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Journal of Computer-Aided Molecular Design

  1573-4951

 

 

Cơ quản chủ quản:  Springer Netherlands , SPRINGER

Lĩnh vực:
Computer Science ApplicationsDrug DiscoveryPhysical and Theoretical Chemistry

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Các bài báo tiêu biểu

Estimation of relative binding free energy based on a free energy variational principle for the FKBP-ligand system
Tập 27 - Trang 479-490 - 2013
Takeshi Ashida, Takeshi Kikuchi
Predicting an accurate binding free energy between a target protein and a ligand can be one of the most important steps in a drug discovery process. Often, many molecules must be screened to find probable high potency ones. Thus, a computational technique with low cost is highly desirable for the estimation of binding free energies of many molecules. Several techniques have thus far been developed for estimating binding free energies. Some techniques provide accurate predictions of binding free energies but high large computational cost. Other methods give good predictions but require tuning of some parameters to predict them with high accuracy. In this study, we propose a method to predict relative binding free energies with accuracy comparable to the results of prior methods but with lower computational cost and with no parameter needing to be carefully tuned. Our technique is based on the free energy variational principle. FK506 binding protein (FKBP) with 18 ligands is taken as a test system. Our results are compared to those from other widely used techniques. Our method provides a correlation coefficient (r 2 ) of 0.80 between experimental and calculated relative binding free energies and yields an average absolute error of 0.70 kcal/mol compared to experimental values. These results are comparable to or better than results from other techniques. We also discuss the possibility to improve our method further.
Artificial intelligence for prediction of biological activities and generation of molecular hits using stereochemical information
- 2023
Tiago Pereira, Maryam Abbasi, Rita I Oliveira, Romina A. Guedes, Jorge A. R. Salvador, Joel P. Arrais
AbstractIn this work, we develop a method for generating targeted hit compounds by applying deep reinforcement learning and attention mechanisms to predict binding affinity against a biological target while considering stereochemical information. The novelty of this work is a deep model Predictor that can establish the relationship between chemical structures and their corresponding $$pIC_{50}$$ p I C 50 values. We thoroughly study the effect of different molecular descriptors such as ECFP4, ECFP6, SMILES and RDKFingerprint. Also, we demonstrated the importance of attention mechanisms to capture long-range dependencies in molecular sequences. Due to the importance of stereochemical information for the binding mechanism, this information was employed both in the prediction and generation processes. To identify the most promising hits, we apply the self-adaptive multi-objective optimization strategy. Moreover, to ensure the existence of stereochemical information, we consider all the possible enumerated stereoisomers to provide the most appropriate 3D structures. We evaluated this approach against the Ubiquitin-Specific Protease 7 (USP7) by generating putative inhibitors for this target. The predictor with SMILES notations as descriptor plus bidirectional recurrent neural network using attention mechanism has the best performance. Additionally, our methodology identify the regions of the generated molecules that are important for the interaction with the receptor’s active site. Also, the obtained results demonstrate that it is possible to discover synthesizable molecules with high biological affinity for the target, containing the indication of their optimal stereochemical conformation.
Activity cliffs in PubChem confirmatory bioassays taking inactive compounds into account
Tập 27 Số 2 - Trang 115-124 - 2013
Ye Hu, Gerald M. Maggiora, Jürgen Bajorath
Representation, searching and discovery of patterns of bases in complex RNA structures
Tập 17 - Trang 537-549 - 2003
Anne-Marie Harrison, Darren R. South, Peter Willett, Peter J. Artymiuk
We describe a graph theoretic method designed to perform efficient searches for substructural patterns in nucleic acid structural coordinate databases using a simplified vectorial representation. Two vectors represent each nucleic acid base and the relative positions of bases with respect to one another are described in terms of distances between the defined start and end points of the vectors on each base. These points comprise the nodes and the distances the edges of a graph, and a pattern search can then be performed using a subgraph isomorphism algorithm. The minimal representation was designed to facilitate searches for complex patterns but was first tested on simple, well-characterised arrangements of bases such as base pairs and GNRA-tetraloop receptor interactions. The method performed very well for these interaction types. A survey of side-by-side base interactions, of which the adenosine platform is the best known example, also locates examples of similar base rearrangements that we consider to be important in structural regulation. A number of examples were found, with GU platforms being particularly prevalent. A GC platform in the RNA of the Thermus thermophilus small ribosomal subunit is in an analogous position to an adenosine platform in other species. An unusual GG platform is also observed close to one of the substrate binding sites in Haloarcula marismortui large ribosomal subunit RNA.
Structure-based design, synthesis and biological evaluation of β-glucuronidase inhibitors
Tập 28 - Trang 577-585 - 2014
Khalid M. Khan, Nida Ambreen, Muhammad Taha, Sobia A. Halim, Zaheer-ul-Haq, Shagufta Naureen, Saima Rasheed, Shahnaz Perveen, Sajjad Ali, Mohammad Iqbal Choudhary
Using structure-based virtual screening approach, a coumarin derivative (1) was identified as β-glucuronidase inhibitor. A focused library of coumarin derivatives was synthesized by eco-benign version of chemical reaction, and all synthetic compounds were characterized by using spectroscopy. These compounds were found to be inhibitor of β-glucuronidase with IC50 values in a micromolar range. All synthetic compounds exhibited interesting inhibitory activity against β-glucuronidase, however, their potency varied substantially from IC50 = 9.9–352.6 µM. Of twenty-one compounds, four exhibited a better inhibitory profile than the initial hit 1. Interestingly, compounds 1e, 1k, 1n and 1p exhibited more potency than the standard inhibitor with IC50 values 34.2, 21.4, 11.7, and 9.9 µM, respectively. We further studied their dose responses and also checked our results by using detergent Triton ×-100. We found that our results are true and not affected by detergent.
Conformational study of insect adipokinetic hormones using NMR constrained molecular dynamics
Tập 15 - Trang 259-270 - 2001
Margie M. Nair, Graham E. Jackson, Gerd Gäde
Mem-CC (pGlu-Leu-Asn-Tyr-Ser-Pro-Asp-Trp-NH2), Tem-HrTH (pGlu-Leu-Asn-Phe-Ser-Pro-Asn-Trp-NH2) and Del-CC (pGlu-Leu-Asn-Phe-Ser-Pro-Asn-Trp-Gly-Asn-NH2) are adipokinetic hormones, isolated from the corpora cardiaca of different insect species. These hormones regulate energy metabolism during flight and so are intimately involved in an insect's mobility. Secondary structural elements of these peptides and the N7 analogue, [N7]-Mem-CC (pGlu-Leu-Asn-Tyr-Ser-Pro-Asn-Trp-NH2), have been determined in dimethylsulfoxide solution using NMR restrained molecular mechanic simulations. The neuropeptides were all found to have an extended structure for the first 4 residues and a β-turn between residues 4–8. For Tem-HrTH and Del-CC, asparagine (N7) which is postulated to be involved in receptor binding and/or activation, projects outward form the β-turn. Mem-CC does not have an asparagine at position 7 while, for [N7]-Mem-CC, the N7 sidechain folds inside the β-turn preventing its interaction with the receptor.
Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening
Tập 22 - Trang 593-609 - 2008
Jui-Hua Hsieh, Xiang S. Wang, Denise Teotico, Alexander Golbraikh, Alexander Tropsha
The use of inaccurate scoring functions in docking algorithms may result in the selection of compounds with high predicted binding affinity that nevertheless are known experimentally not to bind to the target receptor. Such falsely predicted binders have been termed ‘binding decoys’. We posed a question as to whether true binders and decoys could be distinguished based only on their structural chemical descriptors using approaches commonly used in ligand based drug design. We have applied the k-Nearest Neighbor (kNN) classification QSAR approach to a dataset of compounds characterized as binders or binding decoys of AmpC beta-lactamase. Models were subjected to rigorous internal and external validation as part of our standard workflow and a special QSAR modeling scheme was employed that took into account the imbalanced ratio of inhibitors to non-binders (1:4) in this dataset. 342 predictive models were obtained with correct classification rate (CCR) for both training and test sets as high as 0.90 or higher. The prediction accuracy was as high as 100% (CCR = 1.00) for the external validation set composed of 10 compounds (5 true binders and 5 decoys) selected randomly from the original dataset. For an additional external set of 50 known non-binders, we have achieved the CCR of 0.87 using very conservative model applicability domain threshold. The validated binary kNN QSAR models were further employed for mining the NCGC AmpC screening dataset (69653 compounds). The consensus prediction of 64 compounds identified as screening hits in the AmpC PubChem assay disagreed with their annotation in PubChem but was in agreement with the results of secondary assays. At the same time, 15 compounds were identified as potential binders contrary to their annotation in PubChem. Five of them were tested experimentally and showed inhibitory activities in millimolar range with the highest binding constant Ki of 135 μM. Our studies suggest that validated QSAR models could complement structure based docking and scoring approaches in identifying promising hits by virtual screening of molecular libraries.
A simple, fast and convenient new method for predicting the stability of nitro compounds
Tập 29 Số 5 - Trang 471-483 - 2015
Zhang, Xueli, Gong, Xuedong
A new method has been proposed to understand and predict the stability of nitro compounds. This method uses the maximum electron densities at the critical points of two N–O bonds of nitro groups (ρ max), and it is more simple and faster than the existing methods and applicable to bigger systems. The correlations between the ρ max and total energy (E), bond lengths ( $$ R_{{{\text{C}}{-}{\text{NO}}_{2} }} $$ , $$ R_{{{\text{N}}{-}{\text{NO}}_{2} }} $$ and $$ R_{{{\text{O}}{-}{\text{NO}}_{2} }} $$ ), bond dissociation energy (BDE), and impact sensitivity (h 50) reveal that the molecular stability, which can be reflected by E, R, BDE and h 50, generally decreases with the increasing ρ max. The compound with the larger ρ max is less stable. For the nitrating reaction, the smaller ρ max of the product generally implies the easier and faster reaction and the higher occurrence ratio of the product. Therefore, ρ max can be applied to predict the stability of nitro compounds and the easiness of the nitrating reaction.
Phosphorylation and ATP-binding induced conformational changes in the PrkC, Ser/Thr kinase from B. subtilis
Tập 24 - Trang 733-747 - 2010
Paweł Gruszczyński, Michał Obuchowski, Rajmund Kaźmierkiewicz
Recent studies on the PrkC, serine-threonine kinase show that that the enzyme is located at the inner membrane of endospores and is responsible for triggering spore germination. The activity of the protein increases considerably after phosphorylation of four threonine residues placed on the activation loop and one serine placed in the C-terminal lobe of the PrkC. The molecular relationship between phosphorylation of these residues and enzyme activity is not known. In this work molecular dynamics simulation is performed on four forms of the protein kinase PrkC from B. subtilis—phosphorylated or unphosphorylated; with or without ATP bound—in order to gain insight into phosphorylation and ATP binding on the conformational changes and functions of the protein kinase. Our results show how phosphorylation, as well as the presence of ATP, is important for the activity of the enzyme through its molecular interaction with the catalytic core residues. Three of four threonine residues were found to be involved in the interactions with conservative motifs important for the enzyme activity. Two of the threonine residues (T167 and T165) are involved in ionic interactions with an arginine cluster from αC-helix. The third residue (T163) plays a crucial role, interacting with His-Arg-Asp triad (HRD). Last of the threonine residues (T162), as well as the serine (S214), were indicated to play a role in the substrate recognition or dimerization of the enzyme. The presence of ATP in the unphosphorylated model induced conformational instability of the activation loop and Asp-Phe-Gly motif (DFG). Based on our calculations we put forward a hypothesis suggesting that the ATP binds after phosphorylation of the activation loop to create a fully active conformation in the closed position.