Evaluation of drug efficacy based on the spatial position comparison of drug–target interaction centers

2019 ◽  
Vol 21 (3) ◽  
pp. 762-776 ◽  
Author(s):  
Yu Ding ◽  
Hong Wang ◽  
Hewei Zheng ◽  
Lianzong Wang ◽  
Guosi Zhang ◽  
...  

Abstract The spatial position and interaction of drugs and their targets is the most important characteristics for understanding a drug’s pharmacological effect, and it could help both in finding new and more precise treatment targets for diseases and in exploring the targeting effects of the new drugs. In this work, we develop a computational pipeline to confirm the spatial interaction relationship of the drugs and their targets and compare the drugs’ efficacies based on the interaction centers. First, we produce a 100-sample set to reconstruct a stable docking model of the confirmed drug–target pairs. Second, we set 5.5 Å as the maximum distance threshold for the drug–amino acid residue atom interaction and construct 3-dimensional interaction surface models. Third, by calculating the spatial position of the 3-dimensional interaction surface center, we develop a comparison strategy for estimating the efficacy of different drug–target pairs. For the 1199 drug–target interactions of the 649 drugs and 355 targets, the drugs that have similar interaction center positions tend to have similar efficacies in disease treatment, especially in the analysis of the 37 targeted relationships between the 15 known anti-cancer drugs and 10 target molecules. Furthermore, the analysis of the unpaired anti-cancer drug and target molecules suggests that there is a potential application for discovering new drug actions using the sampling molecular docking and analyzing method. The comparison of the drug–target interaction center spatial position method better reflect the drug–target interaction situations and could support the discovery of new efficacies among the known anti-cancer drugs.


Author(s):  
Kumar Sharp ◽  
Dr. Shubhangi Dange

Identification of potential drug-target interaction for approved drugs serves as the basis of repurposing drugs. Studies have shown polypharmacology as common phenomenon. In-silico approaches help in screening large compound libraries at once which could take years in a laboratory. We screened a library of 1050 FDA-approved drugs against spike glycoprotein of SARS-CoV2 in-silico. Anti-cancer drugs have shown good binding affinity which is much better than hydroxychloroquine and arbidol. We have also introduced a hypothesis named “Bump” hypothesis which and be developed further in field of computational biology.



2020 ◽  
Author(s):  
Kumar Sharp ◽  
Dr. Shubhangi Dange

Identification of potential drug-target interaction for approved drugs serves as the basis of repurposing drugs. Studies have shown polypharmacology as common phenomenon. In-silico approaches help in screening large compound libraries at once which could take years in a laboratory. We screened a library of 1050 FDA-approved drugs against spike glycoprotein of SARS-CoV2 in-silico. Anti-cancer drugs have shown good binding affinity which is much better than hydroxychloroquine and arbidol. We have also introduced a hypothesis named “Bump” hypothesis which and be developed further in field of computational biology.





1993 ◽  
Vol 55 (1) ◽  
pp. 43-46
Author(s):  
Jun YOSHIDA ◽  
Juichiro NAKAYAMA ◽  
Nobuyuki SHIMIZU ◽  
Shonosuke NAGAE ◽  
Yoshiaki HORI


2019 ◽  
Vol 24 (32) ◽  
pp. 3829-3841 ◽  
Author(s):  
Lakshmanan Loganathan ◽  
Karthikeyan Muthusamy

Worldwide, colorectal cancer takes up the third position in commonly detected cancer and fourth in cancer mortality. Recent progress in molecular modeling studies has led to significant success in drug discovery using structure and ligand-based methods. This study highlights aspects of the anticancer drug design. The structure and ligand-based drug design are discussed to investigate the molecular and quantum mechanics in anti-cancer drugs. Recent advances in anticancer agent identification driven by structural and molecular insights are presented. As a result, the recent advances in the field and the current scenario in drug designing of cancer drugs are discussed. This review provides information on how cancer drugs were formulated and identified using computational power by the drug discovery society.



2020 ◽  
Vol 21 (10) ◽  
pp. 1011-1026
Author(s):  
Bruna O. Costa ◽  
Marlon H. Cardoso ◽  
Octávio L. Franco

: Aminoglycosides and β-lactams are the most commonly used antimicrobial agents in clinical practice. This occurs because they are capable of acting in the treatment of acute bacterial infections. However, the effectiveness of antibiotics has been constantly threatened due to bacterial pathogens producing resistance enzymes. Among them, the aminoglycoside-modifying enzymes (AMEs) and β-lactamase enzymes are the most frequently reported resistance mechanisms. AMEs can inactivate aminoglycosides by adding specific chemical molecules in the compound, whereas β-lactamases hydrolyze the β-lactams ring, preventing drug-target interaction. Thus, these enzymes provide a scenario of multidrug-resistance and a significant threat to public health at a global level. In response to this challenge, in recent decades, several studies have focused on the development of inhibitors that can restore aminoglycosides and β-lactams activity. In this context, peptides appear as a promising approach in the field of inhibitors for future antibacterial therapies, as multiresistant bacteria may be susceptible to these molecules. Therefore, this review focused on the most recent findings related to peptide-based inhibitors that act on AMEs and β-lactamases, and how these molecules could be used for future treatment strategies.





2020 ◽  
Vol 20 (9) ◽  
pp. 779-787
Author(s):  
Kajal Ghosal ◽  
Christian Agatemor ◽  
Richard I. Han ◽  
Amy T. Ku ◽  
Sabu Thomas ◽  
...  

Chemotherapy employs anti-cancer drugs to stop the growth of cancerous cells, but one common obstacle to the success is the development of chemoresistance, which leads to failure of the previously effective anti-cancer drugs. Resistance arises from different mechanistic pathways, and in this critical review, we focus on the Fanconi Anemia (FA) pathway in chemoresistance. This pathway has yet to be intensively researched by mainstream cancer researchers. This review aims to inspire a new thrust toward the contribution of the FA pathway to drug resistance in cancer. We believe an indepth understanding of this pathway will open new frontiers to effectively treat drug-resistant cancer.



2013 ◽  
Vol 13 (14) ◽  
pp. 1636-1649 ◽  
Author(s):  
Esvieta Tenorio-Borroto ◽  
Xerardo Garcia-Mera ◽  
Claudia Penuelas-Rivas ◽  
Juan Vasquez-Chagoyan ◽  
Francisco Prado-Prado ◽  
...  


Sign in / Sign up

Export Citation Format

Share Document