Comparative Genomics in Drug Discovery

2007 ◽  
pp. 157-175
Author(s):  
James Brown
Keyword(s):  
Drug Discovery ◽  
Comparative Genomics

scholarly journals The antifungal pipeline: the need is established. Are there new compounds?

2020 ◽  
Vol 20 (4) ◽  
Author(s):  
Dongmei Li ◽  
Xiaodong She ◽  
Richard Calderone
Keyword(s):  
Clinical Trials ◽  
Drug Discovery ◽  
Comparative Genomics ◽  
Phase I ◽  
Antimicrobial Drug ◽  
Antifungal Drug ◽  
Temporal Development ◽  
Number Of Publications ◽  
New Compounds ◽  
Country Specific

ABSTRACT Our review summarizes and compares the temporal development (eras) of antifungal drug discovery as well as antibacterial ventures. The innovation gap that occurred in antibacterial discovery from 1960 to 2000 was likely due to tailoring of existing compounds to have better activity than predecessors. Antifungal discovery also faced innovation gaps. The semi-synthetic antibiotic era was followed closely by the resistance era and the heightened need for new compounds and targets. With the immense contribution of comparative genomics, antifungal targets became part of the discovery focus. These targets by definition are absolutely required to be fungal- or even lineage (clade) specific. Importantly, targets need to be essential for growth and/or have important roles in disease and pathogenesis. Two types of antifungals are discussed that are mostly in the FDA phase I–III clinical trials. New antifungals are either modified to increase bioavailability and stability for instance, or are new compounds that inhibit new targets. One of the important developments in incentivizing new antifungal discovery has been the prolific number of publications of global and country-specific incidence. International efforts that champion global antimicrobial drug discovery are discussed. Still, interventions are needed. The current pipeline of antifungals and alternatives to antifungals are discussed including vaccines.

scholarly journals In silico Methods for Identification of Potential Therapeutic Targets

2021 ◽  
Author(s):  
Xuting Zhang ◽  
Fengxu Wu ◽  
Nan Yang ◽  
Xiaohui Zhan ◽  
Jianbo Liao ◽  
...  
Keyword(s):  
Big Data ◽  
Drug Discovery ◽  
Comparative Genomics ◽  
Infectious Diseases ◽  
Computational Methods ◽  
In Silico ◽  
Therapeutic Targets ◽  
Full Potential ◽  
Advantages And Disadvantages ◽  
In Silico Methods

AbstractAt the initial stage of drug discovery, identifying novel targets with maximal efficacy and minimal side effects can improve the success rate and portfolio value of drug discovery projects while simultaneously reducing cycle time and cost. However, harnessing the full potential of big data to narrow the range of plausible targets through existing computational methods remains a key issue in this field. This paper reviews two categories of in silico methods—comparative genomics and network-based methods—for finding potential therapeutic targets among cellular functions based on understanding their related biological processes. In addition to describing the principles, databases, software, and applications, we discuss some recent studies and prospects of the methods. While comparative genomics is mostly applied to infectious diseases, network-based methods can be applied to infectious and non-infectious diseases. Nonetheless, the methods often complement each other in their advantages and disadvantages. The information reported here guides toward improving the application of big data-driven computational methods for therapeutic target discovery. Graphical abstract

Sign in / Sign up

Export Citation Format

Share Document