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In Vitro Models for Preclinical Drug Development
Published in Hyun Jung Kim, Biomimetic Microengineering, 2020
Jason Ekert, Sunish Mohanan, Julianna Deakyne, Philippa Pribul Allen, Nikki Marshall, Claire Jeong, Spiro Getsios
Safety and toxicity testing after identifying a series of leads or a lead compound typically involves a series of in vivo animal studies to assess mechanisms such as carcinogenicity, genetic toxicity, safety pharmacology, and immunotoxicology. There is, however, considerable in vitro and in silico work that occurs before and during in vivo testing. Cytotoxicity screening for cell health parameters can be implemented using 2D cell cultures and is suitable for high-throughput systems; however, to more faithfully recapitulate the complexity of cellular, or organ, systems, CIVMs are required to understand the mechanistic processes and more accurately predict toxic responses. Ad hoc investigations can also be undertaken to support toxicity findings in preclinical as well as clinical studies. In line with the overall drive in pharmaceutical development for in vitro and in silico alternatives to support the 3Rs (replacement, refinement, and reduction), CIVMs can be used in the safety space. In addition, the ability to carry out human in vitro modeling enables the generation of human safety data prior to clinical trials, which is particularly beneficial for immune-related targets for which preclinical safety testing in rodents and dogs will not generate species relevant toxicity data.
Drug Discovery in Microbial Metabolites: The Search for Microbial Products with Bioactive Properties
Published in Nduka Okafor, Benedict C. Okeke, Modern Industrial Microbiology and Biotechnology, 2017
Nduka Okafor, Benedict C. Okeke
The search for antimicrobial compounds and other drugs can nowadays start on the computer, i.e. in silico. New drugs can be created on the computer and their efficacy determined through assessing whether or not they will bind to proteins on ‘pathogenic microorganisms’ or ‘diseased tissues’. Drug discovery and development is immensely expensive and time-consuming. The success rate of new chemical entities selected for clinical development is approximately 20% with most failures attributed to unacceptable pharmacokinetic properties. Undesirable properties, such as poor absorption, low and variable bioavailability, and drug interactions may be predicted from in vitro and in silico data, thus facilitating selection of the most appropriate lead compound. The in silico approach is not only rapid, but it is also cost-effective. The successful in silico antibiotic or drug must then be tested in the wet laboratory using in vitro and in vivo methods as required by regulatory agencies discussed later in this chapter. Perhaps the best example of in silico drug development is the development of inhibitors of HIV-1 protease by computer- aided drug design. HIV-1 genome encodes an aspartic protease (HIV-1 PR). Inactivation of HIV-1 PR by either mutation or chemical inhibition leads to the production of immature, noninfectious viral particles. Thus, the function of this enzyme was shown to be essential for proper virion assembly and maturation. Therefore, HIV-1 PR was identified over a decade ago as the prime target for structure- or computer-assisted (sometimes called ‘rational’) drug design. The structure-assisted drug design and discovery process utilizes structural biochemical methods, such as protein crystallography, nuclear magnetic resonance (NMR), and computational biochemistry to guide the synthesis of potential drugs. This information can in turn be used to help explain the basis of their activity and to improve the potency and specificity of new lead compounds.
Response Surface Designs
Published in John Lawson, Design and Analysis of Experiments with R, 2014
Structure Activity Relation) used in drug design. In this type of study, when a lead compound is discovered with desirable bioactivity, many derivatives of this compound are considered in an attempt to find one that will increase the desired effect. For example, Figure 10.12 shows the general structure of hydroxyphenylureas, which have been shown to be active as antioxidants.
Molecular modeling strategy to design novel anticancer agents against UACC-62 and UACC-257 melanoma cell lines
Published in Egyptian Journal of Basic and Applied Sciences, 2023
Abdullahi Bello Umar, Adamu Uzairu
In drug discovery research, the identification and validation of lead compounds and the determination of active binding sites of biological targets related to a particular lead compound performed through wet lab experiments are pretty expensive and time-consuming [10]. Computational approaches effectively reduce the time required to obtain valuable drugs and decrease their associated economic costs, making it possible to propose new potential drugs with low expenditures and selective targeting [11,12]. Quantitative structure–activity relationship (QSAR) modeling is an example of an in silico method, which can be used to understand drug action, design new compounds and screen chemical libraries [13,14]. QSAR studies have been used to identify important structural features responsible for the anticancer activity of drugs [15]. Quantitative structure–activity relationships are a significant factor in drug design; consequently, it is quite evident why many users of QSAR [16,17] are located in industrial research units. Combinatorial approaches are an influential tool in selection to speed up drug discovery, and with different mechanisms of action, this method is being adopted to cure cancer [1,18]. Molecular docking is an exceptional computational technique for screening a huge chemical library to detect prospective chemicals that could be used to discover the binding capability for a particular target. In the last two decades, molecular docking has become the model of structure-based virtual screening of several chemical databases [16, 19]. It is widely used to determine the proper orientation of drug molecules in the protein active site and their binding affinity. Previously, extensive molecular docking studies were conducted to explore the biological activity of many chemical materials [16,19]. It is widely used to determine the proper orientation of drug molecules in the protein active site and their binding affinity. Previously, extensive molecular docking studies were conducted to explore the biological activity of many chemical materials [19–21]
Sombor indices of γ-sheet of boron clusters
Published in Molecular Physics, 2023
Eshrag Ali Refaee, Ali Ahmad, Muhammad Azeem
Drug design: By foreseeing the activity and toxicity of potential compounds, Sombor indices can be utilised to create new medications. They have been utilised in lead compound optimisation to enhance their characteristics as well as in the virtual screening of sizable databases of compounds to uncover prospective therapeutic candidates [49].