Current Computer - Aided Drug Design - Volume 13, Issue 4, 2017

Background: Alzheimer's disease (AD) affects mainly elderly people over 60 years of age. Currently, there are more than 35 million people with this disease worldwide. The enzyme β-secretase is involved in the processing of the amyloid precursor protein and plays a key role in the physiopathology of AD. The action of some acetylcholinesterase inhibitors (AChEI) as β-secretase inhibitors has been reported. Objective: The aim of this study was to highlight the modes of the binding of acetylcholinesterase ligands onto the active site of the β-secretase enzyme. Methods: Molecular dynamics and docking were used in order to identify pivotal interactions that favor the inhibitory activity and provide a rational basis for planning novel β-secretase inhibitors. Additionally, density functional theory (DFT) was used to provide accurate energy values for the complexes. A mechanistic study of the amide hydrolysis was also performed at the M06/6-31G(d) basis set. Results: Of the 100 AChE inhibitors, 10 were able to interact with Asp32 and/or Asp228 residues from the enzyme BACE-1, suggesting that these could act as multi-target compounds. These inhibitors were selected for DFT studies in order to provide more accurate energy values. Interestingly, the range of energy values (-27.01 to -8.64 kJ mol-1) obtained was in agreement with the anti-AChE activity. The results obtained in the mechanistic study of compound 93 using DFT are in agreement with theoretical studies described in the literature. Conclusion: The results reported in this study will advance our understanding of the influence of the distinct chemical structures of inhibitors at the active site and aid the development of new virtual screening protocols to design novel AChE multi-target inhibitors.

Background: Lanosterol synthase (Oxidosqualene cyclase) is an enzyme, which plays a central role in cholesterol and sterols biosynthesis. Lanosterol synthase drugs are used to lower the level of cholesterol in the blood and treat wide variety of diseases like atherosclerosis, coronary heart diseases etc. Objective: There is a great interest in the identification of drugs that target this enzyme for anticholesteraemic agent using in silico tools. Methods: Ligand based pharmacophore model was developed using Discovery Studio 2.5. The best model was used as a tool to retrieve suitable molecule for Lanosterol synthase inhibitor from commercial database and Virtual screening of large commercially available databases to retrieve the best mole of Hypo1 using. Molecular docking was done using three different tools named as GOLD, GLIDE and AUTODOCK 4.0. Density functional theory approach and Density of State spectrum were carried out using Gaussian 09 and GAUSS SUM 3.0. Contribution of these methods in the selection of anticholesteraemic compounds has been discussed. Results: The best pharmacophore model was used to screen the commercial database. Totally 8 compounds were showed with the best orientation, binding mode and binging energy in the docking analyses. The orbital energies such as HOMO, LUMO and DOS spectrum for 8 hit compounds showed the energy gap that results in charge transfer and stability in the active site region. The results showed that our 8 potent leads could serve for further findings. Conclusion: In silico approaches, our 8 hit compounds could serve as the better understanding to design the novel lanosterol synthase inhibitors as anticholesteraemic activity.

Background: Targeting of multiple sites is a pharmacologically, pharmacokinetic and dynamically more acceptable approach for complex diseases such as BC. It is recommended that the women who are at high risk of developing BC might be given foods enhanced by indole alkaloids from vegetables like cabbage and broccoli. Administration of indole-3-carbinol is associated with decreased incidence of hormone-responsive BC (HRBC) which is implicated due to the induction of cytochrome P450 and glutathione-S-transferase which metabolizes chemical mutagens and by altering estrogen metabolism. Objective: To determine the molecular mechanism behind the anticancer activity of natural indole alkaloids present in various food and nutraceuticals products by utilizing Induced-fit docking (IFD) approach. Methods: Indole alkaloids were obtained from the database maintained by ChEBI (The database and ontology of Chemical Entities of Biological Interest) with ChEBI id 38958. The 3-dimentional and X-ray structure coordinates of Estrogen receptor- α (ER-α), Estrogen receptor- β (ER-β), and aromatase were obtained from protein data bank with PDB id codes 3ERT, 3OLS, and 3S7S (www.rcsb.org). The Induced fit molecular docking and ADME properties were calculated using Maestro 9.6. Results: IFD analysis showed that bromocriptine exhibits maximum binding affinity towards ER-α and fellutanine B towards ER-β and aromatase. Conclusion: Present research provided in-depth analysis of molecular mechanism and helped in the future design of new pharmacophores based on natural indole alkaloids targeting BC.

Background: Discovery of apicoplast as a drug target offers a new direction in the development of novel anti-malarial compounds, especially against the drug-resistant strains. Drugs such as azithromycin were reported to block the apicoplast development that leads to unusual phenotypes affecting the parasite. This phenomenon suggests that identification of new apicoplast inhibitors will aid in the anti-malarial drug discovery. Therefore, in this study, we developed a computational model to predict apicoplast inhibitors by applying state-of-the-art machine learning techniques. Methods: We have used two high-throughput chemical screening data (AID-504850, AID-504848) from PubChem BioAssay database and applied machine learning techniques. The performance of the models were assessed on various types of binary fingerprints. Results: In this study, we developed a robust computational algorithm for the prediction of apicoplast inhibition. We observed 73.7% sensitivity and 84% specificity along with 81.4% accuracy rate only on 41 PubChem fingerprints on 48 hrs dataset. Similarly, an accuracy rate of 75.8% was observed for 96 hrs dataset. Additionally, we observed that our model has ~70% positive prediction rate on the independent dataset obtained from ChEMBL-NTD database. Furthermore, the fingerprint analysis suggested that compounds with at least one heteroatom containing hexagonal ring would most likely belong to the antimalarial category as compared to simple aliphatic compounds. We also observed that aromatic compounds with oxygen and chlorine atoms were preferred in inhibitors class as compared to sulphur. Additionally, the compounds with average molecular weight >380Da and XlogP>4 were most likely to belong to the inhibitor category. Conclusion: This study highlighted the significance of simple interpretable molecular properties along with some preferred substructure in designing the novel anti-malarial compounds. In addition to that, robustness and accuracy of models developed in the present work could be utilized to screen a large chemical library. Based on this study, we developed freely available software at http://deepaklab. com/capi. This study would provide the best alternative for searching the novel apicoplast inhibitors against Plasmodium.

Background: The present study clarifies the molecular interactions of human BACE1 with novel natural ligands and also with the well-known ligand 2, 2, 4-trihydroxychalcone and Galangin for comparison. Objective: The study of enzyme- ligands interaction is interesting, thus description of ligands binding to the active site of target molecule could be beneficial for better understanding the mechanism of the ligand on the target molecule. Methods: Lipinski rule of five and docking study were performed between ligands and enzyme using ‘Autodock4.2’. Results: It was found that hydrogen bond interactions play a significant role in the accurate positioning of ligands within the ‘active site’ of BACE1 to permit docking. Such information may aid to propose the BACE1 -inhibitors and is estimated to aid in the safe medical use of ligands. Selected ligands of BACE1 also inhibit the aggregated amyloid beta peptide. The aggregation of amyloid peptides Aβ1–42 may be responsible for AD. Conclusion: Scope lies in the determination of the 3-dimensional structure of BACE1 and ligands complex by X-ray crystallography to certify the explained data. To validate the enzyme –ligands results, we considered 2, 2, 4-trihydroxychalconeas and Galangin as a positive control. Moreover, the current study verifies that ligands are more capable inhibitors of human BACE1 compared to positive control with reference to ΔG values.

Background: Protein tyrosine phosphatase non-receptor type 1 is a therapeutic target for the type 2 diabetes mellitus. According to the International Diabetes Federation 2015 report, one out of 11 adults suffers from diabetes mellitus globally. Objective: Current anti-diabetic drugs can cause life-threatening side-effects. The present study proposes a pipeline for the development of effective and plant-derived anti-diabetic drugs that may be safer and better tolerated. Methods: Plant-derived protein tyrosine phosphatase non-receptor type 1 inhibitors possessing antidiabetic activity less than 10μM were used as a training set. A common feature pharmacophore model was generated. Pharmacophore-based screening of plant-derived compounds of the ZINC database was conducted using ZINCpharmer. Screened hits were assessed to evaluate their drug-likeness, pharmacokinetics, detailed binding behavior, and aggregator possibility based on their physiochemical properties and chemical similarity with reported aggregators. Results: Through virtual screening and in silico pharmacology protocol isosilybin (ZINC30731533) was identified as a lead compound with optimal properties. This compound can be recommended for laboratory tests and further analyses to confirm its activity as protein tyrosine phosphatase nonreceptor type 1 inhibitor. Conclusion: The present study has identified plant-derived anti-diabetic virtual lead compound with the potential to inhibit protein tyrosine phosphatase non-receptor type 1, which may be helpful to enhance insulin production. This computer-aided study could facilitate the development of novel pharmacological inhibitors for diabetes treatment.

Background: Unconventional Knoevenagel-type indoles have been the topic of interest of many synthetic chemists because of its promising efficacy in different diseases including cancer. Objective: To explore the structural requirements of Knoevenagel-type cytotoxic indoles for higher efficacy. Methods: Multi-QSAR modeling (MLR, ANN, SVM, Bayesian classification, HQSAR and Topomer CoMFA) was performed on these analogs. Results: All these modeling techniques were validated individually and interpreted with the experimental SAR observations. Phenyl or p-methoxyphenyl substitution at 2nd position, electron withdrawing groups (such as sulphonyl, cyano etc.) at 3rd position and methoxy substation at 5th position of the indole scaffold may favor cytotoxicity. Eight new indole molecules were predicted from the developed QSAR models. Conclusion: These newly designed compounds may bind to the colchicine binding site of the tubulin protein as suggested by the molecular docking study.

Background: Chikungunya is a viral infection caused by Chikungunya virus (CHIKV), an arbovirus transmitted through mosquito (Aedes aegypti and Aedes albopictus) bite. The virus from sylvatic cycle in Africa mutated to new vector adaptation and became one of the major emerging and re-emerging viral infections in the past decade, affecting more than 40 countries. Efforts are being made by many researches to develop means to prevent and control the infection through vaccines and vector control strategy. On the other hand, search for novel chemotherapeutic agents for the treatment of infected patients is on. Approach of repurposed drug is one way of identifying an existing drug for the treatment of CHIKV infection. Objective: Review the history of CHIKV nsp2 protease inhibitors derived through structure-based computer-aided drug design along with phytochemicals identified as anti-CHIKV agents. Methods: A survey on CHIKV inhibitors reported till date has been carriedout. The data obtained were organized and discussed under natural substances and synthetic derivatives obtained as result of rational design. Results: The review provides a well organized content in chronological order that has highly significant information for medicinal chemist who wish to explore the area of Anti-CHIKV drug design and development. Natural compounds with different scaffolds provides an opportunity to explore Ligand based drug design (LBDD), while rational drug design approaches provides opportunity to explore the Structure based drug design. Conclusion: From the presented mini-review, readers can understand that this area is less explored and has lots of potential in anti-CHIKVviral drug design & development. of reported literature inferred that, unlike other viral proteases, the nsP2 protease can be targeted for CHIKV viral inhibition. The HTVS process for the identification of anti-CHIK agents provided a few successive validated lead compounds against CHIKV infections.