scholarly journals Quantitative and Systems Pharmacology. 1. In Silico Prediction of Drug–Target Interactions of Natural Products Enables New Targeted Cancer Therapy

2017 ◽  
Vol 57 (11) ◽  
pp. 2657-2671 ◽  
Author(s):  
Jiansong Fang ◽  
Zengrui Wu ◽  
Chuipu Cai ◽  
Qi Wang ◽  
Yun Tang ◽  
...  
Keyword(s):  
Natural Products ◽  
Cancer Therapy ◽  
In Silico ◽  
Drug Target ◽  
Targeted Cancer Therapy ◽  
Systems Pharmacology ◽  
In Silico Prediction

Isolation and in silico prediction of potential drug-like compounds from Anethum sowa L. root extracts targeted towards cancer therapy

2019 ◽  
Vol 78 ◽  
pp. 242-259 ◽  
Author(s):  
Md. Moshfekus Saleh-e-In ◽  
Ayan Roy ◽  
Muhammad Abdullah Al-Mansur ◽  
Choudhury Mahmood Hasan ◽  
Md. Matiur Rahim ◽  
...  
Keyword(s):  
Cancer Therapy ◽  
In Silico ◽  
Potential Drug ◽  
In Silico Prediction ◽  
Root Extracts ◽  
Anethum Sowa

scholarly journals In-silico prediction of novel drug-target complex of nsp3 of CHIKV through molecular dynamic simulation

Heliyon ◽  
2020 ◽  
Vol 6 (8) ◽  
pp. e04720 ◽  
Author(s):  
Durgesh Kumar ◽  
Mahendra Kumar Meena ◽  
Kamlesh Kumari ◽  
Rajan Patel ◽  
Abhilash Jayaraj ◽  
...  
Keyword(s):  
Molecular Dynamic Simulation ◽  
Molecular Dynamic ◽  
Dynamic Simulation ◽  
In Silico ◽  
Drug Target ◽  
In Silico Prediction ◽  
Novel Drug

Design, Synthesis and In Vitro Evaluation of Novel Anti-HIV 3-Pyrazol-3- yl-Pyridin-2-One Analogs

2019 ◽  
Vol 15 (5) ◽  
pp. 561-570 ◽  
Author(s):  
Sanjay Kumar ◽  
Shiv Gupta ◽  
Shraddha Gaikwad ◽  
Leila F. Abadi ◽  
Late K. K. Bhutani ◽  
...  
Keyword(s):  
Natural Products ◽  
In Silico ◽  
Chemical Space ◽  
Therapeutic Index ◽  
In Silico Prediction ◽  
New Class ◽  
Ic50 Values ◽  
Anti Hiv ◽  
Hiv 1

Background: Natural products have shown potent anti-HIV activity, but some of these also possess toxicity. The pharmacophoric fragments of these natural products have scope of combination with other pharmacophoric fragment and derivatization to reduce toxicity and increase the potency. Combination of natural product fragments from different classes of anti–HIV compounds may lead to a new class of potent anti–HIV agents. Objective: Design, in silico prediction of drug-likeness, ADMET properties and synthesis of pyrazol– pyridones. Evaluation of the anti–HIV–1 activity of synthesized pyrazol–pyridones. Methods: Pyrazol–pyridones were designed by combining reported anti–HIV pharmacophoric fragments. Designed molecules were synthesized after in silico prediction of drug-likeness and ADMET properties. Compounds were evaluated for activity against HIV–1VB59 and HIV–1UG070. Results: QED value of designed pyrazol–pyridones was greater than the known drug zidovudine. The designed compounds were predicted to be noncarcinogenic and nonmutagenic in nature. Seventeen novel pyrazol–pyridones were synthesized with good yield. Compound 6q and 6l showed activity with IC50 values 6.14 µM and 15.34 µM against HIV–1VB59 and 16.21 µM and 18.21 µM against HIV–1UG070, respectively. Conclusion: Compound 6q was found to be most potent among the synthesized compounds with a therapeutic index of 54.31against HIV–1VB59. This is the first report of anti–HIV–1 activity of pyrazol–pyridone class of compounds. Although the anti–HIV–1 activity of these compounds is moderate, this study opens up a new class for exploration of chemical space for anti–HIV–1 activity.

scholarly journals In silico prediction of antimalarial drug target candidates

2012 ◽  
Vol 2 ◽  
pp. 191-199 ◽  
Author(s):  
Philipp Ludin ◽  
Ben Woodcroft ◽  
Stuart A. Ralph ◽  
Pascal Mäser
Keyword(s):  
Antimalarial Drug ◽  
In Silico ◽  
Drug Target ◽  
In Silico Prediction

In silico prediction of UV-Vis spectra for dereplication of natural products extracts

Planta Medica ◽  
2016 ◽  
Vol 81 (S 01) ◽  
pp. S1-S381
Author(s):  
C Audoin ◽  
G Cuvier ◽  
G Genta-Jouve
Keyword(s):  
Natural Products ◽  
In Silico ◽  
In Silico Prediction

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.

In Silico Design of Novel Mutant Anti-MUC1 Aptamers for Targeted Cancer Therapy

2019 ◽  
Vol 60 (2) ◽  
pp. 786-793 ◽  
Author(s):  
Brianda L. Santini ◽  
Matías Zúñiga-Bustos ◽  
Abraham Vidal-Limon ◽  
Joel B. Alderete ◽  
Sergio A. Águila ◽  
...  
Keyword(s):  
Cancer Therapy ◽  
In Silico ◽  
Targeted Cancer Therapy ◽  
In Silico Design
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