Bibliography of computer-aided Drug Design

Updated on 7/18/2014. Currently 2130 references

Last additions

  • Assessment of ligand binding site predictions in CASP10.
    Gallo Cassarino, Tiziano and Bordoli, Lorenza and Schwede, Torsten
    Proteins, 2014, 82 Suppl 2, 154-163
    PMID: 24339001     doi: 10.1002/prot.24495
    The identification of amino acid residues in proteins involved in binding small molecule ligands is an important step for their functional characterization, as the function of a protein often depends on specific interactions with other molecules. The accuracy of computational methods aiming to predict such binding residues was evaluated within the "function prediction (prediction of binding sites, FN)" category of the critical assessment of protein structure prediction (CASP) experiment. In the last edition of the experiment (CASP10), 17 research groups participated in this category, and their predictions were evaluated on 13 prediction targets containing biologically relevant ligands. The results of this experiment indicate that several methods achieved an overall good performance, showing the usefulness of such methods in predicting ligand binding residues. As in previous years, methods based on a homology transfer approach were dominating. In comparison to CASP9, a larger fraction of the top predictors are automated servers. However, due to the small number of targets and the characteristics of the prediction format, the differences observed among the first ten methods were not statistically significant and it was also not possible to analyze differences in accuracy for different ligand types or overall structure, difficulty. To overcome these limitations and to allow for a more detailed evaluation, in future editions of CASP, methods in the FN category will no longer be evaluated on the "normal" CASP targets, but assessed continuously by CAMEO (continuous automated model evaluation) based on weekly prereleased sequences from the PDB.

  • The optimization of running time for a maximum common substructure-based algorithm and its application in drug design.
    Chen, Jian and Sheng, Jia and Lv, Dijing and Zhong, Yang and Zhang, Guoqing and Nan, Peng
    Computational biology and chemistry, 2014, 48, 14-20
    PMID: 24291488     doi: 10.1016/j.compbiolchem.2013.10.003
    In the field of drug discovery, it is particularly important to discover bioactive compounds through high-throughput virtual screening. The maximum common substructure-based (MCS) algorithm is a promising method for the virtual screening of drug candidates. However, in practical applications, there is always a trade-off between efficiency and accuracy. In this paper, we optimized this method by running time evaluation using essential drugs defined by WHO and FDA-approved small-molecule drugs. The amount of running time allocated to the MCS-based virtual screening was varied, and statistical analysis was conducted to study the impact of computation running time on the screening results. It was determined that the running time efficiency can be improved without compromising accuracy by setting proper running time thresholds. In addition, the similarity of compound structures and its relevance to biological activity are analyzed quantitatively, which highlight the applicability of the MCS-based methods in predicting functions of small molecules. 15-30s was established as a reasonable range for selecting a candidate running time threshold. The effect of CPU speed is considered and the conclusion is generalized. The potential biological activity of small molecules with unknown functions can be predicted by the MCS-based methods.

  • HTS navigator: freely accessible cheminformatics software for analyzing high-throughput screening data.
    Fourches, Denis and Sassano, Maria F and Roth, Bryan L and Tropsha, Alexander
    Bioinformatics (Oxford, England), 2014, 30(4), 588-589
    PMID: 24376084     doi: 10.1093/bioinformatics/btt718
    SUMMARY:We report on the development of the high-throughput screening (HTS) Navigator software to analyze and visualize the results of HTS of chemical libraries. The HTS Navigator processes output files from different plate readers' formats, computes the overall HTS matrix, automatically detects hits and has different types of baseline navigation and correction features. The software incorporates advanced cheminformatics capabilities such as chemical structure storage and visualization, fast similarity search and chemical neighborhood analysis for retrieved hits. The software is freely available for academic laboratories.

  • Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4.
    Voet, Arnout R D and Kumar, Ashutosh and Berenger, Francois and Zhang, Kam Y J
    Journal of computer-aided molecular design, 2014
    PMID: 24446075     doi: 10.1007/s10822-013-9702-2
    The SAMPL challenges provide an ideal opportunity for unbiased evaluation and comparison of different approaches used in computational drug design. During the fourth round of this SAMPL challenge, we participated in the virtual screening and binding pose prediction on inhibitors targeting the HIV-1 integrase enzyme. For virtual screening, we used well known and widely used in silico methods combined with personal in cerebro insights and experience. Regular docking only performed slightly better than random selection, but the performance was significantly improved upon incorporation of additional filters based on pharmacophore queries and electrostatic similarities. The best performance was achieved when logical selection was added. For the pose prediction, we utilized a similar consensus approach that amalgamated the results of the Glide-XP docking with structural knowledge and rescoring. The pose prediction results revealed that docking displayed reasonable performance in predicting the binding poses. However, prediction performance can be improved utilizing scientific experience and rescoring approaches. In both the virtual screening and pose prediction challenges, the top performance was achieved by our approaches. Here we describe the methods and strategies used in our approaches and discuss the rationale of their performances.

  • DiSCuS: an open platform for (not only) virtual screening results management.
    Wójcikowski, Maciej and Zielenkiewicz, Piotr and Siedlecki, Pawel
    Journal of chemical information and modeling, 2014, 54(1), 347-354
    PMID: 24364790     doi: 10.1021/ci400587f
    DiSCuS, a "Database System for Compound Selection", has been developed. The primary goal of DiSCuS is to aid researchers in the steps subsequent to generating high-throughput virtual screening (HTVS) results, such as selection of compounds for further study, purchase, or synthesis. To do so, DiSCuS provides (1) a storage facility for ligand-receptor complexes (generated with external programs), (2) a number of tools for validating these complexes, such as scoring functions, potential energy contributions, and med-chem features with ligand similarity estimates, and (3) powerful searching and filtering options with logical operators. DiSCuS supports multiple receptor targets for a single ligand, so it can be used either to evaluate different variants of an active site or for selectivity studies. DiSCuS documentation, installation instructions, and source code can be found at .

  • SABRE: ligand/structure-based virtual screening approach using consensus molecular-shape pattern recognition.
    Wei, Ning-Ning and Hamza, Adel
    Journal of chemical information and modeling, 2014, 54(1), 338-346
    PMID: 24328054     doi: 10.1021/ci4005496
    We present an efficient and rational ligand/structure shape-based virtual screening approach combining our previous ligand shape-based similarity SABRE (shape-approach-based routines enhanced) and the 3D shape of the receptor binding site. Our approach exploits the pharmacological preferences of a number of known active ligands to take advantage of the structural diversities and chemical similarities, using a linear combination of weighted molecular shape density. Furthermore, the algorithm generates a consensus molecular-shape pattern recognition that is used to filter and place the candidate structure into the binding pocket. The descriptor pool used to construct the consensus molecular-shape pattern consists of four dimensional (4D) fingerprints generated from the distribution of conformer states available to a molecule and the 3D shapes of a set of active ligands computed using SABRE software. The virtual screening efficiency of SABRE was validated using the Database of Useful Decoys (DUD) and the filtered version (WOMBAT) of 10 DUD targets. The ligand/structure shape-based similarity SABRE algorithm outperforms several other widely used virtual screening methods which uses the data fusion of multiscreening tools (2D and 3D fingerprints) and demonstrates a superior early retrieval rate of active compounds (EF(0.1%)

  • BP-Dock: A Flexible Docking Scheme for Exploring Protein-Ligand Interactions Based on Unbound Structures.
    Bolia, Ashini and Gerek, Z Nevin and Ozkan, S Banu
    Journal of chemical information and modeling, 2014, 54(3), 913-925
    PMID: 24380381     doi: 10.1021/ci4004927
    Molecular docking serves as an important tool in modeling protein-ligand interactions. However, it is still challenging to incorporate overall receptor flexibility, especially backbone flexibility, in docking due to the large conformational space that needs to be sampled. To overcome this problem, we developed a novel flexible docking approach, BP-Dock (Backbone Perturbation-Dock) that can integrate both backbone and side chain conformational changes induced by ligand binding through a multi-scale approach. In the BP-Dock method, we mimic the nature of binding-induced events as a first-order approximation by perturbing the residues along the protein chain with a small Brownian kick one at a time. The response fluctuation profile of the chain upon these perturbations is computed using the perturbation response scanning method. These response fluctuation profiles are then used to generate binding-induced multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, we applied our approach on a large and diverse data set using unbound structures as receptors. We also compared the BP-Dock results with bound and unbound docking, where overall receptor flexibility was not taken into account. Our results highlight the importance of modeling backbone flexibility in docking for recapitulating the experimental binding affinities, especially when an unbound structure is used. With BP-Dock, we can generate a wide range of binding site conformations realized in nature even in the absence of a ligand that can help us to improve the accuracy of unbound docking. We expect that our fast and efficient flexible docking approach may further aid in our understanding of protein-ligand interactions as well as virtual screening of novel targets for rational drug design.

  • SAMPL4 & DOCK3.7: lessons for automated docking procedures.
    Coleman, Ryan G and Sterling, Teague and Weiss, Dahlia R
    Journal of computer-aided molecular design, 2014, 28(3), 201-209
    PMID: 24515818     doi: 10.1007/s10822-014-9722-6
    The SAMPL4 challenges were used to test current automated methods for solvation energy, virtual screening, pose and affinity prediction of the molecular docking pipeline DOCK 3.7. Additionally, first-order models of binding affinity were proposed as milestones for any method predicting binding affinity. Several important discoveries about the molecular docking software were made during the challenge: (1) Solvation energies of ligands were five-fold worse than any other method used in SAMPL4, including methods that were similarly fast, (2) HIV Integrase is a challenging target, but automated docking on the correct allosteric site performed well in terms of virtual screening and pose prediction (compared to other methods) but affinity prediction, as expected, was very poor, (3) Molecular docking grid sizes can be very important, serious errors were discovered with default settings that have been adjusted for all future work. Overall, lessons from SAMPL4 suggest many changes to molecular docking tools, not just DOCK 3.7, that could improve the state of the art. Future difficulties and projects will be discussed.

  • Incorporating replacement free energy of binding-site waters in molecular docking
    Sun, Hanzi and Zhao, Lifeng and Peng, Shiming and Huang, Niu
    Proteins, 2014, n/a-n/a
    PMID: 24549784     doi: 10.1002/prot.24530
    Binding-site water molecules play a crucial role in protein-ligand recognition, either being displaced upon ligand binding or forming water bridges to stabilize the complex. However, rigorously treating explicit binding-site waters is challenging in molecular docking, which requires to fully sample ensembles of waters and to consider the free energy cost of replacing waters. Here, we describe a method to incorporate structural and energetic properties of binding-site waters into molecular docking. We first developed a solvent property analysis (SPA) program to compute the replacement free energies of binding-site water molecules by post-processing molecular dynamics trajectories obtained from ligand-free protein structure simulation in explicit water. Next, we implemented a distance-dependent scoring term into DOCK scoring function to take account of the water replacement free energy cost upon ligand binding. We assessed this approach in protein targets containing important binding-site waters, and we demonstrated that our approach is reliable in reproducing the crystal binding geometries of protein-ligand-water complexes, as well as moderately improving the ligand docking enrichment performance. In addition, SPA program (free available to academic users upon request) may be applied in identifying hot-spot binding-site residues and structure-based lead optimization.Proteins 2014.

  • Exhaustive docking and solvated interaction energy scoring: lessons learned from the SAMPL4 challenge.
    Hogues, Hervé and Sulea, Traian and Purisima, Enrico O
    Journal of computer-aided molecular design, 2014
    PMID: 24474162     doi: 10.1007/s10822-014-9715-5
    We continued prospective assessments of the Wilma-solvated interaction energy (SIE) platform for pose prediction, binding affinity prediction, and virtual screening on the challenging SAMPL4 data sets including the HIV-integrase inhibitor and two host-guest systems. New features of the docking algorithm and scoring function are tested here prospectively for the first time. Wilma-SIE provides good correlations with actual binding affinities over a wide range of binding affinities that includes strong binders as in the case of SAMPL4 host-guest systems. Absolute binding affinities are also reproduced with appropriate training of the scoring function on available data sets or from comparative estimation of the change in target's vibrational entropy. Even when binding modes are known, SIE predictions lack correlation with experimental affinities within dynamic ranges below 2 kcal/mol as in the case of HIV-integrase ligands, but they correctly signaled the narrowness of the dynamic range. Using a common protein structure for all ligands can reduce the noise, while incorporating a more sophisticated solvation treatment improves absolute predictions. The HIV-integrase virtual screening data set consists of promiscuous weak binders with relatively high flexibility and thus it falls outside of the applicability domain of the Wilma-SIE docking platform. Despite these difficulties, unbiased docking around three known binding sites of the enzyme resulted in over a third of ligands being docked within 2\AA} from their actual poses and over half of the ligands docked in the correct site, leading to better-than-random virtual screening results.

  • Assessing protein-ligand docking for the binding of organometallic compounds to proteins.
    Ortega-Carrasco, Elisabeth and Lledós, Agusti and Maréchal, Jean-Didier
    Journal of computational chemistry, 2014, 35(3), 192-198
    PMID: 24375319     doi: 10.1002/jcc.23472
    Organometallic compounds are increasingly used as molecular scaffolds in drug development projects; their structural and electronic properties offering novel opportunities in protein-ligand complementarities. Interestingly, while protein-ligand dockings have long become a spearhead in computer assisted drug design, no benchmarking nor optimization have been done for their use with organometallic compounds. Pursuing our efforts to model metal mediated recognition processes, we herein present a systematic study of the capabilities of the program GOLD to predict the interactions of protein with organometallic compounds. The study focuses on inert systems for which no alteration of the first coordination sphere of the metal occurs upon binding. Several scaffolds are used as test systems with different docking schemes and scoring functions. We conclude that ChemScore is the most robust scoring function with ASP and ChemPLP providing with good results too and GoldScore slightly underperforming. This study shows that current state-of-the-art protein-ligand docking techniques are reliable for the docking of inert organometallic compounds binding to protein.

  • Importance of ligand conformational energies in carbohydrate docking: Sorting the wheat from the chaff.
    Nivedha, Anita K and Makeneni, Spandana and Foley, Bethany Lachele and Tessier, Matthew B and Woods, Robert J
    Journal of computational chemistry, 2014, 35(7), 526-539
    PMID: 24375430     doi: 10.1002/jcc.23517
    Docking algorithms that aim to be applicable to a broad range of ligands suffer reduced accuracy because they are unable to incorporate ligand-specific conformational energies. Here, we develop a set of Carbohydrate Intrinsic (CHI) energy functions that quantify the conformational properties of oligosaccharides, based on the values of their glycosidic torsion angles. The relative energies predicted by the CHI energy functions mirror the conformational distributions of glycosidic linkages determined from a survey of oligosaccharide-protein complexes in the protein data bank. Addition of CHI energies to the standard docking scores in Autodock 3, 4.2, and Vina consistently improves pose ranking of oligosaccharides docked to a set of anticarbohydrate antibodies. The CHI energy functions are also independent of docking algorithm, and with minor modifications, may be incorporated into both theoretical modeling methods, and experimental NMR or X-ray structure refinement programs.

  • istar: a web platform for large-scale protein-ligand docking.
    Li, Hongjian and Leung, Kwong-Sak and Ballester, Pedro J and Wong, Man-Hon
    PloS one, 2014, 9(1), e85678
    PMID: 24475049     doi: 10.1371/journal.pone.0085678
    Protein-ligand docking is a key computational method in the design of starting points for the drug discovery process. We are motivated by the desire to automate large-scale docking using our popular docking engine idock and thus have developed a publicly-accessible web platform called istar. Without tedious software installation, users can submit jobs using our website. Our istar website supports 1) filtering ligands by desired molecular properties and previewing the number of ligands to dock, 2) monitoring job progress in real time, and 3) visualizing ligand conformations and outputting free energy and ligand efficiency predicted by idock, binding affinity predicted by RF-Score, putative hydrogen bonds, and supplier information for easy purchase, three useful features commonly lacked on other online docking platforms like DOCK Blaster or iScreen. We have collected 17,224,424 ligands from the All Clean subset of the ZINC database, and revamped our docking engine idock to version 2.0, further improving docking speed and accuracy, and integrating RF-Score as an alternative rescoring function. To compare idock 2.0 with the state-of-the-art AutoDock Vina 1.1.2, we have carried out a rescoring benchmark and a redocking benchmark on the 2,897 and 343 protein-ligand complexes of PDBbind v2012 refined set and CSAR NRC HiQ Set 24Sept2010 respectively, and an execution time benchmark on 12 diverse proteins and 3,000 ligands of different molecular weight. Results show that, under various scenarios, idock achieves comparable success rates while outperforming AutoDock Vina in terms of docking speed by at least 8.69 times and at most 37.51 times. When evaluated on the PDBbind v2012 core set, our istar platform combining with RF-Score manages to reproduce Pearson's correlation coefficient and Spearman's correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. istar is freely available at

  • iview: an interactive WebGL visualizer for protein-ligand complex.
    Li, Hongjian and Leung, Kwong-Sak and Nakane, Takanori and Wong, Man-Hon
    Bmc Bioinformatics, 2014, 15, 56
    PMID: 24564583     doi: 10.1186/1471-2105-15-56
    BACKGROUND:Visualization of protein-ligand complex plays an important role in elaborating protein-ligand interactions and aiding novel drug design. Most existing web visualizers either rely on slow software rendering, or lack virtual reality support. The vital feature of macromolecular surface construction is also unavailable.