scholarly journals Structure-based drug design (SBDD) and in silico pharmacophore screening approaches coupled with biochemical validation enabled the discovery of small organic molecules modulators of Y-49, TEM-1 and ampC beta lactamases

Author(s):  
Cristina C Clement
2020 ◽  
Vol 8 ◽  
Author(s):  
Sharon Shechter ◽  
David R. Thomas ◽  
David A. Jans

The development of new drugs is costly and time-consuming, with estimates of over $US1 billion and 15 years for a product to reach the market. As understanding of the molecular basis of disease improves, various approaches have been used to target specific molecular interactions in the search for effective drugs. These include high-throughput screening (HTS) for novel drug identification and computer-aided drug design (CADD) to assess the properties of putative drugs before experimental work begins. We have applied conventional HTS and CADD approaches to the problem of identifying antiviral compounds to limit infection by Venezuelan equine encephalitis virus (VEEV). Nuclear targeting of the VEEV capsid (CP) protein through interaction with the host nuclear import machinery has been shown to be essential for viral pathogenicity, with viruses incapable of this interaction being greatly attenuated. Our previous conventional HTS and in silico structure-based drug design (SBDD) screens were successful in identifying novel inhibitors of CP interaction with the host nuclear import machinery, thus providing a unique opportunity to assess the relative value of the two screening approaches directly. This focused review compares and contrasts the two screening approaches, together with the properties of the inhibitors identified, as a case study for parallel use of the two approaches to identify antivirals. The utility of SBDD screens, especially when used in parallel with traditional HTS, in identifying agents of interest to target the host–pathogen interface is highlighted.


2018 ◽  
Author(s):  
Traci Clymer ◽  
Vanessa Vargas ◽  
Eric Corcoran ◽  
Robin Kleinberg ◽  
Jakub Kostal

Chemicals are the basis of our society and economy, yet many existing chemicals are known to have unintended adverse effects on human and environmental health. Testing all existing and new chemicals on animals is both economically and ethically unfeasible. In this paper, a new in silico framework is presented that affords redesign of existing hazardous chemicals in commerce based on specific molecular initiating events in their adverse outcomes pathways. Our approach is based on a successful methodology implemented in computational drug discovery, and promises to dramatically lower costs associated with new chemical development by synergistically addressing chemical function and safety at the design stage. <br>


Parasitology ◽  
2013 ◽  
Vol 141 (1) ◽  
pp. 17-27 ◽  
Author(s):  
FRASER CUNNINGHAM ◽  
MARTIN J. McPHILLIE ◽  
A. PETER JOHNSON ◽  
COLIN W. G. FISHWICK

SUMMARYIn light of the low success rate of target-based genomics and HTS (High Throughput Screening) approaches in anti-infective drug discovery, in silico structure-based drug design (SBDD) is becoming increasingly prominent at the forefront of drug discovery. In silico SBDD can be used to identify novel enzyme inhibitors rapidly, where the strength of this approach lies with its ability to model and predict the outcome of protein-ligand binding. Over the past 10 years, our group have applied this approach to a diverse number of anti-infective drug targets ranging from bacterial D-ala-D-ala ligase to Plasmodium falciparum DHODH. Our search for new inhibitors has produced lead compounds with both enzyme and whole-cell activity with established on-target mode of action. This has been achieved with greater speed and efficiency compared with the more traditional HTS initiatives and at significantly reduced cost and manpower.


Author(s):  
Conrad Stork ◽  
Gerd Embruch ◽  
Martin Šícho ◽  
Christina de Bruyn Kops ◽  
Ya Chen ◽  
...  

Abstract Summary The New E-Resource for Drug Discovery (NERDD) is a quickly expanding web portal focused on the provision of peer-reviewed in silico tools for drug discovery. NERDD currently hosts tools for predicting the sites of metabolism (FAME) and metabolites (GLORY) of small organic molecules, for flagging compounds that are likely to interfere with biological assays (Hit Dexter), and for identifying natural products and natural product derivatives in large compound collections (NP-Scout). Several additional models and components are currently in development. Availability and implementation The NERDD web server is available at https://nerdd.zbh.uni-hamburg.de. Most tools are also available as software packages for local installation. Contact [email protected]


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