After a long pause, the adventure in the PERL programming language series continues with another example of biophysics and molecular biology science application.This time, we are going to make a program to model the effect of the temperature on DNA stability in solution.
The effect of temperature DNA structure integrity plays an important role in molecular biology applications. For example, the DNA amplification method based on polymerase (the PCR method) is based on a series of temperature cycles to separate the two strand of DNA to replicate. DNA primers are used to initiate the process and the knowledge of their melting temperature (Tm) play an important role in optimizing the DNA amplification process.
The first attempts to create a model of DNA thermodynamics date back to the beginnings of 1960. Studies pionered by the groups of Zimm [1] and Tinoco [2], have shown that the relative stability of a double-stranded DNA molecule depends primarily on the nature of the nearest-neighbor bases along the sequence. This finding brought to the formulation of a simple mathematical model (called the nearest-neighbor (NN) model) to predict relative stabilities of double stranded DNA according to the nucleotide sequence [see Cantor]. Subseguently, the NN model was further improved by the contribution of several research groups. In particular, Santalucia and co-workers. proposed a set of parameters for the NN model that provides an excellent prediction of the thermodynamic properties of short DNA homo oligonucleotides and are commonly used to calculate the stability of DNA primers used for PCR applications.
In this third article on PERL programming, I will give some indication on how to implement a simple version of the NN model. To make more fancy the programming task, we are also going to provide the program with a simple Graphical user interface using PERL/Tk.
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, where N is the total number of electrons in the system. To overcome this problem, it was clear since the beginning that a reduction, by means of ad hoc approximations, of the description of the dynamic behavior of atoms, using a classic physics model would be necessary. In the classical representation, the electrons on the atoms are not explicitly considered but their mean-field effect is taken into account. The first simulation of an atomic fluid using this approximation was performed approximately 63 years ago by Alder and Wainwright (1957). They developed and used the method in order to study simple fluids by means of a model that represented atoms as discs and rigid spheres. These first pioneer studies mark the birth of the classical molecular dynamics (MD) simulation technique. The successive use of more realistic interaction potentials has allowed obtaining simulations comparable to experimental data, showing that MD can be used as a valid tool for surveying the microscopical properties of real systems. The first simulations of this type were carried out by Rahman and Verlet (1964): in these simulations, a Lennard-Jones type potential was used in order to describe the atomic interactions of argon in the liquid state. Another very important hallmark in this field was the simulation of the first protein (the bovine pancreatic trypsin inhibitor) by McCammon and Karplus in 1977. In the following years, the success obtained in reproducing structural properties of proteins and other macromolecules led to a great spread of the MD within the studies of structural biology. The continuous increase of computer power and improvement of programming languages has concurred to a further refinement of the technique. Its application was progressively expanded to more complex biological systems, comprising large protein complexes in a membrane environment. In this way, MD is becoming a powerful and flexible tool with application in disparate fields reaching from structural biology to material science.
-bonds. In this third article, we will apply the method to cyclic molecules and will derive some other useful properties. 
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