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1.
Virtual screening has become a popular tool to identify novel leads in the early phases of drug discovery. A variety of docking
and scoring methods used in virtual screening have been the subject of active research in an effort to gauge limitations and
articulate best practices. However, how to best utilize different scoring functions and various crystal structures, when available,
is not yet well understood. In this work we use multiple crystal structures of PI3 K-γ in both prospective and retrospective
virtual screening experiments. Both Glide SP scoring and Prime MM-GBSA rescoring are utilized in the prospective and retrospective
virtual screens, and consensus scoring is investigated in the retrospective virtual screening experiments. The results show
that each of the different crystal structures that was used, samples a different chemical space, i.e. different chemotypes
are prioritized by each structure. In addition, the different (re)scoring functions prioritize different chemotypes as well.
Somewhat surprisingly, the Prime MM-GBSA scoring function generally gives lower enrichments than Glide SP. Finally we investigate
the impact of different ligand preparation protocols on virtual screening enrichment factors. In summary, different crystal
structures and different scoring functions are complementary to each other and allow for a wider variety of chemotypes to
be considered for experimental follow-up. 相似文献
2.
Zhou Z Felts AK Friesner RA Levy RM 《Journal of chemical information and modeling》2007,47(4):1599-1608
Virtual screening by molecular docking has become a widely used approach to lead discovery in the pharmaceutical industry when a high-resolution structure of the biological target of interest is available. The performance of three widely used docking programs (Glide, GOLD, and DOCK) for virtual database screening is studied when they are applied to the same protein target and ligand set. Comparisons of the docking programs and scoring functions using a large and diverse data set of pharmaceutically interesting targets and active compounds are carried out. We focus on the problem of docking and scoring flexible compounds which are sterically capable of docking into a rigid conformation of the receptor. The Glide XP methodology is shown to consistently yield enrichments superior to the two alternative methods, while GOLD outperforms DOCK on average. The study also shows that docking into multiple receptor structures can decrease the docking error in screening a diverse set of active compounds. 相似文献
3.
Using the kinases in the DUD dataset and an in-house HTS dataset from PI3K-γ, receptor-based virtual screening experiments
were performed using Glide SP docking. While significant enrichments were observed for eight of the nine targets in the set,
more detailed analyses highlighted that much of the early enrichment (10–80%) is the result of retrieval of a single cluster
of active compounds. This biased retrieval was not necessarily due to early enrichment of the cluster containing the co-crystallized
ligand. Virtual screening validation studies could thus benefit from including cluster-based analyses to assess enrichment
of diverse chemotypes. 相似文献
4.
Kathryn Loving Noeris K. Salam Woody Sherman 《Journal of computer-aided molecular design》2009,23(8):541-554
We have developed a method that uses energetic analysis of structure-based fragment docking to elucidate key features for molecular recognition. This hybrid ligand- and structure-based methodology uses an atomic breakdown of the energy terms from the Glide XP scoring function to locate key pharmacophoric features from the docked fragments. First, we show that Glide accurately docks fragments, producing a root mean squared deviation (RMSD) of <1.0 Å for the top scoring pose to the native crystal structure. We then describe fragment-specific docking settings developed to generate poses that explore every pocket of a binding site while maintaining the docking accuracy of the top scoring pose. Next, we describe how the energy terms from the Glide XP scoring function are mapped onto pharmacophore sites from the docked fragments in order to rank their importance for binding. Using this energetic analysis we show that the most energetically favorable pharmacophore sites are consistent with features from known tight binding compounds. Finally, we describe a method to use the energetically selected sites from fragment docking to develop a pharmacophore hypothesis that can be used in virtual database screening to retrieve diverse compounds. We find that this method produces viable hypotheses that are consistent with known active compounds. In addition to retrieving diverse compounds that are not biased by the co-crystallized ligand, the method is able to recover known active compounds from a database screen, with an average enrichment of 8.1 in the top 1% of the database. 相似文献
5.
McGaughey GB Sheridan RP Bayly CI Culberson JC Kreatsoulas C Lindsley S Maiorov V Truchon JF Cornell WD 《Journal of chemical information and modeling》2007,47(4):1504-1519
Virtual screening benchmarking studies were carried out on 11 targets to evaluate the performance of three commonly used approaches: 2D ligand similarity (Daylight, TOPOSIM), 3D ligand similarity (SQW, ROCS), and protein structure-based docking (FLOG, FRED, Glide). Active and decoy compound sets were assembled from both the MDDR and the Merck compound databases. Averaged over multiple targets, ligand-based methods outperformed docking algorithms. This was true for 3D ligand-based methods only when chemical typing was included. Using mean enrichment factor as a performance metric, Glide appears to be the best docking method among the three with FRED a close second. Results for all virtual screening methods are database dependent and can vary greatly for particular targets. 相似文献
6.
Sheridan RP McGaughey GB Cornell WD 《Journal of computer-aided molecular design》2008,22(3-4):257-265
As an extension to a previous published study (McGaughey et al., J Chem Inf Model 47:1504–1519, 2007) comparing 2D and 3D
similarity methods to docking, we apply a subset of those virtual screening methods (TOPOSIM, SQW, ROCS-color, and Glide)
to a set of protein/ligand pairs where the protein is the target for docking and the cocrystallized ligand is the target for
the similarity methods. Each protein is represented by a maximum of five crystal structures. We search a diverse subset of
the MDDR as well as a diverse small subset of the MCIDB, Merck’s proprietary database. It is seen that the relative effectiveness
of virtual screening methods, as measured by the enrichment factor, is highly dependent on the particular crystal structure
or ligand, and on the database being searched. 2D similarity methods appear very good for the MDDR, but poor for the MCIDB.
However, ROCS-color (a 3D similarity method) does well for both databases.
Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. 相似文献
7.
Sheridan RP 《Journal of chemical information and modeling》2008,48(2):426-433
We introduce two ways of testing the robustness of conclusions from studies comparing virtual screening methods: alternative "global goodness" metrics and sensitivity analysis. While the robustness tests cannot eliminate all biases in virtual screening comparisons, they are useful as a "reality check" for any given study. To illustrate this, we apply them to a set of enrichments published in McGaughey et al. (J. Chem. Inf. Model. 2007, 47, 1504-1519) where 11 target protein/ligand combinations are tested on 2D and 3D similarity methods, plus docking. The major conclusions in that paper, for instance, that ligand-based methods are better than docking methods, hold up. However, some minor conclusions, such as Glide being the best docking method, do not. 相似文献
8.
Repasky MP Murphy RB Banks JL Greenwood JR Tubert-Brohman I Bhat S Friesner RA 《Journal of computer-aided molecular design》2012,26(6):787-799
Glide SP mode enrichment results for two preparations of the DUD dataset and native ligand docking RMSDs for two preparations of the Astex dataset are presented. Following a best-practices preparation scheme, an average RMSD of 1.140 ? for native ligand docking with Glide SP is computed. Following the same best-practices preparation scheme for the DUD dataset an average area under the ROC curve (AUC) of 0.80 and average early enrichment via the ROC (0.1?%) metric of 0.12 were observed. 74 and 56?% of the 39 best-practices prepared targets showed AUC over 0.7 and 0.8, respectively. Average AUC was greater than 0.7 for all best-practices protein families demonstrating consistent enrichment performance across a broad range of proteins and ligand chemotypes. In both Astex and DUD datasets, docking performance is significantly improved employing a best-practices preparation scheme over using minimally-prepared structures from the PDB. Enrichment results for WScore, a new scoring function and sampling methodology integrating WaterMap and Glide, are presented for four DUD targets, hivrt, hsp90, cdk2, and fxa. WScore performance in early enrichment is consistently strong and all systems examined show AUC?>?0.9 and superior early enrichment to DUD best-practices Glide SP results. 相似文献
9.
Sameer Kawatkar Hongming Wang Ryszard Czerminski Diane Joseph-McCarthy 《Journal of computer-aided molecular design》2009,23(8):527-539
Fragment-based drug discovery approaches allow for a greater coverage of chemical space and generally produce high efficiency
ligands. As such, virtual and experimental fragment screening are increasingly being coupled in an effort to identify new
leads for specific therapeutic targets. Fragment docking is employed to create target-focussed subset of compounds for testing
along side generic fragment libraries. The utility of the program Glide with various scoring schemes for fragment docking
is discussed. Fragment docking results for two test cases, prostaglandin D2 synthase and DNA ligase, are presented and compared
to experimental screening data. Self-docking, cross-docking, and enrichment studies are performed. For the enrichment runs,
experimental data exists indicating that the docking decoys in fact do not inhibit the corresponding enzyme being examined.
Results indicate that even for difficult test cases fragment docking can yield enrichments significantly better than random.
Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. 相似文献
10.
Novikov FN Stroylov VS Zeifman AA Stroganov OV Kulkov V Chilov GG 《Journal of computer-aided molecular design》2012,26(6):725-735
Lead Finder is a molecular docking software. Sampling uses an original implementation of the genetic algorithm that involves a number of additional optimization procedures. Lead Finder's scoring functions employ a set of semi-empiric molecular mechanics functionals that have been parameterized independently for docking, binding energy predictions and rank-ordering for virtual screening. Sampling and scoring both utilize a staged approach, moving from fast but less accurate algorithm versions to computationally more intensive but more accurate versions. Lead Finder includes tools for the preparation of full atom protein and ligand models. In this exercise, Lead Finder achieved 72.9% docking success rate on the Astex test set when the original author-prepared full atom models were used, and 74.1% success rate when the structures were prepared by Lead Finder. The major cause of docking failures were scoring errors resulting from the use of imperfect solvation models. In many cases, docking errors could be corrected by the proper protonation and the use of correct cyclic conformations of ligands. In virtual screening experiments on the DUD test set the early enrichment factor of several tens was achieved on average. However, the area under the ROC curve ("AUC ROC") ranged from 0.70 to 0.74 depending on the screening protocol used, and the separation from the null model was not perfect-0.12-0.15 units of AUC ROC. We assume that effective virtual screening in the whole range of enrichment curve and not just at the early enrichment stages requires more accurate solvation modeling and accounting for the protein backbone flexibility. 相似文献
11.
Rao S Sanschagrin PC Greenwood JR Repasky MP Sherman W Farid R 《Journal of computer-aided molecular design》2008,22(9):621-627
While it may seem intuitive that using an ensemble of multiple conformations of a receptor in structure-based virtual screening experiments would necessarily yield improved enrichment of actives relative to using just a single receptor, it turns out that at least in the p38 MAP kinase model system studied here, a very large majority of all possible ensembles do not yield improved enrichment of actives. However, there are combinations of receptor structures that do lead to improved enrichment results. We present here a method to select the ensembles that produce the best enrichments that does not rely on knowledge of active compounds or sophisticated analyses of the 3D receptor structures. In the system studied here, the small fraction of ensembles of up to 3 receptors that do yield good enrichments of actives were identified by selecting ensembles that have the best mean GlideScore for the top 1% of the docked ligands in a database screen of actives and drug-like "decoy" ligands. Ensembles of two receptors identified using this mean GlideScore metric generally outperform single receptors, while ensembles of three receptors identified using this metric consistently give optimal enrichment factors in which, for example, 40% of the known actives outrank all the other ligands in the database. 相似文献
12.
Lee HS Choi J Kufareva I Abagyan R Filikov A Yang Y Yoon S 《Journal of chemical information and modeling》2008,48(3):489-497
Receptor flexibility is a critical issue in structure-based virtual screening methods. Although a multiple-receptor conformation docking is an efficient way to account for receptor flexibility, it is still too slow for large molecular libraries. It was reported that a fast ligand-centric, shape-based virtual screening was more consistent for hit enrichment than a typical single-receptor conformation docking. Thus, we designed a "distributed docking" method that improves virtual high throughput screening by combining a shape-matching method with a multiple-receptor conformation docking. Database compounds are classified in advance based on shape similarities to one of the crystal ligands complexed with the target protein. This classification enables us to pick the appropriate receptor conformation for a single-receptor conformation docking of a given compound, thereby avoiding time-consuming multiple docking. In particular, this approach utilizes cross-docking scores of known ligands to all available receptor structures in order to optimize the algorithm. The present virtual screening method was tested for reidentification of known PPARgamma and p38 MAP kinase active compounds. We demonstrate that this method improves the enrichment while maintaining the computation speed of a typical single-receptor conformation docking. 相似文献
13.
Knox AJ Meegan MJ Carta G Lloyd DG 《Journal of chemical information and modeling》2005,45(6):1908-1919
Structure-based virtual screening (SBVS) utilizing docking algorithms has become an essential tool in the drug discovery process, and significant progress has been made in successfully applying the technique to a wide range of receptor targets. In silico validation of virtual screening protocols before application to a receptor target using a corporate or commercially available compound collection is key to establishing a successful process. Ultimately, retrieval of a set of active compounds from a database of inactives is required, and the metric of enrichment (E) is habitually used to discern the quality of separation of the two. Numerous reports have addressed the performance of docking algorithms with regard to the quality of binding mode prediction and the issue of postprocessing "hit lists" of docked ligands. However, the impact of ligand database preprocessing has yet to be examined in the context of virtual screening and prioritization of compounds for biological evaluation. We provide an insight into the implications of cheminformatic preprocessing of a validation database of compounds where multiple protonated, tautomeric, stereochemical, and conformational states have been enumerated. Several commonly used methods for the generation of ligand conformations and conformational ensembles are examined, paired with an exhaustive rigid-body algorithm for the docking of different "multimeric" compound representations to the ligand binding site of the human estrogen receptor alpha. Chemgauss, a shapegaussian scoring function with intrinsic chemical knowledge, was combined with PLP as a consensus-scoring scheme to rank output from the docking protocol and enrichment rates calculated for each screen. The overheads of CPU consumption and the effect on relative database size (disk requirement) for each of the protocols employed are considered. Assessment of these parameters indicates that SBVS enrichments are highly dependent on the initial cheminformatic treatment(s) used in database construction. The interplay of SMILES representations, stereochemical information, protonation state enumeration, and ligand conformation ensembles are critical in achieving optimum enrichment rates in such screening. 相似文献
14.
15.
Ebalunode JO Ouyang Z Liang J Zheng W 《Journal of chemical information and modeling》2008,48(4):889-901
Computationally efficient structure-based virtual screening methods have recently been reported that seek to find effective means to utilize experimental structure information without employing detailed molecular docking calculations. These tools can be coupled with efficient experimental screening technologies to improve the probability of identifying hits and leads for drug discovery research. Commercial software ROCS (rapid overlay of chemical structures) from Open Eye Scientific is such an example, which is a shape-based virtual screening method using the 3D structure of a ligand, typically from a bound X-ray costructure, as the query. We report here the development of a new structure-based pharmacophore search method (called Shape4) for virtual screening. This method adopts a variant of the ROCS shape technology and expands its use to work with an empty crystal structure. It employs a rigorous computational geometry method and a deterministic geometric casting algorithm to derive the negative image (i.e., pseudoligand) of a target binding site. Once the negative image (or pseudoligand) is generated, an efficient shape comparison algorithm in the commercial OE SHAPE Toolkit is adopted to compare and match small organic molecules with the shape of the pseudoligand. We report the detailed computational protocol and its computational validation using known biologically active compounds extracted from the WOMBAT database. Models derived for five selected targets were used to perform the virtual screening experiments to obtain the enrichment data for various virtual screening methods. It was found that our approach afforded similar or better enrichment ratios than other related methods, often with better diversity among the top ranking computational hits. 相似文献
16.
Shah F Mukherjee P Gut J Legac J Rosenthal PJ Tekwani BL Avery MA 《Journal of chemical information and modeling》2011,51(4):852-864
Malaria, in particular that caused by Plasmodium falciparum , is prevalent across the tropics, and its medicinal control is limited by widespread drug resistance. Cysteine proteases of P. falciparum , falcipain-2 (FP-2) and falcipain-3 (FP-3), are major hemoglobinases, validated as potential antimalarial drug targets. Structure-based virtual screening of a focused cysteine protease inhibitor library built with soft rather than hard electrophiles was performed against an X-ray crystal structure of FP-2 using the Glide docking program. An enrichment study was performed to select a suitable scoring function and to retrieve potential candidates against FP-2 from a large chemical database. Biological evaluation of 50 selected compounds identified 21 diverse nonpeptidic inhibitors of FP-2 with a hit rate of 42%. Atomic Fukui indices were used to predict the most electrophilic center and its electrophilicity in the identified hits. Comparison of predicted electrophilicity of electrophiles in identified hits with those in known irreversible inhibitors suggested the soft-nature of electrophiles in the selected target compounds. The present study highlights the importance of focused libraries and enrichment studies in structure-based virtual screening. In addition, few compounds were screened against homologous human cysteine proteases for selectivity analysis. Further evaluation of structure-activity relationships around these nonpeptidic scaffolds could help in the development of selective leads for antimalarial chemotherapy. 相似文献
17.
Efficient and sufficient incorporation of protein flexibility into docking is still a challenging task. Docking to an ensemble of protein structures has proven its utility for docking, but using a large ensemble of structures can reduce the efficiency of docking and can increase the number of false positives in virtual screening. In this paper, we describe the application of our new methodology, Limoc, to generate an ensemble of holo-like protein structures in combination with the relaxed complex scheme (RCS), to virtual screening. We describe different schemes to reduce the ensemble of protein structures to increase efficiency and enrichment quality. Utilizing experimental knowledge about actives for a target protein allows the reduction of ensemble members to a minimum of three protein structures, increasing enrichment quality and efficiency simultaneously. 相似文献
18.
Vinh NB Simpson JS Scammells PJ Chalmers DK 《Journal of computer-aided molecular design》2012,26(4):409-423
We have used virtual screening to develop models for the binding of aryl substituted heterocycles to p38α MAPK. Virtual screening
was conducted on a number of p38α MAPK crystal structures using a library of 46 known p38α MAPK inhibitors containing a heterocyclic
core substituted by pyridine and fluorophenyl rings (structurally related to SB203580) and a set of decoy compounds. Multiple
protonation states and tautomers of active and decoy compounds were considered. Each docking model was evaluated using receiver
operating characteristic (ROC) curves and enrichment factors. The two best performing single crystal structures were found
to be 1BL7 and 2EWA, with enrichment factors of 14.1 and 13.0 at 2 % of the virtual screen respectively. Ensembles of up to
four receptors of similar conformations were generated, generally giving good or very good performances with high ROC AUCs
and good enrichment. The 1BL7-2EWA ensemble was able to outperform each of its constituent receptors and gave high enrichment
factors of 17.3, 12.0, 8.0 at 2, 5 and 10 % respectively, of the virtual screen. A ROC AUC of 0.94 was obtained for this ensemble.
This method may be applied to other proteins where there are a large number of inhibitor classes with different binding site
conformations. 相似文献
19.
Nanjie Deng William F. Flynn Junchao Xia R. S. K. Vijayan Baofeng Zhang Peng He Ahmet Mentes Emilio Gallicchio Ronald M. Levy 《Journal of computer-aided molecular design》2016,30(9):743-751
We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein–ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity. 相似文献
20.
Candida Manelfi Jonas Gossen Silvia Gervasoni Carmine Talarico Simone Albani Benjamin Joseph Philipp Francesco Musiani Giulio Vistoli Giulia Rossetti Andrea Rosario Beccari Alessandro Pedretti 《Molecules (Basel, Switzerland)》2021,26(4)
The 3CL-Protease appears to be a very promising medicinal target to develop anti-SARS-CoV-2 agents. The availability of resolved structures allows structure-based computational approaches to be carried out even though the lack of known inhibitors prevents a proper validation of the performed simulations. The innovative idea of the study is to exploit known inhibitors of SARS-CoV 3CL-Pro as a training set to perform and validate multiple virtual screening campaigns. Docking simulations using four different programs (Fred, Glide, LiGen, and PLANTS) were performed investigating the role of both multiple binding modes (by binding space) and multiple isomers/states (by developing the corresponding isomeric space). The computed docking scores were used to develop consensus models, which allow an in-depth comparison of the resulting performances. On average, the reached performances revealed the different sensitivity to isomeric differences and multiple binding modes between the four docking engines. In detail, Glide and LiGen are the tools that best benefit from isomeric and binding space, respectively, while Fred is the most insensitive program. The obtained results emphasize the fruitful role of combining various docking tools to optimize the predictive performances. Taken together, the performed simulations allowed the rational development of highly performing virtual screening workflows, which could be further optimized by considering different 3CL-Pro structures and, more importantly, by including true SARS-CoV-2 3CL-Pro inhibitors (as learning set) when available. 相似文献