestin-mediated internalization and subsequent down-regulation with chronic exposure to most agonists. However, by manipulating the agonist structure, biasing toward G-protein coupling but away from long-term down-regulation can be achieved.-Woo, J. A., Castaño, M., Goss, A., Kim, D., Lewandowski, E. M., Chen, Y., Liggett, S. B. Differential long-term regulation of TAS2R14 by structurally distinct agonists.

Solvation Free Energy Calculations with Quantum Mechanics/Molecular Mechanics and Machine Learning Models

For exploration of chemical and biological systems, the combined quantum mechanics and molecular mechanics (QM/MM) and machine learning (ML) models have been developed recently to achieve high accuracy and efficiency for molecular dynamics (MD) simulations. Despite its success on reaction free energy calculations, how to identify new configurations on insufficiently sampled regions during MD and how to update the current ML models with the growing database on the fly are both very important but still challenging. In this article, we apply the QM/MM ML method to solvation free energy calculations and address these two challenges. We employ three approaches to detect new data points and introduce the gradient boosting algorithm to reoptimize efficiently the ML model during ML-based MD sampling. The solvation free energy calculations on several typical organic molecules demonstrate that our developed method provides a systematic, robust, and efficient way to explore new chemistry using ML-based QM/MM MD simulations.

Rational screening of peroxisome proliferator-activated receptor-γ agonists from natural products: potential therapeutics for heart failure

CONTEXT

Peroxisome proliferator-activated receptor-γ (PPARγ) is a member of the nuclear hormone receptor superfamily of ligand-activated transcription factors. Activation of PPARγ pathway has been shown to enhance fatty acid oxidation, improve endothelial cell function, and decrease myocardial fibrosis in heart failure. Thus, the protein has been raised as an attractive target for heart failure therapy.

OBJECTIVE

This work attempted to discover new and potent PPARγ agonists from natural products using a synthetic strategy of computer virtual screening and transactivation reporter assay.

MATERIALS AND METHODS

A large library of structurally diverse, drug-like natural products was compiled, from which those with unsatisfactory pharmacokinetic profile and/or structurally redundant compounds were excluded. The binding mode of remaining candidates to PPARγ ligand-binding domain (LBD) was computationally modelled using molecular docking and their relative binding potency was ranked by an empirical scoring scheme. Consequently, eight commercially available hits with top scores were selected and their biological activity was determined using a cell-based reporter-gene assay.

RESULTS

Four natural product compounds, namely ZINC13408172, ZINC4292805, ZINC44179 and ZINC901461, were identified to have high or moderate agonistic potency against human PPARγ with EC₅₀ values of 0.084, 2.1, 0.35 and 5.6 μM, respectively, which are comparable to or even better than that of the approved PPARγ full agonists pioglitazone (EC₅₀=0.16 μM) and rosiglitazone (EC₅₀=0.034 μM). Hydrophobic interactions and van der Waals contacts are the primary chemical forces to stabilize the complex architecture of PPARγ LBD domain with these agonist ligands, while few hydrogen bonds, salt bridges and/or π-π stacking at the complex interfaces confer selectivity and specificity for the domain-agonist recognition.

DISCUSSION AND CONCLUSION

The integrated in vitro-in silico screening strategy can be successfully applied to rational discovery of biologically active compounds. The newly identified natural products with PPARγ agonistic potency are considered as promising lead scaffolds to develop novel chemical therapeutics for heart failure.

Two-track virtual screening approach to identify both competitive and allosteric inhibitors of human small C-terminal domain phosphatase 1

Despite a wealth of persuasive evidence for the involvement of human small C-terminal domain phosphatase 1 (Scp1) in the impairment of neuronal differentiation and in Huntington's disease, small-molecule inhibitors of Scp1 have been rarely reported so far. This study aims to the discovery of both competitive and allosteric Scp1 inhibitors through the two-track virtual screening procedure. By virtue of the improvement of the scoring function by implementing a new molecular solvation energy term and by reoptimizing the atomic charges for the active-site Mg²⁺ ion cluster, we have been able to identify three allosteric and five competitive Scp1 inhibitors with low-micromolar inhibitory activity. Consistent with the results of kinetic studies on the inhibitory mechanisms, the allosteric inhibitors appear to be accommodated in the peripheral binding pocket through the hydrophobic interactions with the nonpolar residues whereas the competitive ones bind tightly in the active site with a direct coordination to the central Mg²⁺ ion. Some structural modifications to improve the biochemical potency of the newly identified inhibitors are proposed based on the binding modes estimated with docking simulations.

The Role of the Hydroxyl Group in Propofol-Protein Target Recognition: Insights from ONIOM Studies

Propofol (PFL, 1-hydroxyl-2,6-diisopropylbenzene) is currently used widely as one of the most well-known intravenous anesthetics to relieve surgical suffering, but its mechanism of action is not yet clear. Previous experimental studies have demonstrated that the hydroxyl group of PFL plays a dominant role in the molecular recognition of PFL with receptors that lead to hypnosis. To further explore the mechanism of anesthesia induced by PFL in the present work, the exact binding features and interaction details of PFL with three important proteins, human serum albumin (HSA), the pH-gated ion channel from Gloeobacter violaceus (GLIC), and horse spleen apoferritin (HSAF), were investigated systematically by using a rigorous three-layer ONIOM (M06-2X/6-31+G*:PM6:AMBER) method. Additionally, to further characterize the possible importance of such hydroxyl interactions, a similar set of calculations was carried out on the anesthetically inactive fropofol (FFL, 1-fluoro-2,6-diisopropylbenzene) in which the fluorine was substituted for the hydroxyl. According to the ONIOM calculations, atoms in molecules (AIM) analyses, and electrostatic potential (ESP) analyses, the significance of hydrogen bond, halogen bond, and hydrophobic interactions in promoting proper molecular recognition was revealed. The binding interaction energies of PFL with different proteins were generally larger than FFL and are a significant determinant of their differential anesthetic efficacies. Interestingly, although the hydrogen-bonding effect of the hydroxyl moiety was prominent in propofol, the substitution of the 1-hydroxyl by a fluorine atom did not prevent FFL from binding to the protein via a halogen-bonding interaction. It therefore became clear that multiple specific interactions rather than just hydrogen or halogen bonds must be taken into account to explain the different anesthesia endpoints caused by PFL and FFL. The contributions of key residues in ligand-receptor binding were also quantified, and the calculated results agreed with many available experimental observations. This work will provide complementary insights into the molecular mechanisms of anesthetic action for PFL from a robust theoretical point of view. This will not only assist in interpreting experimental observations but will also help to develop working hypotheses for further experiments and future drug design.

Towards a critical evaluation of an empirical and volume-based solvation function for ligand docking

Molecular docking is an important tool for the discovery of new biologically active molecules given that the receptor structure is known. An excellent environment for the development of new methods and improvement of the current methods is being provided by the rapid growth in the number of proteins with known structure. The evaluation of the solvation energies outstands among the challenges for the modeling of the receptor-ligand interactions, especially in the context of molecular docking where a fast, though accurate, evaluation is ought to be achieved. Here we evaluated a variation of the desolvation energy model proposed by Stouten (Stouten P.F.W. et al, Molecular Simulation, 1993, 10: 97–120), or SV model. The SV model showed a linear correlation with experimentally determined solvation energies, as available in the database FreeSolv. However, when used in retrospective docking simulations using the benchmarks DUD, charged-matched DUD and DUD-Enhanced, the SV model resulted in poorer enrichments when compared to a pure force field model with no correction for solvation effects. The data provided here is consistent with other empirical solvation models employed in the context of molecular docking and indicates that a good model to account for solvent effects is still a goal to achieve. On the other hand, despite the inability to improve the enrichment of retrospective simulations, the SV solvation model showed an interesting ability to reduce the number of molecules with net charge -2 and -3 e among the top-scored molecules in a prospective test.

Molecular Modelling, Dynamics, and Docking of Membrane Proteins

Computational tools and techniques are now most popular and promising to progress the research at rapid rate. Molecular modelling studies contribute their maximum role in wide variety of disciplines especially in proteomics and drug discovery strategies. Molecular dynamics and molecular docking algorithms are now became an essential part in daily research activities of every laboratory throughout the world. These strategies are now well established and standardised to study any specific protein of interest and drug molecule. But still there exist considerable drawbacks in a special concern with membrane proteins as the presently available tools and methods cannot be applied directly to them. Modelling, dynamics and docking studies of membrane proteins need a special care and attention as several challenges are to be crossed with an intensive care to produce a reliable result. This chapter is aimed to discuss such challenges and solutions to handle membrane proteins.

AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking

Water plays a significant role in the binding process between protein and ligand. However, the thermodynamics of water molecules are often underestimated, or even ignored, in protein-ligand docking. Usually, the free energies of active-site water molecules are substantially different from those of waters in the bulk region. The binding of a ligand to a protein causes a displacement of these waters from an active site to bulk, and this displacement process substantially contributes to the free energy change of protein-ligand binding. The free energy of active-site water molecules can be calculated by grid inhomogeneous solvation theory (GIST), using molecular dynamics (MD) and the trajectory of a target protein and water molecules. Here, we show a case study of the combination of GIST and a docking program and discuss the effectiveness of the displacing gain of unfavorable water in protein-ligand docking. We combined the GIST-based desolvation function with the scoring function of AutoDock4, which is called AutoDock-GIST. The proposed scoring function was assessed employing 51 ligands of coagulation factor Xa (FXa), and results showed that both scoring accuracy and docking success rate were improved. We also evaluated virtual screening performance of AutoDock-GIST using FXa ligands in the directory of useful decoys-enhanced (DUD-E), thus finding that the displacing gain of unfavorable water is effective for a successful docking campaign.

Application of Fragment-Based de Novo Design to the Discovery of Selective Picomolar Inhibitors of Glycogen Synthase Kinase-3 Beta

A systematic fragment-based de novo design procedure was developed and applied to discover new potent and selective inhibitors of glycogen synthase kinase-3 beta (GSK3β). Candidate inhibitors were generated to simultaneously maximize the biochemical potency and the specificity for GSK3β through three design steps: identification of the optimal molecular fragments for the three sub-binding regions, design of proper linking moieties to connect the fragmental building blocks, and final scoring of the generated molecules. By virtue of modifying the ligand hydration free energy term in the scoring function using hybrid scaled particle theory and the extended solvent-contact model, we identified several GSK3β inhibitors with biochemical potencies ranging from low nanomolar to picomolar levels. Among them, the two most potent inhibitors (12 and 27) are anticipated to serve as promising starting points of drug discovery for various diseases caused by GSK3β because of the high specificity for the inhibition of GSK3β.

Virtual Screening with Docking Simulations and Biochemical Evaluation of VHY Phosphatase Inhibitors

Although VH1-related member Y (VHY) phosphatase is responsible for the pathogenesis of neuroinflammatory diseases, no small-molecule inhibitor of VHY has been reported so far. Here we first report eight VHY inhibitors identified from molecular docking-based virtual screening and subsequent enzyme inhibition assays. These inhibitors exhibit good biochemical potencies against VHY, with associated IC50 values ranging from 1 to 9 µM. Because all these inhibitors were also screened in silico for having desirable physicochemical properties as a drug candidate, they deserve further investigation by structure-activity relationship studies to develop new medicines for the treatment of neuroinflammatory diseases. The structural features of VHY-inhibitor interactions relevant to the micromolar-level inhibitory activity are addressed in detail.

KECSA-Movable Type Implicit Solvation Model (KMTISM)

Computation of the solvation free energy for chemical and biological processes has long been of significant interest. The key challenges to effective solvation modeling center on the choice of potential function and configurational sampling. Herein, an energy sampling approach termed the “Movable Type” (MT) method, and a statistical energy function for solvation modeling, “Knowledge-based and Empirical Combined Scoring Algorithm” (KECSA) are developed and utilized to create an implicit solvation model: KECSA-Movable Type Implicit Solvation Model (KMTISM) suitable for the study of chemical and biological systems. KMTISM is an implicit solvation model, but the MT method performs energy sampling at the atom pairwise level. For a specific molecular system, the MT method collects energies from prebuilt databases for the requisite atom pairs at all relevant distance ranges, which by its very construction encodes all possible molecular configurations simultaneously. Unlike traditional statistical energy functions, KECSA converts structural statistical information into categorized atom pairwise interaction energies as a function of the radial distance instead of a mean force energy function. Within the implicit solvent model approximation, aqueous solvation free energies are then obtained from the NVT ensemble partition function generated by the MT method. Validation is performed against several subsets selected from the Minnesota Solvation Database v2012. Results are compared with several solvation free energy calculation methods, including a one-to-one comparison against two commonly used classical implicit solvation models: MM-GBSA and MM-PBSA. Comparison against a quantum mechanics based polarizable continuum model is also discussed (Cramer and Truhlar’s Solvation Model 12).

Discovery of Low Micromolar Dual Inhibitors for Wild Type and L1196M Mutant of Anaplastic Lymphoma Kinase through Structure-Based Virtual Screening

Although anaplastic lymphoma kinase (ALK) is involved in a variety of malignant human cancers, the emergence of constitutively active mutants with drug resistance has rendered it difficult to identify the new medicines for ALK-dependent cancers. To find the common inhibitors of the wild type ALK and the most abundant drug-resistant mutant (L1196M), we performed molecular docking-based virtual screening of a large chemical library in parallel for the two target proteins. As a consequence of augmenting the accuracy of the docking simulation by implementing a sophisticated hydration free energy term in the scoring function, 12 common inhibitors are discovered with the inhibitory activities ranging from submicromolar to low micromolar levels. The results of the binding free energy decomposition indicate that the biochemical potency of ALK inhibitors can be optimized by reducing the dehydration cost for binding to the receptor protein as well as by strengthening the interactions with amino acid residues in the ATP-binding site. The newly identified ALK inhibitors are found to have a little higher inhibitory activity for the L1196M mutant than for the wild type due to the strengthening of the hydrogen bond interactions in the ATP-binding site. Of the 12 common inhibitors, 2-(5-methyl-benzooxazol-2-ylamino)-quinazolin-4-ol (3) is anticipated to serve as a new molecular scaffold to optimize the biochemical potency because it exhibits low micromolar inhibitory activity with respect to both the wild type and L1196M mutant in spite of the low molecular weight (292.3 amu).

Discovery of Dual Inhibitors for Wild Type and D816V Mutant of c-KIT Kinase through Virtual and Biochemical Screening of Natural Products

Although stem cell factor receptor (c-KIT) kinase is responsible for various malignant human cancers, the presence of constitutively active gain-of-function mutants has made it difficult to discover new anticancer agents using c-KIT as the target protein. To identify the common inhibitors of wild-type c-KIT and the most abundant gain-of-function mutant (D816V), the virtual screening of natural products was performed for the two target proteins in parallel with the scoring function improved by implementing a sophisticated solvation free energy term. As a result, four common inhibitors of natural origin are found with biochemical potencies ranging from low micromolar to submicromolar levels. The results of extensive docking simulations show that although the natural-product inhibitors establish weaker hydrophobic interactions with the D816V mutant than with the wild type, they exhibit a little higher inhibitory activity for the former than the latter by strengthening the hydrogen-bond interactions to a sufficient extent. Of the four natural-product inhibitors, (Z)-6-hydroxy-2-(4-methoxybenzylidene)benzofuran-3(2H)-one (3) is anticipated to serve as a new molecular core for the structure-activity relationship studies to optimize the biochemical potencies because it exhibits good inhibitory activity against both the wild type and D816V mutant despite its low molecular weight (268.3 amu).

The Ascaris suum nicotinic receptor, ACR-16, as a drug target: Four novel negative allosteric modulators from virtual screening

Soil-transmitted helminth infections in humans and livestock cause significant debility, reduced productivity and economic losses globally. There are a limited number of effective anthelmintic drugs available for treating helminths infections, and their frequent use has led to the development of resistance in many parasite species. There is an urgent need for novel therapeutic drugs for treating these parasites. We have chosen the ACR-16 nicotinic acetylcholine receptor of Ascaris suum (Asu-ACR-16), as a drug target and have developed three-dimensional models of this transmembrane protein receptor to facilitate the search for new bioactive compounds. Using the human α7 nAChR chimeras and Torpedo marmorata nAChR for homology modeling, we defined orthosteric and allosteric binding sites on the Asu-ACR-16 receptor for virtual screening. We identified four ligands that bind to sites on Asu-ACR-16 and tested their activity using electrophysiological recording from Asu-ACR-16 receptors expressed in Xenopus oocytes. The four ligands were acetylcholine inhibitors (SB-277011-A, IC₅₀, 3.12 ± 1.29 μM; (+)-butaclamol Cl, IC₅₀, 9.85 ± 2.37 μM; fmoc-1, IC₅₀, 10.00 ± 1.38 μM; fmoc-2, IC₅₀, 16.67 ± 1.95 μM) that behaved like negative allosteric modulators. Our work illustrates a structure-based in silico screening method for seeking anthelmintic hits, which can then be tested electrophysiologically for further characterization.

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Three-dimensional structural models of the Ascaris nicotinic (Asu-ACR-16) receptor made by homology modeling.

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High affinity ligands selected by in silico screening.

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Four ligands validated by electrophysiological studies as negative allosteric modulators.