Conformational Sampling for Large-Scale Virtual Screening: Accuracy versus Ensemble Size

2009 ◽  
Vol 49 (10) ◽  
pp. 2303-2311 ◽  
Author(s):  
Axel Griewel ◽  
Ole Kayser ◽  
Jochen Schlosser ◽  
Matthias Rarey
Keyword(s):  
Virtual Screening ◽  
Large Scale ◽  
Conformational Sampling ◽  
Ensemble Size ◽  
Screening Accuracy

scholarly journals A novel ligand of the translationally controlled tumor protein (TCTP) identified by virtual drug screening for cancer differentiation therapy

2021 ◽  
Author(s):  
Nicolas Fischer ◽  
Ean-Jeong Seo ◽  
Sara Abdelfatah ◽  
Edmond Fleischer ◽  
Anette Klinger ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Virtual Screening ◽  
Small Molecules ◽  
Large Scale ◽  
Differentiation Therapy ◽  
P53 Expression ◽  
Microscale Thermophoresis ◽  
Cycle Arrest ◽  
G1 Cell Cycle Arrest ◽  
Mcf 7

SummaryIntroduction Differentiation therapy is a promising strategy for cancer treatment. The translationally controlled tumor protein (TCTP) is an encouraging target in this context. By now, this field of research is still at its infancy, which motivated us to perform a large-scale screening for the identification of novel ligands of TCTP. We studied the binding mode and the effect of TCTP blockade on the cell cycle in different cancer cell lines. Methods Based on the ZINC-database, we performed virtual screening of 2,556,750 compounds to analyze the binding of small molecules to TCTP. The in silico results were confirmed by microscale thermophoresis. The effect of the new ligand molecules was investigated on cancer cell survival, flow cytometric cell cycle analysis and protein expression by Western blotting and co-immunoprecipitation in MOLT-4, MDA-MB-231, SK-OV-3 and MCF-7 cells. Results Large-scale virtual screening by PyRx combined with molecular docking by AutoDock4 revealed five candidate compounds. By microscale thermophoresis, ZINC10157406 (6-(4-fluorophenyl)-2-[(8-methoxy-4-methyl-2-quinazolinyl)amino]-4(3H)-pyrimidinone) was identified as TCTP ligand with a KD of 0.87 ± 0.38. ZINC10157406 revealed growth inhibitory effects and caused G0/G1 cell cycle arrest in MOLT-4, SK-OV-3 and MCF-7 cells. ZINC10157406 (2 × IC50) downregulated TCTP expression by 86.70 ± 0.44% and upregulated p53 expression by 177.60 ± 12.46%. We validated ZINC10157406 binding to the p53 interaction site of TCTP and replacing p53 by co-immunoprecipitation. Discussion ZINC10157406 was identified as potent ligand of TCTP by in silico and in vitro methods. The compound bound to TCTP with a considerably higher affinity compared to artesunate as known TCTP inhibitor. We were able to demonstrate the effect of TCTP blockade at the p53 binding site, i.e. expression of TCTP decreased, whereas p53 expression increased. This effect was accompanied by a dose-dependent decrease of CDK2, CDK4, CDK, cyclin D1 and cyclin D3 causing a G0/G1 cell cycle arrest in MOLT-4, SK-OV-3 and MCF-7 cells. Our findings are supposed to stimulate further research on TCTP-specific small molecules for differentiation therapy in oncology.

Proactive Optimization of Intelligent-Well Production Using Stochastic Gradient-Based Algorithms

2016 ◽  
Vol 19 (02) ◽  
pp. 239-252 ◽  
Author(s):  
Morteza Haghighat Sefat ◽  
Khafiz M. Muradov ◽  
Ahmed H. Elsheikh ◽  
David R. Davies
Keyword(s):  
Large Scale ◽  
Optimization Problem ◽  
Stochastic Gradient ◽  
Real Field ◽  
Directional Derivatives ◽  
Optimization Approach ◽  
Layer By Layer ◽  
Monitoring And Control ◽  
Ensemble Size ◽  
Local Optima

Summary The popularity of intelligent wells (I-wells), which provide layer-by-layer monitoring and control capability of production and injection, is growing. However, the number of available techniques for optimal control of I-wells is limited (Sarma et al. 2006; Alghareeb et al. 2009; Almeida et al. 2010; Grebenkin and Davies 2012). Currently, most of the I-wells that are equipped with interval control valves (ICVs) are operated to enhance the current production and to resolve problems associated with breakthrough of the unfavorable phase. This reactive strategy is unlikely to deliver the long-term optimum production. On the other side, the proactive-control strategy of I-wells, with its ambition to provide the optimum control for the entire well's production life, has the potential to maximize the cumulative oil production. This strategy, however, results in a high-dimensional, nonlinear, and constrained optimization problem. This study provides guidelines on selecting a suitable proactive optimization approach, by use of state-of-the-art stochastic gradient-approximation algorithms. A suitable optimization approach increases the practicality of proactive optimization for real field models under uncertain operational and subsurface conditions. We evaluate the simultaneous-perturbation stochastic approximation (SPSA) method (Spall 1992) and the ensemble-based optimization (EnOpt) method (Chen et al. 2009). In addition, we present a new derivation of the EnOpt by use of the concept of directional derivatives. The numerical results show that both SPSA and EnOpt methods can provide a fast solution to a large-scale and multiple I-well proactive optimization problem. A criterion for tuning the algorithms is proposed and the performance of both methods is compared for several test cases. The used methodology for estimating the gradient is shown to affect the application area of each algorithm. SPSA provides a rough estimate of the gradient and performs better in search environments, characterized by several local optima, especially with a large ensemble size. EnOpt was found to provide a smoother estimation of the gradient, resulting in a more-robust algorithm to the choice of the tuning parameters, and a better performance with a small ensemble size. Moreover, the final optimum operation obtained by EnOpt is smoother. Finally, the obtained criteria are used to perform proactive optimization of ICVs in a real field.

scholarly journals Computational generation of an annotated gigalibrary of synthesizable, composite peptidic macrocycles

2020 ◽  
Vol 117 (40) ◽  
pp. 24679-24690
Author(s):  
Ishika Saha ◽  
Eric K. Dang ◽  
Dennis Svatunek ◽  
Kendall N. Houk ◽  
Patrick G. Harran
Keyword(s):  
Virtual Screening ◽  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Three Dimensional ◽  
Pharmacological Properties ◽  
Robust Methods ◽  
Small Peptide ◽  
Multistep Reaction ◽  
Condensed Heterocycles

Peptidomimetic macrocycles have the potential to regulate challenging therapeutic targets. Structures of this type having precise shapes and drug-like character are particularly coveted, but are relatively difficult to synthesize. Our laboratory has developed robust methods that integrate small-peptide units into designed scaffolds. These methods create macrocycles and embed condensed heterocycles to diversify outcomes and improve pharmacological properties. The hypothetical scope of the methodology is vast and far outpaces the capacity of our experimental format. We now describe a computational rendering of our methodology that creates an in silico three-dimensional library of composite peptidic macrocycles. Our open-source platform, CPMG (Composite Peptide Macrocycle Generator), has algorithmically generated a library of 2,020,794,198 macrocycles that can result from the multistep reaction sequences we have developed. Structures are generated based on predicted site reactivity and filtered on the basis of physical and three-dimensional properties to identify maximally diverse compounds for prioritization. For conformational analyses, we also introduce ConfBuster++, an RDKit port of the open-source software ConfBuster, which allows facile integration with CPMG and ready parallelization for better scalability. Our approach deeply probes ligand space accessible via our synthetic methodology and provides a resource for large-scale virtual screening.

Large-scale virtual screening for the identification of new Helicobacter pylori urease inhibitor scaffolds

2011 ◽  
Vol 18 (7) ◽  
pp. 2917-2927 ◽  
Author(s):  
Homa Azizian ◽  
Farzaneh Nabati ◽  
Amirhossein Sharifi ◽  
Farideh Siavoshi ◽  
Mohammad Mahdavi ◽  
...  
Keyword(s):  
Helicobacter Pylori ◽  
Virtual Screening ◽  
Large Scale ◽  
Urease Inhibitor ◽  
Inhibitor Scaffolds

Large-scale virtual screening for discovering leads in the postgenomic era

2001 ◽  
Vol 40 (2) ◽  
pp. 360-376 ◽  
Author(s):  
B. Waszkowycz ◽  
T. D. J. Perkins ◽  
R. A. Sykes ◽  
J. Li
Keyword(s):  
Virtual Screening ◽  
Large Scale

scholarly journals Assessment of a Nonlinear Ensemble Transform Filter for High-Dimensional Data Assimilation

2016 ◽  
Vol 144 (1) ◽  
pp. 409-427 ◽  
Author(s):  
Julian Tödter ◽  
Paul Kirchgessner ◽  
Lars Nerger ◽  
Bodo Ahrens
Keyword(s):  
Data Assimilation ◽  
Particle Filtering ◽  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Second Order ◽  
High Dimensional ◽  
Deterministic System ◽  
Ensemble Size ◽  
Ensemble Transform

Abstract This work assesses the large-scale applicability of the recently proposed nonlinear ensemble transform filter (NETF) in data assimilation experiments with the NEMO ocean general circulation model. The new filter constitutes a second-order exact approximation to fully nonlinear particle filtering. Thus, it relaxes the Gaussian assumption contained in ensemble Kalman filters. The NETF applies an update step similar to the local ensemble transform Kalman filter (LETKF), which allows for efficient and simple implementation. Here, simulated observations are assimilated into a simplified ocean configuration that exhibits globally high-dimensional dynamics with a chaotic mesoscale flow. The model climatology is used to initialize an ensemble of 120 members. The number of observations in each local filter update is of the same order resulting from the use of a realistic oceanic observation scenario. Here, an importance sampling particle filter (PF) would require at least 106 members. Despite the relatively small ensemble size, the NETF remains stable and converges to the truth. In this setup, the NETF achieves at least the performance of the LETKF. However, it requires a longer spinup period because the algorithm only relies on the particle weights at the analysis time. These findings show that the NETF can successfully deal with a large-scale assimilation problem in which the local observation dimension is of the same order as the ensemble size. Thus, the second-order exact NETF does not suffer from the PF’s curse of dimensionality, even in a deterministic system.

Large-Scale Systematic Analysis of 2D Fingerprint Methods and Parameters to Improve Virtual Screening Enrichments

2010 ◽  
Vol 50 (5) ◽  
pp. 771-784 ◽  
Author(s):  
Madhavi Sastry ◽  
Jeffrey F. Lowrie ◽  
Steven L. Dixon ◽  
Woody Sherman
Keyword(s):  
Virtual Screening ◽  
Large Scale ◽  
Systematic Analysis

scholarly journals A Multi-Pronged Approach Targeting SARS-CoV-2 Proteins Using Ultra-Large Virtual Screening

2020 ◽  
Author(s):  
Christoph Gorgulla ◽  
Krishna PadmanabhaDas ◽  
Kendra E. Leigh ◽  
Marco Cespugli ◽  
Patrick D. Fischer ◽  
...  
Keyword(s):  
Virtual Screening ◽  
In Silico ◽  
Active Sites ◽  
Large Scale ◽  
Protein Protein Interaction ◽  
The Face ◽  
Computing Platforms ◽  
Screening Platform ◽  
Novel Coronavirus ◽  
Further Development

<p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), previously known as 2019 novel coronavirus (2019-nCoV), has spread rapidly across the globe, creating an unparalleled global health burden and spurring a deepening economic crisis. As of July 7th, 2020, almost seven months into the outbreak, there are no approved vaccines and few treatments available. Developing drugs that target multiple points in the viral life cycle could serve as a strategy to tackle the current as well as future coronavirus pandemics. Here we leverage the power of our recently developed <i>in silico</i> screening platform, VirtualFlow, to identify inhibitors that target SARS-CoV-2. VirtualFlow is able to efficiently harness the power of computing clusters and cloud-based computing platforms to carry out ultra-large scale virtual screens. In this unprecedented structure-based multi-target virtual screening campaign, we have used VirtualFlow to screen an average of approximately 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets in the cloud. In addition to targeting the active sites of viral enzymes, we also target critical auxiliary sites such as functionally important protein-protein interaction interfaces. This multi-target approach not only increases the likelihood of finding a potent inhibitor, but could also help identify a collection of anti-coronavirus drugs that would retain efficacy in the face of viral mutation. Drugs belonging to different regimen classes could be combined to develop possible combination therapies, and top hits that bind at highly conserved sites would be potential candidates for further development as coronavirus drugs. Here, we present the top 200 <i>in silico</i> hits for each target site. While in-house experimental validation of some of these compounds is currently underway, we want to make this array of potential inhibitor candidates available to researchers worldwide in consideration of the pressing need for fast-tracked drug development.</p>

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