| 1. |
- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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| 2. |
- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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| 3. |
- Thomas, HS, et al.
(author)
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- 2019
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swepub:Mat__t
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| 4. |
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| 5. |
- Ballante, Flavio, et al.
(author)
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An Automated Strategy for Binding-Pose Selection and Docking Assessment in Structure-Based Drug Design.
- 2016
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In: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 56:1, s. 54-72
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Journal article (peer-reviewed)abstract
- Molecular docking is a widely used technique in drug design to predict the binding pose of a candidate compound in a defined therapeutic target. Numerous docking protocols are available, each characterized by different search methods and scoring functions, thus providing variable predictive capability on a same ligand-protein system. To validate a docking protocol, it is necessary to determine a priori the ability to reproduce the experimental binding pose (i.e., by determining the docking accuracy (DA)) in order to select the most appropriate docking procedure and thus estimate the rate of success in docking novel compounds. As common docking programs use generally different root-mean-square deviation (RMSD) formulas, scoring functions, and format results, it is both difficult and time-consuming to consistently determine and compare their predictive capabilities in order to identify the best protocol to use for the target of interest and to extrapolate the binding poses (i.e., best-docked (BD), best-cluster (BC), and best-fit (BF) poses) when applying a given docking program over thousands/millions of molecules during virtual screening. To reduce this difficulty, two new procedures called Clusterizer and DockAccessor have been developed and implemented for use with some common and "free-for-academics" programs such as AutoDock4, AutoDock4(Zn), AutoDock Vina, DOCK, MpSDockZn, PLANTS, and Surflex-Dock to automatically extrapolate BD, BC, and BF poses as well as to perform consistent cluster and DA analyses. Clusterizer and DockAccessor (code available over the Internet) represent two novel tools to collect computationally determined poses and detect the most predictive docking approach. Herein an application to human lysine deacetylase (hKDAC) inhibitors is illustrated.
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| 6. |
- Ballante, Flavio, et al.
(author)
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Comprehensive model of wild-type and mutant HIV-1 reverse transciptases.
- 2012
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In: Journal of Computer-Aided Molecular Design. - : Springer Science+Business Media B.V.. - 0920-654X .- 1573-4951. ; 26:8, s. 907-19
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Journal article (peer-reviewed)abstract
- An enhanced version of COMBINE that uses both ligand-based and structure-based alignment of ligands has been used to build a comprehensive 3-D QSAR model of wild-type HIV-1 reverse transcriptase and drug-resistant mutants. The COMBINEr model focused on 7 different RT enzymes complexed with just two HIV-RT inhibitors, niverapine (NVP) and efavirenz (EFV); therefore, 14 inhibitor/enzyme complexes comprised the training set. An external test set of chiral 2-(alkyl/aryl)amino-6-benzylpyrimidin-4(3H)-ones (DABOs) was used to test predictability. The COMBINEr model MC4, although developed using only two inhibitors, predicted the experimental activities of the test set with an acceptable average absolute error of prediction (0.89 pK (i)). Most notably, the model was able to correctly predict the right eudismic ratio for two R/S pairs of DABO derivatives. The enhanced COMBINEr approach was developed using only software freely available to academics.
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| 7. |
- Ballante, Flavio, et al.
(author)
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Structural insights of SmKDAC8 inhibitors : Targeting Schistosoma epigenetics through a combined structure-based 3D QSAR, in vitro and synthesis strategy.
- 2017
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In: Bioorganic & Medicinal Chemistry. - : Elsevier BV. - 0968-0896 .- 1464-3391. ; 25:7, s. 2105-2132
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Journal article (peer-reviewed)abstract
- A predictive structure-based 3D QSAR (COMBINEr 2.0) model of the Schistosoma mansoni lysine deacetylase 8 enzyme (SmKDAC8) was developed, validated and used to perform virtual screening (VS) of the NCI Diversity Set V database (1593 compounds). Three external datasets (with congeneric structures to those experimentally resolved in complexes by X-ray and previously reported as SmKDAC8 inhibitors) were employed to compose and validate the most predictive model. Two series characterized by 104 benzodiazepine derivatives (BZDs) and 60 simplified largazole analogs (SLAs), recently reported by our group as human KDAC inhibitors, were tested for their inhibition potency against SmKDAC8 to probe the predictive capability of the quantitative models against compounds with diverse structures. The SmKDAC8 biochemical results confirmed: (1) the benzodiazepine moiety as a valuable scaffold to further investigate when pursuing SmKDAC8 inhibition; (2) the predictive capability of the COMBINEr 2.0 model towards non-congeneric series of compounds, highlighting the most influencing ligand-protein interactions and refining the structure-activity relationships. From the VS investigations, the first 40 top-ranked compounds were obtained and biologically tested for their inhibition potency against SmKDAC8 and hKDACs 1, 3, 6 and 8. Among them, a non-hydroxamic acid benzothiadiazine dioxide derivative (code NSC163639), showed interesting activity and selectivity against SmKDAC8. To further elucidate the structure-activity relationships of NSC163639, two analogs (herein reported as compounds 3 and 4) were synthesized and biologically evaluated. Results suggest the benzothiadiazine dioxide moiety as a promising scaffold to be used in a next step to derive selective SmKDAC8 inhibitors.
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| 8. |
- Berglund, Anders, et al.
(author)
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ProVal : A protein-scoring function for the selection of native and near-native folds
- 2004
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In: Proteins. - : Wiley-Liss, Inc. - 0887-3585 .- 1097-0134. ; 54:2, s. 289-302
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Journal article (peer-reviewed)abstract
- A low-resolution scoring function for the selection of native and near-native structures from a set of predicted structures for a given protein sequence has been developed. The scoring function, ProVal (Protein Validate), used several variables that describe an aspect of protein structure for which the proximity to the native structure can be assessed quantitatively. Among the parameters included are a packing estimate, surface areas, and the contact order. A partial least squares for latent variables (PLS) model was built for each candidate set of the 28 decoy sets of structures generated for 22 different proteins using the described parameters as independent variables. The C(alpha) RMS of the candidate structures versus the experimental structure was used as the dependent variable. The final generalized scoring function was an average of all models derived, ensuring that the function was not optimized for specific fold classes or method of structure generation of the candidate folds. The results show that the crystal structure was scored best in 64% of the 28 test sets and was clearly separated from the decoys in many examples. In all the other cases in which the crystal structure did not rank first, it ranked within the top 10%. Thus, although ProVal could not distinguish between predicted structures that were similar overall in fold quality due to its inherently low resolution, it can clearly be used as a primary filter to eliminate approximately 90% of fold candidates generated by current prediction methods from all-atom modeling and further evaluation. The correlation between the predicted and actual C(alpha) RMS values varies considerably between the candidate fold sets.
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| 9. |
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| 10. |
- Marshall, Garland R, et al.
(author)
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Limiting Assumptions in the Design of Peptidomimetics
- 2017
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In: Drug development research. - : Wiley. - 0272-4391 .- 1098-2299. ; 78:6, s. 245-267
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Research review (peer-reviewed)abstract
- Limiting the flexibility of organic compounds to enhance their affinity and selectivity for targeting a macromolecule involved in molecular recognition has become a well-developed paradigm in medicinal chemistry. While the role of reverse-turn motifs as peptidomimetics has received the most attention, β-sheets and helices are also important motifs for protein/protein interactions. The more complicated problem of mimicking the interacting surface of noncontiguous epitopes will not be considered in this review. This limited overview focuses on efforts to use amino acid synthons as secondary-structure mimetics as well as providing examples of peptidomimetic design focused on nonpeptide synthetic chemistry in contrast. In particular, the rationale of optimal design criteria for mimicry and the many naïve violations of those criteria made in its pursuit are emphasized.
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