Bibliography of computer-aided Drug Design

Updated on 7/18/2014. Currently 2130 references

Ligand design / Reviews

2013 / 2012 / 2011 / 2010 / 2009 / 2007 / 2005 / 2004 /


  • Fragment Informatics and Computational Fragment-Based Drug Design: An Overview and Update
    Sheng, Chunquan and Zhang, Wannian
    Medicinal research reviews, 2013, 33(3), 554-598
    PMID: 22430881     doi: 10.1002/med.21255
    Fragment-based drug design (FBDD) is a promising approach for the discovery and optimization of lead compounds. Despite its successes, FBDD also faces some internal limitations and challenges. FBDD requires a high quality of target protein and good solubility of fragments. Biophysical techniques for fragment screening necessitate expensive detection equipment and the strategies for evolving fragment hits to leads remain to be improved. Regardless, FBDD is necessary for investigating larger chemical space and can be applied to challenging biological targets. In this scenario, cheminformatics and computational chemistry can be used as alternative approaches that can significantly improve the efficiency and success rate of lead discovery and optimization. Cheminformatics and computational tools assist FBDD in a very flexible manner. Computational FBDD can be used independently or in parallel with experimental FBDD for efficiently generating and optimizing leads. Computational FBDD can also be integrated into each step of experimental FBDD and help to play a synergistic role by maximizing its performance. This review will provide critical analysis of the complementarity between computational and experimental FBDD and highlight recent advances in new algorithms and successful examples of their applications. In particular, fragment-based cheminformatics tools, high-throughput fragment docking, and fragment-based de novo drug design will provide the focus of this review. We will also discuss the advantages and limitations of different methods and the trends in new developments that should inspire future research.


  • In silico design of small molecules.
    Bernardo, Paul H and Tong, Joo Chuan
    Methods in molecular biology (Clifton, N.J.), 2012, 800, 25-31
    PMID: 21964780     doi: 10.1007/978-1-61779-349-3_3
    Computational methods now play an integral role in modern drug discovery, and include the design and management of small molecule libraries, initial hit identification through virtual screening, optimization of the affinity and selectivity of hits, and improving the physicochemical properties of the lead compounds. In this chapter, we survey the most important data sources for the discovery of new molecular entities, and discuss the key considerations and guidelines for virtual chemical library design.

  • Classification of scaffold-hopping approaches.
    Sun, Hongmao and Tawa, Gregory and Wallqvist, Anders
    Drug discovery today, 2012, 17(7-8), 310-324
    PMID: 22056715     doi: 10.1016/j.drudis.2011.10.024
    The general goal of drug discovery is to identify novel compounds that are active against a preselected biological target with acceptable pharmacological properties defined by marketed drugs. Scaffold hopping has been widely applied by medicinal chemists to discover equipotent compounds with novel backbones that have improved properties. In this article we classify scaffold hopping into four major categories, namely heterocycle replacements, ring opening or closure, peptidomimetics and topology-based hopping. We review the structural diversity of original and final scaffolds with respect to each category. We discuss the advantages and limitations of small, medium and large-step scaffold hopping. Finally, we summarize software that is frequently used to facilitate different kinds of scaffold-hopping methods.


  • Progress in structure based drug design for G protein-coupled receptors.
    Congreve, Miles and Langmead, Christopher J and Mason, Jonathan S and Marshall, Fiona H
    Journal of medicinal chemistry, 2011, 54(13), 4283-4311
    PMID: 21615150     doi: 10.1021/jm200371q

  • Computational ligand-based rational design: Role of conformational sampling and force fields in model development.
    Shim, Jihyun and MacKerell, Alexander D
    MedChemComm, 2011, 2(5), 356-370
    PMID: 21716805     doi: 10.1039/C1MD00044F
    A significant number of drug discovery efforts are based on natural products or high throughput screens from which compounds showing potential therapeutic effects are identified without knowledge of the target molecule or its 3D structure. In such cases computational ligand-based drug design (LBDD) can accelerate the drug discovery processes. LBDD is a general approach to elucidate the relationship of a compound's structure and physicochemical attributes to its biological activity. The resulting structure-activity relationship (SAR) may then act as the basis for the prediction of compounds with improved biological attributes. LBDD methods range from pharmacophore models identifying essential features of ligands responsible for their activity, quantitative structure-activity relationships (QSAR) yielding quantitative estimates of activities based on physiochemical properties, and to similarity searching, which explores compounds with similar properties as well as various combinations of the above. A number of recent LBDD approaches involve the use of multiple conformations of the ligands being studied. One of the basic components to generate multiple conformations in LBDD is molecular mechanics (MM), which apply an empirical energy function to relate conformation to energies and forces. The collection of conformations for ligands is then combined with functional data using methods ranging from regression analysis to neural networks, from which the SAR is determined. Accordingly, for effective application of LBDD for SAR determinations it is important that the compounds be accurately modelled such that the appropriate range of conformations accessible to the ligands is identified. Such accurate modelling is largely based on use of the appropriate empirical force field for the molecules being investigated and the approaches used to generate the conformations. The present chapter includes a brief overview of currently used SAR methods in LBDD followed by a more detailed presentation of issues and limitations associated with empirical energy functions and conformational sampling methods.

  • Computational design of peptide ligands.
    Vanhee, Peter and van der Sloot, Almer M and Verschueren, Erik and Serrano, Luis and Rousseau, Frederic and Schymkowitz, Joost
    Trends in biotechnology, 2011, 29(5), 231-239
    PMID: 21316780     doi: 10.1016/j.tibtech.2011.01.004
    Peptides possess several attractive features when compared to small molecule and protein therapeutics, such as high structural compatibility with target proteins, the ability to disrupt protein-protein interfaces, and small size. Efficient design of high-affinity peptide ligands via rational methods has been a major obstacle to the development of this potential drug class. However, structural insights into the architecture of protein-peptide interfaces have recently culminated in several computational approaches for the rational design of peptides that target proteins. These methods provide a valuable alternative to experimental high-resolution structures of target protein-peptide complexes, bringing closer the dream of in silico designed peptides for therapeutic applications.

  • Fragment-Based Approaches and Computer-Aided Drug Discovery.
    Rognan, Didier
    Topics in current chemistry, 2011, 37, 201-222
    PMID: 21710380     doi: 10.1007/128_2011_182
    Fragment-based design has significantly modified drug discovery strategies and paradigms in the last decade. Besides technological advances and novel therapeutic avenues, one of the most significant changes brought by this new discipline has occurred in the minds of drug designers. Fragment-based approaches have markedly impacted rational computer-aided design both in method development and in applications. The present review illustrates the importance of molecular fragments in many aspects of rational ligand design, and discusses how thinking in "fragment space" has boosted computational biology and chemistry.

  • Using computational techniques in fragment-based drug discovery.
    Desjarlais, Renee L
    Methods in enzymology, 2011, 493, 137-155
    PMID: 21371590     doi: 10.1016/B978-0-12-381274-2.00006-6
    Fragment-based drug discovery has emerged over the past 15 years as an effective lead discovery paradigm that is complementary to traditional high-throughput screening. The starting point for fragment-based drug discovery is the identification of low-molecular weight, typically low-affinity compounds that bind to a target of interest. These fragments can then be elaborated by growing or linking to create compounds with high affinity and selectivity. A wide variety of techniques from the computational chemistry tool chest can be applied in a fragment-based project. The computational tools are equally useful in combination with experimental-binding determination or in a completely in silico design procedure. This chapter will outline these techniques, their utility, and their validation in the design of novel lead compounds.

  • Integrating structure-based and ligand-based approaches for computational drug design.
    Wilson, Gregory L and Lill, Markus A
    Future medicinal chemistry, 2011, 3(6), 735-750
    PMID: 21554079     doi: 10.4155/fmc.11.18
    Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.


  • The challenges of in silico contributions to drug metabolism in lead optimization.
    Vaz, Roy J and Zamora, Ismael and Li, Yi and Reiling, Stephan and Shen, Jian and Cruciani, Gabriele
    Expert opinion on drug metabolism & toxicology, 2010, 6(7), 851-861
    PMID: 20565339     doi: 10.1517/17425255.2010.499123
    IMPORTANCE OF THE FIELD:The site of metabolism (SOM) predictions by CYP 3A4 are extremely important during the drug discovery process especially during the lead discovery or library design phases. With the ability to rapidly characterize metabolites from these enzymes, the challenges facing in silico contribution change during the drug optimization phase. Some of the challenges are addressed in this article. Some aspects of the SOM prediction software and methodology are discussed in this opinion article and examples of software utility in overcoming metabolic instability in drug optimization are shown.

  • De novo design: balancing novelty and confined chemical space
    Kutchukian, Peter S. and Shakhnovich, Eugene I
    Expert opinion on drug discovery, 2010, 5(8), 789-812
    doi: 10.1517/17460441.2010.497534
    Importance of the field: De novo drug design serves as a tool for the discovery of new ligands for macromolecular targets as well as optimization of known ligands. Recently developed tools aim to address the multi-objective nature of drug design in an unprecedented manner.Areas covered in this review: This article discusses recent advances in de novo drug design programs and accessory programs used to evaluate compounds post-generation.What the reader will gain: The reader is introduced to the challenges inherent in de novo drug design and will become familiar with current trends in de novo design. Furthermore, the reader will be better prepared to assess the value of a tool, and be equipped to design more elegant tools in the future.Take home message: De novo drug design can assist in the efficient discovery of new compounds with a high affinity for a given target. The inclusion of existing chemoinformatic methods with current structure-based de novo design tools provides a means of enhancing the therapeutic value of these generated compounds.

  • Bioisosteric Replacement and Scaffold Hopping in Lead Generation and Optimization
    Langdon, Sarah R and Ertl, Peter and Brown, Nathan
    Molecular Informatics, 2010, 29(5), 366-385
    doi: 10.1002/minf.201000019


  • Efficient drug lead discovery and optimization
    Jorgensen, WL
    Accounts of chemical research, 2009, 42(6), 724-733
    During the 1980s, advances in the abilities to perform computer simulations of chemical and biomolecular systems and to calcu- late free energy changes led to the expectation that such methodol- ogy would soon show great utility for guiding molecular design. Important potential applications included design of selective recep- tors, catalysts, and regulators of biological function including enzyme inhibitors. This time also saw the rise of high-throughput screening and combinatorial chemistry along with complementary computa- tional methods for de novo design and virtual screening including docking. These technologies appeared poised to deliver diverse lead compounds for any biological target. As with many technological advances, realization of the expectations required significant addi- tional effort and time. However, as summarized here, striking suc- cess has now been achieved for computer-aided drug lead generation and optimization. De novo design using both molecular growing and docking are illustrated for lead generation, and lead optimization features free energy perturbation calculations in conjunction with Monte Carlo statistical mechanics simulations for protein-inhibitor complexes in aqueous solution. The specific applications are to the discovery of non-nucleoside inhibi- tors of HIV reverse transcriptase (HIV-RT) and inhibitors of the binding of the proinflammatory cytokine MIF to its recep- tor CD74. A standard protocol is presented that includes scans for possible additions of small substituents to a molecular core, interchange of heterocycles, and focused optimization of substituents at one site. Initial leads with activities at low- micromolar concentrations have been advanced rapidly to low-nanomolar inhibitors.

  • The multiple roles of computational chemistry in fragment-based drug design.
    Law, Richard and Barker, Oliver and Barker, John J and Hesterkamp, Thomas and Godemann, Robert and Andersen, Ole and Fryatt, Tara and Courtney, Steve and Hallett, Dave and Whittaker, Mark
    Journal of computer-aided molecular design, 2009, 23(8), 459-473
    PMID: 19533374     doi: 10.1007/s10822-009-9284-1
    Fragment-based drug discovery (FBDD) represents a change in strategy from the screening of molecules with higher molecular weights and physical properties more akin to fully drug-like compounds, to the screening of smaller, less complex molecules. This is because it has been recognised that fragment hit molecules can be efficiently grown and optimised into leads, particularly after the binding mode to the target protein has been first determined by 3D structural elucidation, e.g. by NMR or X-ray crystallography. Several studies have shown that medicinal chemistry optimisation of an already drug-like hit or lead compound can result in a final compound with too high molecular weight and lipophilicity. The evolution of a lower molecular weight fragment hit therefore represents an attractive alternative approach to optimisation as it allows better control of compound properties. Computational chemistry can play an important role both prior to a fragment screen, in producing a target focussed fragment library, and post-screening in the evolution of a drug-like molecule from a fragment hit, both with and without the available fragment-target co-complex structure. We will review many of the current developments in the area and illustrate with some recent examples from successful FBDD discovery projects that we have conducted.

  • Docking, virtual high throughput screening and in silico fragment-based drug design.
    Zoete, Vincent and Grosdidier, Aurélien and Michielin, Olivier
    Journal of cellular and molecular medicine, 2009, 13(2), 238-248
    PMID: 19183238     doi: 10.1111/j.1582-4934.2008.00665.x
    The drug discovery process has been profoundly changed recently by the adoption of computational methods helping the design of new drug candidates more rapidly and at lower costs. In silico drug design consists of a collection of tools helping to make rational decisions at the different steps of the drug discovery process, such as the identification of a biomolecular target of therapeutical interest, the selection or the design of new lead compounds and their modification to obtain better affinities, as well as pharmacokinetic and pharmacodynamic properties. Among the different tools available, a particular emphasis is placed in this review on molecular docking, virtual high-throughput screening and fragment-based ligand design.


  • Computer-aided drug design: Integration of structure-based and ligand-based approaches in drug design
    Prathipati, Philip and Dixit, Anshuman and Saxena, Anil K.
    Current computer-aided drug design, 2007, 3(2), 133-148
    In silico high throughput screens provide an efficient (time and money) and effective (with comparable or better accuracy) alternatives in comparison to their experimental counterparts, and hence is of enormous interest to drug discovery research. However the assessment of a variety of virtual screening techniques ranging from simple fingerprint based similarity searching to the sophisticated docking algorithms reveals the inverse proportionality of the speed and accuracy of these algorithms, thus presenting a significant challenge, in enabling the use of computational tools to drug research. Some of the advantages and disadvantages of the structure-based (direct) and ligand-based (indirect) drug design techniques are typically discussed in terms of their requirements vis-A-vis the accuracy and time required for the analysis. The various integration strategies conceptualized to circumvent the above problems in the recent years are summarized with their merits and demerits.


  • Maximizing discovery efficiency with a computationally driven fragment approach.
    Moore, William R
    Current opinion in drug discovery & development, 2005, 8(3), 355-364
    PMID: 15892251    
    A reliable and accurate method for the computational design of novel drug candidates has been a passionate pursuit of the pharmaceutical industry. Such technology would dramatically improve the efficiency of drug discovery by quickly and inexpensively providing potent molecules that can be further prioritized for synthesis based on characteristics such as patentability, specific protein-ligand interactions, ease of chemical synthesis, protein selectivity and pharmacological considerations. Described herein is the progress made at Locus Pharmaceuticals Inc toward achieving this ideal with a fragment-driven, computationally directed approach to small-molecule discovery. Specific lead identification examples from Locus Pharmaceuticals discovery programs demonstrate the efficiency and cost-effectiveness realized by such an approach.


  • Scaffold hopping
    Böhm, Hans-Joachim and Flohr, Alexander and Stahl, Martin
    Drug Discovery Today: Technologies, 2004, 1(3), 217-224
    doi: 10.1016/j.ddtec.2004.10.009
    ... for example by the large number of publications using the word `` bioisostere '' in the ... 3D protein structures, access to large databases on successful bioisosteric replacements and also ... of peptidomimetic replacement towards more tractable tasks such as the replacement of ring ...

  • Scaffold hopping
    Böhm, Hans-Joachim and Flohr, Alexander and Stahl, Martin
    Drug Discovery Today: Technologies, 2004, 1(3), 217-224
    doi: 10.1016/j.ddtec.2004.10.009
    ... for example by the large number of publications using the word `` bioisostere '' in the ... 3D protein structures, access to large databases on successful bioisosteric replacements and also ... of peptidomimetic replacement towards more tractable tasks such as the replacement of ring ...