Optimization Studies
5.2 SCREENING TOOLS IN DRUG DISCOVERY .1 High Throughput Screening in Drug Discovery
High throughput screening (HTS) is one of the leading technological break- throughs in drug discovery. The pharmaceutical industry strictly depends on HTS for generating hits from the explosive library of the compound data- base. The stepwise screening strategy tends to eliminate both compounds that fail the standard criteria and the probability of errors generated [5]. Ro- botic and automation technology permits handling of an enormously large number of compounds. Robotic liquid handlers are tailored technologies
for micropipetting at blistering speeds, well suited to over a million screen- ing assays conducted within 1–3 months. Since initial screens always need validation and optimizations for any drug discovery approach, the relevance or usefulness of HTS is not directly determined. In general, due to project complexity, a number of procedures and techniques confirm function and delivery of the right drug compound that is not directly attributable to HTS. An important part of cell-based HTS is high content screening, which has drawn interest because of its multiplexing ability and the efficiency in enabling detection of functional cell characteristics [6]. High throughput experimental technologies have stimulated increasing incorporation of the systems’ point of view in cellular and molecular biology, promoting the study cells as systems.
HTS has been instrumental to the empirical approach to drug discovery, which is based on trial and error but not on any prior known biological properties or mechanism of action. It has been dedicated to early drug discovery processes, but is now increasingly being integrated to down- stream processes of lead optimization, encouraging scientists and engineers to streamline workflows with reduced timelines [7]. The changing drug discovery program that incorporates parallel programs (which is shifting from the earlier sequential process of the past) allows much of the informa- tion generated to be utilized concurrently, and thus increases the number of compounds generated through robotic systems. The multidimensional workflow and use of low-volume assays underlie its cost effectiveness. In- creased miniaturization, through micro- or nanochip-based approaches and on-bead screening, has helped to expand its capabilities. Solid-sup- port-on-bead screening has reduced reactions to nanoscale levels, making it easier to process large datasets within a short period of time. Thus, high throughput screening is no longer a concern [8].
Larger databases provide a greater variety of options and more insight into possible leads during the critical stages of the discovery process. The timely access of information allows a more managed and distribution sys- tem. The statistical computations and algorithms are proven standards that permit better organization of HTS data for high performance [9,10].
Development of the Molecular Libraries Initiative, the Molecular Li- braries and the Screening Center Network, and eventually the Production Center Network was part of the National Institutes of Health Roadmap program strategy to advance chemical biology. This led to the setting up of translational- and chemical-screening programs at academic screening cen- ters in many US universities. All contributed to generating diverse chemical
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libraries and the development of novel chemistries based on HTS. These tools are indispensable in advancing understanding of complex biology for target and disease pathway identification and are well-validated potential medical therapies [11,12].
5.2.2 Setbacks in HTS Application
A known fact is the effectiveness of HTS in the discovery of new che- motypes in translational research, which has enabled the progression of compound optimization studies. But still, productivity decline has not been completely addressed. Sound performance of HTS also depends on the tar- get classes, which is very limiting as the broad screening approaches remain ineffective for certain subclasses like Class B G-protein-coupled receptors.
As a major contributor to finding drug leads, HTS has often been criti- cized for its “dead end” lead compounds [13,14]. Certain compounds in the HTS libraries are too complex, making it difficult to access the cellular protein targets for these compounds [15]. This is because not all the hits harbor the required structural features following the primary screening [16].
The problem of compound solubility in physical stability could limit HTS effectiveness.
In HTS, the number of hits multiplies with the number of compounds screened but since the budget for HTS is always limited to cover the cost for screening a huge number whole collection this could reach millions of compounds. The postgenomic era inspired technological novelty that led to a burst in the number of therapeutic targets, which are mostly large- molecule modulators. Heightening increase in cost of innovative thera- pies and tightening of budgets are continuing to shape policy decisions throughout the world. This has pressurized bio/pharmaceutical research and development (R&D) to actively generate new molecular entities as fully developed commercialized drugs [17].
5.2.3 Bioassays
Biological assays are biological experimental methods for screening poten- tial bioactive molecules for the identification of structural leads and the prediction of potentially useful pharmacological activity or therapeutic po- tential that informs compound development. These assays are often carried to assign biological properties to the compounds. The biologically active moieties are validated and then screened in series in more specific or sec- ondary assays.
Primary bioassays are the first line of screening that identifies possible bioactivity. These assays are usually high capacity, low cost, and rapid. Poten- tial drug targets in the form of recombinant proteins are expressed in these cells and then measured with linked secondary messenger systems in order to measure functional response. It is very useful in determining whether a drug is an agonist or antagonist at the target.
Cell-based assays are specifically used to detect a functional response [18]. It is generally applicable to selected target categories such as mem- brane receptors, ion channels, and nuclear receptors, and is mostly based on mammalian cell lines overexpressing the target of interest. These receptors have been shown as specific sites of action of the biochemical messenger systems. Primary cell systems are increasingly being employed for compound screening [19]. Cell-based assays offer the advantage associated with its applicability in evaluating human targets when the human cell systems are in use. If a drug exhibits a functional response, then biochemical assay is initiated. The functional assay can enable determination of efficacy, toxicity, and allosteric effectors (distant actors) in the primary screen. Challenges for cellular assays include the need to keep low dimethyl sulfoxide concentration and cell culture volume.
Identifying off-target activities would need additional exhaustive steps to rectify the problem.
Biochemical assays are focused on measuring the compound-target affinity. They also are applicable to both receptor and enzyme targets [20].
They do not provide any information on the pharmacological mechanism of the drug action, like determination of an inhibitory or stimulatory (agonists or antagonists) action but utility is based on the assumption that human binding activity will be equivalent at the native human target. The relevance becomes obvious when tested in functional in vitro or in vivo assays.
The use of cell-based and biochemical assays has been debated else- where [21]. Pharmacologists utilize bioassays to identify biological proper- ties of drug compounds under early development. As the discovery program progresses, from early exploratory research to clinical evaluation, the ex- periments become more extensive since the molecules become increasingly complex, and are scrutinized more intensely as the drug discovery cycle approaches the clinical stage. This is a time when a wide range of biophar- maceutical properties of the compound are optimized by the chemist re- quiring intact physiological systems and testing of absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties over the mas- sive data generated with combinatorial chemistry.
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5.3 IN SILICO MODELS IN DRUG DISCOVERY AND DESIGN