scholarly journals MOLECULAR DOCKING AND MOLECULAR DYNAMICS STUDIES OF ACALYPHA INDICA L. PHYTOCHEMICAL CONSTITUENTS WITH CASPASE-3

2021 ◽  
pp. 210-215
Author(s):  
ELLIN FEBRINA ◽  
RYAN KHUNAM ALAMHARI ◽  
RIZKY ABDULAH ◽  
KERI LESTARI ◽  
JUTTI LEVITA ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Interactions ◽  
Caspase 3 ◽  
Md Simulations ◽  
Binding Mode ◽  
Lead Compounds ◽  
Phytochemical Constituents ◽  
Acalypha Indica ◽  
Native Ligand

Objective: This study investigated the structure-based molecular interactions between phytochemical constituents of Acalypha indica L. and caspase-3. Methods: Thirty-three phytochemical constituents of A. indica were screened against caspase-3. The X-ray crystal structure of human caspase-3 was retrieved from https://www.rcsb.org/structure/. The molecular interactions of the phytochemicals were studied using the AutoDock 4.2 software and followed by molecular dynamics (MD) simulations using the Amber18 software. Results: From this study, 25 screened phytochemicals were found to have a better binding mode than the native ligand. Moreover, the binding stability of the top four hits evaluated by MD indicated that the hydrogen bonds in MD were quite different from the molecular docking results due to the massive receptor and ligand movement in the MD simulations. However, with the exception of stigmasterol, all ligands were able to stabilize the protein. Conclusion: This study suggested that γ-sitosterol acetate, β-sitosterol acetate, and γ-sitosterol might be able to induce caspase-3, thereby activating apoptosis. These high-affinity compounds can bind to caspase-3 more efficiently and were able to stabilize the protein. Therefore, they have the potential to be used as lead compounds in the treatment of cancer.

scholarly journals Identification of Novel Src Inhibitors: Pharmacophore-Based Virtual Screening, Molecular Docking and Molecular Dynamics Simulations

Molecules ◽  
2020 ◽  
Vol 25 (18) ◽  
pp. 4094
Author(s):  
Yi Zhang ◽  
Ting-jian Zhang ◽  
Shun Tu ◽  
Zhen-hao Zhang ◽  
Fan-hao Meng
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Root Mean Square ◽  
Protein Complexes ◽  
Md Simulations ◽  
Binding Mode ◽  
Strong Interactions ◽  
Mean Square ◽  
Dynamics Simulations

Src plays a crucial role in many signaling pathways and contributes to a variety of cancers. Therefore, Src has long been considered an attractive drug target in oncology. However, the development of Src inhibitors with selectivity and novelty has been challenging. In the present study, pharmacophore-based virtual screening and molecular docking were carried out to identify potential Src inhibitors. A total of 891 molecules were obtained after pharmacophore-based virtual screening, and 10 molecules with high docking scores and strong interactions were selected as potential active molecules for further study. Absorption, distribution, metabolism, elimination and toxicity (ADMET) property evaluation was used to ascertain the drug-like properties of the obtained molecules. The proposed inhibitor–protein complexes were further subjected to molecular dynamics (MD) simulations involving root-mean-square deviation and root-mean-square fluctuation to explore the binding mode stability inside active pockets. Finally, two molecules (ZINC3214460 and ZINC1380384) were obtained as potential lead compounds against Src kinase. All these analyses provide a reference for the further development of novel Src inhibitors.

scholarly journals Design, Synthesis, Biological Evaluation, and Molecular Modeling of 2-Difluoromethylbenzimidazole Derivatives as Potential PI3Kα Inhibitors

Molecules ◽  
2022 ◽  
Vol 27 (2) ◽  
pp. 387
Author(s):  
Xiangcong Wang ◽  
Moxuan Zhang ◽  
Ranran Zhu ◽  
Zhongshan Wu ◽  
Fanhong Wu ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Modeling ◽  
3D Qsar ◽  
Binding Mode ◽  
Biological Evaluation ◽  
Field Analysis ◽  
Dynamics Simulation ◽  
Comfa Model ◽  
Qsar Models

PI3Kα is one of the potential targets for novel anticancer drugs. In this study, a series of 2-difluoromethylbenzimidazole derivatives were studied based on the combination of molecular modeling techniques 3D-QSAR, molecular docking, and molecular dynamics. The results showed that the best comparative molecular field analysis (CoMFA) model had q2 = 0.797 and r2 = 0.996 and the best comparative molecular similarity indices analysis (CoMSIA) model had q2 = 0.567 and r2 = 0.960. It was indicated that these 3D-QSAR models have good verification and excellent prediction capabilities. The binding mode of the compound 29 and 4YKN was explored using molecular docking and a molecular dynamics simulation. Ultimately, five new PI3Kα inhibitors were designed and screened by these models. Then, two of them (86, 87) were selected to be synthesized and biologically evaluated, with a satisfying result (22.8 nM for 86 and 33.6 nM for 87).

scholarly journals An Analysis Based on Molecular Docking and Molecular Dynamics Simulation Study of Bromelain as Anti-SARS-CoV-2 Variants

2021 ◽  
Vol 12 ◽  
Author(s):  
Trina Ekawati Tallei ◽  
Fatimawali ◽  
Afriza Yelnetty ◽  
Rinaldi Idroes ◽  
Diah Kusumawaty ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Three Dimensional ◽  
Md Simulations ◽  
Inhibitory Effect ◽  
Dynamics Simulation ◽  
Novel Coronavirus

The rapid spread of a novel coronavirus known as SARS-CoV-2 has compelled the entire world to seek ways to weaken this virus, prevent its spread and also eliminate it. However, no drug has been approved to treat COVID-19. Furthermore, the receptor-binding domain (RBD) on this viral spike protein, as well as several other important parts of this virus, have recently undergone mutations, resulting in new virus variants. While no treatment is currently available, a naturally derived molecule with known antiviral properties could be used as a potential treatment. Bromelain is an enzyme found in the fruit and stem of pineapples. This substance has been shown to have a broad antiviral activity. In this article, we analyse the ability of bromelain to counteract various variants of the SARS-CoV-2 by targeting bromelain binding on the side of this viral interaction with human angiotensin-converting enzyme 2 (hACE2) using molecular docking and molecular dynamics simulation approaches. We have succeeded in making three-dimensional configurations of various RBD variants using protein modelling. Bromelain exhibited good binding affinity toward various variants of RBDs and binds right at the binding site between RBDs and hACE2. This result is also presented in the modelling between Bromelain, RBD, and hACE2. The molecular dynamics (MD) simulations study revealed significant stability of the bromelain and RBD proteins separately up to 100 ns with an RMSD value of 2 Å. Furthermore, despite increases in RMSD and changes in Rog values of complexes, which are likely due to some destabilized interactions between bromelain and RBD proteins, two proteins in each complex remained bonded, and the site where the two proteins bind remained unchanged. This finding indicated that bromelain could have an inhibitory effect on different SARS-CoV-2 variants, paving the way for a new SARS-CoV-2 inhibitor drug. However, more in vitro and in vivo research on this potential mechanism of action is required.

Applications of Molecular Docking

2016 ◽  
pp. 278-306
Author(s):  
Josephine Anthony ◽  
Vijaya Raghavan Rangamaran ◽  
Kumar T. Shivasankarasubbiah ◽  
Dharani Gopal ◽  
Kirubagaran Ramalingam
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Fatty Acid ◽  
Molecular Mechanisms ◽  
Fatty Acid Biosynthesis ◽  
Dynamics Simulation ◽  
Computational Techniques ◽  
Lead Compounds ◽  
Medical Interest ◽  
Insight Into

Computational tools have extended their reach into different realms of scientific research. Often coupled with molecular dynamics simulation, docking provides comprehensive insight into molecular mechanisms of biological processes. Influence of molecular docking is highly experienced in the field of structure based drug discovery, wherein docking is vital in validating novel lead compounds. The significance of molecular docking is also understood in several environmental and industrial research, in order to untangle the interactions among macromolecules of non-medical interest. Various processes such as bioremediation (REMEDIDOCK), nanomaterial interactions (NANODOCK), nutraceutical interactions (NUTRADOCK), fatty acid biosynthesis (FADOCK), and antifoulers interactions (FOULDOCK) find the application of molecular docking. This chapter emphasizes the involvement of computational techniques in the aforementioned fields to expand our knowledge on macromolecular interacting mechanisms.

scholarly journals Molecular docking, pharmacophore based virtual screening and molecular dynamics studies towards the identification of potential leads for the management of H. pylori

RSC Advances ◽  
2019 ◽  
Vol 9 (45) ◽  
pp. 26176-26208 ◽  
Author(s):  
Manoj G. Damale ◽  
Rajesh B. Patil ◽  
Siddique Akber Ansari ◽  
Hamad M. Alkahtani ◽  
Abdulrahman A. Almehizia ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Md Simulations ◽  
Pharmacophore Modeling ◽  
Gastric Ulcers ◽  
Computational Approaches ◽  
Gastric Cancers ◽  
H Pylori

Computational approaches such as pharmacophore modeling, virtual screening and MD simulations were explored to find the potential hits as H. pylori specific panC inhibitors for the management of gastric ulcers and gastric cancers.

A boosted unbiased molecular dynamics method for predicting ligands binding mechanisms: probing the binding pathway of dasatinib to Src-kinase

2020 ◽  
Vol 36 (18) ◽  
pp. 4714-4720
Author(s):  
Farzin Sohraby ◽  
Mostafa Javaheri Moghadam ◽  
Masoud Aliyar ◽  
Hassan Aryapour
Keyword(s):  
Molecular Dynamics ◽  
Ligand Binding ◽  
Md Simulation ◽  
Src Kinase ◽  
Deep Understanding ◽  
Md Simulations ◽  
Binding Mode ◽  
Supplementary Information ◽  
Computational Resources ◽  
Binding Mechanisms

Abstract Summary Small molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased MD simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased MD simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) MD simulations, in this case a protein–ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding’s process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nanosecond time scales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction. Availability and implementation The links of the tutorial and technical documents are accessible in the article. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Prediction of Molecular Interactions And Physicochemical Properties Relevant For Vasopressin V2 Receptor Antagonism

2021 ◽  
Author(s):  
Ania de la Nuez Veulens ◽  
Yoanna María Álvarez Ginarte ◽  
Rolando Eduardo Rodríguez Fernandez ◽  
Fabrice Leclerc ◽  
Luis Alberto Montero Cabrera
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Physicochemical Properties ◽  
Molecular Dynamics Simulations ◽  
Binding Mode ◽  
Qsar Model ◽  
Antagonist Activity ◽  
Vasopressin V2 Receptor ◽  
V2 Receptor ◽  
Dynamics Simulations

Abstract We have developed two ligand and receptor-based computational approaches to study the physicochemical properties relevant to the biological activity of vasopressin V2 receptor (V2R) antagonist and eventually to predict the expected binding mode to V2R. The obtained Quantitative Structure Activity Relationship (QSAR) model showed a correlation of the antagonist activity with the hydration energy (EH2O) , the polarizability (P) and the calculated partial charge on atom N7 (q6) of the common substructure. The first two descriptors showed a positive contribution to antagonist activity, while the third one had a negative contribution. V2R was modeled and further relaxed on a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocoline (POPC) membrane by molecular dynamics simulations. The receptor antagonist complexes were guessed by molecular docking, and the stability of the most relevant structures were also evaluated by molecular dynamics simulations. As a result, amino acid residues Q96, W99, F105, K116, F178, A194, F307, and M311 were identified with the probably most relevant antagonist-receptor interactions on the studied complexes. The proposed QSAR model could explain the molecular properties relevant to the antagonist activity. The contributions to the antagonist-receptor interaction appeared also in agreement with the binding mode of the complexes obtained by molecular docking and Molecular Dynamics. These models will be used in further studies to look for new V2R potential antagonist molecules.

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