A review on density functional theory to biological system
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a review on density functional theory biological system
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Density functional theory (DFT) is a quantum-mechanical (QM) method used in chemistry and physics to calculate the electronic structure of atoms, molecules and solids. It has been very popular in computational solid-state physics since the 1970s. However, it was not until the 1990s that improvements to the method made it acceptably accurate for quantum-chemical applications, resulting in a surge of applications. The real forte of DFT is its favourable price/performance ratio compared with electron-correlated wave function-based methods such as Møller–Plesset perturbation theory or coupled cluster. Thus, larger (and often more relevant) molecular systems can be studied with sufficient accuracy, thereby expanding the predictive power inherent in electronic structure theory. As a result, DFT is now by far the most widely used electronic structure method. The huge importance of DFT in physics and chemistry is evidenced by the 1998 award of the Nobel Prize to Walter Kohn ‘for his development of the density-functional theory’ [1].
Nevertheless, even though DFT is an exact theory in principle, its approximate variants currently used are far from being fail-safe. Validation of these approximations is an important part of ongoing research in the field. New pitfalls are being discovered constantly, and there are still problems in using DFT for certain systems or interactions. One such fundamental problem that has become increasingly apparent as the systems that could be treated have become larger is the description of dispersion. A seemingly weak interaction per se, dispersion is omnipresent and can add up to a substantial force in large assemblies of atoms and molecules. It thus becomes very important in systems ranging from biomolecules to the areas of supramolecular chemistry and nanomaterials. However, in particular over the last decade, several new DFT approaches have been developed to overcome these problems. These range from highly parametrized density functionals to the addition of explicit, empirical dispersion terms. Research into this area (including the development of new functionals as well as assessment studies of these) continues to be very active.
The speed of DFT can also be exploited to perform very many energy and gradient calculations for a system to study its time evolution. DFT-based molecular dynamics (MD) methods, such as Car–Parrinello MD (CPMD [2]) and Born–Oppenheimer MD (sometimes collectively called ab initio MD, AIMD), have enjoyed a rapidly increasing popularity in the past decade, and are now ‘routinely’ applied in many areas of chemistry, physics, material and biomolecular sciences. Fully classical MD simulations based on inexpensive empirical force fields have long been a stronghold of biomolecular sciences. The DFT-based variants have the added benefit of higher predictive power beyond the validity of a bespoke force field and open the possibility to study chemical reactivity from first principles. DFT-based MD simulations allow a more realistic description of molecular systems and chemical processes, with a full description of dynamical ensembles at a given temperature, thus mimicking actual experimental conditions ever more closely. Large and complex condensed phase molecular systems can be investigated with AIMD, typically molecules immersed in solvents or infinite periodic surfaces in contact with solvents. To expand the length and time scales accessible with first-principles MD remains a challenge and a topical area of research in years to come.