scholarly journals Application of the SwissDrugDesign Online Resources in Virtual Screening

2019 ◽  
Vol 20 (18) ◽  
pp. 4612 ◽  
Author(s):  
Antoine Daina ◽  
Vincent Zoete
Keyword(s):  
Virtual Screening ◽  
Small Molecules ◽  
Short Description ◽  
Online Resources ◽  
Computer Aided Drug Design ◽  
Web Based ◽  
Online Tools ◽  
Modeling Group ◽  
Computer Aided ◽  
Swiss Institute

SwissDrugDesign is an important initiative led by the Molecular Modeling Group of the SIB Swiss Institute of Bioinformatics. This project provides a collection of freely available online tools for computer-aided drug design. Some of these web-based methods, i.e., SwissSimilarity and SwissTargetPrediction, were especially developed to perform virtual screening, while others such as SwissADME, SwissDock, SwissParam and SwissBioisostere can find applications in related activities. The present review aims at providing a short description of these methods together with examples of their application in virtual screening, where SwissDrugDesign tools successfully supported the discovery of bioactive small molecules.

scholarly journals Sanitize It Yourself: Web-based molecular sanitization for machine-generated chemical structures

2021 ◽  
Author(s):  
Naruki Yoshikawa ◽  
Kentaro Rikimaru ◽  
Kazuki Yamamoto
Keyword(s):  
Deep Learning ◽  
Web Service ◽  
Chemical Space ◽  
Computer Aided Drug Design ◽  
Web Based ◽  
Chemical Structures ◽  
Structural Formulas ◽  
Computer Aided ◽  
Novel Structures ◽  
The Web

Many computer-aided drug design (CADD) methods using deep learning have recently been proposed to explore the chemical space toward novel scaffolds efficiently. However, there is a tradeoff between the ease of generating novel structures and the chemical feasibility of structural formulas. To overcome the limitations of computational filtering, we have implemented a web-based software in which users can share and evaluate computer-generated compounds. The web service is available at https://sanitizer.chemical.space/.

scholarly journals COMPUTER AIDED DRUG DESIGN: AN OVERVIEW

2018 ◽  
Vol 8 (5) ◽  
pp. 504-509 ◽  
Author(s):  
Surabhi Surabhi ◽  
BK Singh
Keyword(s):  
Molecular Docking ◽  
Drug Discovery ◽  
Virtual Screening ◽  
Drug Design ◽  
Computer Aided Drug Design ◽  
Structure Based Drug Design ◽  
Drug Discovery And Development ◽  
Research Areas ◽  
Computer Aided ◽  
Pharmaceutical Industries

Discovery and development of a new drug is generally known as a very complex process which takes a lot of time and resources. So now a day’s computer aided drug design approaches are used very widely to increase the efficiency of the drug discovery and development course. Various approaches of CADD are evaluated as promising techniques according to their need, in between all these structure-based drug design and ligand-based drug design approaches are known as very efficient and powerful techniques in drug discovery and development. These both methods can be applied with molecular docking to virtual screening for lead identification and optimization. In the recent times computational tools are widely used in pharmaceutical industries and research areas to improve effectiveness and efficacy of drug discovery and development pipeline. In this article we give an overview of computational approaches, which is inventive process of finding novel leads and aid in the process of drug discovery and development research. Keywords: computer aided drug discovery, structure-based drug design, ligand-based drug design, virtual screening and molecular docking

Structure-based virtual screening towards the discovery of novel FOXM1 inhibitors

2021 ◽  
Author(s):  
Zhuo-Song Xie ◽  
Zi-Ying Zhou ◽  
Lian-Qi Sun ◽  
Hong Yi ◽  
Si-Tu Xue ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Virtual Screening ◽  
Mouse Model ◽  
Small Molecules ◽  
Antiproliferative Activity ◽  
Binding Sites ◽  
Specific Inhibitor ◽  
Activity Analysis ◽  
Computer Aided Drug Design

Aim: Given the importance of FOXM1 in the treatment of ovarian cancer, we aimed to identify an excellent specific inhibitor and examined its underlying therapeutic effect. Materials & methods: The binding statistics for FDI-6 with FOXM1 were calculated through computer-aided drug design (CADD). We selected XST-119 through virtual screening, performed surface plasmon resonance and in vitro cell antiproliferative activity analysis and evaluated its antitumor efficacy in a mouse model. Results: XST-119 had significantly higher affinity for FOXM1 and antiproliferative activity than FDI-6. XST-119 had a definite inhibitory activity in a xenograft mouse model. Conclusion: We identified XST-119, a FOXM1 inhibitor, with better efficacy for treatment of ovarian cancer. FOXM1 binding sites for small molecules are also highlighted, which may provide the foundation for further drug discovery.

The discovery of new acetylcholinesterase inhibitors derived from pharmacophore modeling, virtual screening, docking simulation and bioassays

2016 ◽  
Vol 12 (12) ◽  
pp. 3734-3742 ◽  
Author(s):  
Yunqin Zhang ◽  
Shuqun Zhang ◽  
Guowei Xu ◽  
Hui Yan ◽  
Yinglan Pu ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Drug Design ◽  
Docking Simulation ◽  
Acetylcholinesterase Inhibitors ◽  
Pharmacophore Modeling ◽  
Computer Aided Drug Design ◽  
Ache Inhibitors ◽  
Computer Aided

Novel AChE inhibitors are discovered using computer aided drug design and bioassays.

scholarly journals A Computer-Aided Drug Design Approach to Predict Marine Drug-Like Leads for SARS-CoV-2 Main Protease Inhibition

Marine Drugs ◽  
2020 ◽  
Vol 18 (12) ◽  
pp. 633
Author(s):  
Susana P. Gaudêncio ◽  
Florbela Pereira
Keyword(s):  
Virtual Screening ◽  
Drug Design ◽  
Predictive Accuracy ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Classification Model ◽  
Protease Inhibition ◽  
Computer Aided Drug Design ◽  
Main Protease ◽  
Computer Aided

The investigation of marine natural products (MNPs) as key resources for the discovery of drugs to mitigate the COVID-19 pandemic is a developing field. In this work, computer-aided drug design (CADD) approaches comprising ligand- and structure-based methods were explored for predicting SARS-CoV-2 main protease (Mpro) inhibitors. The CADD ligand-based method used a quantitative structure–activity relationship (QSAR) classification model that was built using 5276 organic molecules extracted from the ChEMBL database with SARS-CoV-2 screening data. The best model achieved an overall predictive accuracy of up to 67% for an external and internal validation using test and training sets. Moreover, based on the best QSAR model, a virtual screening campaign was carried out using 11,162 MNPs retrieved from the Reaxys® database, 7 in-house MNPs obtained from marine-derived actinomycetes by the team, and 14 MNPs that are currently in the clinical pipeline. All the MNPs from the virtual screening libraries that were predicted as belonging to class A were selected for the CADD structure-based method. In the CADD structure-based approach, the 494 MNPs selected by the QSAR approach were screened by molecular docking against Mpro enzyme. A list of virtual screening hits comprising fifteen MNPs was assented by establishing several limits in this CADD approach, and five MNPs were proposed as the most promising marine drug-like leads as SARS-CoV-2 Mpro inhibitors, a benzo[f]pyrano[4,3-b]chromene, notoamide I, emindole SB beta-mannoside, and two bromoindole derivatives.

scholarly journals VIRTUAL SCREENING STATEGIES IN DRUG DISCOVERY – A BRIEF OVERVIEW

2021 ◽  
Vol 59 (4) ◽  
pp. 415
Author(s):  
Quan Minh PHAM ◽  
Long Quoc PHAM
Keyword(s):  
Drug Discovery ◽  
Virtual Screening ◽  
Development Process ◽  
Biological Activities ◽  
Computer Aided Drug Design ◽  
Computational Approaches ◽  
Drug Discovery And Development ◽  
Drug Lead ◽  
Lead Identification ◽  
Computer Aided

Computer-aided drug design has now become a compulsory tool in the drug discovery and development process which uses computational approaches to discover potential compounds with expected biological activities. Firstly, this review provides a comprehensive introduction of the virtual screening technique, knowledge and advances in both SBVS and LBVS strategies also presented. Secondly, recent database of compounds provided worldwide and drug-like parameters which are helpful in supporting the VS process will be discussed. These information will provides a good platform to estimate the advance of applying these techniques in the new drug-lead identification and optimization.

scholarly journals Synthesis and Anti-Tumor Activity of Oleanolic Acid Derivatives

2017 ◽  
Author(s):  
Kuai ZhenYu ◽  
Lei Li ◽  
Shengwen Zhan ◽  
Chunlin Li ◽  
Yuwei Zhao ◽  
...  
Keyword(s):  
Amino Acid ◽  
Small Molecules ◽  
Oleanolic Acid ◽  
Carboxyl Group ◽  
Lead Compound ◽  
Computer Aided Drug Design ◽  
Mtt Method ◽  
Computer Aided ◽  
Anti Tumor Activity

Using the techniques of computer-aided drug design, the docking of Survivin and known active small molecules was simulated and then the key amino acid residue fragment of the target protein was analyzed. It led to the discovery of active groups capable of binding to the critical sites. Through the use of the natural product, Oleanolic Acid, as a lead compound, the introduction of the active groups onto the A-ring, and the modification of the carboxyl group at the C-28 position using esterification or amidation, twenty new Oleanolic acid derivatives had been designed and synthesized.A549 and SGC-7901 cells were used to screen the antitumor activity in vitro through the standard MTT method. The compounds, II3, III5 and Ⅳ4, exhibited more potent cytotoxicity than positive drugs.

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