| 1. |
- Abraham, Mark James, et al.
(författare)
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Sharing Data from Molecular Simulations
- 2019
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Ingår i: Journal of Chemical Information and Modeling. - : AMER CHEMICAL SOC. - 1549-9596 .- 1549-960X. ; 59:10, s. 4093-4099
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Tidskriftsartikel (refereegranskat)abstract
- Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations has become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 (https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way toward more open, interoperable, and reproducible outputs coming from research studies using MD simulations.
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| 2. |
- Aftab, Obaid, 1984-, et al.
(författare)
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NMR spectroscopy based metabolic profiling of drug induced changes in vitro can discriminate between pharmacological classes
- 2014
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Ingår i: Journal of chemical information and modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 54:11, s. 3251-3258
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Tidskriftsartikel (refereegranskat)abstract
- Drug induced changes in mammalian cell line models have already been extensively profiled at the systemic mRNA level and subsequently used to suggest mechanisms of action for new substances as well as to support drug repurposing, i.e. identifying new potential indications for drugs already licensed for other pharmacotherapy settings. The seminal work in this field, which includes a large database and computational algorithms for pattern matching, is known as the “Connectivity Map” (CMap). The potential of similar exercises at the metabolite level is, however, still largely unexplored. Only recently the first high throughput metabolomic assay pilot study was published, involving screening of metabolic response to a set of 56 kinase inhibitors in a 96-well format. Here we report results from a separately developed metabolic profiling assay, which leverages 1H NMR spectroscopy to the quantification of metabolic changes in the HCT116 colorectal cancer cell line, in response to each of 26 compounds. These agents are distributed across 12 different pharmacological classes covering a broad spectrum of bioactivity. Differential metabolic profiles, inferred from multivariate spectral analysis of 18 spectral bins, allowed clustering of most tested drugs according to their respective pharmacological class. A more advanced supervised analysis, involving one multivariate scattering matrix per pharmacological class and using only 3 spectral bins (three metabolites), showed even more distinct pharmacology-related cluster formations. In conclusion, this kind of relatively fast and inexpensive profiling seems to provide a promising alternative to that afforded by mRNA expression analysis, which is relatively slow and costly. As also indicated by the present pilot study, the resulting metabolic profiles do not seem to provide as information rich signatures as those obtained using systemic mRNA profiling, but the methodology holds strong promise for significant refinement.
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| 3. |
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| 4. |
- Ahlström, Marie M, et al.
(författare)
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Virtual screening and scaffold hopping based on GRID molecular interaction fields.
- 2005
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Ingår i: Journal of chemical information and modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 45:5, s. 1313-23
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Tidskriftsartikel (refereegranskat)abstract
- In this study, a set of strategies for structure-based design using GRID molecular interaction fields (MIFs) to derive a pharmacophoric representation of a protein is reported. Thrombin, one of the key enzymes involved in the blood coagulation cascade, was chosen as the model system since abundant published experimental data are available related to both crystal structures and structurally diverse sets of inhibitors. First, a virtual screening methodology was developed either using a pharmacophore representation of the protein based on GRID MIFs or using GRID MIFs from the 3D structure of a set of chosen thrombin inhibitors. The search was done in a 3D multiconformation version of the Available Chemical Directory (ACD) database, which had been spiked with 262 known thrombin inhibitors (multiple conformers available per compound). The model managed to find 80% of the known thrombin inhibitors among the 74,291 conformers in the ACD by only searching 5% of the database; hence, a 15-fold enrichment of the library was achieved. Second, a scaffold hopping methodology was developed using GRID MIFs, giving the scaffold interaction pattern and the shape of the scaffold, together with the distance between the anchor points. The scaffolds reported by Dolle in the Journal of Combinatorial Chemistry summaries (2000 and 2001) and scaffolds built or derived from ligands cocomplexed with the thrombin enzyme were parameterized using a new set of descriptors and saved into a searchable database. The scaffold representation from the database was then compared to a template scaffold (from a thrombin crystal structure), and the thrombin-derived scaffolds included in the database were found among the top solutions. To validate the usefulness of the methodology to replace the template scaffold, the entire molecule was built (scaffold and side chains) and the resulting compounds were docked into the active site of thrombin. The docking solutions showed the same binding pattern as the cocomplexed compound, hence, showing that this method can be a valuable tool for medicinal chemists to select interchangeable core structures (scaffolds) in an easy manner and retaining the binding properties from the original ligand.
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| 5. |
- Alogheli, Hiba, et al.
(författare)
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Docking of Macrocycles : Comparing Rigid and Flexible Docking in Glide
- 2017
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 57:2, s. 190-202
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, there has been an increased interest in using macrocyclic compounds for drug discovery and development. For docking of these commonly large and flexible compounds to be addressed, a screening and a validation set were assembled from the PDB consisting of 16 and 31 macrocycle-containing protein complexes, respectively. The macrocycles were docked in Glide by rigid docking of pregenerated conformational ensembles produced by the macrocycle conformational sampling method (MCS) in Schrödinger Release 2015-3 or by direct Glide flexible docking after performing ring-templating. The two protocols were compared to rigid docking of pregenerated conformational ensembles produced by an exhaustive Monte Carlo multiple minimum (MCMM) conformational search and a shorter MCMM conformational search (MCMM-short). The docking accuracy was evaluated and expressed as the RMSD between the heavy atoms of the ligand as found in the X-ray structure after refinement and the poses obtained by the docking protocols. The median RMSD values for top-scored poses of the screening set were 0.83, 0.80, 0.88, and 0.58 Å for MCMM, MCMM-short, MCS, and Glide flexible docking, respectively. There was no statistically significant difference in the performance between rigid docking of pregenerated conformations produced by the MCS and direct docking using Glide flexible docking. However, the flexible docking protocol was 2-times faster in docking the screening set compared to that of the MCS protocol. In a final study, the new Prime-MCS method was evaluated in Schrödinger Release 2016-3. This method is faster compared that of to MCS; however, the conformations generated were found to be suboptimal for rigid docking. Therefore, on the basis of timing, accuracy, and ease of set up, standard Glide flexible docking with prior ring-templating is recommended over current gold standard protocols using rigid docking of pregenerated conformational ensembles.
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| 6. |
- Alvarsson, Jonathan, et al.
(författare)
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Benchmarking Study of Parameter Variation When Using Signature Fingerprints Together with Support Vector Machines
- 2014
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 54:11, s. 3211-3217
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Tidskriftsartikel (refereegranskat)abstract
- QSAR modeling using molecular signatures and support vector machines with a radial basis function is increasingly used for virtual screening in the drug discovery field. This method has three free parameters: C, ?, and signature height. C is a penalty parameter that limits overfitting, ? controls the width of the radial basis function kernel, and the signature height determines how much of the molecule is described by each atom signature. Determination of optimal values for these parameters is time-consuming. Good default values could therefore save considerable computational cost. The goal of this project was to investigate whether such default values could be found by using seven public QSAR data sets spanning a wide range of end points and using both a bit version and a count version of the molecular signatures. On the basis of the experiments performed, we recommend a parameter set of heights 0 to 2 for the count version of the signature fingerprints and heights 0 to 3 for the bit version. These are in combination with a support vector machine using C in the range of 1 to 100 and gamma in the range of 0.001 to 0.1. When data sets are small or longer run times are not a problem, then there is reason to consider the addition of height 3 to the count fingerprint and a wider grid search. However, marked improvements should not be expected.
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| 7. |
- Alvarsson, Jonathan, et al.
(författare)
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Ligand-Based Target Prediction with Signature Fingerprints
- 2014
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 54:10, s. 2647-2653
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Tidskriftsartikel (refereegranskat)abstract
- When evaluating a potential drug candidate it is desirable to predict target interactions in silico prior to synthesis in order to assess, e.g., secondary pharmacology. This can be done by looking at known target binding profiles of similar compounds using chemical similarity searching. The purpose of this study was to construct and evaluate the performance of chemical fingerprints based on the molecular signature descriptor for performing target binding predictions. For the comparison we used the area under the receiver operating characteristics curve (AUC) complemented with net reclassification improvement (NRI). We created two open source signature fingerprints, a bit and a count version, and evaluated their performance compared to a set of established fingerprints with regards to predictions of binding targets using Tanimoto-based similarity searching on publicly available data sets extracted from ChEMBL. The results showed that the count version of the signature fingerprint performed on par with well-established fingerprints such as ECFP. The count version outperformed the bit version slightly; however, the count version is more complex and takes more computing time and memory to run so its usage should probably be evaluated on a case-by-case basis. The NRI based tests complemented the AUC based ones and showed signs of higher power.
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| 8. |
- Alzghoul, Ahmad, et al.
(författare)
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Experimental and Computational Prediction of Glass Transition Temperature of Drugs
- 2014
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Ingår i: JOURNAL OF CHEMICAL INFORMATION AND MODELING. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 54:12, s. 3396-3403
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Tidskriftsartikel (refereegranskat)abstract
- Glass transition temperature (T-g) is an important inherent property of an amorphous solid material which is usually determined experimentally. In this study, the relation between T-g and melting temperature (T-m) was evaluated using a data set of 71 structurally diverse druglike compounds. Further, in silico models for prediction of T-g were developed based on calculated molecular descriptors and linear (multilinear regression, partial least-squares, principal component regression) and nonlinear (neural network, support vector regression) modeling techniques. The models based on T-m predicted T-g with an RMSE of 19.5 K for the test set. Among the five computational models developed herein the support vector regression gave the best result with RMSE of 18.7 K for the test set using only four chemical descriptors. Hence, two different models that predict T-g of drug-like molecules with high accuracy were developed. If T-m is available, a simple linear regression can be used to predict T-g. However, the results also suggest that support vector regression and calculated molecular descriptors can predict T-g with equal accuracy, already before compound synthesis.
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| 9. |
- Amarasinghe, Kosala N., et al.
(författare)
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Virtual Screening Expands the Non-Natural Amino Acid Palette for Peptide Optimization
- 2022
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Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 62:12, s. 2999-3007
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Tidskriftsartikel (refereegranskat)abstract
- Peptides are an important modality in drug discovery. While current peptide optimization focuses predominantly on the small number of natural and commercially available non-natural amino acids, the chemical spaces available for small molecule drug discovery are in the billions of molecules. In the present study, we describe the development of a large virtual library of readily synthesizable non-natural amino acids that can power the virtual screening protocols and aid in peptide optimization. To that end, we enumerated nearly 380 thousand amino acids and demonstrated their vast chemical diversity compared to the 20 natural and commercial residues. Furthermore, we selected a diverse ten thousand amino acid subset to validate our virtual screening workflow on the Keap1-Neh2 complex model system. Through in silico mutations of Neh2 peptide residues to those from the virtual library, our docking-based protocol identified a number of possible solutions with a significantly higher predicted affinity toward the Keap1 protein. This protocol demonstrates that the non-natural amino acid chemical space can be massively extended and virtually screened with a reasonable computational cost.
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| 10. |
- Andersson, Claes R., et al.
(författare)
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In vitro drug sensitivity-gene expression correlations involve a tissue of origin dependency
- 2007
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Ingår i: Journal of chemical information and modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 47:1, s. 239-248
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Tidskriftsartikel (refereegranskat)abstract
- A major concern of chemogenomics is to associate drug activity with biological variables. Several reports have clustered cell line drug activity profiles as well as drug activity-gene expression correlation profiles and noted that the resulting groupings differ but still reflect mechanism of action. The present paper shows that these discrepancies can be viewed as a weighting of drug-drug distances, the weights depending on which cell lines the two drugs differ in.
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