Virtual molecules

De novo design approaches computationally generate virtual molecules based on protein active sites or simply just de noco-designed molecules [39]. 

Step4 Perform standard similarity searches against those explicit virtual molecules using the query molecule. 

The most common tool for discovering hits is library screening. The library may consist of traditional compounds with potentially high activity molecules, smaller fragments of less activity, or even virtual molecules tested through molecular modeling simulations. 

To validate the equilibrated receptor, its potency to predict free energies of binding (AGpiej) is examined. Therefore, classical QSAR methods such as cross-validation via leave-X%-out analyses and/or prediction of activity for an external set of compounds (test set) are accomplished. Since all QSAR models are typically constructed to predict properties of new or even virtual molecules, model validation with an external test set reflects reality best (unbiased or biased random selection of training set and test set ligands is supported by the software). 

The computer program PASS was designed to predict many kinds of biological activity simultaneously based on the structural formulae of chemical compounds. Thus, PASS may estimate the biological activity profiles for virtual molecules, prior to their chemical synthesis and biological testing. 

Evaluation of candidate compounds is the most critical step in de novo design. It is the duty of the fitness function to decide whether a composed virtual molecule is kept or discarded in deterministic algorithms. One must always be aware that it is the used fitness function that defines the search space for novel molecules. 

With the rapid improvement of computational power and algorithms, VS methods have become an important complementary technique to experimental uHTS. It has many distinct advantages, such as investigating virtual molecules that can cover a broader area of chemical space. Compared with uHTS, VS is also a relatively inexpensive means to probe many molecular structures. 

Molecular diversity Synthetic and virtual molecule libraries used in combinatorial chemistry and high throughput screening can only be efficient if they contain as much information as possible. The molecular diversity should be comparable to the diversity of natural compounds. The first combinatorial libraries were biased during screening toward large, hydrophobic molecules, which led to poor bioavailability and the rule-of-5. 

With today s computational resources it is usually not a problem to exhaustively search compounds from corporate collections, vendor libraries, or small combinatorial libraries, which typically range in the order of 10 -10 molecules. However, for large virtual combinatorial libraries and collections thereof it becomes quickly unfeasible to enumerate all possible virtual molecules in advance due to combinatorial explosion. Consequently, there has been an increasing interest in computational methods to find alternative ways to systematically search large virtual combinatorial libraries, allowing a dramatic expansion of unexplored chemical space. 

To effectively and efficiently propose the most appropriate molecules for synthesis, two key points should be considered by the project team exploration and exploitation. Exploration uses a molecular diversity measure to efficiently cover the space of virtual molecules with an even distribution of known properties. This leads to a high confidence that the entirety of the space is represented with as few molecules as necessary to demonstrate regions of specific interest This can be achieved using a wide variety of diversity selection algorithms [11]. Here, the question being asked is that of the entirety of the chemical space. 

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