Image by Pexels from Pixabay

The process to develop a new ingredient is long and expensive, whether it’s for a cosmetic, nutraceutical, or pharmaceutical ingredient.

The first task in the development process is the identification of the target. The ingredient to develop will cause the desired effect by blocking or activating this target. Once the target is identified, starts the phase to look for candidate compounds that have activity on the target. These candidate compounds have to be subsequently tested, using in vitro techniques and in volunteers, until their approval and arrival on the market.

How long does a new ingredient take to develop?

The process of developing a new drug is the longest one, it can last from 10 to 14 years. While the design of new cosmetic or nutraceutical ingredients usually takes two or three years. But it takes around 5 years for the final product, which contains that ingredient, to reach the market.

The first step in designing a new ingredient is to identify the molecules or compounds that will interact with the chosen molecular target. This long list of candidate molecules (thousands), it is then limited to hundreds for in vitro testing. This first screening, needs the use of molecular models to predict the affinity of each candidate compound for the target molecule.

ingredient development timeline

By studying the possible interactions that can occur with the molecular target, we can obtaine thousands of candidate sequences or compounds that are likely to be the chosen ingredient. All of this is possible thanks to the large amount of information available, such as genomic, epigenetic, genomic architecture, transcriptome, proteomics and ribosomics’ data [1].

The discovery of candidate compounds and the selection of the most related ones for their in vitro study involves a great deal of computational modeling work. With this work the best interactions between a certain compound and the molecular target are identified using virtual chemical libraries that identify active compounds by molecular docking.

Molecular docking analyses the conformation and orientation of candidate molecules at their target binding site. To perform this analysis, it is necessary to obtain the three-dimensional structure of the target molecule [2]. However, on many occasions, this structure is not available in 3D, so it is necessary to use predictive methods in order to obtain this structure. Here again, using molecular modeling techniques, a predictive three-dimensional structure can be achieved using the sequence of the target and comparing with known and similar structures in sequence [3].

Once the three-dimensional structure has been obtained and the coupling analysis has been performed, the candidate compounds are classified based on binding energy, free energy or a qualitative numerical measure to approximate the interaction energies between target and candidate [4].

This classification selects the best candidates to proceed to the validation phase, which consists of a first phase of preclinical studies and later in volunteers (clinical phase).

Image by Moo YuenSheng from Pixabay

Search for functions of natural extracts

Natural products have focused the discovery of new active ingredients in recent years, especially in the cosmetic and nutraceutical industry. Natural products are not only those based on plants, but their scope has been extended to ingredients derived from marine organisms, exotic or microorganisms.

Natural products have served as the basis for the development of many synthetic compounds [5] and their biological properties are often based on studies in traditional medicine. The natural extracts are titled in an active ingredient that is the one providing the activities or claims. These activities can be redirected thanks to the use of virtual chemical libraries through computational design.

The computational or in silico design allows to develop the potential of a synthetic or natural compound on its target. In the same way, we can configure and develop the potential of candidate molecules and qualify the predictions of interaction between molecules that already exist in nature [6].

The most common method to search for natural extract functions is the use of virtual chemical libraries. Knowing the ingredients of the natural extract we can select them in these libraries and thus, study the interaction of these compounds with the desired target. This study includes the sampling of various conformations of flexible molecules and the calculation of the interaction energy in a specific environment [7].

Giving new life to known molecules

The molecular modeling also allows the redirection of already designed ingredients. By redesigning molecules we can search for new actions or activities that are complementary to those that the molecule already have.

This is the case of proteins, their redesign entails a conformational change after the binding of a ligand, and presents a range of new biotechnological applications [8] that can be very interesting in the field of cosmetics and nutraceuticals.

In the same way, there are certain biological processes mediated by proteins such as the interaction between proteins, between protein and ligand or enzymatic activities, which can be studied by computational design. The specificity of an interaction can be measured by calculating the energy between the molecules that compose the interaction. The tools to redesign the specificity of an interaction allow us to manipulate complex and regulatory cellular networks [8], and provide new functions to known molecules, giving them a second life in the market.

Image by WikimediaImages from Pixabay

Artificial intelligence for computational design

Computational design allows several activities; from the design of new molecules from scratch, to the repositioning of already known ingredients, giving them a second life in the market. Molecular modeling is not limited only to the design of synthetic molecules, it is also possible to determine new functionalities in plant extracts or new natural products.

The possibilities of computational design will increase as our knowledge and use of artificial intelligence advances, which will further reduce the time and costs of developing pharmaceutical, nutraceutical or cosmetic active ingredients.

References

  1. Xia X. Bioinformatics and Drug Discovery. Curr Top Med Chem. 2017;17(15):1709-1726.
  2. Torres, P.H.M.; Sodero, A.C.R.; Jofily, P.; Silva-Jr, F.P. Key Topics in Molecular Docking for Drug Design. J. Mol. Sci. 2019, 20, 4574.
  3. Liu, Y.; Zhang, Y.; Zhong, H.; Jiang, Y.; Li, Z.; Zeng, G.; Chen, M.; Shao, B.; Liu, Z.; Liu, Y. Application of molecular docking for the degradation of organic pollutants in the environmental remediation: A review. Chemosphere 2018, 203, 139–150.
  4. Makhouri, F.R.; Ghasemi, J.B. Combating Diseases with Computational Strategies Used for Drug Design and Discovery. Curr. Top. Med. Chem. 2019, 18, 2743–2773.
  5. Arun H.S. Kumar. Rediscovering the drug discovery with natural products as therapeutic tools. J Nat Sci Biol Med. 2018 Jan-Jun; 9(1): 1.
  6. Grabenhofer R. 6 New Trends in Cosmetic Technology. Cosmetic Technology. April 17, 2018.
  7. Brian K. Shoichet. Virtual screening of chemical libraries. 2004 Dec 16; 432(7019): 862–865.
  8. Suarez M., Jaramillo A. Challenges in the computational design of proteins. J R Soc Interface. 2009 Aug 6; 6(Suppl 4): S477–S491.