BIOINFORMATICS-Molecular visualization –use of Rasmol

Molecular visualization –use of Rasmol

RasMol is a molecular structure –viewing program developed by Roger A.Sayle in 1993 at the University of Edinburgh’s Biocomputing research Unit,UK. The name Rasmol is derived from Raster (the array of pixels on a computer screen) Molecules. RASMOL is a free software that can diplay proteins and organic molecules. It has a powerful scripting language and simple visual display. One can visualize proteins in wireframe, ribbons, cartoons, or space-fill mode. Rasmol is aimed at display, teaching, and generation of publication quality images. Rasmol interactively diaplays molecule on the screen ina variety of color schemes and representations. The displayed molecule can be rotated, translated, zoomed, z-clipped interactively using either the mouse or the scroll bars. Rasmol is available in multiple platforms: UNIX, windows, and Mac. RasTop is a new version of RasMol for windows with a more enhanced user interface. Irrespective of the chemical nature of the molecules RasMol can get details of simple to complex compounds

HOMOLOGY MODELLING OF PROTEIN AND STRUCTURE PREDICTION

HOMOLOGY MODELLING OF PROTEIN AND STRUCTURE PREDICTION

Protein structure prediction

The aminoacid sequence of a protein determines its three dimensional structure. If the structure of a protein is known, it would be easier for the biologist to tell the function of the protein. As the protein sequences are relatively easy to obtain, it is desirable that a protein’s structure can be decided from its sequence through computer analysis.

Aminoacid sequence of a protein is called its primary structure. Hydrogen bonding of the molecules results in certain substructures called the secondary structure. Interactions between secondary structures assemble them into them tertiary and quaternary structures. As preliminary step to protein structure prediction scientists have devised a stepwise approach ie. Primary  --- > secondary--àtertiary structure. The second approach applies the principle of physics related to the forces between different molecules of protein. Angle constraints of the chemical bonds are used to find the optimal solution of the angles and the tertiary structure can be decided.

Secondary Structure Prediction

Secondary structural elements are formed due to repeated occurrence of weak hydrogen bonds in protein. Secondary structure prediction focuses on segments of the primary sequence which form helices and strands of sheets. There are 4 types of sec. structure elements to predict secondary structure. They are namely,   α helix,   β sheets,   β turns and Random coils.  Α Helix is a spiral shaped sheet consisting one form of the secondary structure of proteins.  β Sheet is a zigzag shaped structure of protein.  β Turns are part of protein chain which suddenly changes direction. A sequence of 4 aminoacids residues which change direction of the polypeptide chain is called   β turn.  Coils are also called loops.

 The main goal in secondary structure prediction of protein is to take primary structure and tertiary structure of protein with known structures to develop general rules. These rules can be used to predict the final structure of other proteins using only the primary sequences.

Some of the notable software used for the secondary structure prediction are  PHD,  PSI_PRED, PREDATOR, and JPRED

Tertiary Structure Prediction

Amino acid sequence of proein folds in space until it reaches a three dimensional configuration known as tertiary structure. The tertiary structure of protein greatly influences its biological function. Prediction of three-dimensional structure of a protein from its amino acid sequence is known as tertiary structure prediction. Accurate secondary structure prediction is a key element in the prediction of tertiary structure. The different strategies involved in 3D protein structure prediction are;1. Comparative modeling 2. Fold recognition or threading 3. Ab Initio prediction

1.      Comparative modeling or homology modeling

Comparative modeling uses experimentally determined protein structures as models (templates). This method predicts the structure of another protein that exhibits amino acid sequence similarity to the template protein. Evolutionarily related proteins with similar sequences have similar structures. The similarity of structures is very high in core regions. Protein structures can be predicted if sequence similarity is about or above 35%

2.      Fold recognition or threading

This method is useful to determine the structure of unrelated proteins that share some amount of structural similarity. It has been estimated that total number of possible protein folds is about 1000. If the 3D structure of all the folds is known, it should be possible to predict the fold of any given amino acid sequence.  The sequence is simply aligned in 3 d on each of the folds. Each of the fits is scored and the best score indicates the correct fold. The process is known as threading.

3.      Ab Initio prediction

Ab initio structure prediction seeks to predict the native conformation of protein from the amino acid sequence alone. It includes molecular dynamics (MD) simulations of proteins and protein-substrate complexes provide a detailed and dynamic picture of the nature of interatomic interactions with regards to protein structure and function. The folding of the protein sequence is ultimately determined by the physical forces acting on the atoms on the atoms of the protein. Successful structure prediction requires a free energy function sufficiently close to one of the lowest free energy minima. The predicted structure can be validated using PROCHEK, WHATCHECK etc. The Ramachandran plot for the 3D structure is used to finally confirm stability based on the free energy of protein structure.