The acid dissociation constant is an important molecular property, and it can be successfully predicted by Quantitative Structure-Property Relationship (QSPR) models, even for in silico designed molecules. We analyzed how the methodology of in silico 3D structure preparation influences the quality of QSPR models. Specifically, we evaluated and compared QSPR models based on six different 3D structure sources (DTP NCI, Pubchem, Balloon, Frog2, OpenBabel, and RDKit) combined with four different types of optimization. These analyses were performed for three classes of molecules (phenols, carboxylic acids, anilines), and the QSPR model descriptors were quantum mechanical (QM) and empirical partial atomic charges. Specifically, we developed 516 QSPR models and afterward systematically analyzed the influence of the 3D structure source and other factors on their quality. Our results confirmed that QSPR models based on partial atomic charges are able to predict pKa with high accuracy. We also confirmed that ab initio and semiempirical QM charges provide very accurate QSPR models and using empirical charges based on electronegativity equalization is also acceptable, as well as advantageous, because their calculation is very fast. On the other hand, Gasteiger-Marsili empirical charges are not applicable for pKa prediction. We later found that QSPR models for some classes of molecules (carboxylic acids) are less accurate. In this context, we compared the influence of different 3D structure sources. We found that an appropriate selection of 3D structure source and optimization method is essential for the successful QSPR modeling of pKa. Specifically, the 3D structures from the DTP NCI and Pubchem databases performed the best, as they provided very accurate QSPR models for all the tested molecular classes and charge calculation approaches, and they do not require optimization. Also, Frog2 performed very well. Other 3D structure sources can also be used but are not so robust, and an unfortunate combination of molecular class and charge calculation approach can produce weak QSPR models. Additionally, these 3D structures generally need optimization in order to produce good quality QSPR models.
- MeSH
- Chemical Phenomena * MeSH
- Quantitative Structure-Activity Relationship * MeSH
- Quantum Theory MeSH
- Molecular Conformation * MeSH
- Models, Molecular * MeSH
- Computer Simulation MeSH
- Drug Design MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
Úvod: 3D tisk, koncept starý přes 40 let, nachází díky technologickému pokroku stále širší uplatnění v klinické praxi. Ve FN Ostrava je využíván k vytváření anatomických modelů konkrétních pacientů před chirurgickými výkony na základě dat ze zobrazovacích vyšetření. Kazuistiky: 3D tisk nachází uplatnění jako doplněk ke konvenčním zobrazovacím metodám s cílem zhotovit morfologicky přesné modely anatomických struktur konkrétních pacientů. Tyto modely slouží především pro předoperační přípravu v elektivní břišní, cévní a hrudní chirurgii. Využívají se rovněž při plánování osteosyntéz složitých zlomenin a korekčních osteotomií. Vícebarevný tisk, přestože zvyšuje časovou náročnost procesu, umožňuje lepší přehlednost a diferenciaci jednotlivých anatomických struktur v rámci jednoho modelu. Diskuze: 3D modely poskytují lepší prostorovou orientaci a rozpoznání operovaných struktur než 2D obrazy, což přispívá k lepším výsledkům zákroků. Jejich přínos je potvrzen studiemi napříč obory, od kardiochirurgie po traumatologii. Závěr: Po odstranění počátečních překážek se 3D tisk stal spolehlivou součástí arzenálu Chirurgické kliniky FN Ostrava pro elektivní chirurgii. I když 3D tisk nepředstavuje univerzální odpověď na všechny výzvy, kterým v medicíně čelíme, jeho role je v řadě indikovaných případů velmi přínosná a perspektivní.
Introduction: 3D printing, a concept over 40 years old, is finding broader application in clinical practice thanks to technological advancements. At University Hospital Ostrava, 3D printing is utilized to create anatomically accurate models of specific patients before surgical procedures based on imaging data. Case series: 3D printing is employed as a complement to conventional imaging methods to produce morphologically precise models of anatomical structures of individual patients. These models primarily serve for preoperative planning in elective abdominal, vascular, and thoracic surgery. They are also used in planning osteosynthesis of complex fractures and corrective osteotomies. Multicolor printing, although increasing the process‘s time demands, allows better clarity and differentiation of individual anatomical structures within a single model. Discussion: Compared to 2D images, 3D models provide better spatial orientation and awareness of the operated structures, contributing to improved surgical outcomes. The benefits of 3D printing in preoperative planning and patient education are confirmed by studies across the fields ranging from cardiac surgery to traumatology. Conclusion: After overcoming initial challenges, 3D printing has become a reliable component of the surgical arsenal at University Hospital Ostrava for elective surgery. While 3D printing does not represent a universal answer to all medical challenges, its role is highly beneficial and promising in many indicated cases.
Proteins are naturally formed by domains edging their functional and structural properties. A domain out of the context of an entire protein can retain its structure and to some extent also function on its own. These properties rationalize construction of artificial fusion multidomain proteins with unique combination of various functions. Information on the specific functional and structural characteristics of individual domains in the context of new artificial fusion proteins is inevitably encoded in sequential order of composing domains defining their mutual spatial positions. So the challenges in designing new proteins with new domain combinations lie dominantly in structure/function prediction and its context dependency. Despite the enormous body of publications on artificial fusion proteins, the task of their structure/function prediction is complex and nontrivial. The degree of spatial freedom facilitated by a linker between domains and their mutual orientation driven by noncovalent interactions is beyond a simple and straightforward methodology to predict their structure with reasonable accuracy. In the presented manuscript, we tested methodology using available modeling tools and computational methods. We show that the process and methodology of such prediction are not straightforward and must be done with care even when recently introduced AlphaFold II is used. We also addressed a question of benchmarking standards for prediction of multidomain protein structures-x-ray or Nuclear Magnetic Resonance experiments. On the study of six two-domain protein chimeras as well as their composing domains and their x-ray structures selected from PDB, we conclude that the major obstacle for justified prediction is inappropriate sampling of the conformational space by the explored methods. On the other hands, we can still address particular steps of the methodology and improve the process of chimera proteins prediction.
A quantitative structure-activity relationship (QSAR) model dependent on log P(n - octanol/water), or log P(OW), was developed with acute toxicity index EC50, the median effective concentration measured as inhibition of movement of the oligochaeta Tubifex tubifex with 3 min exposure, EC50(Tt) (mol/L): log EC50(Tt) = -0.809 (+/-0.035) log P(OW) - 0.495 (+/-0.060), n=82, r=0.931, r2=0.867, residual standard deviation of the estimate 0.315. A learning series for the QSAR model with the oligochaete contained alkanols, alkenols, and alkynols; saturated and unsaturated aldehydes; aniline and chlorinated anilines; phenol and chlorinated phenols; and esters. Three cross-validation procedures proved the robustness and stability of QSAR models with respect to the chemical structure of compounds tested within a series of compounds used in the learning series. Predictive ability was described by q2 .801 (cross-validated r2; predicted variation estimated with cross-validation) in LSO (leave-a structurally series-out) cross-validation.
Cílem studie bylo stanovit úlohu vyšetření power Dopplerem při iniciální diagnostice karcinomu prostaty, při posouzení extraprostatické invaze, při hodnocení velikosti nádoru a při hodnocení buněčné diferenciace pomocí stupně vaskularizace nádoru. Bylo vyšetřeno 87 pacientů s hypoechogenním ložiskem v oblasti periferie prostaty. Vyšetření power Dopplerem bylo v případě lokalizovaných karcinomů srovnáno s histologickým výsledkem sextantových biopsii a radikálních prostatektomií. Stupeň vaskularizace byl kvantifikován pomocí indexu vaskularizace 1-3. U 21 pacientů, kteří podstoupili radikální prostatektomií, byla prospektivně vyhodnocena extraprostatická invaze nádoru. Vyšetření power Dopplerem má při diagnostice karcinomu prostaty senzitivitu 98,1 % a specificitu 77,1 %. Pro prevalenci onemocnění 0,4 - 0,9 je pozitivní prediktivní hodnota vyšetření 86,4 - 74 % a negativní prediktivní hodnota 96,4 - 98,4 % (p = 0,02). U lokálně pokročilých nádorů bylo zjištěno. že nádorová vaskularizace přesahuje okraje hypoechogenního ložiska a cílená biopsie pomocí power Doppleru umožňuje přesnější stanovení velikosti nádoru. U lokalizovaných nádorů byla přítomnost centrální anomální vaskularizace často spojena s efektem expanzivního procesu. Kvalitativně byly odlišeny 3 typy vaskularizace: A, B a C, u kterých byla prospektivně zjištěna pravděpodobnost extraprostatické invaze. V osmi případech typu A (centrální vaskularizace nádoru a pravidelná avaskulámí prostatická kapsula) nebyla extraprostatická invaze zjištěna u 7 pacientů (12,5% riziko invaze). V osmi případech typu C (bohatá nádorová vaskularizace, zasahující do periferie a ztenčující nebo penetrující prostatickou kapsulu) byla invaze zjištěna u 6 pacientů (75% riziko invaze). Index vaskularizace roven novým skóre rovným nebo větším než 7 a u 6 ze 17 pacientů s Gleasonovým skóre nižším než 7 (R = 0,283, p = 0,033).
The objective of the study was to determine the role of Power Doppler for initial diagnosis of prostate cancer, for extraprostatic invasion assessment, for tumour size determination and for evaluation of the cellular differentiation using the tumour vascularization index. A total of 87 patients with a hypoechogenous structure in the area of the posterior prostate periphery were examined. In the case of localized cancers, Power Doppler results were compared with the histological findings of sextant biopsy and radical prostatectomy. The vascularization rate was quantified using a vascularization index of 1 to 3. The prospective evaluation of extraprostatic invasion of the tumour was stated for 21 patients who underwent radical prostatectomy. Power Doppler has a 98.1% sensitivity and a 77.1% specificity in respect of the diagnosis of a prostate cancer. For disease prevalence of 0.4 to 0.9, the examination's positive predictive value is 86.4 to 74% and the negative predictive value is 96.4 to 98.4% (p = 0.02). It was ascertained that in locally advanced tumours, tumour vascularization exceeded the borders of the hypoechogenous structure and biopsy using Power Doppler facilitated a more precise determination of the tumours size. In respect of localized tumours, the presence of central abnormal vascularization was often associated with the mass effect. Three qualitative types of vascularization were differentiated: A, B, and C, where probability of extraprostatic invasion was prospectively determined. In 8 type A cases (central vascularization of the tumour and a regular avascular prostatic capsule) no extraprostatic invasion was ascertained in 7 patients (a 12.5% invasion risk). In 8 type C cases (ample tumour vascularization affecting the periphery and attenuating or penetrating the prostatic capsule). invasion was ascertained in 6 patients (a 75% invasion risk). A vascularization index equal to or higher than 3 was found in 20 patients out of 40 with Gleason's score equal to or higher than 7, and in 6 patients out of 17 with Gleason's score below 7 (R = 0.283, p = 0.033).
- MeSH
- Cell Differentiation MeSH
- Neoplasm Invasiveness MeSH
- Carcinoma diagnosis pathology ultrasonography MeSH
- Humans MeSH
- Prostatic Neoplasms complications pathology ultrasonography MeSH
- Neovascularization, Pathologic MeSH
- Neoplasm Staging MeSH
- Ultrasonography, Doppler methods instrumentation MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Publication type
- Review MeSH
Cardiac arrhythmias are a very frequent illness. Pharmacotherapy is not very effective in persistent arrhythmias and brings along a number of risks. Catheter ablation has became an effective and curative treatment method over the past 20 years. To support complex arrhythmia ablations, the 3D X-ray cardiac cavities imaging is used, most frequently the 3D reconstruction of CT images. The 3D cardiac rotational angiography (3DRA) represents a modern method enabling to create CT like 3D images on a standard X-ray machine equipped with special software. Its advantage lies in the possibility to obtain images during the procedure, decreased radiation dose and reduction of amount of the contrast agent. The left atrium model is the one most frequently used for complex atrial arrhythmia ablations, particularly for atrial fibrillation. CT data allow for creation and segmentation of 3D models of all cardiac cavities. Recently, a research has been made proving the use of 3DRA to create 3D models of other cardiac (right ventricle, left ventricle, aorta) and non-cardiac structures (oesophagus). They can be used during catheter ablation of complex arrhythmias to improve orientation during the construction of 3D electroanatomic maps, directly fused with 3D electroanatomic systems and/or fused with fluoroscopy. An intensive development in the 3D model creation and use has taken place over the past years and they became routinely used during catheter ablations of arrhythmias, mainly atrial fibrillation ablation procedures. Further development may be anticipated in the future in both the creation and use of these models.
- MeSH
- Action Potentials MeSH
- Surgery, Computer-Assisted MeSH
- Radiography, Interventional MeSH
- Catheter Ablation methods MeSH
- Coronary Angiography methods MeSH
- Humans MeSH
- Multidetector Computed Tomography methods MeSH
- Predictive Value of Tests MeSH
- Heart Conduction System physiopathology radiography surgery MeSH
- Radiographic Image Interpretation, Computer-Assisted * MeSH
- Software MeSH
- Arrhythmias, Cardiac physiopathology radiography surgery MeSH
- Imaging, Three-Dimensional * MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
The problem of designing tablet geometry and its internal structure that results into a specified release profile of the drug during dissolution was considered. A solution method based on parametric programming, inspired by CAD (computer-aided design) approaches currently used in other fields of engineering, was proposed and demonstrated. The solution of the forward problem using a parametric series of structural motifs was first carried out in order to generate a library of drug release profiles associated with each structural motif. The inverse problem was then solved in three steps: first, the combination of basic structural motifs whose superposition provides the closest approximation of the required drug release profile was found by a linear combination of pre-calculated release profiles. In the next step, the final tablet design was constructed and its dissolution curve found computationally. Finally, the proposed design was 3D printed and its dissolution profile was confirmed experimentally. The computational method was based on the numerical solution of drug diffusion in a boundary layer surrounding the tablet, coupled with erosion of the tablet structure encoded by the phase volume function. The tablets were 3D printed by fused deposition modelling (FDM) from filaments produced by hot-melt extrusion. It was found that the drug release profile could be effectively controlled by modifying the tablet porosity. Custom release profiles were obtained by combining multiple porosity regions in the same tablet. The computational method yielded accurate predictions of the drug release rate for both single- and multi-porosity tablets.
To predict unknown reactivation potencies of 12 mono- and bis-pyridinium aldoximes for VX-inhibited rat acetylcholinesterase (rAChE), three-dimensional quantitative structure-activity relationship (3D QSAR) analysis has been carried out. Utilizing molecular interaction fields (MIFs) calculated by molecular mechanical (MMFF94) and quantum chemical (B3LYP/6-31G*) methods, two satisfactory ligand-based CoMFA models have been developed: 1. R(2)=0.9989, Q(LOO)(2)=0.9090, Q(LTO)(2)=0.8921, Q(LMO(20%))(2)=0.8853, R(ext)(2)=0.9259, SDEP(ext)=6.8938; 2. R(2)=0.9962, Q(LOO)(2)=0.9368, Q(LTO)(2)=0.9298, Q(LMO(20%))(2)=0.9248, R(ext)(2)=0.8905, SDEP(ext)=6.6756. High statistical significance of the 3D QSAR models has been achieved through the application of several data noise reduction techniques (i.e. smart region definition SRD, fractional factor design FFD, uninformative/iterative variable elimination UVE/IVE) on the original MIFs. Besides the ligand-based CoMFA models, an alignment molecular set constructed by flexible molecular docking has been also studied. The contour maps as well as the predicted reactivation potencies resulting from 3D QSAR analyses help better understand which structural features are associated with increased reactivation potency of studied compounds.
- MeSH
- Acetylcholinesterase chemistry MeSH
- Enzyme Activation MeSH
- Chemical Warfare Agents chemistry MeSH
- Cholinesterase Inhibitors chemistry MeSH
- GPI-Linked Proteins agonists antagonists & inhibitors chemistry MeSH
- Kinetics MeSH
- Rats MeSH
- Quantitative Structure-Activity Relationship MeSH
- Quantum Theory MeSH
- Ligands MeSH
- Organothiophosphorus Compounds chemistry MeSH
- Oximes chemistry MeSH
- Pyridinium Compounds chemistry MeSH
- Cholinesterase Reactivators chemistry MeSH
- Molecular Dynamics Simulation MeSH
- Molecular Docking Simulation MeSH
- Thermodynamics MeSH
- Animals MeSH
- Check Tag
- Rats MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
