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12 Experimental Assays: Chemical Properties, Biochemical and... 367
predictions aiming to prioritize which inhibitors or potential repurposing drugs
would be experimentally validated in vitro and ultimately tested in vivo [309, 310].
6 In Vivo Evaluation of Compounds
In general, in vivo evaluation is the third step of a pipeline for bioactive compounds
screening (in silico, in vitro, and in vivo, respectively) [311]. The most widely used
experimental models used for in vivo assays are mice, used to validate in vitro tests
and observe efficacy in whole organisms. This model has advantages such as fast
procreation, low cost, easy maneuver and care, the option for using inbred or outbred
animals, the possibility of knock-in and knockout animals, and a diversity of
background options for making them susceptible for human infectious diseases
[312, 313]. Similar to in vitro assays, toxicity should be assessed in vivo, which
translates to assessing lethal dose of 50% (DL
chosen animal model, usually by assessing different compound or drug concentrations (mg/kg) tolerated by the animal. Afterwards, one should determine or choose
the most suit able concentration range as well as the pathogens’ infection parameters
[314, 315].
In this sense, regarding a compound concentration, solubility may play a key role
in oral absorption, as poor aqueous solubility may be decisive in drug discovery
studies, including in translating in vitro to in vivo [316] and different experimental
evaluation approaches [317], potentially requiring another round of lead optimization or failing a given drug candidate [318]. PK modeling based on validated data
may help with many different approaches and their implications regarding aqueous
solubility, including temperature, pH-dependency, and ultimately bioavailability
[136, 318]. As for pathogens, researchers can also use mouse models for analyzing
infection effects directly and indirectly. These models can be used for testing drug
protection against lethality, or to test mitigation of an infection and/or disease by a
given compound or drug, thus evaluating the animal response or reestablishment
against an infection [319, 320]. Different mice and other murine models can be used
for specific pathogenic infections or can be standardized in the laboratory. Herein,
one should consider a variety of parameters such as pathogen inoculum, route of
infection, clinical score of disease, difference between genetic backgrounds, age and
gender, and the necessity of genetic modification to make the animal susceptible for
a specific infectious disea se [235, 321].
Notwithstanding, even if solubility and infection issues are overcome, compounds that are correctly predicted for a given target should still be validated
concerning their ability to ultimately display the desired activity, while also permeating cell membranes or tissue barriers [228]. Predictions in this sense should also
consider the specificity and stability of compounds, as well as previously assessing
predictions for the potential ADMET and PK properties [18]. Despite the fact that
ADMET simulations are more directed at translating in vitro experimentally determined effect to in vivo [317], they also aim to potentially increase the success rate of
) or tolerability assays of drugs in the
50
368 M. Sá Magalhães Serafim et al.
predicted hits as favorable compounds for optimization, which could ultimately
reach a potential lead candidate and become a drug [202]. These aspects are
important to reduce the risks in the late drug discovery stages and also optimize
the bridging between computational simulations, and experimental validations,
focusing on promising compounds [322].
7 Conclusions
Considering the field of drug design and discovery, the search for novel drugs
requires a lasting effort to tackle long known, emerging, or re-emerging diseases.
The focus on targets of interest, such as enzymes, may be a starting point for
discovery campaigns. In this sense, designing and develo ping potential inhibitors
and lead drug candidates should account for PK and ADMET, as well as cytotoxicity. Moreover, if related to an infectious disease, as in the search for antivirals,
antibacterials, and antifungals, it is essential to focus on selectivity and specificity.
Here, the combination of in silico, in vitro, and in vivo approaches is an important
triad to any drug discovery campaign that can encompass compounds’ chemical
properties, biochemical and cellular assays, and in vivo evaluation to reach a
successful drug candidate. Although challenging, many options are available to
translate different computational simulations into various experimental validations.
Examples include the discovery of some protease inhibitors, such as nirmatrelvir,
and recently ensitrelvir, successfully obtained by combining computer-aided
approaches and experimental assays. Herein, we discussed the possibilities and
feasibility, challenges and pitfalls, and the current scenario of such computational
approaches that, especially when combined, may contribute to a successful protocol
in drug discovery.
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