Homology modeling in drug discovery: Overview, current applications, and future perspectives

Abstract

Homology modeling is one of the computational structure prediction methods that are used to determine protein 3D structure from its amino acid sequence. It is considered to be the most accurate of the computational structure prediction methods. It consists of multiple steps that are straightforward and easy to apply. There are many tools and servers that are used for homology modeling. There is no single modeling program or server which is superior in every aspect to others. Since the functionality of the model depends on the quality of the generated protein 3D structure, maximizing the quality of homology modeling is crucial. Homology modeling has many applications in the drug discovery process. Since drugs interact with receptors that consist mainly of proteins, protein 3D structure determination, and thus homology modeling is important in drug discovery. Accordingly, there has been the clarification of protein interactions using 3D structures of proteins that are built with homology modeling. This contributes to the identification of novel drug candidates. Homology modeling plays an important role in making drug discovery faster, easier, cheaper, and more practical. As new modeling methods and combinations are introduced, the scope of its applications widens.

Engineering cytochrome P450 enzyme systems for biomedical and biotechnological applications

“…The availability of a tertiary protein structure is considered to be a major limitation in rational and semi-rational design, in that experimental structural information is not often available for the Ͼ370,000 P450 sequences. Homology modeling has often been used to bridge the "structure knowledge gap," based on the general observation that proteins with homologous sequences share similar structures (66,67). A well-known example of P450 semi-rational design for industrial application is the development of a highly efficient mutant of P450sca-2 involved in the production of pravastatin (68).…”

Ten quick tips for homology modeling of high-resolution protein 3D structures

“…The gap between the number of protein sequences and experimentally determined protein 3D structures is widening. A recent estimate of the number of discovered protein sequences was shown to be 736 times larger than the number of resolved protein 3D structures compared to previous estimate of 120 times in 2006 [5].…”

How Computational Chemistry and Drug Delivery Techniques Can Support the Development of New Anticancer Drugs

“…While LBDD is usually pursued when a significant number of molecules able to bind a given target is known [20], SBDD approach requires the knowledge of the three dimensional structure of the target. In the majority of the cases, the target structure is obtained by experimental techniques such as x-ray, NMR or Cryo-EM [21], however, the homology modeling technique can be used when the target structure is missing, but structures with sufficient level of homology (>25%-30%) are available [22].…”