Molecular docking is the process that involves placing molecules in appropriate configuration to interact with a receptor. Molecular docking is a natural process which occurs within seconds in a cell. In molecular modelling the term molecular docking refers to the study of how two or more molecular structures fit together.

PROCESS OF MOLECULAR DOCKING
Taleh Munir
Taleh Munir

Process Of Molecular Docking 

Keywords: Molecular Docking, Molecular Modelling, Bioinformatic, Modern Drug Discovery, Applications Of Computational Chemistry Tools, Interaction Of Two or More Molecules, Understanding Molecular Recognition, The Lock and Key Theory, The Induced Fit Theory, The Conformation Ensemble Model

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Molecular docking is the process that involves placing molecules in appropriate configuration to interact with a receptor. Molecular docking is a natural process which occurs within seconds in a cell. In molecular modelling the term molecular docking refers to the study of how two or more molecular structures fit together.

Molecular docking is a kind of bioinformatic modelling which involves the interaction of two or more molecules to give the stable adduct. Depending upon binding properties of ligand and target, it predicts the three-dimensional structure of any complex.

 

Molecular docking is an invaluable tool in modern drug discovery. This review focuses on methodological developments relevant to the field of molecular docking. The forces important in molecular recognition are reviewed and followed by a discussion of how different scoring functions account for these forces. More recent applications of computational chemistry tools involve library design and database screening.

Understanding Molecular Recognition:

Understanding the principles of molecular recognition at the molecular level is essential to a good understanding of molecular function and biological function. Knowledge of the novel therapeutic agents.

Understanding the principles whereby macromolecular biological receptors can recognize small molecule substrates or inhibitors is the subject of a major effort. This is of paramount importance in rational drug design where the receptor structure is known (the “docking” problem).

Understanding the principles of molecular recognition at the molecular level is essential to a good understanding of molecular function and biological function

Over the year’s biochemists have developed numerous models to capture the key elements of the molecular recognition process. Although very simplified, these models have proven highly useful to the scientific community.

Over the years biochemists have developed numerous models to capture the key elements of the molecular recognition process

Molecular Docking Models:

In 1890 Emil Fisher introduced the lock-and-key model. In 1958 Daniel Koshland proposed the induced-fit model. In 2003 Buyong Ma et al. proposed the Confirmation Ensemble.

The Lock and Key Theory:

As far back as 1890 Emil fisher proposed a model called the “Lock-and-Key model” that explains how biological systems function.  Substrates fit into the active site of a macro molecule, just like a key fit into the lock. Biological ‘locks’ have unique stereochemical features that are necessary to their function.

As far back as 1890 Emil fisher proposed a model called the “ Lock-and-Key model” that explains how biological systems function

The Induced-Fit Theory:

In 1958 Daniel Koshland introduced the “induced-fit-theory”. The basic idea is that in the recognition process, both ligand and target mutually adapt to each other through small conformational changes, until an optimal fit is achieved.

In 1958 Daniel Koshland introduced the “induced-fit-theory

The Conformational Ensemble Model:

In addition to small induced-fit adaptation, it has been observed that proteins can undergo much larger conformational changes. A recent model describes proteins as a pre-existing ensemble of conformational states. The plasticity of the protein allows it to switch from one state to another.

These methods depend on using multiple input receptor conformations into docking programs. Many studies have now demonstrated that using an ensemble approach is superior to a single receptor conformation input. However, the main shortcoming of these approaches is a lack of a broadly applicable protocol for a priori selection of the most predictive structures. Furthermore, even the issue of how many structures should be included into an ensemble for its optimal performance has not yet been resolved.

However, the main shortcoming of these approaches is a lack of a broadly applicable protocol for a priori selection of the most predictive structures
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