| 1. |
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| 2. |
- Andersson, C. David, et al.
(författare)
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Benefits of statistical molecular design, covariance analysis, and reference models in QSAR : a case study on acetylcholinesterase
- 2015
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Ingår i: Journal of Computer-Aided Molecular Design. - : Springer Science and Business Media LLC. - 0920-654X .- 1573-4951. ; 29:3, s. 199-215
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Tidskriftsartikel (refereegranskat)abstract
- Scientific disciplines such as medicinal- and environmental chemistry, pharmacology, and toxicology deal with the questions related to the effects small organic compounds exhort on biological targets and the compounds' physicochemical properties responsible for these effects. A common strategy in this endeavor is to establish structure-activity relationships (SARs). The aim of this work was to illustrate benefits of performing a statistical molecular design (SMD) and proper statistical analysis of the molecules' properties before SAR and quantitative structure-activity relationship (QSAR) analysis. Our SMD followed by synthesis yielded a set of inhibitors of the enzyme acetylcholinesterase (AChE) that had very few inherent dependencies between the substructures in the molecules. If such dependencies exist, they cause severe errors in SAR interpretation and predictions by QSAR-models, and leave a set of molecules less suitable for future decision-making. In our study, SAR- and QSAR models could show which molecular sub-structures and physicochemical features that were advantageous for the AChE inhibition. Finally, the QSAR model was used for the prediction of the inhibition of AChE by an external prediction set of molecules. The accuracy of these predictions was asserted by statistical significance tests and by comparisons to simple but relevant reference models.
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| 3. |
- Ballante, Flavio, et al.
(författare)
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Comprehensive model of wild-type and mutant HIV-1 reverse transciptases.
- 2012
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Ingår i: 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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Tidskriftsartikel (refereegranskat)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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| 4. |
- Basu, Sankar Chandra, et al.
(författare)
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Proteus: a random forest classifier to predict disorder-to-order transitioning binding regions in intrinsically disordered proteins
- 2017
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Ingår i: Journal of Computer-Aided Molecular Design. - : SPRINGER. - 0920-654X .- 1573-4951. ; 31:5, s. 453-466
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Tidskriftsartikel (refereegranskat)abstract
- The focus of the computational structural biology community has taken a dramatic shift over the past one-and-a-half decades from the classical protein structure prediction problem to the possible understanding of intrinsically disordered proteins (IDP) or proteins containing regions of disorder (IDPR). The current interest lies in the unraveling of a disorder-to-order transitioning code embedded in the amino acid sequences of IDPs/ IDPRs. Disordered proteins are characterized by an enormous amount of structural plasticity which makes them promiscuous in binding to different partners, multi-functional in cellular activity and atypical in folding energy landscapes resembling partially folded molten globules. Also, their involvement in several deadly human diseases (e.g. cancer, cardiovascular and neurodegenerative diseases) makes them attractive drug targets, and important for a biochemical understanding of the disease(s). The study of the structural ensemble of IDPs is rather difficult, in particular for transient interactions. When bound to a structured partner, an IDPR adapts an ordered conformation in the complex. The residues that undergo this disorder-to-order transition are called protean residues, generally found in short contiguous stretches and the first step in understanding the modus operandi of an IDP/IDPR would be to predict these residues. There are a few available methods which predict these protean segments from their amino acid sequences; however, their performance reported in the literature leaves clear room for improvement. With this background, the current study presents Proteus, a random forest classifier that predicts the likelihood of a residue undergoing a disorder-toorder transition upon binding to a potential partner protein. The prediction is based on features that can be calculated using the amino acid sequence alone. Proteus compares favorably with existing methods predicting twice as many true positives as the second best method (55 vs. 27%) with a much higher precision on an independent data set. The current study also sheds some light on a possible disorderto-order transitioning consensus, untangled, yet embedded in the amino acid sequence of IDPs. Some guidelines have also been suggested for proceeding with a real-life structural modeling involving an IDPR using Proteus.
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| 5. |
- Bhakat, Soumendranath, et al.
(författare)
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Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling
- 2018
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Ingår i: Journal of Computer-Aided Molecular Design. - : Springer Science and Business Media LLC. - 0920-654X .- 1573-4951. ; 32:1, s. 59-73
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Tidskriftsartikel (refereegranskat)abstract
- Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.
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| 6. |
- Bhakat, Soumendranath, et al.
(författare)
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Resolving the problem of trapped water in binding cavities : prediction of host–guest binding free energies in the SAMPL5 challenge by funnel metadynamics
- 2017
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Ingår i: Journal of Computer-Aided Molecular Design. - : Springer Science and Business Media LLC. - 0920-654X .- 1573-4951. ; , s. 119-132
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Tidskriftsartikel (refereegranskat)abstract
- The funnel metadynamics method enables rigorous calculation of the potential of mean force along an arbitrary binding path and thereby evaluation of the absolute binding free energy. A problem of such physical paths is that the mechanism characterizing the binding process is not always obvious. In particular, it might involve reorganization of the solvent in the binding site, which is not easily captured with a few geometrically defined collective variables that can be used for biasing. In this paper, we propose and test a simple method to resolve this trapped-water problem by dividing the process into an artificial host-desolvation step and an actual binding step. We show that, under certain circumstances, the contribution from the desolvation step can be calculated without introducing further statistical errors. We apply the method to the problem of predicting host–guest binding free energies in the SAMPL5 blind challenge, using two octa-acid hosts and six guest molecules. For one of the hosts, well-converged results are obtained and the prediction of relative binding free energies is the best among all the SAMPL5 submissions. For the other host, which has a narrower binding pocket, the statistical uncertainties are slightly higher; longer simulations would therefore be needed to obtain conclusive results.
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| 7. |
- Bhattacharyya, Dhananjay, et al.
(författare)
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RNAHelix: computational modeling of nucleic acid structures with Watson-Crick and non-canonical base pairs
- 2017
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Ingår i: Journal of Computer-Aided Molecular Design. - : SPRINGER. - 0920-654X .- 1573-4951. ; 31:2, s. 219-235
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Tidskriftsartikel (refereegranskat)abstract
- Comprehensive analyses of structural features of non-canonical base pairs within a nucleic acid double helix are limited by the availability of a small number of three dimensional structures. Therefore, a procedure for model building of double helices containing any given nucleotide sequence and base pairing information, either canonical or non-canonical, is seriously needed. Here we describe a program RNAHelix, which is an updated version of our widely used software, NUCGEN. The program can regenerate duplexes using the dinucleotide step and base pair orientation parameters for a given double helical DNA or RNA sequence with defined Watson-Crick or non-Watson-Crick base pairs. The original structure and the corresponding regenerated structure of double helices were found to be very close, as indicated by the small RMSD values between positions of the corresponding atoms. Structures of several usual and unusual double helices have been regenerated and compared with their original structures in terms of base pair RMSD, torsion angles and electrostatic potentials and very high agreements have been noted. RNAHelix can also be used to generate a structure with a sequence completely different from an experimentally determined one or to introduce single to multiple mutation, but with the same set of parameters and hence can also be an important tool in homology modeling and study of mutation induced structural changes.
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| 8. |
- Caldararu, Octav, et al.
(författare)
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Binding free energies in the SAMPL5 octa-acid host–guest challenge calculated with DFT-D3 and CCSD(T)
- 2017
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Ingår i: Journal of Computer-Aided Molecular Design. - : Springer Science and Business Media LLC. - 0920-654X .- 1573-4951. ; 31:1, s. 87-106
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Tidskriftsartikel (refereegranskat)abstract
- We have tried to calculate the free energy for the binding of six small ligands to two variants of the octa-acid deep cavitand host in the SAMPL5 blind challenge. We employed structures minimised with dispersion-corrected density-functional theory with small basis sets and energies were calculated using large basis sets. Solvation energies were calculated with continuum methods and thermostatistical corrections were obtained from frequencies calculated at the HF-3c level. Care was taken to minimise the effects of the flexibility of the host by keeping the complexes as symmetric and similar as possible. In some calculations, the large net charge of the host was reduced by removing the propionate and benzoate groups. In addition, the effect of a restricted molecular dynamics sampling of structures was tested. Finally, we tried to improve the energies by using the DLPNO–CCSD(T) approach. Unfortunately, results of quite poor quality were obtained, with no correlation to the experimental data, systematically too positive affinities (by ~50 kJ/mol) and a mean absolute error (after removal of the systematic error) of 11–16 kJ/mol. DLPNO–CCSD(T) did not improve the results, so the accuracy is not limited by the energy function. Instead, four likely sources of errors were identified: first, the minimised structures were often incorrect, owing to the omission of explicit solvent. They could be partly improved by performing the minimisations in a continuum solvent with four water molecules around the charged groups of the ligands. Second, some ligands could bind in several different conformations, requiring sampling of reasonable structures. Third, there is an indication the continuum-solvation model has problems to accurately describe the binding of both the negatively and positively charged guest molecules. Fourth, different methods to calculate the thermostatistical corrections gave results that differed by up to 30 kJ/mol and there is an indication that HF-3c overestimates the entropy term. In conclusion, it is a challenge to calculate binding affinities for this octa-acid system with quantum–mechanical methods.
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| 9. |
- Caldararu, Octav, et al.
(författare)
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Binding free energies in the SAMPL6 octa-acid host–guest challenge calculated with MM and QM methods
- 2018
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Ingår i: Journal of Computer-Aided Molecular Design. - : Springer Science and Business Media LLC. - 0920-654X .- 1573-4951. ; 32:10, s. 1027-1046
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Tidskriftsartikel (refereegranskat)abstract
- We have estimated free energies for the binding of eight carboxylate ligands to two variants of the octa-acid deep-cavity host in the SAMPL6 blind-test challenge (with or without endo methyl groups on the four upper-rim benzoate groups, OAM and OAH, respectively). We employed free-energy perturbation (FEP) for relative binding energies at the molecular mechanics (MM) and the combined quantum mechanical (QM) and MM (QM/MM) levels, the latter obtained with the reference-potential approach with QM/MM sampling for the MM → QM/MM FEP. The semiempirical QM method PM6-DH+ was employed for the ligand in the latter calculations. Moreover, binding free energies were also estimated from QM/MM optimised structures, combined with COSMO-RS estimates of the solvation energy and thermostatistical corrections from MM frequencies. They were performed at the PM6-DH+ level of theory with the full host and guest molecule in the QM system (and also four water molecules in the geometry optimisations) for 10–20 snapshots from molecular dynamics simulations of the complex. Finally, the structure with the lowest free energy was recalculated using the dispersion-corrected density-functional theory method TPSS-D3, for both the structure and the energy. The two FEP approaches gave similar results (PM6-DH+/MM slightly better for OAM), which were among the five submissions with the best performance in the challenge and gave the best results without any fit to data from the SAMPL5 challenge, with mean absolute deviations (MAD) of 2.4–5.2 kJ/mol and a correlation coefficient (R2) of 0.77–0.93. This is the first time QM/MM approaches give binding free energies that are competitive to those obtained with MM for the octa-acid host. The QM/MM-optimised structures gave somewhat worse performance (MAD = 3–8 kJ/mol and R2 = 0.1–0.9), but the results were improved compared to previous studies of this system with similar methods.
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| 10. |
- Chavan, Swapnil, et al.
(författare)
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A k-nearest neighbor classification of hERG K+ channel blockers
- 2016
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Ingår i: Journal of Computer-Aided Molecular Design. - : Springer Science and Business Media LLC. - 0920-654X .- 1573-4951. ; 30:3, s. 229-236
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Tidskriftsartikel (refereegranskat)abstract
- A series of 172 molecular structures that block the hERG K+ channel were used to develop a classification model where, initially, eight types of PaDEL fingerprints were used for k-nearest neighbor model development. A consensus model constructed using Extended-CDK, PubChem and Substructure count fingerprint-based models was found to be a robust predictor of hERG activity. This consensus model demonstrated sensitivity and specificity values of 0.78 and 0.61 for the internal dataset compounds and 0.63 and 0.54 for the external (PubChem) dataset compounds, respectively. This model has identified the highest number of true positives (i.e. 140) from the PubChem dataset so far, as compared to other published models, and can potentially serve as a basis for the prediction of hERG active compounds. Validating this model against FDA-withdrawn substances indicated that it may even be useful for differentiating between mechanisms underlying QT prolongation.
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