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.

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

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

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

GRP78‐targeted in‐silico virtual screening of novel anticancer agents

2018 ◽  
Vol 92 (2) ◽  
pp. 1555-1566 ◽  
Author(s):  
Ambily Nath Indu Viswanath ◽  
Ji Woong Lim ◽  
Seon Hee Seo ◽  
Jae Yeol Lee ◽  
Sang Min Lim ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Anticancer Agents ◽  
In Silico

Virtual Screening of Novel Hybrid Non-Steroidal Anti-Inflammatory Drugs (NSAIDs): Exploring Multiple Targeted Cancer Therapy by an In Silico Approach

2020 ◽  
Vol 16 (1) ◽  
pp. 70-77
Author(s):  
Ashish P. Shah ◽  
Chhagan N. Patel
Keyword(s):  
Cancer Therapy ◽  
Virtual Screening ◽  
Binding Affinity ◽  
Anticancer Agents ◽  
In Silico ◽  
Software Tool ◽  
Docking Studies ◽  
Targeted Cancer Therapy ◽  
Bioactivity Prediction ◽  
Glide Docking

Background: Dual-targeting/Multi-targeting of oncoproteins by a single drug molecule represents an efficient, logical and alternative approach to drug combinations. In silico methods are useful tool for the search and design of selective multi-target agents. Objective: The objective of the present study was to design new hybrid compounds by linking the main structural unit of the NSAIDs with the benzothiazole and thiadiazole ring and to discover new hybrid NSAIDs as multi targeted anticancer agents through in silico approach. Method: Structure-based virtual screening was performed by applying ADMET filtration and Glide docking using Virtual screening Workflow. The docking studies were performed on three different types of receptors TNF-α, COX-II and protein kinase. Bioactivity prediction of screened compounds were done using Molinspiration online software tool. Results: Out of 54 designed compounds eighteen were screened on the basis of binding affinity on various receptors and ADMET filtration. Bioactivity prediction reveals that screened compounds may act through kinase inhibition or enzyme inhibition. Compounds 2sa, 5sa, 6sa and 7sa shows higher binding affinity with all three receptors. Conclusion: The study concluded that compound 2sa, 5sa, 6sa, and 7sa could be further explored for multiple targeted cancer therapy.

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.

Pharmacophore Based 3D-QSAR, Virtual Screening and Docking Studies on Novel Series of HDAC Inhibitors with Thiophen Linker as Anticancer Agents

2016 ◽  
Vol 19 (9) ◽  
pp. 735-751 ◽  
Author(s):  
Preeti Patel ◽  
Avineesh Singh ◽  
Vijay Patel ◽  
Deepak Jain ◽  
Ravichandran Veerasamy ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Anticancer Agents ◽  
Hdac Inhibitors ◽  
3D Qsar ◽  
Docking Studies
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