Molecular Docking of Antimycin A3 Analogs and Its Aromatic Segments as Inhibitors of Apoptosis Protein Marker BCL-XL and MCL-1 (original) (raw)
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Apoptosis is a major cell death mechanism in multi-cellular organisms. Bcl-B (also known as Bcl2-L-10) is an anti-apoptotic protein and protects cells from apoptosis upon sequestering proapoptotic Bax protein. BIM, the BH3-only protein, binds on the BH3-binding groove of the protein and promotes Bax-mediated apoptosis. In this context, we retrieved 14 BH3-mimetics reported to the Bcl-B to date and the compounds were used for designing novel inhibitor to the protein using fragment-based drug designing (FBDD) method. The 14 BH3-mimetics showed 12 unique scaffolds and 51 nonredundant fragments. The 14 parent compounds, the 12 scaffolds and 51 fragments were docked on the BH3-binding groove of the protein and comprehensive analysis of the docking data resulted in a scaffold (1-phenyl-1H-pyrrole-2,5-dione) and a set of fragments, which were effectively used to design tens of novel small molecular compounds by means of CombiGlide. High-throughput virtual screening of the novel compounds on the binding groove of the protein brought into fore a de novo antagonist, (5amino-2-(ethylamino)-N-(2-hydroxyphenyl)-3-(1-phenyl-2,5-dioxo-2,5-dihydro-1H-pyrrol-3yl)benzenesulfonamide), which showed binding affinities on the Bcl-B about two folds greater than the binding affinities of the 14 parent compounds reported in the literature.
International Journal of Pharmacy and Pharmaceutical Sciences, 2021
Molecular docking is a modeling tool of Bioinformatics which includes two or more molecules which interact to provide a stable product in the form of a complex. Molecular docking is helpful in predicting the 3-d structure of a complex which depends on the binding characteristics of Ligand and target. Also, it is a structure-based virtual screening (SBVS) utilized to keep the 3-d structures of small molecule which are generated by computers into a target structure in various types of conformations, positions and orientations. This molecular docking has come out to be a novel concept with various types of advantages. It behaves as a highly exploring domain due to its significant structure-based drug design (SBDD), Assessment of Biochemical pathways, Lead Optimization and in De Novo drug design. In spite of all potential approaches, there are certain challenges which arescoring function (differentiate the true binding mode), ligand chemistry (tautomerism and ionization) and receptor flexibility (single conformation of rigid receptor). The area of computer-aided drug design and discovery (CADDD) has achieved large favorable outcomes in the past few years. CADD has been adopted by various big pharmaceutical companies for leading discoveries of drugs. Many researchers have worked in order to examine different docking algorithms and to predict molecules' active site. Hence, this Review article depicts the whole sole of Molecular Docking.
BCL-2 as Target for Molecular Docking of Some Neoplastic Drugs
2012
B-Cell Lymphoma (Bcl) is an apoptosis regulator protein which plays an important role in many types of cancers. The Bcl-2 gene has been identified as over expressed in different cancers. In this study we identified the binding affinity of commonly used neoplastic drugs such as Gefitinib, Cisplatin, 5-FU, Gemcitabine and Vinorelbine on Bcl-2 using insilico techniques. Bcl-2 structure (PDB: 1G5M) was used as a target for evaluating the binding efficacy of inhibitors (drugs) using GOLD software. The inhibitor binding positions and affinities were determined using GOLD scoring fitness functions. We identified that amino acid residues ASP10, GLU13, LYS17, GLU42, and SER49 in Bcl-2 were important for inhibitor recognition via hydrogen bonding interactions. These hydrogen bonding interactions play an important role for stability of the target-ligand complex. This technique also determined the comparative efficacy of neoplastic drugs very elegantly using Bcl-2 as its target. The insilico docking techniques can be exploited to build targets and design inhibitors for novel therapeutic agents. Molecular docking helps in understanding the action of neoplastic drugs through affinity binding.
Molecular Docking: An Explanatory Approach in Structure-Based Drug Designing and Discovery
International Journal of Pharmacy and Pharmaceutical Sciences, 2021
Molecular docking is a modeling tool of bioinformatics which includes two or more molecules which interact to provide a stable product in the form of a complex. Molecular docking is helpful in predicting the 3-d structure of a complex which depends on the binding characteristics of ligand and target. Also, it is a structure-based virtual screening (SBVS) utilized to keep the 3-d structures of small molecules which are generated by computer into a target structure in various types of conformations, positions and orientations. This molecular docking has come out to be a novel concept with various types of advantages. It behaves as a highly exploring domain due to its significant structure-based drug design (SBDD), Assessment of Biochemical pathways, Lead Optimization and in De Novo drug design. In spite of all potential approaches there are certain challenges which are-scoring function (differentiate true binding mode), ligand chemistry (tautomerism and ionization) and receptor flexib...
Molecular Docking in Drug Discovery
Journal of Pharmaceutical Research, 2021
In last few years the Computer Aided Drug Design and Discovery is many success rates. In academics and many pharmaceutical industries for drug lead discovery they adopt the Computational Drug Design. The modern era of drug discovery and development structural information play an important role. For visualization of 3D-structure of molecule different docking program are developed. The docking score is analysed by using computer-based drug design software. It is structure based virtual screening method for the orientation, conformation, position into a structure of target molecule. Ligand and Protein docking is new concept. Molecular docking method complication is optimization of lead molecule, biological pathway evaluation and de Novo drug design.
A Review on Molecular Docking: Novel Tool for Drug Discovery
The field of computer aided drug design and discovery (CADDD) is a rapidly growing area that has seen many successes in the last few years. Many giant pharmaceutical companies, in addition to academia, adopt CADDD ford rug lead discovery. The explosion of structural informatics, genomics and proteomic plays a major role in leading the efforts towards modern era drug discovery and development. Enormous research from last two decades has been pursued to study various docking algorithms and predicting the active site of the molecule. Various docking programs were developed to visualize the3D structure of the molecule and docking score can also be analyzed with the aid of different computational methods. Molecular Docking is a structure-based virtual screening (SBVS) that is used to place the computer-generated three-dimensional Structures of small molecules into a target structure in a variety of positions, conformations and orientations. Protein-ligand docking is a new concept with a variety of applications. It acts as a vivacious explore domain because of its significance to structure-based drug design (SBDD), Lead Optimization, Evaluation of Biochemical pathways, in De Novo drug design. In this Review whole description on Molecular Docking are mentioned here. Through Molecular Docking the Binding mode and affinity of the complex so formed is estimated and thus helps in the Molecular Recognition Process docking towards discovery of new drug leads.
Molecular Docking Studies of Enzyme Inhibitors and Cytotoxic Chemical Entities
Molecular Docking, 2018
Docking is a powerful approach to perform virtual screening on large library of compounds, rank the conformations using a scoring function, and propose structural hypotheses of how the ligands inhibit the target, which is invaluable in lead optimization. Using experimentally proven active compounds, detailed docking studies were performed to determine the mechanism of molecular interaction and its binding mode in the active site of the modeled yeast α-glucosidase and human intestinal maltase-glucoamylase. All active ligands were found to have greater binding affinity with the yeast α-glucosidase as compared to that of human homologs, intestinal, and pancreatic maltase, by an average value of~À1.3 and~À0.8 kcal/ mol, respectively. Thirty quinoline derivatives have been synthesized and evaluated against β-glucuronidase inhibitory potential. Twenty-four analogs, which showed outstanding βglucuronidase activity, have IC 50 values ranging between 2.11 AE 0.05 and 46.14 AE 0.95 μM than standard D-saccharic acid 1,4-lactone (IC 50 = 48.4 AE 1.25 μM). Structure activity relationship and the interaction of the active compounds and enzyme active site with the help of docking studies were established. In addition, Small series of morpholine hydrazones synthesized to form morpholine hydrazones scaffold. The in vitro anti-cancer potential of all these compounds were checked against human cancer cell lines such as HepG2 (Human hepatocellular liver carcinoma) and MCF-7 (Human breast adenocarcinoma). Molecular docking studies were also performed to understand the binding interaction.
In silico- internet and analogue based drug design of new anticancer agent
The Pharma Innovation Journal, 2016
As now a day there is development and importance of computational chemistry including molecular docking and a SAR study which deals with pharmacophore based drug design approach. As the methodology linked with modification of the target based drug discovery by using sophisticated computational tools which are generally not very easy to understand and also got many incompatibility issues with many operating systems (OS) and other system configurations. Thus, the present study deals with the SAR (Structure Activity Relationship) study and pharmacophore based drug design approaches with the use of free internet based tools which are much user friendly and almost compatible with any platform. Here, in this paper attempts are made to design some daunomycin analogues using pharmacophore study as more potent or equivalent anticancer agents and their drug like properties, toxicity, metabolic sites and some other parameters that are predicted by the free internet based tools.
Current Cancer Therapy Reviews, 2017
Background: Laryngeal cancers affect one quarter of all head and neck cancers. Chemotherapy is a standard method in treatment laryngeal carcinoma. However, cancer chemotherapy is often a failure due to the appearance of drug resistance. This fact suggests that the search for novel, safe, and more effective laryngeal cancer drugs are required. Antimycin A 3 is a fit ligand of anti-apoptotic Bcl-2. While Bcl-2 is known to be over-expressed in laryngeal cancer cell, it is quite reasonable to expect antimycin A 3 and its analogue to induce apoptosis in those cells. Methods: With this viewpoint, we decided to conduct research that is aimed to evaluate cytotoxic activity of the synthesized open-chain analogues of antimycin A 3 against HEP-2 laryngeal cancer cells, as well as to conduct in silico study of the analogues on receptor binding target Bcl-2 of laryngeal cancer. Results and Conclusion: Open-chain analogues of antimycin A 3 were successfully synthesized in a good yield from Boc-L-Threonine by esterification, amidation, and Sharpless asymmetric dihydroxylation. Consistent with in silico study, the analogues exhibited a greater anticancer activity against laryngeal HEP-2 cells than the original antimycin A 3 with IC 50 ranging of 31.6 M to 46.3 M. Our results clearly demonstrate that the open-chain analogues of antimycin A 3 as a promising candidates of new anti-laryngeal cancer agents.
Molecular modeling method has been used for modeling a new molecule for Breast and colorectal cancer using Topotecan, a drug that’s already designed. This drug is drawn using HYPERCHEM and its R group is modified by replacing different functional groups like OH, CCl2OH, CF2OH, CH2CH2CH3, CH2CH3, CH3, Cl, F, H, and NH2, etc in its place. Molecules designed as such are optimized using different algorithms and their affinity is checked with the protein. The binding free energy of the protein is calculated by performing docking process. The docking process is done with the help of GOLD software. The molecule with minimum binding energy will have the maximum binding affinity. From the results obtained it’s clear that ligand “2(CCl2OH)”has the maximum binding affinity and this molecule is determined as the best lead molecule targets computationally. The calculated binding affinities between inhibitors 1,2,3,4,5,6, 7,8,9,10 are compared. The calculated binding affinities of the inhibitors indicate that inhibitor “2” (CCl2OH) would be expected to be better inhibitor than lead inhibitor 1,3,4,5,6,7,8,9 and 10. Inhibitor “2’’ predicted to be the most potent inhibitor of TOPOTECAN inhibitor as compared to all the other inhibitors considered in this study. For all the cases the minimization results provided qualitative agreement with experimental results. Therefore, this approach could be very useful for screening a larger set of compounds prior to synthesis accordingly; there is a need for methods that enable rapid assessment of large number of structurally unrelated molecules in a reasonably accurate manner. Energy components calculated by performing molecular mechanics calculations both in explicit solvent and complex states are sufficient to estimate the relative binding free energy differences between inhibitors qualitatively.