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- Volume 2, Issue 3, 2006
Current Computer - Aided Drug Design - Volume 2, Issue 3, 2006
Volume 2, Issue 3, 2006
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Molecular Dynamics Simulations and Analysis of ABC Transporters
Authors: Anthony M. George and Peter M. JonesThe increasing availability of atomic-level protein structures derived from X-ray crystallography and NMR spectroscopy, together with advances in computational power, have ushered in a new era of powerful theoretical approaches to study protein mechanisms and, by extension, use a computer-aided structural approach to drug design. Classical molecular dynamics calculations, in which Newton's equations of motion are solved for all atoms in the system, has emerged as an important tool for analysing protein dynamics at physiologically relevant timescales, in ways that are either very difficult or impossible to do experimentally. Indeed, the computer is becoming a kind of virtual microscope that can observe things not observable by any other means. The availability of more sophisticated parallel computer clusters and program suites will lead to simulations that will be capable of examining entire processes such as polypeptide folding pathways and reaction mechanisms. In this review, the incipient application of molecular dynamics analysis of ABC (ATPBinding Cassette) transporters is surveyed and discussed, with particular relevance to unresolved and controversial issues.
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An Introduction to Molecular Modeling of G-Protein Coupled Receptors
Authors: Minghua Wang, Lakshmi P. Kotra and David R. HampsonG-protein coupled receptors (GPCRs) are the largest single family of signaling molecules in mammals and represent approximately 2-3% of all genes in the human genome. Estimates of the total number of GPCR genes in the human genome range from about 750 to 1000. GPCRs mediate signaling by a wide variety of ligands including amino acids, ions, biogenic amines, peptides, glycoproteins, light, pheromones, and odorants. There are presently only a handful of GPCRs whose structures have been elucidated. Of these, the mGluR1 subtype of metabotropic glutamate receptor (mGluR) and rhodopsin are the most widely used in modeling GPCRs. In the case of mGluR1, the three-dimensional structure of the extracellular ligand binding domain of the molecule has been solved, while the crystallographic data for rhodopsin encompasses the whole protein in the ground state with bound 11-cis-retinal. In this review, we discuss the use of homology modeling to investigate the structures and functions of GPCRs. We illustrate the use of homology modeling with a particular emphasis on ligand and drug binding sites in the Family C subfamily of GPCRs.
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Molecular Modeling Studies of Estrogen Receptor Modulators
Authors: Subhendu Mukherjee and Achintya SahaThe dimensional expansion in the research domain of Selective Estrogen Receptor (ER) Modulators (SERM) has been driven by discovering molecules with improved endocrine profiles that might be safer and valuable drug candidates for treating variety of estrogen-linked pathologies. Desirable tissue selectivity may result from the unique structural characteristics of a ligand that take advantage of differences in diversities of cell specific factors. The recent discovery of a second ER has provoked the search for ligands which are selective for either the classical ER or newer subtypes. Libraries of compounds, both synthetic and natural are being screened globally for finding ideal SERMs and investigating pharmacophore patterns for apprehending tissue selective parameters. Diverse series of selective synthetic analogs have been developed with high relative binding affinities to the ER as comparable to 17β-estradiol and extensive data sets of phytoestrogens have also been screened for selective binding at the ER surfaces. The successful synthesis, exploration of natural resources and biological testing of SERMs are emerging as vital tools for apprehending the differences in structure and biological functions of ER subtypes as well as for deducing pharmacophore maps of estrogenic analogs through application of virtual molecular modeling applications. Several approaches in calculating ligand-binding affinities have been used over the past decade, ranging from molecular field analysis studies to protein-based methods using empirical scoring functions. One of the most promising areas in present day computational chemistry that has further aided the understanding of mechanistic aspects of estrogenic activity, is the characterization of molecular properties and bio-activities by means of structurebased descriptors generated from theoretical improvement and computational applications that eventually lead to construction of quantitative SAR related to molecular features by statistical procedures. Consequently, this paper overviews the properties investigated towards explaining tissue selectivity of estrogens and structural homology patterns of active analogs on precision based In silico approaches. This review also takes into account some our ongoing research efforts in this area that have contributed significant findings.
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Recent Advances in Chemometric Methodologies for QSAR Studies
Authors: Wei Qi Lin, Jian Hui Jiang, Hai Long Wu, Guo-Li Shen and Ru Qin YuIn recent years chemometrics has been undergoing an exciting development both in the applied areas and in the theoretical and methodological aspects. This review is focused on recent advances in chemometric methodologies for quantitative structure-activity relationship (QSAR) studies, and it covers multiple applications. QSAR is one of the tools for the computer-aided drug design; it is also an important branch of chemometrics. The feature or variable selection is an important aspect in QSAR studies. Basic requirements and different algorithms for feature or variable selection are briefly discussed. Moreover, an overview of the stateof- the-art chemometric methods developed to combat the shortcomings of conventional algorithms and their applications in QSAR is given. A survey of innovative chemometric approaches in QSAR model construction is also presented. Some remarks and outlook about QSAR studies applied to the computer-aided drug design have also been discussed.
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Systems Biology and Computer-Aided Drug Discovery
Authors: Timothy G. Lilburn and Yufeng WangWith the advent of the post-genomic era, systems biology has set the stage for a quantum leap in our understanding of the fundamental cellular processes, phenotypic variations, and disease mechanisms. By integrating the vast amount data from genomics, transcriptomics, and proteomics analyses, systems biology seeks a holistic view of organisms and the modules that compose them. The approaches to a systems level view of biology can be broadly classified as either deterministic or probabilistic. The former approach generates highly detailed views that are mechanistic and often quantitative, while the latter type of approach generates high level views that have usually been qualitative. An ability to see and describe the systems-level processes in the organism and thereby identify potential vulnerabilities could expedite the process of drug discovery and development. A systems biology approach will aid in at least four of the major stages of this process: target identification, target validation, preclinical testing and clinical trials. We give an overview of systems biology and describe, with examples, how it is being used for drug discovery and development.
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Analysis of Similarity/Dissimilarity of DNA Primary Sequences Based on Condensed Matrices and Information Entropies
More LessThe primary sequence of DNA is a sequence of nucleotides over the four-letters alphabet {A, C, G, T}. Characteristic sequences of a DNA sequence are given in term of classification of bases of nucleotides. Using the characteristic sequences, we construct a set of 3 x 8 matrices and a set of 2 x 2 matrices to represent DNA primary sequences and define the information entropy, which is based on counting all triplets of characteristic sequences. Similarity and dissimilarity analysis based on the condensed matrices and the information entropies are given for the first exon of beta-globin genes sequences belonging to eleven different species.
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Recent Advances in Free Energy Calculations with a Combination of Molecular Mechanics and Continuum Models
Authors: Junmei Wang, Tingjun Hou and Xiaojie XuRecently, the combination of state-of-the-art molecular mechanical force fields with continuum solvation models enables us to make relatively accurate predictions of both structures and free energies for macromolecules from molecular dynamics trajectories. The first part of this review is focused on the history and basic theory of free energy calculations based on physically effective energy functions. The second part illustrates the applications of free energy calculations on many biological systems, including proteins, DNA,RNA, protein-ligand, protein-protein, protein-nucleic acid complexes, etc. Finally, the prospective and possible strategies to improve the techniques of MM-PBSA and MM-GBSA is discussed.
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Cancer and Aids: New Trends in Drug Design and Chemotherapy
More LessWe present a comprehensive but not exhaustive review of new trends in drug discovery and targets for cancer and AIDS which begins by highlighting the different historical stages of drug discovery from clinical diagnosis, natural compounds, serendipity and chemotherapy to the present age of modern experimental and computational techniques. The current state of the art of computer-aided drug design and selected recent applications to Cancer and AIDS are discussed. Novel targets and drugs in Cancer and AIDS are analyzed. In conclusion, future perspectives for drug discovery, design and therapeutics in cancer and AIDS are presented.
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Volumes & issues
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Volume 21 (2025)
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Volume 20 (2024)
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Volume 19 (2023)
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Volume 18 (2022)
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Volume 17 (2021)
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Volume 16 (2020)
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Volume 15 (2019)
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Volume 14 (2018)
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Volume 13 (2017)
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Volume 12 (2016)
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Volume 11 (2015)
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Volume 10 (2014)
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Volume 9 (2013)
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Volume 8 (2012)
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Volume 7 (2011)
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Volume 6 (2010)
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Volume 5 (2009)
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Volume 4 (2008)
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Volume 3 (2007)
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Volume 2 (2006)
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Volume 1 (2005)