Improving the Prediction of Absolute Solvation Free Energies Using the Next Generation OPLS Force Field

New class of hantaan virus inhibitors based on conjugation of the isoindole fragment to (+)-camphor or (-)-fenchone hydrazonesv

This work presents the design and synthesis of camphor, fenchone, and norcamphor N-acylhydrazone derivatives as a new class of inhibitors of the Hantaan virus, which causes haemorrhagic fever with renal syndrome (HFRS). A cytopathic model was developed for testing chemotherapeutics against the Hantaan virus, strain 76-118. In addition, a study of the antiviral activity was carried out using a pseudoviral system. It was found that the hit compound possesses significant activity (IC₅₀ = 7.6 ± 2 µM) along with low toxicity (CC₅₀ > 1000 µM). Using molecular docking procedures, the binding with Hantavirus nucleoprotein was evaluated and the correlation between the structure of the synthesised compounds and the antiviral activity was established.

Glycyrrhetinic acid derivatives as Zika virus inhibitors: Synthesis and antiviral activity in vitro

Zika virus (ZIKV) is an arbovirus of the Flaviviridae family (Flavivirus genus), causing serious neurological complications, such as Guillain-Barre Syndrome (GBS) in adults and fetal microcephaly. Licensed vaccines or specific antiviral agents against ZIKV do not currently exist. Therefore, the search and development of anti-ZIKV agents are particularly relevant and necessary. Glycyrrhetinic (3β-hydroxy-11-oxo-18βH-Olean-12-en-30-oic acid) (GA) 1 is one of the well-known pentacyclic triterpenoids isolated from licorice root (Glycyrrhiza glabra L., Gl. uralensis Fisher) (Leguminosae) possessing many biological features, including antiviral activity. This paper is devoted to the synthesis and studies of a number of nitrogen and sulfur-containing GA derivatives as ZIKV inhibitors. Sixteen GA and related triterpenoids (3β-hydroxy-18βH-Olean-12-en-30-oic acid and 3β-hydroxy-11-oxo-18βH-Olean-12(13),18(19)-dien-30-oic acid) derivatives were synthesized (amides, semi- and thiosemicarbazones, and 1,2,3-thiadiazoles) and antiviral activity against ZIKV was studied in vitro, including the inhibitory assays on cytopathic effect (CPE), viral protein synthesis, and replication stages. Four active compounds were found among GA derivatives tested, 13 (3-O-acetyl-30-aminopyridine GA), 16 (3-semicarbazone-30-butyl GA), 18 (1,2,3-thiadiazole-30-methyl GA), and 19 (1,2,3-thiadiazole-30-butyl GA) with IC₅₀ < 1 μM against ZIKV replication. These compounds had a stronger inhibitory activity on ZIKV-induced CPE and viral protein translation in infected cells as compared to derivatives of 11-desoxo-GA. The most active compound was amide 13 (IC₅₀ 0.13 μM, TI ˃ 384). Time-of-addition assays indicated that 1,2,3-thiadiazole ring is important for inhibiting viral entry stage (compounds 18 and 19), while the 30-butyl ester group influenced on post-entry stage (compound 19). The molecular docking analysis demonstrated that lead compounds 13 and 19 forms a hydrogen-bond interaction with the catalytic triad (His51-Asp75-Ser135) of ZIKV NS2B-NS3 protease. Therefore, the active GA derivatives are promising for developing new antiviral agents against ZIKV infection.

Synthesis and Antiviral Activity of Camphene Derivatives against Different Types of Viruses

To date, the 'one bug-one drug' approach to antiviral drug development cannot effectively respond to the constant threat posed by an increasing diversity of viruses causing outbreaks of viral infections that turn out to be pathogenic for humans. Evidently, there is an urgent need for new strategies to develop efficient antiviral agents with broad-spectrum activities. In this paper, we identified camphene derivatives that showed broad antiviral activities in vitro against a panel of enveloped pathogenic viruses, including influenza virus A/PR/8/34 (H1N1), Ebola virus (EBOV), and the Hantaan virus. The lead-compound 2a, with pyrrolidine cycle in its structure, displayed antiviral activity against influenza virus (IC50 = 45.3 µM), Ebola pseudotype viruses (IC50 = 0.12 µM), and authentic EBOV (IC50 = 18.3 µM), as well as against pseudoviruses with Hantaan virus Gn-Gc glycoprotein (IC50 = 9.1 µM). The results of antiviral activity studies using pseudotype viruses and molecular modeling suggest that surface proteins of the viruses required for the fusion process between viral and cellular membranes are the likely target of compound 2a. The key structural fragments responsible for efficient binding are the bicyclic natural framework and the nitrogen atom. These data encourage us to conduct further investigations using bicyclic monoterpenoids as a scaffold for the rational design of membrane-fusion targeting inhibitors.

Determining the hydration free energies of selected small molecules with MP2 and local MP2 through adaptive force matching

Force fields for seven small solute molecules, ethanol, 2-methyl-1-propanol, 2-butanol, cyclohexene, tetrahydropyran, 1,4-dioxane, and 1,4-butanediol, in dilute aqueous solutions were created with the adaptive force matching (AFM) method using MP2 or local MP2 as reference. The force fields provide a way to predict the hydration free energies (HFEs) of these molecules with only electronic structure calculations as reference. For six of the seven molecules, the predicted HFEs are in very good agreement with experiments. For 1,4-butanediol, the model created by force matching LMP2 provides a HFE that is too positive. Further investigation suggests that LMP2 may not be sufficiently accurate for computing HFEs for alcohols with AFM. Other properties, such as enthalpy of hydration, diffusion constants, and vibrational spectra, are also computed with the force field developed. The force fields developed by AFM provide a bridge for computing ensemble properties of the reference electronic structure method. With MP2 and LMP2 as reference methods, the computed properties of the small molecular solutes are found to be in good agreement with experiments.

TIES 20: Relative Binding Free Energy with a Flexible Superimposition Algorithm and Partial Ring Morphing

The TIES (Thermodynamic Integration with Enhanced Sampling) protocol is a formally exact alchemical approach in computational chemistry to the calculation of relative binding free energies. The validity of TIES relies on the correctness of matching atoms across compared pairs of ligands, laying the foundation for the transformation along an alchemical pathway. We implement a flexible topology superimposition algorithm which uses an exhaustive joint-traversal for computing the largest common component(s). The algorithm is employed to enable matching and morphing of partial rings in the TIES protocol along with a validation study using 55 transformations and five different proteins from our previous work. We find that TIES 20 with the RESP charge system, using the new superimposition algorithm, reproduces the previous results with mean unsigned error of 0.75 kcal/mol with respect to the experimental data. Enabling the morphing of partial rings decreases the size of the alchemical region in the dual-topology transformations resulting in a significant improvement in the prediction precision. We find that increasing the ensemble size from 5 to 20 replicas per λ window only has a minimal impact on the accuracy. However, the non-normal nature of the relative free energy distributions underscores the importance of ensemble simulation. We further compare the results with the AM1-BCC charge system and show that it improves agreement with the experimental data by slightly over 10%. This improvement is partly due to AM1-BCC affecting only the charges of the atoms local to the mutation, which translates to even fewer morphed atoms, consequently reducing issues with sampling and therefore ensemble averaging. TIES 20, in conjunction with the enablement of ring morphing, reduces the size of the alchemical region and significantly improves the precision of the predicted free energies.

D-Amino acid substituted peptides as potential alternatives of homochiral L-configurations

On the primitive Earth, both L- and D-amino acids would have been present. However, only L-amino acids are essential blocks to construct proteins in modern life. To study the relative stability of D-amino acid substituted peptides, a variety of computational methods were applied. Ten prebiotic amino acids (Gly, Ala, Asp, Glu, Ile, Leu, Pro, Ser, Thr, and Val) were previously determined by multiple meteorite, spark discharge, and hydrothermal vent studies. Some previously reported early Earth polypeptide analogs were focused on in this study. Tripeptides composed of only Asp, Ser, and Val exemplified that different positions (i.e., N-terminus, C-terminus, and middle) made a difference in the minimal folding energy of peptides, while the chemical classification of amino acid (hydrophobic, acidic, or hydroxylic) did not show a significant difference. Hierarchical cluster analysis for dipeptides with all possible combinations of the proposed ten prebiotic amino acids and their D-amino acid substituted derivatives generated five clusters. Primordial simple polypeptides were modeled to test the significance of molecular fluctuations, secondary structure occupancies, and folding energy differences based on these clusters. We found peptides with α-helices, long β-sheets, and long loops are usually less sensitive to D-amino acid replacements in comparison to short β-sheets. Intriguingly, amongst 129 D-amino acid residues, mutation sensitivity profiles presented that the ratio of more to less stable residues was about 1. In conclusion, some combinations of a mixture of L- and D-amino acids can potentially act as essential building blocks of life.

Can molecular dynamics explain decreased pathogenicity in mutant camphecene-resistant influenza virus?

ABSTARCTThe development of new anti-influenza drugs remains an active area, and efforts in this direction will likely continue far into the future. In this paper, we present the results of a theoretical study explaining the mechanisms behind the antiviral activity of camphor derivatives. These include camphecene and a number of its analogues. The compounds tested can inhibit hemagglutinin (HA) by binding to it at two possible sites. Moreover, the binding site located at the site of proteolysis is the most important. Serial passaging of influenza in the presence of camphecene leads to the formation of mutation-associated resistance. Specifically, camphecene causes a significant mutation in HA (V615L). This substitution likely reduces the affinity of the compound for the binding site due to steric restriction of the positioning of camphecene in the binding cavity. Molecular dynamics (MD) simulation results show that the mutant HA is a more stable structure in terms of thermodynamics. In other words, launching conformational rearrangements preceding the transition from pre- to post-fusion requires more energy than in wild type HA. This may well explain the lower virulence seen with the camphecene-resistant strain.

In silico studies of ASEM analogues targeting α7-nAChR and experimental verification

The α7 nicotinic acetylcholine receptor (α7-nAChR) is implicated in a variety of neurodegenerative and neuropsychiatric disorders, such as Alzheimer's disease (AD) and schizophrenia. The progress of these disorders can be studied using positron emission tomography (PET) with radiotracers for α7-nAChR. [18F]ASEM and [18F] para-ASEM (also referred to as [18F]DBT-10) are novel and potent α7-nAChR PET radiotracers which have successfully been used in human subjects and nonhuman primates, though further improvement of them is still a pressing task in the community of neurodegeneration research. In this work, we demonstrate the use of modern in silico techniques to predict the binding modes, binding strengths, and residence times for molecular PET tracers binding to proteins, using ASEM and DBT-10 as a showcase of the predictive and interpretational power of such techniques, in particular free energy perturbation theory. The corresponding compounds were synthesized and further tested by in vitro binding experiment for validation. Encouragingly, our in silico modeling can correctly predict the binding affinities of the ASEM analogues. The structure-activity relationships for the ortho- and para-substitutions are well explained at the atomistic level and provide structure-based guiding for the future development of PET tracers for α7-nAChR. A discussion is presented on the complementary use of in silico rational methods based on atomic and electronic principles for in vitro characterization of PET tracers.

4-Oxoquinolines and monoamine oxidase: When tautomerism matters

4-Oxoquinoline derivatives have been often used in drug discovery programs due to their pharmacological properties. Inspired on chromone and 4-oxoquinoline chemical structure similarity, a small series of quinoline-based compounds was obtained and screened, for the first time, toward human monoamine oxidases isoforms. The data showed the N-(3,4-dichlorophenyl)-1-methyl-4-oxo-1,4-dihydroquinoline-3-carboxamide 10 was the most potent and selective MAO-B inhibitor (IC₅₀ = 5.30 ± 0.74 nM and SI: ≥1887). The data analysis showed that prototropic tautomerism markedly influences the biological activity. The unequivocal characterisation of the quinoline tautomers was performed to understand the attained data. To our knowledge, there have been no prior reports on the characterisation of quinolone tautomers by 2D NMR techniques, namely by ¹H-¹⁵N HSQC and ¹H-¹⁵N HMBC, which are proposed as expedite tools for medicinal chemistry campaigns. Computational studies on enzyme-ligand complexes, obtained after MM-GBSA calculations and molecular dynamics simulations, supported the experimental data.

Accurate MP2-based force fields predict hydration free energies for simple alkanes and alcohols in good agreement with experiments

Force fields for four small molecules, methane, ethane, methanol, and ethanol, were created by force matching MP2 gradients computed with triple-zeta-quality basis sets using the Adaptive Force Matching method. Without fitting to any experimental properties, the force fields created were able to predict hydration free energies, enthalpies of hydration, and diffusion constants in excellent agreements with experiments. The root mean square error for the predicted hydration free energies is within 1 kJ/mol of experimental measurements of Ben-Naim et al. [J. Chem. Phys. 81(4), 2016-2027 (1984)]. The good prediction of hydration free energies is particularly noteworthy, as it is an important fundamental property. Similar hydration free energies of ethane relative to methane and of ethanol relative to methanol are attributed to a near cancellation of cavitation penalty and favorable contributions from dispersion and Coulombic interactions as a result of the additional methyl group.

Insight on [1,3]thiazolo[4,5-e]isoindoles as tubulin polymerization inhibitors

A series of [1,3]thiazolo[4,5-e]isoindoles has been synthesized through a versatile and high yielding multistep sequence. Evaluation of the antiproliferative activity of the new compounds on the full NCI human tumor cell line panel highlighted several compounds that are able to inhibit tumor cell proliferation at micromolar-submicromolar concentrations. The most active derivative 11g was found to cause cell cycle arrest at the G2/M phase and induce apoptosis in HeLa cells, following the mitochondrial pathway, making it a lead compound for the discovery of new antimitotic drugs.

New type of anti-influenza agents based on benzo[d][1,3]dithiol core

We synthesized a series of amides with a benzo[d][1,3]dithiol core. The chemical library of compounds was tested for their cytotoxicity and inhibiting activity against influenza virus A/California/07/09 (H1N1)pdm09 in MDCK cells. For each compound, values of CC₅₀, IC₅₀ and selectivity index (SI) were determined. Compounds of this structure type were for the first time found to exhibit anti-influenza activity. The structure of an amide substituent in the tested compounds was demonstrated to have a significant effect on their activity against the H1N1 influenza virus and cytotoxicity. Compound 4d has a high selectivity index of about 30. 4d was shown to be most potent at early stages of viral cycle. In direct fusogenic assay it demonstrated dose-dependent activity against fusogenic activity of hemagglutinin of influenza virus. Based on molecular docking and regression analysis data, viral hemagglutinin was suggested as possible target for these new antiviral agents.

Design a synthetic glucose receptor using computational intelligence approach

The synthetic glucose receptors help to develop glucose sensors and alternative insulin therapies. Designing a glucose recognition molecule in an aqueous system remains a considerable challenge. Therefore, In-silico molecular screening hypothesis is proposed to overcome the difficulties found during the modeling of a molecule. The small organic compounds from compound databases are screened for glucose receptor modeling. Thereafter, the different computational models are designed that mimic natural glucose receptors based on screened compounds. The orientation and binding of glucose molecules within the developed receptor are predicted through the molecular interaction approach. The modeled receptors and receptor-glucose complex structures are used for geometry optimization and molecular dynamics computation. The docking results reveal that ZINC82047919, ZINC238094340, and ZINC238519600 compounds-based models provide better interactions with glucose and its orientation within the receptor cavity. The molecular dynamics simulation results showed that the receptor designed using compound ZINC238094340 is unable to hold the glucose and undergo significant conformation changes during simulation process. The receptor designed from ZINC238094340 and ZINC238519600 compounds is utilized as a reference glucose binding receptor in this study. The proposed computational approach is able to develop a novel glucose receptor and other glucose relative sugar molecules.

Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery

Predicting protein-ligand binding affinities and the associated thermodynamics of biomolecular recognition is a primary objective of structure-based drug design. Alchemical free energy simulations offer a highly accurate and computationally efficient route to achieving this goal. While the AMBER molecular dynamics package has successfully been used for alchemical free energy simulations in academic research groups for decades, widespread impact in industrial drug discovery settings has been minimal because of the previous limitations within the AMBER alchemical code, coupled with challenges in system setup and postprocessing workflows. Through a close academia-industry collaboration we have addressed many of the previous limitations with an aim to improve accuracy, efficiency, and robustness of alchemical binding free energy simulations in industrial drug discovery applications. Here, we highlight some of the recent advances in AMBER20 with a focus on alchemical binding free energy (BFE) calculations, which are less computationally intensive than alternative binding free energy methods where full binding/unbinding paths are explored. In addition to scientific and technical advances in AMBER20, we also describe the essential practical aspects associated with running relative alchemical BFE calculations, along with recommendations for best practices, highlighting the importance not only of the alchemical simulation code but also the auxiliary functionalities and expertise required to obtain accurate and reliable results. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative BFE simulations in AMBER20, with a focus on real-world drug discovery applications.

Pyrrolo[2',3':3,4]cyclohepta[1,2-d][1,2]oxazoles, a New Class of Antimitotic Agents Active against Multiple Malignant Cell Types

A new class of pyrrolo[2',3':3,4]cyclohepta[1,2-d][1,2]oxazoles was synthesized for the treatment of hyperproliferative pathologies, including neoplasms. The new compounds were screened in the 60 human cancer cell lines of the NCI drug screen and showed potent activity with GI50 values reaching the nanomolar level, with mean graph midpoints of 0.08-0.41 μM. All compounds were further tested on six lymphoma cell lines, and eight showed potent growth inhibitory effects with IC50 values lower than 500 nM. Mechanism of action studies showed the ability of the new [1,2]oxazoles to arrest cells in the G2/M phase in a concentration dependent manner and to induce apoptosis through the mitochondrial pathway. The most active compounds inhibited tubulin polymerization, with IC50 values of 1.9-8.2 μM, and appeared to bind to the colchicine site. The G2/M arrest was accompanied by apoptosis, mitochondrial depolarization, generation of reactive oxygen species, and PARP cleavage.

Automated Design of Macrocycles for Therapeutic Applications: From Small Molecules to Peptides and Proteins

Macrocycles and cyclic peptides are increasingly attractive therapeutic modalities as they often have improved affinity, are able to bind to extended protein surfaces, and otherwise have favorable properties. Macrocyclization of a known binder may stabilize its bioactive conformation and improve its metabolic stability, cell permeability, and in certain cases oral bioavailability. Herein, we present implementation and application of an approach that automatically generates, evaluates, and proposes cyclizations utilizing a library of well-established chemical reactions and reagents. Using the three-dimensional (3D) conformation of the linear molecule in complex with a target protein as the starting point, this approach identifies attachment points, generates linkers, evaluates their geometric compatibility, and ranks the resulting molecules with respect to their predicted conformational stability and interactions with the target protein. As we show here with prospective and retrospective case studies, this procedure can be applied for the macrocyclization of small molecules and peptides and even PROteolysis TArgeting Chimeras (PROTACs) and proteins.

A fast and high-quality charge model for the next generation general AMBER force field

The General AMBER Force Field (GAFF) has been broadly used by researchers all over the world to perform in silico simulations and modelings on diverse scientific topics, especially in the field of computer-aided drug design whose primary task is to accurately predict the affinity and selectivity of receptor-ligand binding. The atomic partial charges in GAFF and the second generation of GAFF (GAFF2) were originally developed with the quantum mechanics derived restrained electrostatic potential charge, but in practice, users usually adopt an efficient charge method, Austin Model 1-bond charge corrections (AM1-BCC), based on which, without expensive ab initio calculations, the atomic charges could be efficiently and conveniently obtained with the ANTECHAMBER module implemented in the AMBER software package. In this work, we developed a new set of BCC parameters specifically for GAFF2 using 442 neutral organic solutes covering diverse functional groups in aqueous solution. Compared to the original BCC parameter set, the new parameter set significantly reduced the mean unsigned error (MUE) of hydration free energies from 1.03 kcal/mol to 0.37 kcal/mol. More excitingly, this new AM1-BCC model also showed excellent performance in the solvation free energy (SFE) calculation on diverse solutes in various organic solvents across a range of different dielectric constants. In this large-scale test with totally 895 neutral organic solvent-solute systems, the new parameter set led to accurate SFE predictions with the MUE and the root-mean-square-error of 0.51 kcal/mol and 0.65 kcal/mol, respectively. This newly developed charge model, ABCG2, paved a promising path for the next generation GAFF development.

Discovery of new small-molecule cyclin-dependent kinase 6 inhibitors through computational approaches

Excessive cell proliferation due to cell cycle disorders is one of the hallmarks of breast cancer. Cyclin-dependent kinases (CDKs), which are involved in the transition of the cell cycle from G1 phase to S phase by combining CDKs with cyclin, are considered promising targets with broad therapeutic potential based on their critical role in cell cycle regulation. Pharmacological evidence has shown that abnormal cell cycle due to the overexpression of CDK6 is responsible for the hyperproliferation of cancer cells. Blocking CDK6 expression inhibits tumour survival and growth. Therefore, CDK6 can be regarded as a potential target for anticancer therapeutics. Thus, small molecules that can be considered CDK inhibitors have been developed into promising anticancer drugs. In this study, combined structure-based and ligand-based in silicon models were created to identify new chemical entities against CDK6 with the appropriate pharmacokinetic properties. The database used to screen drug-like compounds in this thesis was based on the best E-pharmacophore hypothesis and the best ligand-based drug hypothesis. As a result, 147 common compounds were identified by further molecular docking. Surprisingly, the in vitro evaluation results of 20 of those compounds showed that the two had good CDK6 inhibitory effects. The best compound was subjected to kinase panel screening, followed by molecular dynamic simulations. The 50-ns MD studies revealed the pivotal role of VAL101 in the binding of inhibitors to CDK6. Overall, the identification of two new chemical entities with CDK6 inhibitory activity demonstrated the feasibility and potential of the new method.

Diacetoxy iodobenzene mediated regioselective synthesis and characterization of novel [1,2,4]triazolo[4,3-a]pyrimidines: apoptosis inducer, antiproliferative activities and molecular docking studies

Prompt and regioselective synthesis of eleven novel [1,2,4]triazolo[4,3-a]pyrimidines 2a-2k, via intramolecular oxidative-cyclization of 2-(2-arylidenehydrazinyl)-4-methyl-6-phenylpyrimidine derivatives 1a-1k has been demonstrated here using diacetoxy iodobenzene (DIB) as inexpensive and ecofriendly hypervalent iodine(III) reagent in CH₂Cl₂ at room temperature. Regiochemistry of final product has been established by developing single crystal and studied X-ray crystallographic data for two derivatives 2c and 2h without any ambiguity. These prominent [1,2,4]triazolo[4,3-a]pyrimidines were evaluated for human osteosarcoma bone cancer (MG-63) and breast cancer (MCF-7) cell lines using MTT assay to find potent antiproliferative agent and also on testicular germ cells to find potent apoptotic inducing activities. All compounds show significant cytotoxicity, particularly 3-(2,4-dichlorophenyl)-5-methyl-7-phenyl-[1,2,4]triazolo[4,3-a]pyrimidine (2g) was found significant apoptotic inducing molecule, as well as the most potent cytotoxic agent against bone cancer (MG-63) and breast cancer (MCF-7) cell lines with GI₅₀ value 148.96 µM and 114.3 µM respectively. Molecular docking studies has been carried out to see the molecular interactions of synthesized compounds with the protein thymidylate synthase (PBD ID: 2G8D).Communicated by Ramaswamy H. Sarma.

Pairwise-additive and polarizable atomistic force fields for molecular dynamics simulations of proteins

Protein force fields have been undergoing continual development since the first complete parameter sets were introduced nearly four decades ago. The functional forms that underlie these models have many common elements for the treatment of bonded and nonbonded forces, which are reviewed here. The most widely used force fields to date use a fixed-charge convention in which electronic polarization effects are treated via a mean-field approximation during partial charge assignment. Despite success in modeling folded proteins over many years, the fixed-charge assumption has limitations that cannot necessarily be overcome within their potential energy equations. To overcome these limitations, several force fields have recently been derived that explicitly treat electronic polarization effects with straightforward extensions of the potential energy functions used by nonpolarizable force fields. Here, we review the history of the most popular nonpolarizable force fields (AMBER, CHARMM, OPLS, and GROMOS) as well as studies that have validated them and applied them to studies of protein folding and misfolding. Building upon these force fields are more recent polarizable interaction potentials, including fluctuating charge models, POSSIM, AMOEBA, and the classical Drude oscillator. These force fields differ in their implementations but all attempt to model electronic polarization in a computationally tractable manner. Despite their recent emergence in the field of protein folding, several studies have already applied these polarizable models to challenging problems in this domain, including the role of polarization in folding free energies and sequence-specific effects on the stability of α-helical structures.

A machine learning based intramolecular potential for a flexible organic molecule

Here, we employ the kernel regression machine learning technique to construct an analytical potential that reproduces the quantum mechanical potential energy surface of a small, flexible, drug-like molecule, 3-(benzyloxy)pyridin-2-amine.

Computational investigations and molecular dynamics simulations envisioned for potent antioxidant and anticancer drugs using indole-chalcone-triazole hybrids

Cancer, also called malignancy, is a disease which is closely related with the oxidative stress instigated by the overproduction of vulnerable oxygen and nitrogen species. Available drugs are relatively painful and toxic and so are trailing their captivation. Keeping this in mind, we have attempted to reach a novel anti-cancer drug by taking a set of nineteen ligands which are hybrids of Indole-chalcone and triazole. These ligands were allowed to interact with the DNA dodecamer 5'(CGCGAATTCGCG)3' one by one using various docking protocols of Glide. Better docked complexes screened through docking scores and reported activity data were selected and exposed to molecular dynamics run of 20 ns. The dynamical pathways were investigated for each complex comparing the pre- and post- dynamics run. The outcome of the work is discussed in this paper. Among the better hybrids of this series, one of the molecules has shown interesting features, confirming its non-toxic nature and working as intercalator as well minor groove binder, perhaps making it suitable as a potent drug for further pharmacological use.

Design, Synthesis, and Pharmacological Evaluation of Potent Positive Allosteric Modulators of the Glucagon-like Peptide-1 Receptor (GLP-1R)

The therapeutic success of peptidic GLP-1 receptor agonists for treatment of type 2 diabetes mellitus (T2DM) motivated our search for orally bioavailable small molecules that can activate the GLP-1 receptor (GLP-1R) as a well-validated target for T2DM. Here, the discovery and characterization of a potent and selective positive allosteric modulator (PAM) for GLP-1R based on a 3,4,5,6-tetrahydro-1H-1,5-epiminoazocino[4,5-b]indole scaffold is reported. Optimization of this series from HTS was supported by a GLP-1R ligand binding model. Biological in vitro testing revealed favorable ADME and pharmacological profiles for the best compound 19. Characterization by in vivo pharmacokinetic and pharmacological studies demonstrated that 19 activates GLP-1R as positive allosteric modulator (PAM) in the presence of the much less active endogenous degradation product GLP1(9-36)NH₂ of the potent endogenous ligand GLP-1(7-36)NH₂. While these data suggest the potential of small molecule GLP-1R PAMs for T2DM treatment, further optimization is still required towards a clinical candidate.

Microbe-Derived Indole Metabolite Demonstrates Potent Multidrug Efflux Pump Inhibition in Staphylococcus aureus

Efflux pumps are always at the forefront of bacterial multidrug resistance and account for the failure of antibiotics. The present study explored the potential of 2-(2-Aminophenyl) indole (RP2), an efflux pump inhibitor (EPI) isolated from the soil bacterium, to overcome the efflux-mediated resistance in Staphylococcus aureus. The RP2/antibiotic combination was tested against efflux pump over-expressed S. aureus strains. The compound was further examined for the ethidium bromide (EtBr) uptake and efflux inhibition assay (a hallmark of EPI functionality) and cytoplasmic membrane depolarization. The safety profile of RP2 was investigated using in vitro cytotoxicity assay and Ca²⁺ channel inhibitory effect. The in vivo efficacy of RP2 was studied in an animal model in combination with ciprofloxacin. RP2 exhibited the synergistic activity with several antibiotics in efflux pump over-expressed strains of S. aureus. In the mechanistic experiments, RP2 increased the accumulation of EtBr, and demonstrated the inhibition of its efflux. The antibiotic-EPI combinations resulted in extended post antibiotic effects as well as a decrease in mutation prevention concentration of antibiotics. Additionally, the in silico docking studies suggested the binding of RP2 to the active site of modeled structure of NorA efflux pump. The compound displayed low mammalian cytotoxicity and had no Ca²⁺ channel inhibitory effect. In ex vivo experiments, RP2 reduced the intracellular invasion of S. aureus in macrophages. Furthermore, the RP2/ciprofloxacin combination demonstrated remarkable efficacy in a murine thigh infection model. In conclusion, RP2 represents a promising candidate as bacterial EPI, which can be used in the form of a novel therapeutic regimen along with existing and upcoming antibiotics, for the eradication of S. aureus infections.

Chromenone derivatives as a versatile scaffold with dual mode of inhibition of HIV-1 reverse transcriptase-associated Ribonuclease H function and integrase activity

A number of compounds targeting different processes of the Human Immunodeficiency Virus type 1 (HIV-1) life cycle have been developed in the continuing fight against AIDS. Coumarin-based molecules already proved to act as HIV-1 Protease (PR) or Integrase (IN) inhibitors and also to target HIV-1 reverse transcriptase (RT), blocking the DNA-dependent DNA-polymerase activity or the RNA-dependent DNA-polymerase activity working as common NNRTIs. In the present study, with the aim to exploit a coumarin-based scaffold to achieve the inhibition of multiple viral coded enzymatic functions, novel 4-hydroxy-2H, 5H-pyrano (3, 2-c) chromene-2, 5-dione derivatives were synthesized. The modeling studies calculated the theoretical binding affinity of the synthesized compounds on both HIV-1 IN and RT-associated Ribonuclease H (RNase H) active sites, which was confirmed by biological assays. Our results provide a basis for the identification of dual HIV-1 IN and RT RNase H inhibitors compounds.

Predicting Octanol-Water Partition Coefficients: Are Quantum Mechanical Implicit Solvent Models Better than Empirical Fragment-Based Methods?

In this work, we examined the performance of contemporary quantum mechanical implicit solvent models (SMD, SM8, SM12, and ADF-COSMO-RS) and empirical fragment-based methods for predicting octanol-water partition coefficients (log P_ow). Two test sets were chosen: the first is composed of 34 organic molecules from a recent study by Mobley J. Chem. Theory Comput , 2016 , 12 , 4015 - 4024 , and the second set is based on a collection of 55 fluorinated alkanols and carbohydrates from Linclau Angew. Chem., Int. Ed. , 2016 , 55 , 674 - 678 . Our analysis indicates that the errors in the solvation free energies of implicit models are reasonably systematic in both solvents such that there is substantial cancellation of errors in the calculation of transfer free energies. Overall, implicit solvent models performed very well across the two test sets with mean absolute errors (MAEs) of about 0.6 log unit and are superior to explicit solvent simulations (GAFF and GAFF-DC). Interestingly, the best performers were empirical fragment-based methods, including ALOGP and miLOGP with significantly lower MAEs (0.2 to 0.4 log unit). The ALOGP method was further tested against the recent SAMPL6 log P_ow challenge consisting of 11 drug-like molecules where it obtained an MAE of 0.32 log unit compared to the best-performing COSMOtherm model (0.31 log unit).

Computation of protein-ligand binding free energies using quantum mechanical bespoke force fields

A quantum mechanical bespoke molecular mechanics force field is derived for the L99A mutant of T4 lysozyme and used to compute absolute binding free energies of six benzene analogs to the protein. Promising agreement between theory and experiment highlights the potential for future use of system-specific force fields in computer-aided drug design.

Infinite Dilution Activity Coefficients as Constraints for Force Field Parametrization and Method Development

Molecular simulations begin with an underlying energy model or force field and from this can predict diverse physical properties. However, force fields were often developed with relatively limited data sets, yet accuracy for diverse properties across a broad chemical space is desirable; therefore, tests of such accuracy are particularly important. Here, to this end, we calculated 237 infinite dilution activity coefficients (IDACs), comparing with experimental values from NIST's ThermoML database. We found that calculated IDAC values correlate strongly with experiment (Pearson R of 0.92 ± 0.01) and allow us to identify specific functional groups that appear to present challenges to the force field employed. One potentially valuable aspect of IDACs, as compared to solvation free energies, which have been frequently employed as force field tests, is that the same molecules serve both as solutes and solvents in different cases, allowing us to ensure that force fields are not overly tuned to one particular environment or solvent.

Challenges in the use of atomistic simulations to predict solubilities of drug-like molecules

Background: Solubility is a physical property of high importance to the pharmaceutical industry, the prediction of which for potential drugs has so far been a hard task. We attempted to predict the solubility of acetylsalicylic acid (ASA) by estimating the absolute chemical potentials of its most stable polymorph and of solutions with different concentrations of the drug molecule. Methods: Chemical potentials were estimated from all-atom molecular dynamics simulations.  We used the Einstein molecule method (EMM) to predict the absolute chemical potential of the solid and solvation free energy calculations to predict the excess chemical potentials of the liquid-phase systems. Results: Reliable estimations of the chemical potentials for the solid and for a single ASA molecule using the EMM required an extremely large number of intermediate states for the free energy calculations, meaning that the calculations were extremely demanding computationally. Despite the computational cost, however, the computed value did not agree well with the experimental value, potentially due to limitations with the underlying energy model. Perhaps better values could be obtained with a better energy model; however, it seems likely computational cost may remain a limiting factor for use of this particular approach to solubility estimation.    Conclusions: Solubility prediction of drug-like solids remains computationally challenging, and it appears that both the underlying energy model and the computational approach applied may need improvement before the approach is suitable for routine use.

Unexpected trends in the hydrophobicity of fluorinated amino acids reflect competing changes in polarity and conformation

The hydration free energy of fluorinated amino acids is calculated with molecular simulations and explained with an analytical model.

Small Molecule Inhibitor that Stabilizes the Autoinhibited Conformation of the Oncogenic Tyrosine Phosphatase SHP2

Genetic mutations in the phosphatase PTPN11 (SHP2) are associated with childhood leukemias. These mutations cause hyperactivation of SHP2 due to the disruption of the autoinhibitory conformation. By targeting the activation-associated protein conformational change, we have identified an SHP2 inhibitor ( E)-1-(1-(5-(3-(2,4-dichlorophenyl)acryloyl)-2-ethoxy-4-hydroxybenzyl)-1,2,5,6-tetrahydropyridin-3-yl)-1 H-benzo[ d]imidazol-2(3 H)-one (LY6, 1) using computer-aided drug design database screening combined with cell-based assays. This compound inhibited SHP2 with an IC₅₀ value of 9.8 μM, 7-fold more selective for SHP2 than the highly related SHP1. Fluorescence titration, thermal shift, and microscale thermophoresis quantitative binding assays confirmed its direct binding to SHP2. This compound was further verified to effectively inhibit SHP2-mediated cell signaling and proliferation. Furthermore, mouse and patient leukemia cells with PTPN11 activating mutations were more sensitive to this inhibitor than wild-type cells. This small molecule SHP2 inhibitor has a potential to serve as a lead compound for further optimization studies to develop novel anti-SHP2 therapeutic agents.

Automated Topology Builder Version 3.0: Prediction of Solvation Free Enthalpies in Water and Hexane

The ability of atomic interaction parameters generated using the Automated Topology Builder and Repository version 3.0 (ATB3.0) to predict experimental hydration free enthalpies (Δ G^water) and solvation free enthalpies in the apolar solvent hexane (Δ G^hexane) is presented. For a validation set of 685 molecules the average unsigned error (AUE) between Δ G^water values calculated using the ATB3.0 and experiment is 3.8 kJ·mol^-1. The slope of the line of best fit is 1.00, the intercept -1.0 kJ·mol^-1, and the R² 0.90. For the more restricted set of 239 molecules used to validate OPLS3 ( J. Chem. Theory Comput. 2016 , 12 , 281 - 296 , DOI: 10.1021/acs.jctc.5b00864 ) the AUE using the ATB3.0 is just 2.7 kJ·mol^-1 and the R² 0.93. A roadmap for further improvement of the ATB parameters is presented together with a discussion of the challenges of validating force fields against the available experimental data.

Reproducibility of Free Energy Calculations across Different Molecular Simulation Software Packages

Alchemical free energy calculations are an increasingly important modern simulation technique to calculate free energy changes on binding or solvation. Contemporary molecular simulation software such as AMBER, CHARMM, GROMACS, and SOMD include support for the method. Implementation details vary among those codes, but users expect reliability and reproducibility, i.e., for a given molecular model and set of force field parameters, comparable free energy differences should be obtained within statistical bounds regardless of the code used. Relative alchemical free energy (RAFE) simulation is increasingly used to support molecule discovery projects, yet the reproducibility of the methodology has been less well tested than its absolute counterpart. Here we present RAFE calculations of hydration free energies for a set of small organic molecules and demonstrate that free energies can be reproduced to within about 0.2 kcal/mol with the aforementioned codes. Absolute alchemical free energy simulations have been carried out as a reference. Achieving this level of reproducibility requires considerable attention to detail and package-specific simulation protocols, and no universally applicable protocol emerges. The benchmarks and protocols reported here should be useful for the community to validate new and future versions of software for free energy calculations.

Peptides Derived from Histone 3 and Modified at Position 18 Inhibit Histone Demethylase KDM6 Enzymes

The KDM6 subfamily of histone lysine demethylases has recently been implicated as a putative target in the treatment of a number of diseases; this makes the availability of potent and selective inhibitors important. Due to high sequence similarity of the catalytic domain of Jumonji C histone demethylases, the development of small-molecule, family-specific inhibitors has, however, proven challenging. One approach to achieve the selective inhibition of these enzymes is the use of peptides derived from the substrate, the histone 3 C terminus. Here we used computational methods to optimize such inhibitors of the KDM6 family. Through natural amino acid substitution, it is shown that a K18I variant of a histone H3 derived peptide significantly increases affinity towards the KDM6 enzymes. The crystal structure of KDM6B in complex with a histone 3 derived K18I peptide reveals a tighter fit of the isoleucine side chain, compared with that of the arginine. As a consequence, the peptide R17 residue also has increased hydrophilic interactions. These interactions of the optimized peptide are likely to be responsible for the increased affinity to the KDM6 enzymes.

Biosolvation Nature of Ionic Liquids: Molecular Dynamics Simulation of Methylated Nucleobases in Hydrated 1-Ethyl-3-methylimidazolium Acetate

Solvation free energies of methylated nucleobases were calculated in pure and hydrated 1-ethyl-3-methylimidazolium acetate, [Emim][Ac], ionic liquid, and pure water using classical molecular dynamics simulations using multistate Bennett's acceptance ratio method. The calculated solvation free energies in pure water were compared with the previous experimental and theoretical findings and found to be in agreement. We observe that the solvation free energy of methylated nucleobases is more in the pure ionic liquid compared to that in the pure water and on changing the mole fraction of water in the ionic liquid, the solvation free energy decreases gradually. Comparing the Coulombic and van der Waals contribution to the solvation free energy, electrostatic contribution is more compared to that of the latter for all nucleobases. To obtain the atomistic details and explain the solvation mechanism, we calculated radial distribution functions (RDFs), spatial distribution functions (SDFs), and stacking angle distribution of cations to the nucleobases. From RDFs and SDFs, we find that the acetate anions of the ionic liquid are forming strong hydrogen bonds with the amine hydrogen atoms of the nucleobases. These hydrogen bonds contribute to the major part of the Coulombic contribution to the solvation free energy. Stacking of cations to the nucleobases is primarily due to the van der Waals contribution to the solvation free energy.