Pharmacophore-based virtual screening and density functional theory approach to identifying novel butyrylcholinesterase inhibitors

Exploiting butyrylcholinesterase inhibitors through a combined 3-D pharmacophore modeling, QSAR, molecular docking, and molecular dynamics investigation†

Alzheimer's disease (AD), a neurodegenerative condition associated with ageing, can occur. AD gradually impairs memory and cognitive function, which leads to abnormal behavior, incapacity, and reliance. By 2050, there will likely be 100 million cases of AD in the world's population. Acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibition are significant components of AD treatment. This work developed models using the genetic method multiple linear regression, atom-based, field-based, and 3-D pharmacophore modelling. Due to internal and external validation, all of the models have solid statistical (R² > 0.81 and Q² > 0.77) underpinnings. From a pre-plated CNS library (6055), we discovered a hit compound using virtual screening on a QSAR model. Through molecular docking, additional hit compounds were investigated (XP mode). Finally, a molecular dynamics simulation revealed that the Molecule5093-4BDS complex was stable (100 ns). Finally, the expected ADME properties for the hit compounds (Molecule5093, Molecule1076, Molecule4412, Molecule1053, and Molecule3344) were found. According to the results of our investigation and the prospective hit compounds, BuChE inhibitors may be used as a treatment for AD.

Alzheimer's disease (AD), a neurodegenerative condition associated with ageing, can occur.

3D-QSAR-Based Pharmacophore Modeling, Virtual Screening, and Molecular Dynamics Simulations for the Identification of Spleen Tyrosine Kinase Inhibitors

Spleen tyrosine kinase (SYK) is an essential mediator of immune cell signaling and has been anticipated as a therapeutic target for autoimmune diseases, notably rheumatoid arthritis, allergic rhinitis, asthma, and cancers. Significant attempts have been undertaken in recent years to develop SYK inhibitors; however, limited success has been achieved due to poor pharmacokinetics and adverse effects of inhibitors. The primary goal of this research was to identify potential inhibitors having high affinity, selectivity based on key molecular interactions, and good drug-like properties than the available inhibitor, fostamatinib. In this study, a 3D-QSAR model was built for SYK based on known inhibitor IC₅₀ values. The best pharmacophore model was then used as a 3D query to screen a drug-like database to retrieve hits with novel chemical scaffolds. The obtained compounds were subjected to binding affinity prediction using the molecular docking approach, and the results were subsequently validated using molecular dynamics (MD) simulations. The simulated compounds were ranked according to binding free energy (ΔG), and the binding affinity was compared with fostamatinib. The binding mode analysis of selected compounds revealed that the hit compounds form hydrogen bond interactions with hinge region residue Ala451, glycine-rich loop residue Lys375, Ser379, and DFG motif Asp512. Identified hits were also observed to form a desirable interaction with Pro455 and Asn457, the rare feature observed in SYK inhibitors. Therefore, we argue that identified hit compounds ZINC98363745, ZINC98365358, ZINC98364133, and ZINC08789982 may help in drug design against SYK.

Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation

In the landscape of epigenetic regulation, histone deacetylase 3 (HDAC3) has emerged as a prominent therapeutic target for the design and development of candidate drugs against various types of cancers and other human disorders. Herein, we have performed ligand-based pharmacophore modeling, virtual screening, molecular docking, and MD simulations to design potent and selective inhibitors against HDAC3. The predicted best pharmacophore model ‘Hypo 1’ showed excellent correlation (R² = 0.994), lowest RMSD (0.373), lowest total cost value (102.519), and highest cost difference (124.08). Hypo 1 consists of four salient pharmacophore features viz. one hydrogen bond acceptor (HBA), one ring aromatic (RA), and two hydrophobic (HYP). Hypo 1 was validated by Fischer's randomization with a 95% of confidence level and the external test set of 60 compounds with a good correlation coefficient (R² = 0.970). The virtual screening of chemical databases, drug-like properties calculations followed by molecular docking resulted in identifying 22 representative hit compounds. Performed 50 ns of MD simulations on top three hits were retained the salient π-stacking, Zn²⁺ coordination, hydrogen bonding, and hydrophobic interactions with catalytic residues from the active site pocket of HDAC3. Total binding energy calculated by MM-PBSA showed that the Hit 1 and Hit 2 formed stable complexes with HDAC3 as compared to reference TSA. Further, the PLIP analysis showed a close resemblance between the salient pharmacophore features of Hypo 1 and the presence of molecular interactions in co-crystallized FDA-approved drugs. We conclude that the screened hit compounds may act as potent inhibitors of HDAC3 and further preclinical and clinical studies may pave the way for developing them as effective therapeutic agents for the treatment of different cancers and neurodegenerative disorders.

Disruption of DYRK1A-induced hyperphosphorylation of amyloid-beta and tau protein in Alzheimer's disease: An integrative molecular modeling approach

Alzheimer's disease (AD) is a neurological disorder caused by the abnormal accumulation of hyperphosphorylated proteins. Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is a dual phosphorylation enzyme which phosphorylates the amyloid-β (Aβ) and neurofibrillary tangles (NFTs). A high throughput virtual screening approach was applied to screen a library of 98,071 compounds against DYRK1A using different programs including AutoDock Vina, Smina, and idock. Based on the binding affinities, we selected 330 compounds for absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis. Various pharmacokinetics parameters were predicted using the admetSAR server, and based on the pharmacokinetics results, 14 compounds were selected for cross-docking analysis using AutoDock. Cross-docking analysis revealed four compounds, namely, ZINC3843365 (-11.07 kcal/mol^-1), ZINC2123081 (-10.93 kcal/mol^-1), ZINC5220992 (-10.63 kcal/mol^-1), and ZINC68569602 (-10.35 kcal/mol^-1), which had the highest negative affinity scores compared to the 10 other molecules analyzed. Density functional theory (DFT) analysis was conducted for all the four top-ranked compounds. The molecular interaction stability of these four compounds with DYRK1A has been evaluated using molecular dynamics (MD) simulations on 100 nanoseconds followed by principal component analysis (PCA) and binding free energy calculations. The Gibbs free energy landscape analysis suggested the metastable state and folding pattern of selected docking complexes. Based on the present study outcome, we propose four antagonists, viz., ZINC3843365, ZINC2123081, ZINC5220992, and ZINC68569602 as potential inhibitors against DYRK1A and to reduce the amyloid-β and neurofibrillary tangle burden. These screened molecules can be further investigated using a number of in vitro and in vivo experiments.

Baicalein suppresses lipopolysaccharide-induced acute lung injury by regulating Drp1-dependent mitochondrial fission of macrophages

Acute lung injury (ALI) and its serious form, the acute respiratory distress syndrome (ARDS) are devastating diseases without effective chemotherapy. Exuberant or uncontrolled proinflammation responses in the lung, also known as "cytokine storms", is one of the main culprits in the pathogenesis of organ failure, and anti-inflammatory therapy is essential to alleviate ALI/ARDS-associated injuries. Emerging evidence suggests that baicalein has potent anti-inflammatory and antioxidant properties. However, the underlined mechanism of baicalein to mitigate inflammation in ALI remains unclear. Herein, we demonstrated a critical role for baicalein in suppressing the inflammatory response of LPS-activated macrophages. We found that mitochondria function was restored in the condition of baicalein. Interestingly, results showed that mitochondrial dysfunction positively correlates with inflammatory cytokine generation at each corresponding baicalein concentration. Further mRNA analysis revealed that baicalein mitigates mitochondrial defects via attenuation of dynamin-related protein 1 (Drp1) expression. These reprogrammed mitochondria prevent their function shift from the ATP synthesis to reactive oxygen species (ROS) production after the LPS challenge, thereby dampening NF-κB-dependent inflammatory cytokine transcription. Baicalein reduces the production of inflammatory mediators TNF-α, MIP-1, IL-6, and diminishes neutrophil influx and severity of endotoxin-mediated ALI. Taken together, our results show that baicalein may serve as a new clinical therapeutic strategy in ALI by modulating Drp1-induced mitochondrial impairment, restraining inflammatory responses, and reducing the severity of lung injury.

In Silico Inhibition of BACE-1 by Selective Phytochemicals as Novel Potential Inhibitors: Molecular Docking and DFT Studies

BACKGROUND

Alzheimer's Disease (AD) has become the most common age-dependent disease of dementia. The trademark pathologies of AD are the presence of amyloid aggregates in neurofibrils. Recently phytochemicals being considered as potential inhibitors against various neurodegenerative, antifungal, antibacterial and antiviral diseases in human beings.

OBJECTIVE

This study targets the inhibition of BACE-1 by phytochemicals using in silico drug discovery analysis.

METHODS

A total of 3150 phytochemicals were collected from almost 25 different plants through literature assessment. The ADMET studies, molecular docking and density functional theory (DFT) based analysis were performed to analyze the potential inhibitory properties of these phytochemicals.

RESULTS

The ADMET and docking results exposed seven compounds that have high potential as an inhibitory agent against BACE-1 and show binding affinity >8.0 kcal/mol against BACE-1. They show binding affinity greater than those of various previously reported inhibitors of BACE-1. Furthermore, DFT based analysis has shown high reactivity for these seven phytochemicals in the binding pocket of BACE- 1, based on ELUMO, EHOMO and Kohn-Sham energy gap. All seven phytochemicals were testified (as compared to experimental ones) as novel inhibitors against BACE-1.

CONCLUSION

Out of seven phytochemicals, four were obtained from plant Glycyrrhiza glabra i.e. Shinflavanone, Glabrolide, Glabrol and PrenyllicoflavoneA, one from Huperzia serrate i.e. Macleanine, one from Uncaria rhynchophylla i.e. 3a-dihydro-cadambine and another one was from VolvalerelactoneB from plant Valeriana-officinalis. It is concluded that these phytochemicals are suitable candidates for drug/inhibitor against BACE-1, and can be administered to humans after experimental validation through in vitro and in vivo trials.

3D-QSAR-Based Pharmacophore Modeling, Virtual Screening, and Molecular Docking Studies for Identification of Tubulin Inhibitors with Potential Anticancer Activity

In this study, we aimed to develop a pharmacophore-based three-dimensional quantitative structure activity relationship (3D-QSAR) for a set including sixty-two cytotoxic quinolines (1-62) as anticancer agents with tubulin inhibitory activity. A total of 279 pharmacophore hypotheses were generated based on the survival score to build QSAR models. A six-point pharmacophore model (AAARRR.1061) was identified as the best model which consisted of three hydrogen bond acceptors (A) and three aromatic ring (R) features. The model showed a high correlation coefficient (R 2 = 0.865), cross-validation coefficient (Q 2 = 0.718), and F value (72.3). The best pharmacophore model was then validated by the Y-Randomization test and ROC-AUC analysis. The generated 3D contour maps were used to reveal the structure activity relationship of the compounds. The IBScreen database was screened against AAARRR.1061, and after calculating ADMET properties, 10 compounds were selected for further docking study. Molecular docking analysis showed that compound STOCK2S-23597 with the highest docking score (-10.948 kcal/mol) had hydrophobic interactions and can form four hydrogen bonds with active site residues.

A Comprehensive Review of Cholinesterase Modeling and Simulation

The present article reviews published efforts to study acetylcholinesterase and butyrylcholinesterase structure and function using computer-based modeling and simulation techniques. Structures and models of both enzymes from various organisms, including rays, mice, and humans, are discussed to highlight key structural similarities in the active site gorges of the two enzymes, such as flexibility, binding site location, and function, as well as differences, such as gorge volume and binding site residue composition. Catalytic studies are also described, with an emphasis on the mechanism of acetylcholine hydrolysis by each enzyme and novel mutants that increase catalytic efficiency. The inhibitory activities of myriad compounds have been computationally assessed, primarily through Monte Carlo-based docking calculations and molecular dynamics simulations. Pharmaceutical compounds examined herein include FDA-approved therapeutics and their derivatives, as well as several other prescription drug derivatives. Cholinesterase interactions with both narcotics and organophosphate compounds are discussed, with the latter focusing primarily on molecular recognition studies of potential therapeutic value and on improving our understanding of the reactivation of cholinesterases that are bound to toxins. This review also explores the inhibitory properties of several other organic and biological moieties, as well as advancements in virtual screening methodologies with respect to these enzymes.

Mimicking H3 Substrate Arginine in the Design of G9a Lysine Methyltransferase Inhibitors for Cancer Therapy: A Computational Study for Structure-Based Drug Design

G9a protein methyltransferase is a potential epigenetic drug target in different cancers and other disease conditions overexpressing the enzyme. G9a is responsible for the H3K9 dimethylation mark, which epigenetically regulates gene expression. Arg8 and Lys9 of the H3 substrate peptide are the two crucial residues for substrate-specific recognition and methylation. Several substrate competitive inhibitors are reported for the potent inhibition of G9a by incorporating lysine mimic groups in the inhibitor design. In this study, we explored the concept of arginine mimic strategy. The hydrophobic segment of the reported inhibitors BIX-01294 and UNC0638 was replaced by a guanidine moiety (side-chain moiety of arginine). The newly substituted guanidine moieties of the inhibitors were positioned similar to the Arg8 of the substrate peptide in molecular docking. Additionally, improved reactivity of the guanidine-substituted inhibitors was observed in density functional theory studies. Molecular dynamics, molecular mechanics Poisson-Boltzmann surface area binding free energy, linear interaction energy, and potential mean force calculated from steered molecular dynamics simulations of the newly designed analogues show enhanced conformational stability and improved H-bond potential and binding affinity toward the target G9a. Moreover, the presence of both lysine and arginine mimics together shows a drastic increase in the binding affinity of the inhibitor towards G9a. Hence, we propose incorporating a guanidine group to imitate the substrate arginine's side chain in the inhibitor design to improve the potency of G9a inhibitors.

Structure and therapeutic uses of butyrylcholinesterase: Application in detoxification, Alzheimer's disease, and fat metabolism

Structural information of butyrylcholinesterase (BChE) and its variants associated with several diseases are discussed here. Pure human BChE has been proved safe and effective in treating organophosphorus (OPs) poisoning and has completed Phase 1 and 2 pharmacokinetic (PK) and safety studies. The introduction of specific mutations into native BChE to endow it a self-reactivating property has gained much progress in producing effective OPs hydrolases. The hydrolysis ability of native BChE on cocaine has been confirmed but was blocked to clinical application due to poor PK properties. Several BChE mutants with elevated cocaine hydrolysis activity were published, some of which have shown safety and efficiency in treating cocaine addiction of human. The increased level of BChE in progressed Alzheimer's disease patients made it a promising target to elevate acetylcholine level and attenuate cognitive status. A variety of selective BChE inhibitors with high inhibitory activity published in recent years are reviewed here. BChE could influence the weight and insulin secretion and resistance of BChE knockout (KO) mice through hydrolyzing ghrelin. The BChE-ghrelin pathway could also regulate aggressive behaviors of BChE-KO mice.

Docking based screening and molecular dynamics simulations to identify potential selective PDE4B inhibitor

Inhibition of phosphodiesterase 4 (PDE4) is a promising therapeutic approach for the treatment of inflammatory pulmonary disorders, i.e. asthma and chronic obstructive pulmonary disease. However, the treatment with non-selective PDE4 inhibitors is associated with side effects such as nausea and vomiting. Among the subtypes of PDE4 inhibited by these inhibitors, PDE4B is expressed in immune, inflammatory and airway smooth muscle cells, whereas, PDE4D is expressed in the area postrema and nucleus of the solitary tract. Thus, PDE4D inhibition is responsible for the emetic response. In this regard, a selective PDE4B inhibitor is expected to be a potential drug candidate for the treatment of inflammatory pulmonary disorders. Therefore, a shared feature pharmacophore model was developed and used as a query for the virtual screening of Maybridge and SPECS databases. A number of filters were applied to ensure only compounds with drug-like properties were selected. Accordingly, nine compounds have been identified as final hits, where HTS04529 showed the highest affinity and selectivity for PDE4B over PDE4D in molecular docking. The docked complexes of HTS04529 with PDE4B and PDE4D were subjected to molecular dynamics simulations for 100ns to assess their binding stability. The results showed that HTS04529 was bound tightly to PDE4B and formed a more stable complex with it than with PDE4D.

A Multi-layered Variable Selection Strategy for QSAR Modeling of Butyrylcholinesterase Inhibitors

Background:

Alzheimer’s disease (AD), a neurological disorder, is the most common cause of senile dementia. Butyrylcholinesterase (BuChE) enzyme plays a vital role in regulating the brain acetylcholine (ACh) neurotransmitter, but in the case of Alzheimer’s disease (AD), BuChE activity gradually increases in patients with a decrease in the acetylcholine (ACh) concentration via hydrolysis. ACh plays an essential role in regulating learning and memory as the cortex originates from the basal forebrain, and thus, is involved in memory consolidation in these sites.

Methods:

In this work, we have developed a partial least squares (PLS)-regression based two dimensional quantitative structure-activity relationship (2D-QSAR) model using 1130 diverse chemical classes of compounds with defined activity against the BuChE enzyme. Keeping in mind the strict Organization for Economic Co-operation and Development (OECD) guidelines, we have tried to select significant descriptors from the large initial pool of descriptors using multi-layered variable selection strategy using stepwise regression followed by genetic algorithm (GA) followed by again stepwise regression technique and at the end best subset selection prior to development of final model thus reducing noise in the input. Partial least squares (PLS) regression technique was employed for the development of the final model while model validation was performed using various stringent validation criteria.

Results:

The results obtained from the QSAR model suggested that the quality of the model is acceptable in terms of both internal (R2= 0.664, Q2= 0.650) and external (R2 Pred= 0.657) validation parameters. The QSAR studies were analyzed, and the structural features (hydrophobic, ring aromatic and hydrogen bond acceptor/donor) responsible for enhancement of the activity were identified. The developed model further suggests that the presence of hydrophobic features like long carbon chain would increase the BuChE inhibitory activity and presence of amino group and hydrazine fragment promoting the hydrogen bond interactions would be important for increasing the inhibitory activity against BuChE enzyme.

Conclusion:

Furthermore, molecular docking studies have been carried out to understand the molecular interactions between the ligand and receptor, and the results are then correlated with the structural features obtained from the QSAR models. The information obtained from the QSAR models are well corroborated with the results of the docking study.

Short communication for targeting natural compounds against HER2 kinase domain as potential anticancer drugs applying pharmacophore based molecular modelling approaches- part 2

Breast cancer is one of the common causes of death noticed in women globally. In order to find effective therapeutics, the current investigation has focussed on identifying candidate compounds for EGFR and HER2. Accordingly, the pharmacophore modelling approaches were adapted to identify two prospective compounds and were docked against the target 3RCD that is complexed with TAK-285 a known dual inhibitor. Focussing on the target 3RCD, our results have showed that the compounds have demonstrated a good binding affinity towards the target occupying the binding pocket. They have established key residue interactions with stable molecular dynamics simulation results. The Hit compounds have demonstrated a potential to penetrate the blood brain barrier thereby enriching their therapeutics towards breast cancer brain metastasis. Taken together, our findings propose two candidate compounds as EGFR/HER2 inhibitors that might serve as novel chemical spaces for designing and developing new inhibitors.

Insight into the screening of potential beta-lactamase inhibitors as anti-bacterial chemical agents through pharmacoinformatics study

Drug resistance is an unsolved and major concern in the bacterial infection. Continuous development of drug-resistance to the antibiotics exponentially rises the danger of bacterial infections. Chemical components from the plants are becoming a major resource of potentially effective therapeutic chemical agents for the wide range of diseases including bacterial infections. In the current study, pharmacoinformatics methodologies were implemented on more than two hundred known phytochemicals to find promising beta-lactamase inhibitors for therapeutically effective anti-bacterial agents. Initially, the molecular docking-based score was used to reduce the chemical space of the selected dataset. Fourteen molecules were found to have more affinity towards the beta-lactamase in compared to the well-known anti-bacterial agent, Avibactam. Binding interactions analysis revealed the strong binding interactions between phytochemicals and catalytic amino residues. For further analysis, molecular dynamics (MD) simulations, density functional theory (DFT) and in silico pharmacokinetics studies were performed. Parameters from MD simulations studies suggested that selected molecules are strong enough to retain in the active site in different orientations of the beta-lactamase. The orbital energies obtained from the DFT study was undoubtedly explained the potentiality of the selected compounds for being effective beta-lactamase inhibitors. The drug-likeness and acceptable pharmacokinetics parameters were observed using in silico ADME analysis. Therefore, observations from the multiple pharmacoinformatics approach explained without any doubt that selected molecules are potential enough being promising anti-bacterial compounds. [Formula: see text] Communicated by Ramaswamy H. Sarma.

From in vitro to in silico: Modeling and recombinant production of DT-Diaphorase enzyme

DT-Diaphorase (DTD) belonging to the oxidoreductase family, is among the most important enzymes and is of great significance in present-day biotechnology. Also, it has potential applications in glucose and pyruvate biosensors. Another important role of the DTD enzyme is in the detection of Phenylketonuria disease. According to the above demands, at first, we tried to study molecular cloning and production of recombinant DTD in E. coli BL21 strain. We have successfully cloned, expressed, and purified functionally active diaphorase. The amount of enzyme was increased in 10-h using IPTG induction, and the recombinant protein was purified by Ni-NTA agarose affinity chromatography. After that, the kinetic and thermodynamic parameters of the enzyme, optimum temperature and pH were also investigated to find more in-depth information. In the end, to represent the connections between the structures and function of this enzyme, the molecular dynamics simulations have been considered at two temperatures in which DTD had maximum and minimum activity (310 and 293 K, respectively). The results of MD simulations indicated that the interaction between NADH with phenylalanine 232 residue at 310 K is more severe than other residues. So, to investigate the interaction details of NADH/PHE 232 the DFT calculations were done.

Computer-aided identification of lead compounds as Staphylococcal epidermidis FtsZ inhibitors using molecular docking, virtual screening, DFT analysis, and molecular dynamic simulation

In an effort to face the multiple drug-resistant bacteria, various approaches have been discovered to design potent compounds and search new targets through computational design tools. With an aim to identify selective inhibitors against filamentous temperature-sensitive mutant Z (FtsZ), a library of Phase database compounds have been virtually screened. High-throughput virtual screening of compounds against Staphylococcal epidermidis FtsZ protein (4M8I) was performed using three sequential docking modes like high-throughput virtual screening, Glide standard precision, followed by Glide extra precision. Four top-ranked compounds were selected from molecular mechanics-generalized Born surface area (MM-GBSA) binding energy with better predicted free binding energies of - 89.309, - 54.382, - 53.667, and - 52.133 kcal/mol, respectively. It is also showed that the contribution of van der Waals and electrostatic solvation energy terms are playing a major part to make the hit molecule (T6288784) binding to S. epidermidis FtsZ protein. The result of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) and energy gap analysis predicts the molecular reactivity and stability of hit molecules. Subsequently, Lipinski's rule of five and properties of absorption, distribution, metabolism, and excretion (ADME) were to calculate their bioavailability. The average binding energy - 9.67 kcal/mol of the best proposed hit molecule (T6288784) was found with half-maximal inhibitory concentration (IC50) value to be 75.53 nM. A 15-ns molecular dynamics simulation study revealed the stable conformation of hit molecule. On a wide-range research discipline, in silico studies of our proposed compound confirm promising results and can be successfully used towards the development of novel FtsZ inhibitor with better binding affinity. Graphical Abstract.

Molecular Dynamics Studies on COX-2 Protein-tyrosine Analogue Complex and Ligand-based Computational Analysis of Halo-substituted Tyrosine Analogues

Background:

The quest for new drug entities and novel structural fragments with applications in therapeutic areas is always at the core of medicinal chemistry.

Methods:

As part of our efforts to develop novel selective cyclooxygenase-2 (COX-2) inhibitors containing tyrosine scaffold. The objective of this study was to identify potent COX-2 inhibitors by dynamic simulation, pharmacophore and 3D-QSAR methodologies. Dynamics simulation was performed for COX-2/tyrosine derivatives complex to characterise structure validation and binding stability. Certainly, Arg120 and Tyr355 residue of COX-2 protein formed a constant interaction with tyrosine inhibitor throughout the dynamic simulation phase. A four-point pharmacophore with one hydrogen bond acceptor, two hydrophobic and one aromatic ring was developed using the HypoGen algorithm. The generated, statistically significant pharmacophore model, Hypo 1 with a correlation coefficient of r2, 0.941, root mean square deviation, 1.15 and total cost value of 96.85.

Results:

The QSAR results exhibited good internal (r2, 0.992) and external predictions (r2pred, 0.814). The results of this study concluded the COX-2 docked complex was stable and interactive like experimental protein structure. Also, it offered vital chemical features with geometric constraints responsible for the inhibition of the selective COX-2 enzyme by tyrosine derivatives.

Conclusion:

In principle, this work offers significant structural understandings to design and develop novel COX-2 inhibitors.

Virtual Screening and Statistical Analysis in the Design of New Caffeine Analogues Molecules with Potential Epithelial Anticancer Activity

About 132 thousand cases of melanoma (more severe type of skin cancer) were registered in 2014 according to the World Health Organization. This type of cancer significantly affects the quality of life of individuals. Caffeine has shown potential inhibitory effect against epithelial cancer. In this study, it was proposed to obtain new caffeine-based molecules with potential epithelial anticancer activity. For this, a training set of 21 molecules was used for pharmacophore perception procedures. Multiple linear regression analyses were used to propose mono-, bi-, tri-, and tetra-parametric models applied in the prediction of the activity. The generated pharmacophore was used to select 350 molecules available at the ZINCpharmer server, followed by reduction to 24 molecules, after selection using the Tanimoto index, yielding 10 molecules after final selection by predicted activity values > 1.5229. These ten mole-cules had better pharmacokinetic properties than the other ones used as reference and within the clinical-ly significant limits. Only two molecules show minor hits of toxicity and were submitted to molecular docking procedures, showing BFE (binding free energy) values lower than the reference values. Statisti-cal analyses indicated strong negative correlations between BFE and pharmacophoric properties (high influence on BFE lowering) and practically null correlation between BFE and BBB. The two most prom-ising molecules can be indicated as candidates for further in vitro and in vivo analyzes.

Identification of Novel Scaffolds with Dual Role as Antiepileptic and Anti-Breast Cancer

Aromatase inhibitors with an $\mathrm{IC}_{50}$ IC 50 value ranging from 1.4 to 49.7 µM are known to act as antiepileptic drugs besides being potential breast cancer inhibitors. The aim of the present study is to identify novel antiepileptic aromatase inhibitors with higher activity exploiting the ligand-based pharmacophore approach utilizing the experimentally known inhibitors. The resultant Hypo1 consists of four features and was further validated by using three different strategies. Hypo1 was allowed to screen different databases to identify lead molecules and were further subjected to Lipinski's Rule of Five and ADMET to establish their drug-like properties. Consequently, the obtained 68-screened molecules were subjected to molecular docking by GOLD v5.2.2. Furthermore, the compounds with the highest dock scores were assessed for molecular interactions. Later, the MD simulation was applied to evaluate the protein backbone stabilities and binding energies adapting GROMACS v5.0.6 and MM/PBSA which was followed by the density functional theory (DFT), to analyze their orbital energies, and further the energy gap between them. Eventually, the number of Hit molecules was culled to three projecting Hit1, Hit2, and Hit3 as the potential lead compounds based on their highest dock scores, hydrogen bond interaction, lowest energy gap, and the least binding energies and stable MD results.

Structure-based virtual screening leading to discovery of highly selective butyrylcholinesterase inhibitors with solanaceous alkaloid scaffolds

According to recent research advance, it is interesting to identify new, potent and selective inhibitors of human butyrylcholinesterase (BChE) for therapeutic treatment of both the Alzheimer's disease (AD) and heroin abuse. In this study, we carried out a structure-based virtual screening followed by in vitro activity assays, with the goal to identify new inhibitors that are selective for BChE over acetylcholinesterase (AChE). As a result, a set of new, selective inhibitors of human BChE were identified from natural products with solanaceous alkaloid scaffolds. The most active one of the natural products (compound 1) identified has an IC50 of 16.8 nM against BChE. It has been demonstrated that the desirable selectivity of these inhibitors for BChE over AChE is mainly controlled by three key residues in the active site cavity, i.e. residues Q119, A277, and A328 in BChE versus the respective residues Y124, W286, and Y337 in AChE. Based on this structural insight, future rational design of new, potent and selective BChE inhibitors may focus on these key structural differences in the active site cavity.

Computational insight into the anticholinesterase activities and electronic properties of physostigmine analogs

Aim: Alzheimer's disease (AD) is known to be themajor cause of dementia among the elderly. The structural properties and binding interactions of the AD drug physostigmine (-)-phy, and its analogues (-)-hex and (-)-phe and (+)-phe, were examined, as well as their impact on the conformational changes of two different AD target enzymes AChE and BChE. Materials & methods: The conformational changes were studied using molecular dynamics and structural properties using Quantum mechanics. Results & conclusions: The binding free energy (ΔGbind) and the change in the free energy surface (FES) computed from the funnel metadynamics (FMD) simulation, both support the idea that inhibitors (-)-phe and (-)-hex have better binding activities toward enzyme AChE, and that (-)-phe is stronger in binding than the present AD drug (-)-phy.

Pharmacotherapeutics and Molecular Mechanism of Phytochemicals in Alleviating Hormone-Responsive Breast Cancer

Breast cancer (BC) is the leading cause of death among women worldwide devoid of effective treatment. It is therefore important to develop agents that can reverse, reduce, or slow the growth of BC. The use of natural products as chemopreventive agents provides enormous advantages. The aim of the current investigation is to determine the efficacy of the phytochemicals against BC along with the approved drugs to screen the most desirable and effective phytocompound. In the current study, 36 phytochemicals have been evaluated against aromatase to identify the potential candidate drug along with the approved drugs employing the Cdocker module accessible on the Discovery Studio (DS) v4.5 and thereafter analysing the stability of the protein ligand complex using GROningen MAchine for Chemical Simulations v5.0.6 (GROMACS). Additionally, these compounds were assessed for the inhibitory features employing the structure-based pharmacophore (SBP). The Cdocker protocol available with the DS has computed higher dock scores for the phytochemicals complemented by lower binding energies. The top-ranked compounds that have anchored with key residues located at the binding pocket of the protein were subjected to molecular dynamics (MD) simulations employing GROMACS. The resultant findings reveal the stability of the protein backbone and further guide to comprehend on the involvement of key residues Phe134, Val370, and Met374 that mechanistically inhibit BC. Among 36 compounds, curcumin, capsaicin, rosmarinic acid, and 6-shogaol have emerged as promising phytochemicals conferred with the highest Cdocker interaction energy, key residue interactions, stable MD results than reference drugs, and imbibing the key inhibitory features. Taken together, the current study illuminates the use of natural compounds as potential drugs against BC. Additionally, these compounds could also serve as scaffolds in designing and development of new drugs.

Pharmacophore-based drug design for the identification of novel butyrylcholinesterase inhibitors against Alzheimer's disease

BACKGROUND

Alzheimer's disease is a severe neurodegenerative disease of the central nervous system in the elderly.

HYPOTHESIS/PURPOSE

In our study, we aimed to find the best potential small molecule for AD treatment.

STUDY DESIGN

We used many models in Discovery Studio 2016 to find new potential inhibitors of butyrylcholinesterase (BChE), including pharmacophore model, virtual screening model, molecular docking model, de novo evolution model.

METHODS

Ligand-based pharmacophore models were used to identify the critical chemical features of BChE inhibitors using the module of 3D QSAR Pharmacophore Generation in Discovery Studio 2016. The best pharmacophore model was then validated by cost analysis, Fischer's randomization method, 3D-QSAR Method of the training set and test set. The compounds that match the best pharmacophore model with the predicted activity <1 μM filtered by Lipinski's rule of five were subjected to molecular docking.

RESULT

After virtual screening, 35 compounds filtered by Lipinski's rule of five and ADMET analysis were subjected to molecular docking and then the number were narrowed down on 10 compounds based on -CDOCKER_ENERGY. Finally, we obtained and modified the best potential candidate ENA739155.

CONCLUSION

Ultimately, ENA739155_Evo with -CDOCKER_ENERGY of 47.12, estimate activity of 0.012, fit value of 10.02 could be further subjected to drug development and forwarded as better alternatives to the current batch of medicines used for the treatment of AD.

In Silico Study Probes Potential Inhibitors of Human Dihydrofolate Reductase for Cancer Therapeutics

Dihydrofolate reductase (DHFR) is an essential cellular enzyme and thereby catalyzes thereduction of dihydrofolate to tetrahydrofolate (THF). In cancer medication, inhibition of humanDHFR (hDHFR) remains a promising strategy, as it depletes THF and slows DNA synthesis and cellproliferation. In the current study, ligand-based pharmacophore modeling identified and evaluatedthe critical chemical features of hDHFR inhibitors. A pharmacophore model (Hypo1) was generatedfrom known inhibitors of DHFR with a correlation coefficient (0.94), root mean square (RMS)deviation (0.99), and total cost value (125.28). Hypo1 was comprised of four chemical features,including two hydrogen bond donors (HDB), one hydrogen bond acceptor (HBA), and onehydrophobic (HYP). Hypo1 was validated using Fischer's randomization, test set, and decoy setvalidations, employed as a 3D query in a virtual screening at Maybridge, Chembridge, Asinex,National Cancer Institute (NCI), and Zinc databases. Hypo1-retrieved compounds were filtered byan absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment test andLipinski's rule of five, where the drug-like hit compounds were identified. The hit compounds weredocked in the active site of hDHFR and compounds with Goldfitness score was greater than 44.67(docking score for the reference compound), clustering analysis, and hydrogen bond interactionswere identified. Furthermore, molecular dynamics (MD) simulation identified three compounds asthe best inhibitors of hDHFR with the lowest root mean square deviation (1.2 Å to 1.8 Å), hydrogenbond interactions with hDHFR, and low binding free energy (-127 kJ/mol to -178 kJ/mol). Finally,the toxicity prediction by computer (TOPKAT) affirmed the safety of the novel inhibitors of hDHFRin human body. Overall, we recommend novel hit compounds of hDHFR for cancer and rheumatoidarthritis chemotherapeutics.

Pharmacophore-based virtual screening approach for identification of potent natural modulatory compounds of human Toll-like receptor 7

Toll-like receptor 7 (TLR7) is a transmembrane glycoprotein playing very crucial role in the signaling pathways involved in innate immunity and has been demonstrated to be useful in fighting against infectious disease by recognizing viral ssRNA & specific small molecule agonists. In order to find novel human TLR7 (hTLR7) modulators, computational ligand-based pharmacophore modeling approach was used to identify the molecular chemical features required for the modulation of hTLR7 protein. A training set of 20 TLR7 agonists with their known experimental activity was used to create pharmacophore model using 3D-QSAR pharmacophore generation (HypoGen algorithm) module in Discovery Studio. The best developed hypothesis consists of four pharmacophoric features namely, one hydrogen bond donor (HBD), one ring aromatic (RA), and two hydrophobic (HY) character. The developed hypothesis was then validated by different methods such as cost analysis, test set method, and Fischer's test method for consistency. Hence, this validated model was further employed for screening of natural hit compounds from InterBioScreen Natural product database, consisting of more than 60,000 natural compounds and derivatives. The screened hit compounds were subsequently filtered by Lipinski's rule of 5, ADME and toxicity parameters and molecular docking studies to remove the false positive rates. Finally, molecular docking analysis led to identification of the (3a'S,6a'R)-3'-(3,4-dihydroxybenzyl)-5'-(3,4-dimethoxyphenethyl)-5-ethyl-3',3a'-dihydro-2'H-spiro[indoline-3,1'-pyrrolo[3,4-c]pyrrole]-2,4',6'(5'H,6a'H)-trione (Compound ID: STOCK1N-65837) as potent hTLR7 modulator due to its better docking score and molecular interactions compared to other compounds. The result of virtual screening was further validated using molecular dynamics (MD) simulation analysis. Thus, a 30 ns MD simulation analysis revealed high stability and effective binding of STOCK1N-65837 within the binding site of hTLR7. Therefore, the present study provides confidence for the utility of the selected chemical feature based pharmacophore model to design novel TLR7 modulators with desired biological activity.

Integrating pharmacophore mapping, virtual screening, density functional theory, molecular simulation towards the discovery of novel apolipoprotein (apoE ε4) inhibitors

AIM

An integrated protocol of virtual screening involving molecular docking, pharmacophore probing, and simulations was established to identify small novel molecules targeting crucial residues involved in the variant apoE ε4 to mimic its behavior as apoE2 thereby eliminating the amyloid plaque accumulation and facilitating its clearance.

MATERIALS AND METHODS

An excellent ligand-based and structure-based approach was made to identify common pharmacophoric features involving structure-based docking with respect to apoE ε4 leading to the development of apoE ε4 inhibitors possessing new scaffolds. An effort was made to design multiple-substituted triazine derivatives series bearing a novel scaffold. A structure-based pharmacophore mapping was developed to explore the binding sites of apoE ε4 which was taken into consideration. Subsequently, virtual screening, ADMET, DFT searches were at work to narrow down the proposed hits to be forwarded as a potential drug likes candidates. Further, the binding patterns of the best-proposed hits were studied and were forwarded for molecular dynamic simulations of 10 ns for its structural optimization.

RESULTS

Selectivity profile for the most promising candidates was studied, revealing significantly C13 and C15 to be the most potent compounds. The proposed hits can be forwarded for further study against apoE ε4 involved in neurological disorder Alzheimer's.

Ligand-based Pharmacophore Model for Generation of Active Antidepressant- like Agents from Substituted 1,3,5 Triazine Class

INTRODUCTION

Although the transition of a lead candidate into a drug is currently structured by well-defined milestone, it is still most challenging and offers no guarantee in success to the end. In fact, ligand-based pharmacophore modeling has become a key motive force for retrieving potential leads across several therapeutic areas.

METHODS

An urgent need towards the development of novel antidepressant agents led us to generate a pharmacophore model from an existing 44 compounds dataset. The best model with one hydrophobic, two ring aromatic, and one positive ionization features was chosen on behalf of the correlation coefficient, sensitivity, specificity, yield of actives and accuracy measures using HypoGen module of Discovery Studio. In house library consisting of 10,000 substituted 1,3,5 triazine derivatives were shortlisted to select four insilico hits. All shortlisted compounds were synthesized and characterized by FTIR, 1H-& 13C-NMR spectroscopy and finally tested for antidepressant-like activity using behavioral models on rats viz. Forced Swim Test (FST) and Elevated Plus Maze (EPM).

RESULTS

Two shortlisted compounds with optimal fit values showed a significant decrease in the duration of immobility as compared to standard drug Imipramine in FST while time spent in open arm in enhanced in case of EPM.

Discovery of Non-Peptidic Compounds against Chagas Disease Applying Pharmacophore Guided Molecular Modelling Approaches

Chagas disease is one of the primary causes of heart diseases accounting to 50,000 lives annually and is listed as the neglected tropical disease. Because the currently available therapies have greater toxic effects with higher resistance, there is a dire need to develop new drugs to combat the disease. In this pursuit, the 3D QSAR ligand-pharmacophore (pharm 1) and receptor-based pharmacophore (pharm 2) search was initiated to retrieve the candidate compounds from universal natural compounds database. The validated models were allowed to map the universal natural compounds database. The obtained lead candidates were subjected to molecular docking against cysteine protease (PDB code: 1ME3) employing -Cdocker available on the discovery studio. Subsequently, two Hits have satisfied the selection criteria and were escalated to molecular dynamics simulation and binding free energy calculations. These Hits have demonstrated higher dock scores, displayed interactions with the key residues portraying an ideal binding mode complemented by mapping to all the features of pharm 1 and pharm 2. Additionally, they have rendered stable root mean square deviation (RMSD) and potential energy profiles illuminating their potentiality as the prospective antichagastic agents. The study further demonstrates the mechanism of inhibition by tetrad residues compromising of Gly23 and Asn70 holding the ligand at each ends and the residues Gly65 and Gly160 clamping the Hits at the center. The notable feature is that the Hits lie in close proximity with the residues Glu66 and Leu67, accommodating within the S1, S2 and S3 subsites. Considering these findings, the study suggests that the Hits may be regarded as effective therapeutics against Chagas disease.

Combiphore (Structure and Ligand Based Pharmacophore) - Approach for the Design of GPR40 Modulators in the Management of Diabetes

BACKGROUND

Pharmacophore mapping and molecular docking can be synergistically integrated to improve the drug design and discovery process. A rational strategy, combiphore approach, derived from the combined study of Structure and Ligand based pharmacophore has been described to identify novel GPR40 modulators.

METHODS

DISCOtech module from Discovery studio was used for the generation of the Structure and Ligand based pharmacophore models which gave hydrophobic aromatic, ring aromatic and negative ionizable as essential pharmacophoric features. The generated models were validated by screening active and inactive datasets, GH scoring and ROC curve analysis. The best model was exposed as a 3D query to screen the hits from databases like GLASS (GPCR-Ligand Association), GPCR SARfari and Mini-Maybridge. Various filters were applied to retrieve the hit molecules having good drug-like properties. A known protein structure of hGPR40 (pdb: 4PHU) having TAK-875 as ligand complex was used to perform the molecular docking studies; using SYBYL-X 1.2 software.

RESULTS AND CONCLUSION

Clustering both the models gave RMSD of 0.89. Therefore, the present approach explored the maximum features by combining both ligand and structure based pharmacophore models. A common structural motif as identified in combiphore for GPR40 modulation consists of the para-substituted phenyl propionic acid scaffold. Therefore, the combiphore approach, whereby maximum structural information (from both ligand and biological protein) is explored, gives maximum insights into the plausible protein-ligand interactions and provides potential lead candidates as exemplified in this study.

Discovery of natural product inhibitors of phosphodiesterase 10A as novel therapeutic drug for schizophrenia using a multistep virtual screening

The major complaint that most of the schizophrenic patients' face is the cognitive impairment which affects the patient's quality of life. The current antipsychotic drugs treat only the positive symptoms without alleviating the negative or cognitive symptoms of the disease. In addition, the existing therapies are known to produce extrapyramidal side effects that affect the patient adherence to the treatment. PDE10A inhibitor is the new therapeutic approach which has been proven to be effective in alleviating the negative and cognitive symptoms of the disease. A number of PDE10A inhibitors have been developed, but no inhibitor has made it beyond the clinical trials so far. Thus, the present study has been conducted to identify a PDE10A inhibitor from natural sources to be used as a lead compound for the designing of novel selective PDE10A inhibitors. Ligand and structure-based pharmacophore models for PDE10A inhibitors were generated and employed for virtual screening of universal natural products database. From the virtual screening results, 37 compounds were docked into the active site of the PDE10A. Out of 37 compounds, three inhibitors showed the highest affinity for PDE10A where UNPD216549 showed the lowest binding energy and has been chosen as starting point for designing of novel PDE10A inhibitors. The structure-activity-relationship studies assisted in designing of selective PDE10A inhibitors. The optimization of the substituents on the phenyl ring resulted in 26 derivatives with lower binding energy with PDE10A as compared to the lead compound. Among these, MA 8 and MA 98 exhibited the highest affinity for PDE10A with binding energy (-10.90 Kcal/mol).

Investigation of non-hydroxamate scaffolds against HDAC6 inhibition: A pharmacophore modeling, molecular docking, and molecular dynamics simulation approach

Proteins deacetylation by Histone deacetylase 6 (HDAC6) has been shown in various human chronic diseases like neurodegenerative diseases and cancer, and hence is an important therapeutic target. Since, the existing inhibitors have hydroxamate group, and are not HDAC6-selective, therefore, this study has designed to investigate non-hydroxamate HDAC6 inhibitors. Ligand-based pharmacophore was generated from 26 training set compounds of HDAC6 inhibitors. The statistical parameters of pharmacophore (Hypo1) included lowest total cost of 115.63, highest cost difference of 135.00, lowest RMSD of 0.70 and the highest correlation of 0.98. The pharmacophore was validated by Fischer's Randomization and Test Set validation, and used as screening tool for chemical databases. The screened compounds were filtered by fit value ([Formula: see text]), estimated Inhibitory Concentration (IC[Formula: see text]) ([Formula: see text]), Lipinski's Rule of Five and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) Descriptors to identify drug-like compounds. Furthermore, the drug-like compounds were docked into the active site of HDAC6. The best docked compounds were selected having goldfitness score [Formula: see text] and [Formula: see text], and hydrogen bond interaction with catalytic active residues. Finally, three inhibitors having sulfamoyl group were selected by Molecular Dynamic (MD) simulation, which showed stable root mean square deviation (RMSD) (1.6-1.9[Formula: see text]Å), lowest potential energy ([Formula: see text][Formula: see text]kJ/mol), and hydrogen bonding with catalytic active residues of HDAC6.

Computational Exploration for Lead Compounds That Can Reverse the Nuclear Morphology in Progeria

Progeria is a rare genetic disorder characterized by premature aging that eventually leads to death and is noticed globally. Despite alarming conditions, this disease lacks effective medications; however, the farnesyltransferase inhibitors (FTIs) are a hope in the dark. Therefore, the objective of the present article is to identify new compounds from the databases employing pharmacophore based virtual screening. Utilizing nine training set compounds along with lonafarnib, a common feature pharmacophore was constructed consisting of four features. The validated Hypo1 was subsequently allowed to screen Maybridge, Chembridge, and Asinex databases to retrieve the novel lead candidates, which were then subjected to Lipinski's rule of 5 and ADMET for drug-like assessment. The obtained 3,372 compounds were forwarded to docking simulations and were manually examined for the key interactions with the crucial residues. Two compounds that have demonstrated a higher dock score than the reference compounds and showed interactions with the crucial residues were subjected to MD simulations and binding free energy calculations to assess the stability of docked conformation and to investigate the binding interactions in detail. Furthermore, this study suggests that the Hits may be more effective against progeria and further the DFT studies were executed to understand their orbital energies.

Cinnamaldehyde, Cinnamic Acid, and Cinnamyl Alcohol, the Bioactives of Cinnamomum cassia Exhibit HDAC8 Inhibitory Activity: An In vitro and In silico Study

Background

The altered expression of histone deacetylase family member 8 (HDAC8) has been found to be linked with various cancers, thereby making its selective inhibition a potential strategy in cancer therapy. Recently, plant secondary metabolites, particularly phenolic compounds, have been shown to possess HDAC inhibitory activity.

Objective

In the present work, we have evaluated the potential of cinnamaldehyde (CAL), cinnamic acid (CA), and cinnamyl alcohol (CALC) (bioactives of Cinnamomum) as well as aqueous cinnamon extract (ACE), to inhibit HDAC8 activity in vitro and in silico.

Materials and Methods

HDAC8 inhibitory activity of ACE and cinnamon bioactives was determined in vitro using HDAC8 inhibitor screening kit. Trichostatin A (TSA), a well-known anti-cancer agent and HDAC inhibitor, was used as a positive control. In silico studies included molecular descriptor Analysis molecular docking absorption, distribution, metabolism, excretion, and toxicity prediction, density function theory calculation and synthetic accessibility program.

Results

Pharmacoinformatics studies implicated that ACE and its Bioactives (CAL, CA, and CALC) exhibited comparable activity with that of TSA. The highest occupied molecular orbitals and lowest unoccupied molecular orbitals along with binding energy of cinnamon bioactives were comparable with that of TSA. Molecular docking results suggested that all the ligands maintained two hydrogen bond interactions within the active site of HDAC8. Finally, the synthetic accessibility values showed that cinnamon bioactives were easy to synthesize compared to TSA.

Conclusion

It was evident from both the experimental and computational data that cinnamon bioactives exhibited significant HDAC8 inhibitory activity, thereby suggesting their potential therapeutic implications against cancer.

SUMMARY

Pharmacoinformatics studies revealed that cinnamon bioactives bound to the active site of HDAC8 enzyme in a way similar to that of TSAThe molecular descriptors of cinnamon compounds successfully correlated with TSA values. The binding interactions and energies were also found to be close to TSASynthetic accessibility values showed that cinnamon bioactives were easy to synthesize compared to TSA. Abbreviations used: ACE: Aqueous Cinnamon Extract; DFT: Density Function Theory; CAL: Cinnamaldehyde; CA: Cinnamic Acid; CALC: Cinnamyl Alcohol; MW: Molecular Weight; ROTBs: Rotatable Bonds; ROF: Lipinski's Rule of Five; TSA: Trichostatin A; PDB: Protein Data Bank; RMSD: Root Mean Square Deviation; HBA: Hydrogen Bond Acceptor; HBD: Hydrogen Bond Donor; ADMET: Absorption, Distribution, Metabolism, Excretion and Toxicity; FO: Frontier Orbital; HOMOs: Highest Occupied Molecular Orbitals; LUMOs: Lowest Unoccupied Molecular Orbitals; BE: Binding Energy.

Novel HDAC8 inhibitors: A multi-computational approach

Abnormal HDAC function triggers irregular gene transcription that hampers the essential cellular activities leading to tumour activation and progression. HDAC inhibition has, therefore, been reported as a potential target for cancer treatment. In the present study, a sequential computational framework was carried out to discover newer lead compounds, namely HDAC8 inhibitors for cancer therapy. Pharmacophoric hypotheses were generated based on hydroxamic acid derivatives reported earlier for HDAC inhibition. The model AAADR.122, demonstrated statistical significance (r² = 0.93, Q² = 0.81) and proved robust on validation with a cross-validated correlation coefficient of 0.89. It was utilized to arrive at novel hits through a virtual screening workflow. The specificity of the process was enhanced further by analysing the crucial interactions of the ligands with key catalytic residues, achieved by induced fit docking (PDB ID: 1T64). On assessment, the filtered leads displayed optimal drug like features. Investigations using density functional theory (DFT) also facilitated the recognition of molecular spots in the leads beneficial for HDAC8 interaction. Overall, two leads were proposed for HDAC8 inhibition with potential anti-cancer activity.

Ensemble-based virtual screening: identification of a potential allosteric inhibitor of Bcr-Abl

Ensemble-based virtual screening using different conformations of a target protein is gaining popularity, as it can leverage information from target flexibility for effective lead identification. In this paper, molecular dynamics simulation followed by RMSD-based clustering was employed to generate and choose distinct conformations of Bcr-Abl. Three representative structures from the most-populated clusters along with the crystal structure conformation (PDBID: 3K5V) were used to perform docking-based virtual screening of 14,400 compounds (in the Maybridge database) in order to identify potential allosteric site binders. Seven compounds found as hits in at least three of the four virtual screenings had higher Glide docking scores than the co-crystallized allosteric inhibitor GNF-2. Detailed computational analyses of the seven hits identified SEW02675 (ΔG _bind = -164.92 kJ/mol with the wild-type (wt) Bcr-Abl and -167.37 kJ/mol with the T334I Bcr-Abl mutant) as a better allosteric site binder with both the wt and the mutant Bcr-Abl protein than the reference allosteric inhibitor GNF-2 (ΔG _bind = -103.12 with wt and -142.96 kJ/mol with T334I). Moreover, the presence of SEW02675 in the allosteric site enhanced the binding of imatinib (ΔG _bind = -367.58 with wt and -294.56 kJ/mol with T334I) to the ATP sites of the wt and the mutant Bcr-Abl. However, when GNF-2 was present in the allosteric site, the binding of imatinib (ΔG _bind = -351.76 with wt and -273.94 kJ/mol with T334I) to the ATP site was weaker. The in silico findings suggest that SEW02675 could be used in combination with imatinib to treat chronic myeloid leukemia, and that it could help to overcome resistance due to T334I Bcr-Abl mutation. Graphical abstract Virtual screening strategy to identify allosteric inhbitors of Bcr-Abl for the treatment of Chronic myeloid leukemia.

Potential acetylcholinesterase inhibitors: molecular docking, molecular dynamics, and in silico prediction

This paper deals with molecular modeling of new therapeutic agents for treating the Alzheimer's disease. The therapeutic line adopted for this study is the cholinergic hypothesis. To modulate positively the cholinergic function through the inhibition of the acetylcholinesterase, a set of candidates was designed from a natural compound extracted from the cashew nutshell liquid, anacardic acid. In silico screening of this chemical library revealed a ligand that is more promising once it is correlated with an active drug through specific topological and electronic descriptors. The protein-ligand docking showed stable binding modes and the binding free energy computed for the active site of the receptor suggests that our ligand presents a potential biological response. Graphical Abstract Representation of the three dimensional structure of the AChE, showing the important binding sites of the Gorge and the conformation of the ligand.

3D pharmacophore-based virtual screening, docking and density functional theory approach towards the discovery of novel human epidermal growth factor receptor-2 (HER2) inhibitors

Human epidermal growth factor receptor 2 (HER2) is one of the four members of the epidermal growth factor receptor (EGFR) family and is expressed to facilitate cellular proliferation across various tissue types. Therapies targeting HER2, which is a transmembrane glycoprotein with tyrosine kinase activity, offer promising prospects especially in breast and gastric/gastroesophageal cancer patients. Persistence of both primary and acquired resistance to various routine drugs/antibodies is a disappointing outcome in the treatment of many HER2 positive cancer patients and is a challenge that requires formulation of new and improved strategies to overcome the same. Identification of novel HER2 inhibitors with improved therapeutics index was performed with a highly correlating (r=0.975) ligand-based pharmacophore model (Hypo1) in this study. Hypo1 was generated from a training set of 22 compounds with HER2 inhibitory activity and this well-validated hypothesis was subsequently used as a 3D query to screen compounds in a total of four databases of which two were natural product databases. Further, these compounds were analyzed for compliance with Veber's drug-likeness rule and optimum ADMET parameters. The selected compounds were then subjected to molecular docking and Density Functional Theory (DFT) analysis to discern their molecular interactions at the active site of HER2. The findings thus presented would be an important starting point towards the development of novel HER2 inhibitors using well-validated computational techniques.

In silico study of subtilisin-like protease 1 (SUB1) from different Plasmodium species in complex with peptidyl-difluorostatones and characterization of potent pan-SUB1 inhibitors

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Homology models of four SUB1 orthologues from P. falciparum species were produced.

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We analyzed the binding mode of our previous difluorostatone inhibitors to six SUB1.

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In vitro activity of our difluorostatone-based inhibitors was correctly predicted.

•

We derived a structure-based pan-SUB1 pharmacophore, and validated it in silico.

•

We confirmed that development of pan-SUB1 inhibitors is a feasible task.

Plasmodium falciparum subtilisin-like protease 1 (SUB1) is a novel target for the development of innovative antimalarials. We recently described the first potent difluorostatone-based inhibitors of the enzyme ((4S)-(N-((N-acetyl-l-lysyl)-l-isoleucyl-l-threonyl-l-alanyl)-2,2-difluoro-3-oxo-4-aminopentanoyl)glycine (1) and (4S)-(N-((N-acetyl-l-isoleucyl)-l-threonyl-l-alanylamino)-2,2-difluoro-3-oxo-4-aminopentanoyl)glycine (2)). As a continuation of our efforts towards the definition of the molecular determinants of enzyme-inhibitor interaction, we herein propose the first comprehensive computational investigation of the SUB1 catalytic core from six different Plasmodium species, using homology modeling and molecular docking approaches. Investigation of the differences in the binding sites as well as the interactions of our inhibitors 1,2 with all SUB1 orthologues, allowed us to highlight the structurally relevant regions of the enzyme that could be targeted for developing pan-SUB1 inhibitors. According to our in silico predictions, compounds 1,2 have been demonstrated to be potent inhibitors of SUB1 from all three major clinically relevant Plasmodium species (P. falciparum, P. vivax, and P. knowlesi). We next derived multiple structure-based pharmacophore models that were combined in an inclusive pan-SUB1 pharmacophore (SUB1-PHA). This latter was validated by applying in silico methods, showing that it may be useful for the future development of potent antimalarial agents.

Novel chemical scaffolds of the tumor marker AKR1B10 inhibitors discovered by 3D QSAR pharmacophore modeling

AIM

Recent evidence suggests that aldo-keto reductase family 1 B10 (AKR1B10) may be a potential diagnostic or prognostic marker of human tumors, and that AKR1B10 inhibitors offer a promising choice for treatment of many types of human cancers. The aim of this study was to identify novel chemical scaffolds of AKR1B10 inhibitors using in silico approaches.

METHODS

The 3D QSAR pharmacophore models were generated using HypoGen. A validated pharmacophore model was selected for virtual screening of 4 chemical databases. The best mapped compounds were assessed for their drug-like properties. The binding orientations of the resulting compounds were predicted by molecular docking. Density functional theory calculations were carried out using B3LYP. The stability of the protein-ligand complexes and the final binding modes of the hit compounds were analyzed using 10 ns molecular dynamics (MD) simulations.

RESULTS

The best pharmacophore model (Hypo 1) showed the highest correlation coefficient (0.979), lowest total cost (102.89) and least RMSD value (0.59). Hypo 1 consisted of one hydrogen-bond acceptor, one hydrogen-bond donor, one ring aromatic and one hydrophobic feature. This model was validated by Fischer's randomization and 40 test set compounds. Virtual screening of chemical databases and the docking studies resulted in 30 representative compounds. Frontier orbital analysis confirmed that only 3 compounds had sufficiently low energy band gaps. MD simulations revealed the binding modes of the 3 hit compounds: all of them showed a large number of hydrogen bonds and hydrophobic interactions with the active site and specificity pocket residues of AKR1B10.

CONCLUSION

Three compounds with new structural scaffolds have been identified, which have stronger binding affinities for AKR1B10 than known inhibitors.