Computational Chemistry: Recent Trends

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In the contemporary times, understanding the technicalities of chemical analysis which includes Information regarding the properties of molecules or simulated experimental results defined for solving practical chemical problems, in all of these, computational chemistry plays an extremely pivotal role for deriving fundamental knowledge on various chemical aspects related to practical day to day problems. Various computer software are being used for computational chemistry such as Spartan, MOPAC, Sybyl etc having ability for simulating large chemical problems involving laborious mathematical calculations and Research analysis.

Computational Chemistry exhibits a plethora of applications derived from day to day life situations. For instance, the schrodinger equation is the basis for most of the computations that physical chemistry incorporates. It becomes extremely difficult to accurately determine the electronic structure determinations, geometry optimizations etc. Using computational chemistry, solutions to various practical problems can be easily achieved. Computational chemistry is also widely used in the pharmaceutical industry to explore the interactions of potential drugs with bimolecular, for example by docking a candidate drug into the active site of an enzyme. It is used to investigate the properties of solids (e.g. plastics) in materials science, and to study catalysis in reactions important in the lab and in industry. (Lewars and Errol, 2003).

Generally two approaches are implied in computational chemistry which includes ab-initio methods based on quantum mechanics, attempting the rigorous and non-empirical evaluation of various terms employed.  The other branch, semi-empirical methods, avoids even attempting the evaluation of the integrals involved; instead they are replaced with approximations (Schleyer and Paul, 1998). Ab-initio is a group of methods in which molecular structures can be calculated using nothing but the Schrodinger equation, the values of the fundamental constants and the atomic numbers of the atoms present (Atkins et. al, 1991). Similarly, semi-empirical techniques use approximations from experimental data to provide the input into the mathematical models. Ultimately, the contribution of each of these in solving computational chemical problems is infinitely many and one cannot be realized without the presence of the other.

However, a lot of disadvantages pertain to the use of computational chemistry. Ab-initio method though is widely used for a broad range of systems; however, It does not depend on experimental data and provide pre-determined results in calculating of transition and excited states (Froudakis and Georg, 2002). On the other hand, semi-empirical methods are less rigorous and computationally less demanding than ab-initio, being simple and primitive to use. Recently, a third approach for understanding the basis of computational chemistry is being followed through molecular mechanics as it may be defined as the fastest mode of computation and region-specifically used for molecules as large as enzymes.  Having ability for solving various problems related to the conventional approaches, this may be extremely helpful for achieving undetermined results in the field of computation chemistry in the near future.

In recent years, advances in computer visualization capabilities make it possible for computational experts for drawing viable conclusions obtained from experimental results; along with the ability to present the complex analyses in readily understandable manner is yet another challenge for research analysts. Be it pharmaceutical industry, medicare , chemical or bio informatics all of these employ heavy computational procedures and calculations for achieving the objectives as specified. Undoubtedly, the digital computer being the instrument of the ‘computational chemist’, workers in the field have advantage of this progress to develop and apply new theoretical methodologies at a similarly astonishing pace and this is likely to be achieved in the near future using the art of ‘computational chemistry’ ( Cramer and Christopher, 2013)

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