scholarly journals Elucidating Binding Sites and Affinities of ERα Agonists and Antagonists to Human Alpha-Fetoprotein by In Silico Modeling and Point Mutagenesis

2020 ◽  
Vol 21 (3) ◽  
pp. 893 ◽  
Author(s):  
Nurbubu T. Moldogazieva ◽  
Daria S. Ostroverkhova ◽  
Nikolai N. Kuzmich ◽  
Vladimir V. Kadochnikov ◽  
Alexander A. Terentiev ◽  
...  
Keyword(s):  
Binding Sites ◽  
In Silico ◽  
Electrostatic Interactions ◽  
Molecular Mechanisms ◽  
3D Structure ◽  
Alpha Fetoprotein ◽  
Affinity Binding ◽  
Scoring Functions ◽  
Ligand Interaction ◽  
Ligand Interactions

Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting a variety of hydrophobic ligands, including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth, which can be attributed to its estrogen-binding ability. Despite AFP having long been investigated, its three-dimensional (3D) structure has not been experimentally resolved and molecular mechanisms underlying AFP–ligand interaction remains obscure. In our study, we constructed a homology-based 3D model of human AFP (HAFP) with the purpose of molecular docking of ERα ligands, three agonists (17β-estradiol, estrone and diethylstilbestrol), and three antagonists (tamoxifen, afimoxifene and endoxifen) into the obtained structure. Based on the ligand-docked scoring functions, we identified three putative estrogen- and antiestrogen-binding sites with different ligand binding affinities. Two high-affinity binding sites were located (i) in a tunnel formed within HAFP subdomains IB and IIA and (ii) on the opposite side of the molecule in a groove originating from a cavity formed between domains I and III, while (iii) the third low-affinity binding site was found at the bottom of the cavity. Here, 100 ns molecular dynamics (MD) simulation allowed us to study their geometries and showed that HAFP–estrogen interactions were caused by van der Waals forces, while both hydrophobic and electrostatic interactions were almost equally involved in HAFP–antiestrogen binding. Molecular mechanics/Generalized Born surface area (MM/GBSA) rescoring method exploited for estimation of binding free energies (ΔGbind) showed that antiestrogens have higher affinities to HAFP as compared to estrogens. We performed in silico point substitutions of amino acid residues to confirm their roles in HAFP–ligand interactions and showed that Thr132, Leu138, His170, Phe172, Ser217, Gln221, His266, His316, Lys453, and Asp478 residues, along with two disulfide bonds (Cys224–Cys270 and Cys269–Cys277), have key roles in both HAFP–estrogen and HAFP–antiestrogen binding. Data obtained in our study contribute to understanding mechanisms underlying protein–ligand interactions and anticancer therapy strategies based on ERα-binding ligands.

scholarly journals Elucidating Binding Sites and Affinities of ERα Agonist and Antagonist to Human Alpha-Fetoprotein by in silico Modeling and Point Mutagenesis

2019 ◽  
Author(s):  
Nurbubu T. Moldogazieva ◽  
Daria S. Ostroverkhova ◽  
Nikolai N. Kuzmich ◽  
Vladimir V. Kadochnikov ◽  
Alexander A. Terentiev ◽  
...  
Keyword(s):  
Binding Sites ◽  
In Silico ◽  
Disulfide Bonds ◽  
Electrostatic Interactions ◽  
Molecular Mechanisms ◽  
3D Structure ◽  
Scoring Function ◽  
Alpha Fetoprotein ◽  
Ligand Interaction ◽  
Ligand Interactions

Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting variety of hydrophobic ligands including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth and this can be attributed to its estrogen-binding ability. Despite AFP has long been investigated, its three-dimensional (3D) structure has not been experimentally resolved and molecular mechanisms underlying AFP-ligand interaction remain obscure. In our study we constructed homology-based 3D model of human AFP (HAFP) with the purpose to perform docking of ERα ligands, three agonists (17β-estradiol, estrone and diethylstilbestrol) and three antagonists (tamoxifen, afimoxifene and endoxifen) into the obtained structure. Based on ligand docked scoring function, we identified three putative estrogen- and antiestrogen-binding sites with different ligand binding affinities. Two high-affinity sites were located in (i) a tunnel formed within HAFP subdomains IB and IIA and (ii) opposite side of the molecule in a groove originating from cavity formed between domains I and III, while (iii) the third low-affinity site was found at the bottom of the cavity. 100 ns MD simulation allowed studying their geometries and showed that HAFP-estrogen interactions occur due to van der Waals forces, while both hydrophobic and electrostatic interactions were almost equally involved in HAFP-antiestrogen binding. MM/GBSA rescoring method estimated binding free energies (ΔGbind) and showed that antiestrogens have higher affinities to HAFP as compared to estrogens. We performed in silico point substitutions of amino acid residues to confirm their roles in HAFP-ligand interactions and showed that Thr132, Leu138, His170, Phe172, Ser217, Gln221, His266, His316, Lys453, and Asp478 residues along two disulfide bonds, Cys224-Cys270 and Cys269-Cys277 have key roles in both HAFP-estrogen and HAFP-antiestrogen binding. Data obtained in our study contribute to understanding mechanisms underlying protein-ligand interactions and anti-cancer therapy strategies based on ER-binding ligands.

scholarly journals Homology Modeling and Characterization of Novel Stress Inducing Genes and their Split Sites Recognition in the Genome of Zebra Fish (Danio Rario) by Employing Special Consensus Pattern Matching Algorithms- using an in-Silico Method.

2019 ◽  
Vol 9 (1) ◽  
pp. 6715-6720
Keyword(s):  
Transcription Factor ◽  
Heat Shock ◽  
Pattern Matching ◽  
Binding Sites ◽  
In Silico ◽  
3D Structure ◽  
Transcription Factor Binding Sites ◽  
Heat Shock Transcription Factor ◽  
Zebra Fish ◽  
Transcription Factor 1

Zebra fish has long been considered to be as a strong animal model in biology and modern genetics; however now a days its gaining lot of importance in environmental studies as well. The readily availability of entire genome sequences made to permit carrying out in silico studies at Genomic level. As everyone is known that stress is much more complex and complicated process that involves so much of gene regulations known as up regulation and down regulation, the corresponding stress proteins, broadly known as heat shock proteins. In the current study, the potential transcription factor binding sites were traced out by using bioinformatics tools and about 50 heat shock protein genes were predicted by using special alogorithms using pattern matching and position weight matrices. The 3D structure of DNA-binding domain of HSTF-1 ( Heat Shock Transcription factor-1) which is crucial for regulating heat shot proteins was traced out and builted by using homology modelling methods. The 3D structure of the heat shock transcription factor-1 and together with predicted transcription factor binding sites may be validated in future experimental works which would help us in understanding the complex responsive stress mechanisms lying in Zebra fish.

scholarly journals Ab-initio binding of barnase–barstar with DelPhiForce steered Molecular Dynamics (DFMD) approach

2020 ◽  
Vol 19 (04) ◽  
pp. 2050016
Author(s):  
Mahesh Koirala ◽  
Emil Alexov
Keyword(s):  
Molecular Dynamics ◽  
Electrostatic Interactions ◽  
3D Structure ◽  
Binding Mode ◽  
Steered Molecular Dynamics ◽  
Biological Processes ◽  
Close Proximity ◽  
Ligand Interactions ◽  
Pulling Force

Receptor–ligand interactions are involved in various biological processes, therefore understanding the binding mechanism and ability to predict the binding mode are essential for many biological investigations. While many computational methods exist to predict the 3D structure of the corresponding complex provided the knowledge of the monomers, here we use the newly developed DelPhiForce steered Molecular Dynamics (DFMD) approach to model the binding of barstar to barnase to demonstrate that first-principles methods are also capable of modeling the binding. Essential component of DFMD approach is enhancing the role of long-range electrostatic interactions to provide guiding force of the monomers toward their correct binding orientation and position. Thus, it is demonstrated that the DFMD can successfully dock barstar to barnase even if the initial positions and orientations of both are completely different from the correct ones. Thus, the electrostatics provides orientational guidance along with pulling force to deliver the ligand in close proximity to the receptor.

scholarly journals Combining Molecular Dynamic Information and an Aspherical-Atom Data Bank in the Evaluation of the Electrostatic Interaction Energy in Multimeric Protein-Ligand Complex: A Case Study for HIV-1 Protease

2021 ◽  
Author(s):  
Prashant Kumar ◽  
Paulina Dominiak
Keyword(s):  
Interaction Energy ◽  
Molecular Dynamic ◽  
Binding Affinity ◽  
Electrostatic Interaction ◽  
Electrostatic Interactions ◽  
Data Bank ◽  
Scoring Functions ◽  
Protein Ligand Interactions ◽  
Ligand Interactions ◽  
Hiv 1

<div> <div> <div> <p>Computational analysis of protein-ligand interactions is of crucial importance for drug discovery. Assessment of ligand binding energy allows us to have a glimpse on the potential of a small organic molecule to be a ligand to the binding site of a protein target. Available scoring functions such as in docking programs, we could say that they all rely on equations that sum each type of protein-ligand interactions to model the binding affinity. Most of the scoring functions consider electrostatic interactions involving the protein and the ligand. Electrostatic interactions contribute one of the most important part of total interaction energies between macromolecules, unlike dispersion forces they are highly directional and therefore dominate the nature of molecular packing in crystals and in biological complexes and contribute significantly to differences in inhibition strength among related enzyme inhibitors. In this paper, complexes of HIV-1 protease with inhibitor molecules (JE-2147 and Darunavir) have been analysed using charge densities from a transferable aspherical-atom data bank. Moreover, we analyse the electrostatic interaction energy for an ensemble of structures using molecular dynamic simulation to highlight the main features related to the importance of this interaction for binding affinity. </p> </div> </div> </div>

scholarly journals Combining Molecular Dynamic Information and an Aspherical-Atom Data Bank in the Evaluation of the Electrostatic Interaction Energy in Multimeric Protein-Ligand Complex: A Case Study for HIV-1 Protease

2021 ◽  
Author(s):  
Prashant Kumar ◽  
Paulina Dominiak
Keyword(s):  
Interaction Energy ◽  
Molecular Dynamic ◽  
Binding Affinity ◽  
Electrostatic Interaction ◽  
Electrostatic Interactions ◽  
Data Bank ◽  
Scoring Functions ◽  
Protein Ligand Interactions ◽  
Ligand Interactions ◽  
Hiv 1

<div> <div> <div> <p>Computational analysis of protein-ligand interactions is of crucial importance for drug discovery. Assessment of ligand binding energy allows us to have a glimpse on the potential of a small organic molecule to be a ligand to the binding site of a protein target. Available scoring functions such as in docking programs, we could say that they all rely on equations that sum each type of protein-ligand interactions to model the binding affinity. Most of the scoring functions consider electrostatic interactions involving the protein and the ligand. Electrostatic interactions contribute one of the most important part of total interaction energies between macromolecules, unlike dispersion forces they are highly directional and therefore dominate the nature of molecular packing in crystals and in biological complexes and contribute significantly to differences in inhibition strength among related enzyme inhibitors. In this paper, complexes of HIV-1 protease with inhibitor molecules (JE-2147 and Darunavir) have been analysed using charge densities from a transferable aspherical-atom data bank. Moreover, we analyse the electrostatic interaction energy for an ensemble of structures using molecular dynamic simulation to highlight the main features related to the importance of this interaction for binding affinity. </p> </div> </div> </div>

scholarly journals ABS–Scan: In silico alanine scanning mutagenesis for binding site residues in protein–ligand complex

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 214 ◽  
Author(s):  
Praveen Anand ◽  
Deepesh Nagarajan ◽  
Sumanta Mukherjee ◽  
Nagasuma Chandra
Keyword(s):  
Binding Site ◽  
In Silico ◽  
Ligand Recognition ◽  
Loss Of Function ◽  
Ligand Complex ◽  
Alanine Scanning Mutagenesis ◽  
Ligand Interaction ◽  
Alanine Scanning ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

Most physiological processes in living systems are fundamentally regulated by protein–ligand interactions. Understanding the process of ligand recognition by proteins is a vital activity in molecular biology and biochemistry. It is well known that the residues present at the binding site of the protein form pockets that provide a conducive environment for recognition of specific ligands. In many cases, the boundaries of these sites are not well defined. Here, we provide a web-server to systematically evaluate important residues in the binding site of the protein that contribute towards the ligand recognition through in silico alanine-scanning mutagenesis experiments. Each of the residues present at the binding site is computationally mutated to alanine. The ligand interaction energy is computed for each mutant and the corresponding ΔΔG values are computed by comparing it to the wild type protein, thus evaluating individual residue contributions towards ligand interaction. The server will thus provide clues to researchers about residues to obtain loss-of-function mutations and to understand drug resistant mutations. This web-tool can be freely accessed through the following address: http://proline.biochem.iisc.ernet.in/abscan/.

In Silico Insights on GD2 : A Potential Target for Pediatric Neuroblastoma

2020 ◽  
Vol 19 (30) ◽  
pp. 2766-2781 ◽  
Author(s):  
Akanksha Limaye ◽  
Jajoriya Sweta ◽  
Maddala Madhavi ◽  
Urvy Mudgal ◽  
Sourav Mukherjee ◽  
...  
Keyword(s):  
In Silico ◽  
Electrostatic Interactions ◽  
3D Structure ◽  
Biological Marker ◽  
Morbidity Rate ◽  
Local Alignment ◽  
Pharmacokinetic Studies ◽  
High Morbidity ◽  
High Morbidity Rate

Background: Originating from the abnormal growth of neuroblasts, pediatric neuroblastoma affects the age group below 15 years. It is an aggressive heterogenous cancer with a high morbidity rate. Biological marker GD2 synthesised by the GD2 gene acts as a powerful predictor of neuroblastoma cells. GD2 gangliosides are sialic acid-containing glycosphingolipids. Differential expression during brain development governs the function of the GD2. The present study explains the interaction of the GD2 with its established inhibitors and discovers the compound having a high binding affinity against the target protein. Technically, during the development of new compounds through docking studies, the best drug among all pre-exist inhibitors was filtered. Hence in reference to the best docked compound, the study proceeded further. Methodology: The In silico approach provides a platform to determine and establish potential inhibitor against GD2 in Pediatric neuroblastoma. The 3D structure of GD2 protein was modelled by homology base fold methods using Smith-Watermans’ Local alignment. A total of 18 established potent compounds were subjected to molecular docking and Etoposide (CID: 36462) manifested the highest affinity. The similarity search presented 336 compounds similar to Etoposide. Results: Through virtual screening, the compound having PubChem ID 10254934 showed a better affinity towards GD2 than the established inhibitor. The comparative profiling of the two compounds based on various interactions such as H-bond interaction, aromatic interactions, electrostatic interactions and ADMET profiling and toxicity studies were performed using various computational tools. Conclusion: The docking separated the virtual screened drug (PubChemID: 10254934) from the established inhibitor with a better re-rank score of -136.33. The toxicity profile of the virtual screened drug was also lesser (less lethal) than the established drug. The virtual screened drug was observed to be bioavailable as it does not cross the blood-brain barrier. Conclusively, the virtual screened compound obtained in the present investigation is better than the established inhibitor and can be further augmented by In vitro analysis, pharmacodynamics and pharmacokinetic studies.

Molecular Analyses of the Platelet Glycoprotein Ib-IX-V Receptor

1998 ◽  
Vol 79 (03) ◽  
pp. 466-478 ◽  
Author(s):  
Jerry Ware
Keyword(s):  
Molecular Mechanisms ◽  
Thrombus Formation ◽  
Von Willebrand Disease ◽  
Platelet Glycoprotein ◽  
Ligand Interaction ◽  
Receptor Ligand ◽  
Wide Range ◽  
Ligand Interactions ◽  
Normal Hemostasis ◽  
Von Willebrand

IntroducationGlycoprotein receptors within the platelet membrane are essential for initiating platelet adhesion and aggregation on thrombogenic surfaces. As a response to vascular injury these receptors provide platelets with two essential properties i) the ability to bind adhesive substrates exposed at the site of injury (adhesion) and ii) the ability to recruit additional platelets to form a thrombus (aggregation). It is becoming increasingly evident that defined rheological conditions govern the physiological relevance of specific receptor-ligand interactions along with fundamentally distinct molecular mechanisms for individual receptors and their ligands. Among platelet receptors the glycoprotein (GP) Ib-IX-V complex is important because it initiates thrombus formation over a wide range of flow conditions through an initial interaction with the adhesive ligand, von Willebrand factor. The importance of this receptor-ligand interaction is best exemplified by congenital bleeding disorders resulting from the lack of either the receptor or the ligand, the Bernard-Soulier syndrome and von Willebrand disease, respectively. Additionally, the GP Ib component of the GP Ib-IX-V complex contains a binding site for α-thrombin and recent studies have strengthened the concept that the interaction between α-thrombin and GP Ib is of biological relevance. Unquestionably, studies dissecting the GP Ib-IX-V complex are defining essential aspects of normal hemostasis and thrombosis while providing key information on the molecular mechanisms governing the formation of pathologic platelet thrombi. This review will summarize recent advances in our understanding of the synthesis, structure and function of the platelet GP Ib-IX-V complex. Where possible, directions for future studies will be identified with an overall goal of achieving a more complete understanding on the role of the GP Ib-IX-V complex in platelet biology.

scholarly journals Diffusion theory can be applied to antibodies attaching to ligand sites

2005 ◽  
Vol 46 (4) ◽  
pp. 495-505
Author(s):  
D. P. Wilson ◽  
D. L. S. McElwain
Keyword(s):  
Master Equation ◽  
B Lymphocytes ◽  
Binding Sites ◽  
Numerical Solutions ◽  
Diffusion Theory ◽  
Target Cells ◽  
Ligand Interaction ◽  
One Dimensional ◽  
Dimensional Diffusion ◽  
Ligand Interactions

AbstractHumoral immunity is that aspect of specific immunity that is mediated by B lymphocytes and involves the neutralising of disease-producing microorganisms, called pathogens, by means of antibodies attaching to the pathogen's binding sites. This inhibits the pathogen's entry into target cells. We present a master equation in both discrete and in continuous form for a ligand bound atnsites becoming a ligand bound atmsites in a given interaction time. To track the time-evolution of the antibody-ligand interaction, it is shown that the process is most easily treated classically and that in this case the master equation can be reduced to an equivalent one-dimensional diffusion equation. Thus well-known diffusion theory can be applied to antibody-ligand interactions. We consider three distinct cases depending on whether the probability of antibody binding compared to the probability of dissociation is relatively large, small or comparable, and numerical solutions are given.

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