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      A perspective on multi-target drug discovery and design for complex diseases

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          Diseases of infection, of neurodegeneration (such as Alzheimer’s and Parkinson’s diseases), and of malignancy (cancers) have complex and varied causative factors. Modern drug discovery has the power to identify potential modulators for multiple targets from millions of compounds. Computational approaches allow the determination of the association of each compound with its target before chemical synthesis and biological testing is done. These approaches depend on the prior identification of clinically and biologically validated targets. This Perspective will focus on the molecular and computational approaches that underpin drug design by medicinal chemists to promote understanding and collaboration with clinical scientists.

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          Most cited references 95

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          The influence of drug-like concepts on decision-making in medicinal chemistry.

          The application of guidelines linked to the concept of drug-likeness, such as the 'rule of five', has gained wide acceptance as an approach to reduce attrition in drug discovery and development. However, despite this acceptance, analysis of recent trends reveals that the physical properties of molecules that are currently being synthesized in leading drug discovery companies differ significantly from those of recently discovered oral drugs and compounds in clinical development. The consequences of the marked increase in lipophilicity--the most important drug-like physical property--include a greater likelihood of lack of selectivity and attrition in drug development. Tackling the threat of compound-related toxicological attrition needs to move to the mainstream of medicinal chemistry decision-making.
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            Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation.

            Understanding the principles whereby macromolecular biological receptors can recognise small molecule substrates or inhibitors is the subject of a major effort. This is of paramount importance in rational drug design where the receptor structure is known (the "docking" problem). Current theoretical approaches utilise models of the steric and electrostatic interaction of bound ligands and recently conformational flexibility has been incorporated. We report results based on software using a genetic algorithm that uses an evolutionary strategy in exploring the full conformational flexibility of the ligand with partial flexibility of the protein, and which satisfies the fundamental requirement that the ligand must displace loosely bound water on binding. Results are reported on five test systems showing excellent agreement with experimental data. The design of the algorithm offers insight into the molecular recognition mechanism.
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              Magic shotguns versus magic bullets: selectively non-selective drugs for mood disorders and schizophrenia.


                Author and article information

                Clin Transl Med
                Clin Transl Med
                Clinical and Translational Medicine
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                17 January 2018
                17 January 2018
                : 7
                [1 ]ISNI 0000 0001 0721 1626, GRID grid.11914.3c, Biomedical Sciences Research Complex, University of St Andrews, ; North Haugh, St Andrews, KY16 9ST UK
                [2 ]ISNI 0000 0001 2166 9385, GRID grid.7149.b, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, , University of Belgrade, ; Vojvode Stepe 450, 11000 Belgrade, Serbia
                [3 ]ISNI 0000 0004 1757 1758, GRID grid.6292.f, Department of Pharmacy and Biotechnology, , Alma Mater Studiorum-Bologna University, ; Via Belmeloro 6, 40126 Bologna, Italy
                © The Author(s) 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                Funded by: FundRef, European Cooperation in Science and Technology;
                Award ID: CM15135
                Funded by: FundRef, Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja;
                Award ID: 172033
                Award Recipient :
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                © The Author(s) 2018


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