The Experts below are selected from a list of 214020 Experts worldwide ranked by ideXlab platform
Abby L. Parrill - One of the best experts on this subject based on the ideXlab platform.
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Evolutionary and genetic methods in Drug Design
Drug Discovery Today, 1996Co-Authors: Abby L. ParrillAbstract:Many phases of rational Drug Design involve finding solutions to large combinatorial problems for which an exhaustive search is intractable. A simulation of the evolutionary pressure of natural selection can be incorporated into artificial intelligence algorithms to rapidly find good, if not optimal, solutions to such problems. This review describes implementations and select applications of genetic algorithms and evolutionary programming in various aspects of rational Drug Design. Evolutionary methods have been developed in the areas of pharmacophore elucidation, lead discovery and lead optimization, as well as in many areas of peripheral importance to rational Drug Design.
Adriano D. Andricopulo - One of the best experts on this subject based on the ideXlab platform.
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Fragment-based QSAR strategies in Drug Design.
Expert opinion on drug discovery, 2010Co-Authors: Lívia B. Salum, Adriano D. AndricopuloAbstract:Recently, fragment-based Drug Design has been established as a crucial strategy for hit identification and lead generation, which has strongly encouraged the development of approaches to specifically recognize and evaluate molecular fragments or structural scaffolds that preferentially interact with particular sites of important biological targets. In this context, fragment-based quantitative structure–activity relationship (FB-QSAR) has emerged as a versatile tool to explore the chemical and biological space of data sets of compounds. FB-QSAR approaches have evolved from a classical use in the generation of standard QSAR models into advanced Drug Design tools for database mining, pharmacokinetic property prediction and optimization of multiple parameters. This paper provides a brief perspective on the evolution and current status of FB-QSAR, highlighting new opportunities in Drug Design.
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Fragment-based QSAR: perspectives in Drug Design
Molecular Diversity, 2009Co-Authors: Lívia B. Salum, Adriano D. AndricopuloAbstract:Drug Design is a process driven by innovation and technological breakthroughs involving a combination of advanced experimental and computational methods. A broad variety of medicinal chemistry approaches can be used for the identification of hits, generation of leads, as well as to accelerate the optimization of leads into Drug candidates. Quantitative structure–activity relationship (QSAR) methods are among the most important strategies that can be applied for the successful Design of small molecule modulators having clinical utility. Hologram QSAR (HQSAR) is a modern 2D fragment-based QSAR method that employs specialized molecular fingerprints. HQSAR can be applied to large data sets of compounds, as well as traditional-size sets, being a versatile tool in Drug Design. The HQSAR approach has evolved from a classical use in the generation of standard QSAR models for data correlation and prediction into advanced Drug Design tools for virtual screening and pharmacokinetic property prediction. This paper provides a brief perspective on the evolution and current status of HQSAR, highlighting present challenges and new opportunities in Drug Design.
Zhang Wan-nian - One of the best experts on this subject based on the ideXlab platform.
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Recent progress on fragment-based Drug Design
Chinese Journal of Medicinal Chemistry, 2010Co-Authors: Zhang Wan-nianAbstract:Recently,fragment-based Drug Design has been developed as a very important approach for Drug discovery.Fragments,with weak binding affinities with target proteins,are detected through SPR,NMR,MS or X-ray crystallography technology.And then they are considered as start points for Drug discovery programs.Compared with traditional approach,fragment-based Drug Design is showing a higher success rate in generating lead series with high activity and good Drug-like properties.In this review,the development and evolution of fragment-based Drug Design examples are described.
Mohane Selvaraj Coumar - One of the best experts on this subject based on the ideXlab platform.
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Evolutionary algorithms for de novo Drug Design - A survey
Applied Soft Computing, 2015Co-Authors: R. Vasundhara Devi, S. Siva Sathya, Mohane Selvaraj CoumarAbstract:In de novo Drug Design multiple pharmaceutically important parameters need to be optimized. Various tools using evolutionary algorithm, a soft computing technique for multi-objective optimization to find novel molecules for Drug development are surveyed. De novo Drug Design supplies novel molecules for Drug development.In de novo Drug Design multiple parameters are optimized.Evolutionary algorithms are used for multi-objective optimization.Evolutionary algorithms used in de novo Drug Design tools are analyzed here. The process of Drug Design and discovery demands several man years and huge investment. Computer-aided Drug Design (CADD) technique is an aid to speed up the Drug discovery process. De novo Drug Design, a CADD technique to identify Drug-like novel chemical structures from a huge chemical search space, helps to find new Drugs by the optimization of multiple pharmaceutically relevant parameters required for a successful Drug. As the search space is very large in the case of de novo Drug Design, evolutionary algorithm (EA), a soft computing technique can be used to find an optimal solution, which in this case is a novel Drug. In this paper, various EA techniques used in de novo Drug Design tools are surveyed and analyzed in detail, with particular emphasis on the computational aspects.
Wayne C. Guida - One of the best experts on this subject based on the ideXlab platform.
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Software for structure-based Drug Design
Current Opinion in Structural Biology, 1994Co-Authors: Wayne C. GuidaAbstract:Abstract A number of examples have recently been reported of the successful application of structure-based Drug Design to the discovery of compounds with the potential to become useful therapeutic agents. Computer-assisted molecular modeling has played a key role in these efforts, in large part due to the availability of adequate computer programs to aid in the molecular Design process. Examples illustrating the application of specific software to structure-based Drug Design are presented. In addition, emerging computational methodology for structure-based Drug Design is discussed.
