Ligand-Based Pharmacophore Modeling, Virtual Screening and Molecular Docking Studies for Discovery of Novel Inhibitors against Staphylococcal Infections (original) (raw)
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International Journal of Pharmacy and Pharmaceutical Sciences, 2017
Objective: To understand the essential structural features required for pancreatic lipase (PL) inhibitory activity and to design novel chemical entities, ligand-based pharmacophore modeling, virtual screening and docking studies were carried out. Methods: The pharmacophore model was generated based on 133 compounds with PL inhibitory activity using PHASE. An external test set and decoy dataset methods were applied to validate the hypothesis and to retrieve potential PL inhibitors. The generated hypothesis model was further subjected to virtual screening and molecular docking studies. Results: A five point pharmacophoric hypothesis model which consists of three hydrogen bond acceptor sites and two hydrophobic sites was developed. The generated pharmacophore gave significant 3D QSAR (three-dimensional Quantitative Structural Activity Relationship) model with r 2 of 0.9389 and Q 2 value of 0.4016. After database screening, five molecules were found to have better glide scores and binding interactions with the active site amino acid residues. Conclusion: As an outcome of this study, five hit molecules were suggested as potent PL inhibitors as they showed good glide scores as well as binding interactions with required active site amino acids. The five molecules obtained from this study may serve as potential leads for the development of promising anti-obesity agents.
Background: Obesity is a progressive metabolic disorder in the current world population, and is characterized by the excess deposition of fat in the adipose tissue. Pancreatic lipase is one of the key enzymes in the hydrolysis of triglycerides into monoglycerides and free fatty acids, and is thus considered a promising target for the treatment of obesity. The present drugs used for treating obesity do not give satisfactory results, and on prolonged usage result in severe side effects. In view of the drastic increase in the obese population day-today , there is a greater need to discover new drugs with lesser side effects. Materials and methods: High-throughput virtual screening combined with e-pharmacophore screening and ADME (absorption, distribution, metabolism, and excretion) and PAINS (pan-assay interference compounds) filters were applied to screen out the ligand molecules from the ZINC natural molecule database. The screened molecules were subjected to Glide XP docking to study the molecular interactions broadly. Further, molecular dynamic simulations were used to validate the stability of the enzyme–ligand complexes. Finally, the molecules with better results were optimized for in vitro testing. Results: The screening protocols identified eight hits from the natural molecule database, which were further filtered through pharmacological filters. The final four hits were subjected to extra precision docking, and the complexes were finally studied with molecular dynamic simulations. The results pointed to the zinc 85893731 molecule as the most stable in the binding pocket, producing consistent H-bond interaction with Ser152 (G=-7.18). The optimized lead molecule exhibited good docking score, better fit, and improved ADME profile. Conclusion: The present study specifies zinc 85893731 as a lead molecule with higher binding score and energetically stable complex with pancreatic lipase. This lead molecule, along with its various analogs, can be further tested as a novel inhibitor against pancreatic lipase using in vitro protocols.
Bioinformation, 2015
Increase in obesity rates and obesity associated health issues became one of the greatest health concerns in the present world population. With alarming increase in obese percentage there is a need to design new drugs related to the obesity targets. Among the various targets linked to obesity, pancreatic lipase was one of the promising targets for obesity treatment. Using the in silico methods like structure based virtual screening, QikProp, docking studies and binding energy calculations three molecules namely zinc85531017, zinc95919096 and zinc33963788 from the natural database were reported as the potential inhibitors for the pancreatic lipase. Among them zinc95919096 presented all the interactions matching to both standard and crystal ligand and hence it can be further proceeded to drug discovery process. BIOINFORMATION
Anti-Inflammatory & Anti-Allergy Agents in Medicinal Chemistry, 2018
Background: Inhibition activity of 8 synthetic molecules known as anti-allergy drugs on lipases has been investigated. The enzymatic inhibition produced by these molecules is described here for the first time. Objective: The used anti-allergy drugs are: Loratidine, primalan, zyrtec, histagan, periactin, ketotifene, rifex and bilastine. Methods: Lipase inhibition is studied using the spectrophotometric method. Molecular docking has been achieved for the first time for these drugs using AutoDock Vina program to discuss the nature of interactions, structure-activity relationship and the mechanism of inhibition. Results: The biological evaluation of these molecules showed that most of these drugs are potent lipase inhibitors with competitive type inhibition. The best drug is loratidine with IC50=0.44mg/ml and Ki=0.86 mM and competitive type inhibition. Molecular docking studies of the studied molecules confirmed their competitive inhibitory type with their binding to the Catalytic Active Site (CAS) of lipases. Conclusion: Hence, these drugs could be used for obesity or candidiasis treatment taking advantage of the much-known details of their secondary effects as antiallergy drugs.
Journal of Medicinal Chemistry, 2008
Hormone sensitive lipase (HSL) has been recently implicated in diabetes and obesity, prompting attempts to discover new HSL inhibitors. Toward this end, we explored the pharmacophoric space of HSL inhibitors using four diverse sets of compounds. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of yielding a self-consistent and predictive quantitative structure-activity relationship (QSAR) (r ) 0.822, n ) 99, F ) 11.1, r LOO 2 ) 0.521, r PRESS 2 against 23 external test inhibitors ) 0.522). Interestingly, two pharmacophoric models emerged in the QSAR equation suggesting at least two binding modes. These pharmacophores were employed to screen the National Cancer Institute (NCI) list of compounds and our in-house built database of established drugs and agrochemicals. Active hits included the safe herbicidal agent bifenox (IC 50 ) 0.43 µM) and the nonsteroidal anti-inflammatory naproxen (IC 50 ) 1.20 µM). Our active hits undermined the traditional believe that HSL inhibitors should possess covalent bond-forming groups. : hormone sensitive lipase; QSAR: quantitative structure-activity relationship; MLR: multiple linear regression; GA: genetic algorithm; HBA: hydrogen bond acceptor; HBD: hydrogen bond donor.
Future medicinal chemistry, 2018
The inhibition of pancreatic lipase (PL) enzyme is the most explored strategy for the treatment of obesity. The present study describes the development of quantitative structure-activity relationship (QSAR) models for a diverse set of 293 PL inhibitors by means of the Monte Carlo optimization technique. Methodology & results: The hybrid optimal descriptors were used to build QSAR models with three subsets of three splits. The developed QSAR models were further validated with corresponding external sets. The best QSAR model has the following statistical particulars: R = 0.752, Q LOO 2 = 0 . 736 for the test set and R = 0.768, Q F 1 2 = 0 . 628 , Q F 2 2 = 0 . 621 for the validation set. The developed QSAR models were robust, stable and predictive and led to the design of novel PL inhibitors.
Structural Chemistry, 2017
Staphylococcus aureus is a gram-positive bacterium. It is a foremost cause of skin and respiratory infections, endocarditis, osteomyelitis, Ritter's disease, and bacteraemia. Topoisomerase enzyme is involved in preventing or correcting topological problems of overwinding or underwinding occurring in DNA before replication process. An exhaustive molecular modeling studies that includes pharmacophore modeling, ligandbased three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, molecular dynamics simulation, and ADME calculations were performed on isothiazoloquinolones derivatives which are reported as effective inhibitors against topoisomerase IV of wild type S. aureus. In pharmacophore modeling by using pharmacophore alignment and scoring engine (PHASE) a five-point model (AHHRR.3) was generated with existing compounds having statistical significant as correlation coefficient (R 2 = 0.954), cross-validation coefficient (Q 2 = 0. 650), and F value of 130.5. Ligand-based 3D-QSAR study was applied using comparative molecular field analysis (CoMFA) with Q 2 = 0.616, R 2 = 0.989, and comparative molecular similarity indices analysis (CoMSIA) with Q 2 = 0.510, R 2 = 0.995. The predictive ability of this model was determined using a test set of molecules that gave acceptable predictive correlation (R 2 Pred) values 0.55 and 0.56 for CoMFA and CoMSIA, respectively. Docking and molecular dynamic simulations were employed to position the inhibitors into protein active site to find out the most probable binding mode and most reliable conformations. Developed pharmacophore models and docking methods provide guidance to design enhanced activity molecules. Keywords 3D-QSAR (three-dimensional quantitative structure activity relationship). PHASE (pharmacophore alignment and scoring engine). CoMFA (comparative molecular field analysis). CoMSIA (comparative molecular similarity indices analysis). PLS (partial least square). MD (molecular dynamics)
MedPharmRes, 2017
Nowadays, obesity has been becoming one of the most popular problems to the global health. Molecular design with the aid of computing method is an efficient and cost-saving solution in the initial research of new potential drugs for the treatment of obesity. This study focused on benzyl amino chalcone derivatives as they have a benzyl group that can mimic the hydrophobic effect of the long chain carbon of Orlistat, a drug used to treat obesity. Initially, 102 molecular structures were prepared and docked into the protein by using AutoDock Vina version 1.5.6. Fourteen structures having good docking scores were selected to synthesize using a Claisen-Schmidt reaction. Afterward, these synthesized chalcones were tested biological activity against pancreatic lipase by spectrophotometric determination at a wavelength of 405 nm, using p-nitro phenyl palmitate as the substrate. The co-crystallized ligand of pancreatic lipase enzyme was redocked into the enzyme and the RMSD was 1.4976 A whic...
Modern drug design approaches are based on accurate prediction of the protein-ligand binding interface and binding properties/modes of the ligand, even if experimentally determined (through X-ray or NMR) protein-ligand complex model is not available. The knowledge of the structure and physicochemical determinants of protein-substrate recognition and binding is of fundamental importance in structure-based drug design. What is highlighted herein is the procedure which makes use of tools of bioinformatics in order to test the binding properties of a ligand to a biomacromolecule. Since our research activities oriented in the quest of bioactive compounds as inhibitors towards zinc metallopeptidases, such us Angiotensin-I Converting Enzyme (ACE) [1] and Anthrax Lethal Factor (ALF) [2], we are studying the enzyme's catalytic sites and/or inhibitors conformational characteristics through Nuclear Magnetic Spectroscopy (NMR). Furthermore, we exploit the acquired structural data in an attempt to screen various compounds according their binding affinity in silico, through docking simulations methodology. Possible lead compounds will be optimized, synthesized and their binding properties would be then determined experimentally (using Xray or NMR). In this procedure application of docking simulations approaches is a prerequisite and the evaluation of the binding modes of a ligand to a protein target should be performed. To this effect, we implement docking simulations to the study of enzyme-inhibitor complexes and the results are compared to already known enzyme-inhibitor crystal structures. The potential for a docking algorithm to be used as a virtual screening [3][4]tool is based on both speed and accuracy .
COMPUTATIONAL MODELING AND DRUG DESIGNING OF LIPOPROTEIN LIPASE (LPL)
Homology modeling and flexible docking of Lipoprotein Lipase has been studied in silico approach. Blast result was found to have similarity with Lipoprotein Lipase of 83% identity with 1LPA. Active site of LPL protein was identified by CASTP. Large potential drugs were designed for identifying molecules that can likely bind to protein target of interest. The different drug derivatives designed were used for docking with the generated structure, among the 10 derivatives designed, 3 rd derivative showed highest docking result. The drug derivatives were docked to the protein by hydrogen bonding interactions and these interactions play an important role in the binding studies. Our investigations may be helpful for further studies.