Binding Free-Energy Calculation Is a Powerful Tool for Drug Optimization: Calculation and Measurement of Binding Free Energy for 7-Azaindole Derivatives to Glycogen Synthase Kinase-3β

Discovery of Potential Antiviral Compounds against Hendra Virus by Targeting Its Receptor-Binding Protein (G) Using Computational Approaches

Hendra virus (HeV) belongs to the paramyxoviridae family of viruses which is associated with the respiratory distress, neurological illness, and potential fatality of the affected individuals. So far, no competitive approved therapeutic substance is available for HeV. For that reason, the current research work was conducted to propose some novel compounds, by adopting a Computer Aided Drug Discovery approach, which could be used to combat HeV. The G attachment Glycoprotein (Ggp) of HeV was selected to achieve the primary objective of this study, as this protein makes the entry of HeV possible in the host cells. Briefly, a library of 6000 antiviral compounds was screened for potential drug-like properties, followed by the molecular docking of short-listed compounds with the Protein Data Bank (PDB) structure of Ggp. Docked complexes of top two hits, having maximum binding affinities with the active sites of Ggp, were further considered for molecular dynamic simulations of 200 ns to elucidate the results of molecular docking analysis. MD simulations and Molecular Mechanics Energies combined with the Generalized Born and Surface Area (MMGBSA) or Poisson-Boltzmann and Surface Area (MMPBSA) revealed that both docked complexes are stable in nature. Furthermore, the same methodology was used between lead compounds and HeV Ggp in complex with its functional receptor in human, Ephrin-B2. Surprisingly, no major differences were found in the results, which demonstrates that our identified compounds can also perform their action even when the Ggp is attached to the Ephrin-B2 ligand. Therefore, in light of all of these results, we strongly suggest that compounds (S)-5-(benzylcarbamoyl)-1-(2-(4-methyl-2-phenylpiperazin-1-yl)-2-oxoethyl)-6-oxo-3,6-dihydropyridin-1-ium-3-ide and 5-(cyclohexylcarbamoyl)-1-(2-((2-(3-fluorophenyl)-2-methylpropyl)amino)-2-oxoethyl)-6-oxo-3,6-dihydropyridin-1-ium-3-ide could be considered as potential therapeutic agents against HeV; however, further in vitro and in vivo experiments are required to validate this study.

Understanding the Polypharmacological Profiles of Triple Reuptake Inhibitors by Molecular Simulation

The triple reuptake inhibitors (TRIs) class is a class of effective inhibitors of human monoamine transporters (hMATs), which includes dopamine, norepinephrine, and serotonin transporters (hDATs, hNETs, and hSERTs). Due to the high degree of structural homology of the binding sites of those transporters, it is a great challenge to design potent TRIs with fine-tuned binding profiles. The molecular determinants responsible for the binding selectivity of TRIs to hDATs, hNETs, and hSERTs remain elusive. In this study, the solved X-ray crystallographic structure of hSERT in complex with escitalopram was used as a basis for modeling nine complexes of three representative TRIs (SEP225289, NS2359, and EB1020) bound to their corresponding targets. Molecular dynamics (MD) and effective post-trajectory analysis were performed to estimate the drug binding free energies and characterize the selective profiles of each TRI to hMATs. The common binding mode of studied TRIs to hMATs was revealed by hierarchical clustering analysis of the per-residue energy. Furthermore, the combined protein-ligand interaction fingerprint and residue energy contribution analysis indicated that several conserved and nonconserved "Warm Spots" such as S149, V328, and M427 in hDAT, F317, F323, and V325 in hNET and F335, F341, and V343 in hSERT were responsible for the TRI-binding selectivity. These findings provided important information for rational design of a single drug with better polypharmacological profiles through modulating multiple targets.

In silico approaches using pharmacophore model combined with molecular docking for discovery of novel ULK1 inhibitors

Background: Discovery of effective autophagy-initiating kinase ULK1 inhibitors has attracted more and more attention in cancer treatment. Methodology & results: The present study describes the application of a pharmacophore-based virtual screening and structure-based docking approach guided drug design. Compound U-2 exhibited a nanomolar range of IC₅₀ against the ULK1 target. Molecular dynamics simulation was used to assess the quality of docking studies. The determinants of binding affinity were investigated, and a different binding pattern was observed. Subsequently, prediction properties of ADMET (absorption, distribution, metabolism, excretion and toxicity) and hepatotoxicity in vitro studies indicated that U-2 possessed good drug-like properties. Moreover, western blot analysis indicated that the compound inhibited autophagic flux in cells. Conclusion: The present study provides an appropriate guideline for discovering novel ULK1 inhibitors. The novel compound may serve as a good starting point for further development and optimizations.

SAMPL6 host-guest challenge: binding free energies via a multistep approach

In this effort in the SAMPL6 host-guest binding challenge, a combination of molecular dynamics and quantum mechanical methods were used to blindly predict the host-guest binding free energies of a series of cucurbit[8]uril (CB8), octa-acid (OA), and tetramethyl octa-acid (TEMOA) hosts bound to various guest molecules in aqueous solution. Poses for host-guest systems were generated via molecular dynamics (MD) simulations and clustering analyses. The binding free energies for the structures obtained via cluster analyses of MD trajectories were calculated using the MMPBSA method and density functional theory (DFT) with the inclusion of Grimme's dispersion correction, an implicit solvation model to model the aqueous solution, and the resolution-of-the-identity (RI) approximation (MMPBSA, RI-B3PW91-D3, and RI-B3PW91, respectively). Among these three methods tested, the results for OA and TEMOA systems showed MMPBSA and RI-B3PW91-D3 methods can be used to qualitatively rank binding energies of small molecules with an overbinding by 7 and 37 kcal/mol respectively, and RI-B3PW91 gave the poorest quality results, indicating the importance of dispersion correction for the binding free energy calculations. Due to the complexity of the CB8 systems, all of the methods tested show poor correlation with the experimental results. Other quantum mechanical approaches used for the calculation of binding free energies included DFT without the RI approximation, utilizing truncated basis sets to reduce the computational cost (memory, disk space, CPU time), and a corrected dielectric constant to account for ionic strength within the implicit solvation model.

Biosynthesis of thiocarboxylic acid-containing natural products

Thiocarboxylic acid-containing natural products are rare and their biosynthesis and biological significance remain unknown. Thioplatensimycin (thioPTM) and thioplatencin (thioPTN), thiocarboxylic acid congeners of the antibacterial natural products platensimycin (PTM) and platencin (PTN), were recently discovered. Here we report the biosynthetic origin of the thiocarboxylic acid moiety in thioPTM and thioPTN. We identify a thioacid cassette encoding two proteins, PtmA3 and PtmU4, responsible for carboxylate activation by coenzyme A and sulfur transfer, respectively. ThioPTM and thioPTN bind tightly to β-ketoacyl-ACP synthase II (FabF) and retain strong antibacterial activities. Density functional theory calculations of binding and solvation free energies suggest thioPTM and thioPTN bind to FabF more favorably than PTM and PTN. Additionally, thioacid cassettes are prevalent in the genomes of bacteria, implicating that thiocarboxylic acid-containing natural products are underappreciated. These results suggest that thiocarboxylic acid, as an alternative pharmacophore, and thiocarboxylic acid-containing natural products may be considered for future drug discovery.

Thioplatensimycin (thioPTM) and thioplatencin (thioPTN) are recently discovered thiocarboxylic acid congeners of the antibacterial compounds PTM and PTN. Here, the authors identify a thioacid cassette encoding PtmA3 and PtmU4 that are responsible for carboxylate activation and sulfur transfer, respectively.

Comparative subtractive proteomics based ranking for antibiotic targets against the dirtiest superbug: Acinetobacter baumannii

Multidrug-resistant Acinetobacter baumannii is indeed to be the most successful nosocomial pathogen responsible for myriad infections in modern health care system. Computational methodologies based on genomics and proteomics proved to be powerful tools for providing substantial information about different aspects of A. baumannii biology that made it possible to design new approaches for treating multi, extensive and total drug resistant isolates of A. baumannii. In this current approach, 35 completely annotated proteomes of A. bauamnnii were filtered through a comprehensive subtractive proteomics pipeline for broad-spectrum drug candidates. In total, 10 proteins (KdsA, KdsB, LpxA, LpxC, LpxD, GpsE, PhoB, UvrY, KdpE and OmpR) could serve as ideal candidates for designing novel antibiotics. The work was extended with KdsA enzyme for structure information, prediction of intrinsic disorders, active site details, and structure based virtual screening of library containing natural product-like scaffolds. Most of the enzyme structure has fixed three-dimensional conformation. The selection of inhibitor for KdsA enzyme was based on druglikeness, pharmacokinetics and docking scores. Compound-4636 (5-((3-chloro-5-methyl-2-phenyl-2,3-dihydro-1H-pyrazol-4-yl)methoxy)-2-(((1-hydroxy-4-methylpentan-2-yl)amino)methyl)phenol) was revealed as the most potent inhibitor against A. baumannii KdsA enzyme having Gold fitness score of 77.68 and Autodock binding energy of -6.2 kcal/mol. The inhibitor completely follows Lipinski rule of five, Ghose rule, and Egan rule. Molecular dynamics simulation for KdsA and KdsA-4636 complex was performed for 100 ns to unveil what conformational changes the enzyme underwent in the absence and presence of the inhibitor, respectively. The average root means square deviation (RMSD) for both systems was found 3.5 Å, which signifies stable structure of the enzyme in both bounded and unbounded states. Absolute binding energy using Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) reflected high affinity and vigorous interactions of the inhibitor with enzyme active residues. Findings of the current study could open up new avenues for experimentalists to design new potent antibiotics by targeting the targets screened in this study.

Kinase inhibitors: the road ahead

Receptor tyrosine kinase signalling pathways have been successfully targeted to inhibit proliferation and angiogenesis for cancer therapy. However, kinase deregulation has been firmly demonstrated to play an essential role in virtually all major disease areas. Kinase inhibitor drug discovery programmes have recently broadened their focus to include an expanded range of kinase targets and therapeutic areas. In this Review, we provide an overview of the novel targets, biological processes and disease areas that kinase-targeting small molecules are being developed against, highlight the associated challenges and assess the strategies and technologies that are enabling efficient generation of highly optimized kinase inhibitors.

Effect of Atomic Charges on Octanol-Water Partition Coefficient Using Alchemical Free Energy Calculation

The octanol-water partition coefficient (logPow) is an important index for measuring solubility, membrane permeability, and bioavailability in the drug discovery field. In this paper, the logPow values of 58 compounds were predicted by alchemical free energy calculation using molecular dynamics simulation. In free energy calculations, the atomic charges of the compounds are always fixed. However, they must be recalculated for each solvent. Therefore, three different sets of atomic charges were tested using quantum chemical calculations, taking into account vacuum, octanol, and water environments. The calculated atomic charges in the different environments do not necessarily influence the correlation between calculated and experimentally measured ∆Gwater values. The largest correlation coefficient values of the solvation free energy in water and octanol were 0.93 and 0.90, respectively. On the other hand, the correlation coefficient of logPow values calculated from free energies, the largest of which was 0.92, was sensitive to the combination of the solvation free energies calculated from the calculated atomic charges. These results reveal that the solvent assumed in the atomic charge calculation is an important factor determining the accuracy of predicted logPow values.

Strategies of Virtual Screening in Medicinal Chemistry

Virtual screening represents an effective computational strategy to rise-up the chances of finding new bioactive compounds by accelerating the time needed to move from an initial intuition to market. Classically, the most pursued approaches rely on ligand- and structure-based studies, the former employed when structural data information about the target is missing while the latter employed when X-ray/NMR solved or homology models are instead available for the target. The authors will focus on the most advanced techniques applied in this area. In particular, they will survey the key concepts of virtual screening by discussing how to properly select chemical libraries, how to make database curation, how to applying and- and structure-based techniques, how to wisely use post-processing methods. Emphasis will be also given to the most meaningful databases used in VS protocols. For the ease of discussion several examples will be presented.

Investigation of naphthofuran moiety as potential dual inhibitor against BACE-1 and GSK-3β: molecular dynamics simulations, binding energy, and network analysis to identify first-in-class dual inhibitors against Alzheimer's disease

BACE-1 and GSK-3β are potential therapeutic drug targets for Alzheimer's disease. Recently, both the targets received attention for designing dual inhibitors for Alzheimer's disease. Until now, only two-scaffold triazinone and curcumin have been reported as BACE-1 and GSK-3β dual inhibitors. Docking, molecular dynamics, clustering, binding energy, and network analysis of triazinone derivatives with BACE-1 and GSK-3β was performed to get molecular insight into the first reported dual inhibitor. Further, we designed and evaluated a naphthofuran series for its ability to inhibit BACE-1 and GSK-3β with the computational approaches. Docking study of naphthofuran series showed a good binding affinity towards both the targets. Molecular dynamics, binding energy, and network analysis were performed to compare their binding with the targets and amino acids responsible for binding. Naphthofuran series derivatives showed good interaction within the active site residues of both of the targets. Hydrogen bond occupancy and binding energy suggested strong binding with the targets. Dual-inhibitor binding was mostly governed by the hydrophobic interactions for both of the targets. Per residue energy decomposition and network analysis identified the key residues involved in the binding and inhibiting BACE-1 and GSK-3β. The results indicated that naphthofuran series derivative 11 may be a promising first-in-class dual inhibitor against BACE-1 and GSK-3β. This naphthofuran series may be further explored to design better dual inhibitors. Graphical abstract Naphthofuran derivative as a dual inhibitor for BACE-1 and GSK-3β.

TAK1 inhibition attenuates both inflammation and fibrosis in experimental pneumoconiosis

Pneumoconiosis, caused by inhalation of mineral dusts, is a major occupational disease worldwide. Currently, there are no effective drugs owing to a lack of potential therapeutic targets during either the inflammation or fibrosis molecular events in pneumoconiosis. Here, we performed microarrays to identify aberrantly expressed genes in the above molecular events in vitro and found a hub gene transforming growth factor-β-activated kinase 1 (TAK1), which was highly expressed and activated in pneumoconiosis patients as well as silica-exposed rats with experimental pneumoconiosis. Genetic modulation of TAK1 by CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9, RNA interference and overexpression indicated the important role of TAK1 in both inflammation and fibrosis in experimental pneumoconiosis. To achieve pharmacological TAK1 inhibition, we virtually screened out a natural product resveratrol, which targeted TAK1 at both N161 and A107 residues, and significantly inhibited TAK1 activation to attenuate inflammation and fibrosis in vitro. Consistently, in vivo prevention and intervention studies showed that resveratrol could inhibit pulmonary inflammation and fibrosis in silica-exposed rats.

Identification of lead small molecule inhibitors of glycogen synthase kinase-3 beta using a fragment-linking strategy

Glycogen synthase kinase-3 beta (GSK3β) kinase serves as a promising therapeutic target for the treatment of various human diseases, such as diabetes, obesity, and Alzheimer's disease. In this study, we report lead GSK3β inhibitors identified using a fragment-linking strategy. Through the systematic exploration, a six-atom chain unit bearing the rigid double bond was found to be a suitable linker connecting two fragments, which enables favorable contacts with backbone groups of residues in the pockets. As a consequence, potent GSK3β inhibitor 9i was found with IC₅₀ values of 19nM. The binding mode analysis indicates that the activities of the inhibitors appear to be achieved by the establishment of multiple hydrogen bonds and hydrophobic interactions in the ATP-binding site of GSK3β. The good biochemical potencies and structural uniqueness of the inhibitors support consideration in the further study to optimize the biological activity.

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.

A computational study on role of 6-(hydroxymethyl)-3-[3,4,5-trihydroxy-6-[(3,4,5-trihydroxyoxan-2-yl)oxymethyl]oxan-2-yl]oxyoxane-2,4,5-triol in the regulation of blood glucose level

6-(hydroxymethyl)-3-[3,4,5-trihydroxy-6-[(3,4,5-trihydroxyoxan-2-yl)oxymethyl]oxan-2-yl]oxyoxane-2,4,5-triol (SID 242078875) was isolated from the fruits of Syzygium densiflorum Wall. ex Wight & Arn (Myrtaceae), which has been traditionally used in the treatment of diabetes by the tribes of The Nilgiris, Tamil Nadu, India. In this study, reverse pharmacophore mapping approach and text-based database search identified the dipeptidyl peptidase-IV, protein-tyrosine phosphatase 1B, phosphoenolpyruvate carboxykinase, glycogen synthase kinase-3β and glucokinase as potential targets of SID 242078875 in diabetes management. Further, molecular docking was performed to predict the binding pose of SID 242078875 in the active site region of the target protein. In addition, dynamic behaviour and stability of protein-ligand complexes were observed for a period of 50 ns through molecular dynamics simulation.

Discovery of vascular endothelial growth factor receptor tyrosine kinase inhibitors by quantitative structure–activity relationships, molecular dynamics simulation and free energy calculation

Employing the combined strategy to understand the features of KDR–ligands complexes, and provide a basis for rational design of inhibitors.

Identification of potential CCR5 inhibitors through pharmacophore-based virtual screening, molecular dynamics simulation and binding free energy analysis

Employing the combined strategy to identify novel CCR5 inhibitors and provide a basis for rational drug design.