Editorial
Current Topics in Medicinal Chemistry, 2015, Vol. 15, No. 1
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Editorial Mechanistics in Drug Design - Experimental Molecular Biology vs. Molecular Modeling Discovery and design of new life saving drugs has been crest of private and public investment transpired in life sciences research. Researchers from every corner are generating the necessary thrust to make drug discovery process even faster, cheaper and more successful. Experimental molecular biology (Biology) and computational molecular modeling (Computing) are two parallel streams contributing to the thrust long awaited in drug discovery research. The twenty-first century is going to experience new research upshots in the area of system biology which encompasses study of structure of integral components of cell, their interactions with each other and functional outcomes of such interactions all together [1]. Life-sciences aim to gather even deep insights of molecular mechanisms of life. Though computing has been used in biology for many years toward qualitative and quantitative analyses, probability distribution and classification; molecular modeling enforces particularly molecular mechanics and molecular dynamics part of computing. Rapid rise in computing capacity and technology is a strong indication of future sophisticated symbiosis between experimental biology and molecular modeling. Molecular biology is the study of the structure and the function of the components of a cell, such as the proteins and nucleic acids [2]. The major concerns of the subject are to understand the relationships between such cellular components and also to determine their activity which compels the cells to behave in a particular fashion. On the other hand molecular modeling is that discipline which deals essentially with designing such cellular macromolecules by utilizing modern computational techniques to identify either the relationship between them or to pin-point the problems in their relationships or structural or functional tribulations in any of such singular or group of macromolecules, which quite possibly relate to a disease or a malfunction of the body [3]. With respect to its application in drug designing, molecular biology has essentially proven to be of immense usage. While in the past century, the process of drug discovery and designing did not quite mandate the know-how of the drug target and was based on the pharmacological properties of the drug compounds, in the present century the drug discovery is more concerned with the evaluation and validation of the target-which usually are the proteins, cellular receptors and even genes. So, the very first step of drug designing- namely target evaluation and validation is based on molecular biology techniques. The Human Genome Project (HGP) has widened the possibility of finding a better target for the disease under investigation by increasing the number of targets from a handful to many [4]. Furthermore, the DNA microarray technology has offered the identification of even a single genetic dysfunction, which allows the investigators to recognize the subtle molecular derangements which could essentially be the cause of a disease [5]. Imaging techniques such as the X-ray crystallography, Nuclear Magnetic Resonance (NMR), Mass spectroscopy and Surface Plasmon Resonance (SPR) have also enabled investigators to obtain a sketch of the proteins and receptors intended to be used as potential drug targets. Any protein whose 3D dimensional structure is required to be identified as a drug target may be imaged and subsequently studied by the help of X-ray crystallography [6]. Bioinformatics is another molecular biology technique which has been profusely used since the beginning of this century to transfer immensely large amount of data to be transferred with ease and reliability [7]. Driven by equivalent fundamentals of biophysics, mechanistics of experimental biology (In vitro and In vivo) and molecular modeling (In silico) differ in systems where calculation process occurs. Experimental biology is considered as more accurate, reliable and decisive wherein molecular modeling is estimation, probability driven and largely supported by efficiency of mathematical execution of biophysical laws. Protein structure modeling, molecular docking, molecular dynamics or simulations are few of the examples of main stream approaches used in molecular modeling. The gap between experimental biology and molecular modeling is defined by our limits of understanding of biophysics of cellular components and their interactions with each others. Better and deeper knowledge of system biology from experimental biology will definitely help us to upgrade computing ability in molecular modeling. Conclusively, experimental biology and molecular modeling are in symbiotic relationship. The information retrieved from experimental biology helps to upgrade calculation, estimation and validation capacity of molecular modeling which in turn contributes back in unveiling of experimental biology problems. Free energy calculation of biological interactions (small molecules, proteins and nucleic acids) with accuracy, efficiency and within a short time frame is holding the key to open the overlapping interface on two distinctive shores of experimental biology and molecular modeling [8]. A specific field in molecular modeling has been setting new targets to simulate and analyze bio-molecules in proximity of cellular environment. The present differences between these two fields are expected to dissolve sooner. The upcoming molecular modeling tools are expected to be more robust, with multimodel process capacity, inclusive to multidisciplinary fields and should also be associated with multi scales in calculation. Furthermore, computing capacity must get by biological hypotheses validation. We should, therefore, foresee the streaming of experimental biology and molecular modeling in synchronization; thereby harvesting vital information exchange to mutual enrichment.
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Editorial
We would like to put forward a special thank to authors who have contributed with their research work in this special issue. We are assured about the scientific impact of articles and reviews included in this issue. Few of them add to new frontiers in molecular modeling while others multiply to experimental biology research in progress. We also express gratitude to ChiefEditor and Publication House to provide us this opportunity to conduct and manage this special issue hereby. REFERENCES [1] [2] [3] [4] [5] [6] [7] [8]
Wooley C. John and Lin S. Herbert. Catalyzing inquiry at the interface of computing and biology. National Academic Press, 2005; 9-22. Tropp, B.E. Molecular Biology: Genes to Proteins; Jones & Bartlett Publishers, 2012; 1-7. Offermanns, S.; Rosenthal, W. Encyclopedia of Molecular Pharmacology; Springer Science & Business Media, 2008, 1, 777. Drews, J. Drug discovery: a historical perspective. Science, 2000, 287, 1960-1964. Allison, D.B.; Cui, X.; Page, G.P.; Sabripour, M. Microarray data analysis: from disarray to consolidation and consensus. Nat. Rev. Genet., 2006, 7, 55-65. Deschamps, J.R. The role of crystallography in drug design; The AAPS J., 2005, 7(4), 813-819. Searls, D.B. Using bioinformatics in gene and drug discovery; Drug Discov. Today, 2000, 5(4), 135-143. Chipot, C. Free Energy Calculations in Biological Systems. How Useful Are They in Practice?; New Algorithms for Macromolecular Simulation; Lecture Notes in Computational Science and Engineering, 2006, 46, 185-211.
Anuraj Nayarisseri Guest Editor Current Topics in Medicinal Chemistry Bioinformatics Research Laboratory Eminent Biosciences Vijaynagar, Indore – 452010 India E-mail:
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Mukesh Yadav Guest Editor Current Topics in Medicinal Chemistry Bioinformatics Research Laboratory Eminent Biosciences Vijaynagar, Indore – 452010 India E-mail:
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