3D protein descriptors
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BACKGROUND: Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D structure analysis has been utilised in order to discover indications of antigenic pressure. The latter has been mostly based on the 3D models of the clonotypic B cell receptor immunoglobulin (BcR IG) amino acid sequences. Therefore, their accuracy is directly dependent on the quality of the model construction algorithms and the specific methods used to compare the ensuing models. Thus far, reliable and robust methods that can group the IG 3D models based on their structural characteristics are missing. RESULTS: Here we propose a novel method for clustering a set of proteins based on their 3D structure focusing on 3D structures of BcR IG from a large series of patients with CLL. The method combines techniques from the areas of bioinformatics, 3D object recognition and machine learning. The clustering procedure is based on the extraction of 3D descriptors, encoding various properties of the local and global geometrical structure of the proteins. The descriptors are extracted from aligned pairs of proteins. A combination of individual 3D descriptors is also used as an additional method. The comparison of the automatically generated clusters to manual annotation by experts shows an increased accuracy when using the 3D descriptors compared to plain bioinformatics-based comparison. The accuracy is increased even more when using the combination of 3D descriptors. CONCLUSIONS: The experimental results verify that the use of 3D descriptors commonly used for 3D object recognition can be effectively applied to distinguishing structural differences of proteins. The proposed approach can be applied to provide hints for the existence of structural groups in a large set of unannotated BcR IG protein files in both CLL and, by logical extension, other contexts where it is relevant to characterize BcR IG structural similarity. The method does not present any limitations in application and can be extended to other types of proteins.
Cholesteryl ester transfer protein (CETP), an enzyme which catalyses the transfer of cholesteryl ester from HDL to VLDL, is a promising target for discovery of novel antihyperlipidemic agents due to its pivotal role in HDL metabolism and reverse cholesterol transport. Quantitative structure activity relationship study of a series of CETP inhibitors was carried out using genetic function approximation to study various structural requirements for CETP inhibition. Various lipophilic, electronic, geometric and spatial descriptors were correlated with CETP inhibitory activity. Developed models were found predictive as indicated by their good r2pred values and satisfactory internal and external cross-validation results. Study reveals that lipophilicity (ClogP), with parabolic relationship, contributed significantly to the activity along with some electronic, geometric and quantum mechanical descriptors. The present study can be applied to future lead optimization of CETP inhibitors.
Retinoids are dietary hormones acting through nuclear receptors for retinoic acid, important especially during embryonic development. This study focuses on the disruption of signaling pathways of retinoids by polycyclic aromatic hydrocarbons (PAHs) and their N-heterocyclic analogs (N-PAHs), important environmental contaminants with numerous biological effects. In vitro test with P19/A15 cell line stably transfected with luciferase reporter gene under control of retinoic acid-responsive elements was used to investigate both direct activation of retinoic acid receptors and modulation of response induced by natural ligand all-trans retinoic acid (ATRA) by 26 PAHs and N-PAHs. While none of individual compounds alone activated retinoic acid receptors, many of them modulated ATRA-mediated activity both after 6 h and 24 h exposure. Majority of compounds active after 6h downregulated ATRA-mediated activity (most effective were two analogs of dibenz[a,h]anthracene with LOECs about 185 nM), while most compounds active after 24h upregulated the effects of ATRA (most effective benz[a]acridine and dibenz[a,i]acridine caused 400% induction of ATRA response). Quantitative structure-activity relationship analysis identified molecular volume and dipole moment as the most important descriptors of inhibitory effects after 6h, while length, total molecular energy, gap-HOMO/LUMO and Van der Waals energy are important descriptors for stimulatory effects of PAHs and N-PAHs. This study demonstrates those abundant pollutants such as PAHs and their analogs interfere in vitro with retinoid signaling, which could play role in some in vivo effects of these organic contaminants such as teratogenicity.
- MeSH
- časové faktory MeSH
- down regulace účinky léků MeSH
- embryonální karcinom patologie MeSH
- kvantitativní vztahy mezi strukturou a aktivitou MeSH
- látky znečišťující životní prostředí chemie toxicita MeSH
- luciferasy metabolismus MeSH
- myši MeSH
- nádorové buněčné linie MeSH
- polycyklické aromatické uhlovodíky chemie toxicita MeSH
- receptory kyseliny retinové metabolismus MeSH
- reportérové geny MeSH
- responzivní elementy MeSH
- signální transdukce účinky léků MeSH
- tretinoin metabolismus MeSH
- zvířata MeSH
- Check Tag
- myši MeSH
- zvířata MeSH
- Publikační typ
- práce podpořená grantem MeSH
Protein-ligand affinities can be significantly influenced not only by the interaction itself but also by conformational equilibrium of both binding partners, free ligand and free protein. Identification of important conformational families of a ligand and prediction of their thermodynamics is important for efficient ligand design. Here we report conformational free energy modeling of nine small-molecule drugs in explicitly modeled water by metadynamics with a bias potential applied in the space of weighted holistic invariant molecular (WHIM) descriptors. Application of metadynamics enhances conformational sampling compared to unbiased molecular dynamics simulation and allows to predict relative free energies of key conformations. Selected free energy minima and one example of transition state were tested by a series of unbiased molecular dynamics simulation. Comparison of free energy surfaces of free and target-bound Imatinib provides an estimate of free energy penalty of conformational change induced by its binding to the target.
