scholarly journals In Silico Rational Design and Virtual Screening of Bioactive Peptides Based on QSAR Modeling

ACS Omega ◽  
2020 ◽  
Vol 5 (11) ◽  
pp. 5951-5958 ◽  
Author(s):  
Mehri Mahmoodi-Reihani ◽  
Fatemeh Abbasitabar ◽  
Vahid Zare-Shahabadi
Keyword(s):  
Virtual Screening ◽  
In Silico ◽  
Rational Design ◽  
Bioactive Peptides ◽  
Qsar Modeling

In silico rational design and virtual screening of antixoidant tripeptides based on 3D-QSAR modeling

2019 ◽  
Vol 1193 ◽  
pp. 223-230 ◽  
Author(s):  
Haiqiong Guo ◽  
Yuxuan Wang ◽  
Qingxiu He ◽  
Yuping Zhang ◽  
Yong Hu ◽  
...  
Keyword(s):  
Virtual Screening ◽  
In Silico ◽  
Rational Design ◽  
3D Qsar ◽  
Qsar Modeling

Rational Design of Macrolides by Virtual Screening of Combinatorial Libraries Generated through in Silico Manipulation of Polyketide Synthases

2006 ◽  
Vol 49 (6) ◽  
pp. 2077-2087 ◽  
Author(s):  
Sergey B. Zotchev ◽  
Alla V. Stepanchikova ◽  
Anastasia P. Sergeyko ◽  
Boris N. Sobolev ◽  
Dmitrii A. Filimonov ◽  
...  
Keyword(s):  
Virtual Screening ◽  
In Silico ◽  
Rational Design ◽  
Combinatorial Libraries ◽  
Polyketide Synthases

Rational design of promiscuous binding modulators of p53 inducing E3(Ub)-ligases (Mdm2 and Pirh2) as anticancer agents: an in silico approach

MedChemComm ◽  
2015 ◽  
Vol 6 (11) ◽  
pp. 1959-1968 ◽  
Author(s):  
Sarfaraj Niazi ◽  
Madhusudan Purohit
Keyword(s):  
Virtual Screening ◽  
Anticancer Agents ◽  
In Silico ◽  
Rational Design

Twelve promiscuous binding p53 inducing E3(Ub) ligases (Mdm2 and Pirh2) hit candidates have been identified by structure based virtual screening.

Discovery of New AKT1 Inhibitors by Combination of In silico Structure Based Virtual Screening Approaches and Biological Evaluations

2019 ◽  
Author(s):  
Filip Fratev ◽  
Denisse A. Gutierrez ◽  
Renato J. Aguilera ◽  
suman sirimulla
Keyword(s):  
Virtual Screening ◽  
Success Rate ◽  
Protein Interactions ◽  
In Silico ◽  
Biological Data ◽  
In Vitro Binding ◽  
Vitro Binding ◽  
Screening Protocol ◽  
Screening Approaches

AKT1 is emerging as a useful target for treating cancer. Herein, we discovered a new set of ligands that inhibit the AKT1, as shown by in vitro binding and cell line studies, using a newly designed virtual screening protocol that combines structure-based pharmacophore and docking screens. Taking together with the biological data, the combination of structure based pharamcophore and docking methods demonstrated reasonable success rate in identifying new inhibitors (60-70%) proving the success of aforementioned approach. A detail analysis of the ligand-protein interactions was performed explaining observed activities.<br>

In the Quest for a Stable Triplet State in Small Polyaromatic Hydrocarbons : An In-Silico Tool for Rational Design and Prediction

2019 ◽  
Author(s):  
Madhumita Rano ◽  
Sumanta K Ghosh ◽  
Debashree Ghosh
Keyword(s):  
Triplet State ◽  
Small Molecules ◽  
In Silico ◽  
Qualitative Agreement ◽  
Rational Design ◽  
Polyaromatic Hydrocarbons ◽  
Spin Hamiltonian ◽  
Spin Frustration ◽  
Computationally Efficient ◽  
High Level

<div>Combining the roles of spin frustration and geometry of odd and even numbered rings in polyaromatic hydrocarbons (PAHs), we design small molecules that show exceedingly small singlet-triplet gaps and stable triplet ground states. Furthermore, a computationally efficient protocol with a model spin Hamiltonian is shown to be capable of qualitative agreement with respect to high level multireference calculations and therefore, can be used for fast molecular discovery and screening.</div>

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki
Keyword(s):  
Data Analysis ◽  
Virtual Screening ◽  
In Silico ◽  
Model Development ◽  
In Silico Analysis ◽  
Material Design ◽  
Efficient Solutions ◽  
Biological Data ◽  
Cost Efficient ◽  
Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

Promising Anti-stroke Signature of Voglibose: Investigation through In- Silico Molecular Docking and Virtual Screening in In-Vivo Animal Studies

2020 ◽  
Vol 20 (3) ◽  
pp. 223-235
Author(s):  
Pooja Shah ◽  
Vishal Chavda ◽  
Snehal Patel ◽  
Shraddha Bhadada ◽  
Ghulam Md. Ashraf
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
In Silico ◽  
Reductase Activity ◽  
Infarct Volume ◽  
Docking Studies ◽  
Serum Glucose ◽  
In Vivo Studies ◽  
In Silico Molecular Docking

Background: Postprandial hyperglycemia considered to be a major risk factor for cerebrovascular complications. Objective: The current study was designed to elucidate the beneficial role of voglibose via in-silico in vitro to in-vivo studies in improving the postprandial glycaemic state by protection against strokeprone type 2 diabetes. Material and Methods: In-Silico molecular docking and virtual screening were carried out with the help of iGEMDOCK+ Pymol+docking software and Protein Drug Bank database (PDB). Based on the results of docking studies, in-vivo investigation was carried out for possible neuroprotective action. T2DM was induced by a single injection of streptozotocin (90mg/kg, i.v.) to neonates. Six weeks after induction, voglibose was administered at the dose of 10mg/kg p.o. for two weeks. After eight weeks, diabetic rats were subjected to middle cerebral artery occlusion, and after 72 hours of surgery, neurological deficits were determined. The blood was collected for the determination of serum glucose, CK-MB, LDH and lipid levels. Brains were excised for determination of brain infarct volume, brain hemisphere weight difference, Na+-K+ ATPase activity, ROS parameters, NO levels, and aldose reductase activity. Results: In-silico docking studies showed good docking binding score for stroke associated proteins, which possibly hypotheses neuroprotective action of voglibose in stroke. In the present in-vivo study, pre-treatment with voglibose showed a significant decrease (p<0.05) in serum glucose and lipid levels. Voglibose has shown significant (p<0.05) reduction in neurological score, brain infarct volume, the difference in brain hemisphere weight. On biochemical evaluation, treatment with voglibose produced significant (p<0.05) decrease in CK-MB, LDH, and NO levels in blood and reduction in Na+-K+ ATPase, oxidative stress, and aldose reductase activity in brain homogenate. Conclusion: In-silico molecular docking and virtual screening studies and in-vivo studies in MCAo induced stroke, animal model outcomes support the strong anti-stroke signature for possible neuroprotective therapeutics.

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