Quantitative Structure-Activity Relationship
Structure-Activity Relationship
Molecular Structure
Models, Molecular
Mescaline
Models, Chemical
Drug Design
Binding Sites
Literature, Modern
Circular Dichroism
Quantum Theory
Software
Computational Biology
The carboxy terminus of the herpesvirus saimiri ORF 57 gene contains domains that are required for transactivation and transrepression. (1/699)
Herpesvirus saimiri (HVS) ORF 57 is homologous to genes identified in all classes of herpesviruses. We have previously shown that ORF 57 encodes a multifunctional protein, responsible for both transactivation and repression of viral gene expression at a post-transcriptional level. This suggests that the ORF 57 protein shares some functional similarities with the herpes simplex virus IE63/ICP27 and Epstein-Barr virus Mta proteins. However, little is known about the functional domains responsible for the properties of ORF 57 due to the limited homology shared between these proteins. In this report, we have identified the functional domains responsible for transactivation and repression by the ORF 57 protein. We demonstrate that the carboxy terminus is required for ORF 57 transactivation, repression and an intense SC-35 nuclear spotting. This region contains two highly conserved motifs amongst its homologues, a zinc finger-like motif and a highly hydrophobic domain. We further show that the hydrophobic domain is required for transactivation and is also involved in nuclear localization of the ORF 57 protein, whereas the zinc finger-like domain is required for transactivation, repression and the intense SC-35 nuclear spotting. (+info)Self-organizing neural network for modeling 3D QSAR of colchicinoids. (2/699)
A novel scheme for modeling 3D QSAR has been developed. A method involving multiple self-organizing neural network adjusted to be analyzed by the PLS (partial least squares) analysis was used to model 3D QSAR of the selected colchicinoids. The model obtained allows the identification of some structural determinants of the biological activity of compounds. (+info)MIPSIM: similarity analysis of molecular interaction potentials. (3/699)
SUMMARY: MIPSIM is a computational package designed to analyse and compare 3D distributions of molecular interaction potentials (MIP) of series of biomolecules. (+info)The UL34 gene product of herpes simplex virus type 2 is a tail-anchored type II membrane protein that is significant for virus envelopment. (4/699)
The UL34 gene of herpes simplex virus type 2 (HSV-2) is highly conserved in the herpesvirus family. The UL34 gene product was identified In lysates of HSV-2-infected cells as protein species with molecular masses of 31 and 32.5 kDa, the latter being a phosphorylated product. Synthesis of these proteins occurred at late times post-infection and was highly dependent on viral DNA synthesis. Immunofluorescence assays revealed that the UL34 protein was localized in the cytoplasm in a continuous net-like structure, closely resembling the staining pattern of the endoplasmic reticulum (ER), in both HSV-2-infected cells and in cells transiently expressing UL34 protein. Deletion mutant analysis showed that this colocalization required the C terminus of the UL34 protein. The UL34 protein associated with virions but not with A, B or C capsids. We treated virions, HSV-2-infected cells and cells expressing the UL34 protein with a protease in order to examine the topology of the UL34 protein. In addition, we constructed UL34 deletion mutant proteins and examined their intracellular localization. Our data strongly support the hypothesis that the UL34 protein is inserted into the viral envelope as a tail-anchored type II membrane protein and is significant for virus envelopment. (+info)Recombinant human monoclonal antibodies against different conformational epitopes of the E2 envelope glycoprotein of hepatitis C virus that inhibit its interaction with CD81. (5/699)
The antibody response to the envelope proteins of hepatitis C virus (HCV) may play an important role in controlling the infection. To allow molecular analyses of protective antibodies, we isolated human monoclonal antibodies to the E2 envelope glycoprotein of HCV from a combinatorial Fab library established from bone marrow of a chronically HCV-infected patient. Anti-E2 reactive clones were selected using recombinant E2 protein. The bone marrow donor carried HCV genotype 2b, and E2 used for selection was of genotype 1a. The antibody clones were expressed as Fab fragments in E. coli, and as Fab fragments and IgG1 in CHO cells. Seven different antibody clones were characterized, and shown to have high affinity for E2, genotype 1a. Three clones also had high affinity for E2 of genotype 1b. They all bind to conformation-dependent epitopes. Five clones compete for the same or overlapping binding sites, while two bind to one or two other epitopes of E2. Four clones corresponding to the different epitopes were tested as purified IgG1 for blocking the CD81-E2 interaction in vitro; all four were positive at 0.3-0.5 microg/ml. Thus, the present results suggest the existence of at least two conserved epitopes in E2 that mediate inhibition of the E2-CD81 interaction, of which one appeared immunodominant in this donor. (+info)Isolation of a Spodoptera exigua baculovirus recombinant with a 10.6 kbp genome deletion that retains biological activity. (6/699)
When Spodoptera exigua multicapsid nucleopolyhedrovirus (SeMNPV) is grown in insect cell culture, defective viruses are generated. These viruses lack about 25 kbp of sequence information and are no longer infectious for insects. This makes the engineering of SeMNPV for improved insecticidal activity or as expression vectors difficult to achieve. Recombinants of Autographa californica MNPV have been generated in insects after lipofection with viral DNA and a transfer vector into the haemocoel. In the present study a novel procedure to isolate SeMNPV recombinants was adopted by alternate cloning between insect larvae and cultured cells. The S. exigua cell line Se301 was used to select the putative recombinants by following a green fluorescent protein marker inserted in the p10 locus of SeMNPV. Polyhedra from individual plaques were fed to larvae to select for biological activity. In this way an SeMNPV recombinant (SeXD1) was obtained with the speed of kill improved by about 25%. This recombinant lacked 10593 bp of sequence information, located between 13.7 and 21.6 map units of SeMNPV and including ecdysteroid UDP glucosyl transferase, gp37, chitinase and cathepsin genes, as well as several genes unique to SeMNPV. The result indicated, however, that these genes are dispensable for virus replication both in vitro and in vivo. A mutant with a similar deletion was identified by PCR in the parental wild-type SeMNPV isolate, suggesting that genotypes with differential biological activities exist in field isolates of baculoviruses. The generation of recombinants in vivo, combined with the alternate cloning between insects and insect cells, is likely to be applicable to many baculovirus species in order to obtain biologically active recombinants. (+info)Expression of unglycosylated mutated prion protein facilitates PrP(Sc) formation in neuroblastoma cells infected with different prion strains. (7/699)
Prion replication involves conversion of the normal, host-encoded prion protein PrP(C), which is a sialoglycoprotein bound to the plasma membrane by a glycophosphatidylinositol anchor, into a pathogenic isoform, PrP(Sc). In earlier studies, tunicamycin prevented glycosylation of PrP(C) in scrapie-infected mouse neuroblastoma (ScN2a) cells but it was still expressed on the cell surface and converted into PrP(Sc); mutation of PrP(C) at glycosylation consensus sites (T182A, T198A) produced low steady-state levels of PrP that were insufficient to propagate prions in transgenic mice. By mutating asparagines to glutamines at the consensus sites, we obtained expression of unglycosylated, epitope-tagged MHM2PrP(N180Q,N196Q), which was converted into PrP(Sc) in ScN2a cells. Cultures of uninfected neuroblastoma (N2a) cells transiently expressing mutated PrP were exposed to brain homogenates prepared from mice infected with the RML, Me7 or 301V prion strains. In each case, mutated PrP was converted into PrP(Sc) as judged by Western blotting. These findings raise the possibility that the N2a cell line can support replication of different strains of prions. (+info)Metabonomics: evaluation of nuclear magnetic resonance (NMR) and pattern recognition technology for rapid in vivo screening of liver and kidney toxicants. (8/699)
The purpose of this study was to evaluate the feasibility of metabonomics technology for developing a rapid-throughput toxicity screen using 2 known hepatotoxicants: carbon tetrachloride (CCl(4)) and alpha-naphthylisothiocyanate (ANIT) and 2 known nephrotoxicants: 2-bromoethylamine (BEA) and 4-aminophenol (PAP). In addition, the diuretic furosemide (FURO) was also studied. Single doses of CCl(4) (0.1 and 0.5 ml/kg), ANIT (10 and 100 mg/kg), BEA (15 and 150 mg/kg), PAP (15 and 150 mg/kg) and FURO (1 and 5 mg) were administered as single IP or oral doses to groups of 4 male Wistar rats/dose. Twenty-four-h urine samples were collected pretest, daily through Day 4, and on Day 10 (high dose CCl(4) and BEA only). Blood samples were taken on Days 1, 2, and 4 or 1, 4, and 10 for clinical chemistry assessment, and the appropriate target organ was examined microscopically. NMR spectra of urine were acquired and the data processed and subjected to principal component analyses (PCA). The results demonstrated that the metabonomic approach could readily distinguish the onset and reversal of toxicity with good agreement between clinical chemistry and PCA data. In at least 2 instances (ANIT and BEA), PCA analysis suggested effects at low doses, which were not as evident by clinical chemistry or microscopic analysis. Furosemide, which had no effect at the doses employed, did not produce any changes in PCA patterns. These data support the contention that the metabonomic approach represents a promising new technology for the development of a rapid throughput in vivo toxicity screen. (+info)Quantitative Structure-Activity Relationship (QSAR) is a method used in toxicology and medicinal chemistry that attempts to establish mathematical relationships between the chemical structure of a compound and its biological activity. QSAR models are developed using statistical methods to analyze a set of compounds with known biological activities and their structural properties, which are represented as numerical or categorical descriptors. These models can then be used to predict the biological activity of new, structurally similar compounds.
QSAR models have been widely used in drug discovery and development, as well as in chemical risk assessment, to predict the potential toxicity of chemicals based on their structural properties. The accuracy and reliability of QSAR predictions depend on various factors, including the quality and diversity of the data used to develop the models, the choice of descriptors and statistical methods, and the applicability domain of the models.
In summary, QSAR is a quantitative method that uses mathematical relationships between chemical structure and biological activity to predict the potential toxicity or efficacy of new compounds based on their structural properties.
A Structure-Activity Relationship (SAR) in the context of medicinal chemistry and pharmacology refers to the relationship between the chemical structure of a drug or molecule and its biological activity or effect on a target protein, cell, or organism. SAR studies aim to identify patterns and correlations between structural features of a compound and its ability to interact with a specific biological target, leading to a desired therapeutic response or undesired side effects.
By analyzing the SAR, researchers can optimize the chemical structure of lead compounds to enhance their potency, selectivity, safety, and pharmacokinetic properties, ultimately guiding the design and development of novel drugs with improved efficacy and reduced toxicity.
Molecular structure, in the context of biochemistry and molecular biology, refers to the arrangement and organization of atoms and chemical bonds within a molecule. It describes the three-dimensional layout of the constituent elements, including their spatial relationships, bond lengths, and angles. Understanding molecular structure is crucial for elucidating the functions and reactivities of biological macromolecules such as proteins, nucleic acids, lipids, and carbohydrates. Various experimental techniques, like X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryo-electron microscopy (cryo-EM), are employed to determine molecular structures at atomic resolution, providing valuable insights into their biological roles and potential therapeutic targets.
Molecular models are three-dimensional representations of molecular structures that are used in the field of molecular biology and chemistry to visualize and understand the spatial arrangement of atoms and bonds within a molecule. These models can be physical or computer-generated and allow researchers to study the shape, size, and behavior of molecules, which is crucial for understanding their function and interactions with other molecules.
Physical molecular models are often made up of balls (representing atoms) connected by rods or sticks (representing bonds). These models can be constructed manually using materials such as plastic or wooden balls and rods, or they can be created using 3D printing technology.
Computer-generated molecular models, on the other hand, are created using specialized software that allows researchers to visualize and manipulate molecular structures in three dimensions. These models can be used to simulate molecular interactions, predict molecular behavior, and design new drugs or chemicals with specific properties. Overall, molecular models play a critical role in advancing our understanding of molecular structures and their functions.
Mescaline is a naturally occurring psychoactive alkaloid that is found in several species of cacti, including the peyote (Lophophora williamsii), San Pedro (Echinopsis pachanoi), and Peruvian torch (Echinopsis peruviana) cacti. It is known for its ability to produce profound changes in consciousness, mood, and perception when ingested.
In a medical context, mescaline is classified as a hallucinogen or psychedelic drug. It works by binding to serotonin receptors in the brain, which leads to altered states of consciousness, including visual hallucinations, distorted perceptions of time and space, and altered emotional states.
It's important to note that while mescaline has been used for centuries in religious and spiritual practices among indigenous communities, its use is not without risks. High doses can lead to unpleasant or even dangerous psychological effects, such as anxiety, panic, and psychosis. Additionally, the legal status of mescaline varies by country and region, so it's important to be aware of local laws and regulations before using it.
'Salvia officinalis', also known as garden sage or common sage, is not a medical condition but an herb that has been used in traditional medicine. Here's the botanical definition:
Salvia officinalis, commonly known as sage, garden sage, or common sage, is a perennial, evergreen subshrub, with woody stems, grayish leaves, and blue to purplish flowers. It belongs to the Lamiaceae family, also known as the mint family. The plant is native to the Mediterranean region and has been cultivated throughout the world for its aromatic leaves, which are used in cooking, cosmetics, and medicinal preparations.
In traditional medicine, sage leaves have been used to treat various conditions, such as sore throats, coughs, colds, and digestive issues. However, it is essential to note that the effectiveness of sage for these uses has not been thoroughly studied in clinical trials, and its use should not replace conventional medical care. Always consult with a healthcare professional before starting any new treatment or therapy.
A chemical model is a simplified representation or description of a chemical system, based on the laws of chemistry and physics. It is used to explain and predict the behavior of chemicals and chemical reactions. Chemical models can take many forms, including mathematical equations, diagrams, and computer simulations. They are often used in research, education, and industry to understand complex chemical processes and develop new products and technologies.
For example, a chemical model might be used to describe the way that atoms and molecules interact in a particular reaction, or to predict the properties of a new material. Chemical models can also be used to study the behavior of chemicals at the molecular level, such as how they bind to each other or how they are affected by changes in temperature or pressure.
It is important to note that chemical models are simplifications of reality and may not always accurately represent every aspect of a chemical system. They should be used with caution and validated against experimental data whenever possible.
"Drug design" is the process of creating and developing a new medication or therapeutic agent to treat or prevent a specific disease or condition. It involves identifying potential targets within the body, such as proteins or enzymes that are involved in the disease process, and then designing small molecules or biologics that can interact with these targets to produce a desired effect.
The drug design process typically involves several stages, including:
1. Target identification: Researchers identify a specific molecular target that is involved in the disease process.
2. Lead identification: Using computational methods and high-throughput screening techniques, researchers identify small molecules or biologics that can interact with the target.
3. Lead optimization: Researchers modify the chemical structure of the lead compound to improve its ability to interact with the target, as well as its safety and pharmacokinetic properties.
4. Preclinical testing: The optimized lead compound is tested in vitro (in a test tube or petri dish) and in vivo (in animals) to evaluate its safety and efficacy.
5. Clinical trials: If the preclinical testing is successful, the drug moves on to clinical trials in humans to further evaluate its safety and efficacy.
The ultimate goal of drug design is to create a new medication that is safe, effective, and can be used to improve the lives of patients with a specific disease or condition.
Molecular conformation, also known as spatial arrangement or configuration, refers to the specific three-dimensional shape and orientation of atoms that make up a molecule. It describes the precise manner in which bonds between atoms are arranged around a molecular framework, taking into account factors such as bond lengths, bond angles, and torsional angles.
Conformational isomers, or conformers, are different spatial arrangements of the same molecule that can interconvert without breaking chemical bonds. These isomers may have varying energies, stability, and reactivity, which can significantly impact a molecule's biological activity and function. Understanding molecular conformation is crucial in fields such as drug design, where small changes in conformation can lead to substantial differences in how a drug interacts with its target.
In the context of medical and biological sciences, a "binding site" refers to a specific location on a protein, molecule, or cell where another molecule can attach or bind. This binding interaction can lead to various functional changes in the original protein or molecule. The other molecule that binds to the binding site is often referred to as a ligand, which can be a small molecule, ion, or even another protein.
The binding between a ligand and its target binding site can be specific and selective, meaning that only certain ligands can bind to particular binding sites with high affinity. This specificity plays a crucial role in various biological processes, such as signal transduction, enzyme catalysis, or drug action.
In the case of drug development, understanding the location and properties of binding sites on target proteins is essential for designing drugs that can selectively bind to these sites and modulate protein function. This knowledge can help create more effective and safer therapeutic options for various diseases.
I'm happy to help! However, it seems there might be a bit of confusion in your question. "Modern" is a term that refers to a period in time, specifically the modern period which is generally considered to be from the late 19th century to the present. "Literature," on the other hand, is a broad term that refers to written works, especially those considered to have artistic or intellectual value.
So, when you ask for a medical definition of "Literature, Modern," it's not entirely clear what you are looking for. If you are asking for examples of modern literature that deal with medical themes or issues, there are many notable works to choose from, including:
* "The Immortal Life of Henrietta Lacks" by Rebecca Skloot, which explores the ethical implications of medical research using human cells without consent.
* "The Hot Zone" by Richard Preston, a thriller about the Ebola virus and its potential to cause a global pandemic.
* "Complications: A Surgeon's Notes on an Imperfect Science" by Atul Gawande, a collection of essays that examine the challenges and uncertainties of medical practice.
* "Brain on Fire: My Month of Madness" by Susannah Cahalan, a memoir about the author's experience with a rare autoimmune disorder that affected her brain.
If you are looking for something else, please let me know and I will do my best to assist you!
Circular dichroism (CD) is a technique used in physics and chemistry to study the structure of molecules, particularly large biological molecules such as proteins and nucleic acids. It measures the difference in absorption of left-handed and right-handed circularly polarized light by a sample. This difference in absorption can provide information about the three-dimensional structure of the molecule, including its chirality or "handedness."
In more technical terms, CD is a form of spectroscopy that measures the differential absorption of left and right circularly polarized light as a function of wavelength. The CD signal is measured in units of millidegrees (mdeg) and can be positive or negative, depending on the type of chromophore and its orientation within the molecule.
CD spectra can provide valuable information about the secondary and tertiary structure of proteins, as well as the conformation of nucleic acids. For example, alpha-helical proteins typically exhibit a strong positive band near 190 nm and two negative bands at around 208 nm and 222 nm, while beta-sheet proteins show a strong positive band near 195 nm and two negative bands at around 217 nm and 175 nm.
CD spectroscopy is a powerful tool for studying the structural changes that occur in biological molecules under different conditions, such as temperature, pH, or the presence of ligands or other molecules. It can also be used to monitor the folding and unfolding of proteins, as well as the binding of drugs or other small molecules to their targets.
I'm sorry for any confusion, but "Quantum Theory" is not a term that is typically used in medical definitions. Quantum theory, also known as quantum mechanics, is a branch of physics that deals with phenomena on a very small scale, such as molecules, atoms, and subatomic particles like electrons and photons (which are particles of light).
Quantum theory introduces the concept of wave-particle duality, where particles can exhibit both wave-like and particle-like properties. It also includes principles like superposition, which suggests that a physical system—such as an electron in an atom—can exist in multiple states or places at the same time until it is measured.
While quantum mechanics has had profound implications for our understanding of the physical world, its concepts are not directly applicable to medical definitions or human health. If you have any questions related to medicine or health, I'd be happy to help with those instead!
I am not aware of a widely accepted medical definition for the term "software," as it is more commonly used in the context of computer science and technology. Software refers to programs, data, and instructions that are used by computers to perform various tasks. It does not have direct relevance to medical fields such as anatomy, physiology, or clinical practice. If you have any questions related to medicine or healthcare, I would be happy to try to help with those instead!
Computational biology is a branch of biology that uses mathematical and computational methods to study biological data, models, and processes. It involves the development and application of algorithms, statistical models, and computational approaches to analyze and interpret large-scale molecular and phenotypic data from genomics, transcriptomics, proteomics, metabolomics, and other high-throughput technologies. The goal is to gain insights into biological systems and processes, develop predictive models, and inform experimental design and hypothesis testing in the life sciences. Computational biology encompasses a wide range of disciplines, including bioinformatics, systems biology, computational genomics, network biology, and mathematical modeling of biological systems.
An algorithm is not a medical term, but rather a concept from computer science and mathematics. In the context of medicine, algorithms are often used to describe step-by-step procedures for diagnosing or managing medical conditions. These procedures typically involve a series of rules or decision points that help healthcare professionals make informed decisions about patient care.
For example, an algorithm for diagnosing a particular type of heart disease might involve taking a patient's medical history, performing a physical exam, ordering certain diagnostic tests, and interpreting the results in a specific way. By following this algorithm, healthcare professionals can ensure that they are using a consistent and evidence-based approach to making a diagnosis.
Algorithms can also be used to guide treatment decisions. For instance, an algorithm for managing diabetes might involve setting target blood sugar levels, recommending certain medications or lifestyle changes based on the patient's individual needs, and monitoring the patient's response to treatment over time.
Overall, algorithms are valuable tools in medicine because they help standardize clinical decision-making and ensure that patients receive high-quality care based on the latest scientific evidence.
Quantitative structure-activity relationship
5-MeO-DET
Partition coefficient
Totarol
Difludiazepam
List of benzodiazepines
17α-Bromoprogesterone
Corwin Hansch
Bromethenmadinone acetate
Dinoseb
2,5-Dimethoxy-4-isopropylamphetamine
Adenine phosphoribosyltransferase
Sterimol parameter
Octanol-water partition coefficient
Therapeutic Targets Database
4-Fluoromethylphenidate
3-Bromomethylphenidate
Clomacran
Fish acute toxicity syndrome
Aclonifen
Grunwald-Winstein equation
Molecular Informatics
Pesticide degradation
Taft equation
Sean Ekins
Biological aspects of fluorine
Fluorine
Ro20-8065
Fluclotizolam
Ro07-9749
Quantitative structure-activity relationship - Wikipedia
EuroQSAR 2016 Verona Italy, 21st European Symposium on Quantitative Structure-Activity Relationship
Biocatalytic oxidation of phenolic compounds by bovine methemoglobin in the presence of H2O2: quantitative structure-activity...
Quantitative Structure Activity Relationship Studies of Sulfamide Derivatives as Carbonic Anhydrase Inhibitor: As Antiglaucoma...
Interpretable correlation descriptors for quantitative structure-activity relationships | Journal of Cheminformatics | Full Text
Quantitative Structure Activity Relationship (QSAR) - BioNome
Unbalance Quantitative Structure Activity Relationship Problem Reduction in Drug Design
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4D- quantitative structure-activity relationship modeling: making a comeback - NCSU Bioinformatics Research Center
RI UFLA: Quantitative structure-activity relationship studies for potential rho-associated protein kinase inhibitors
Bisphenol analogues inhibit human and rat 17ß-hydroxysteroid dehydrogenase 1: 3D-quantitative structure-activity relationship ...
Acronyms and Abbreviations - OECD
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Prooxidant toxicity of polyphenolic antioxidants to HL-60 cells : description of quantitative structure-activity relationships<...
Quantitative structure-activity relationships on 5-substituted terbenzimidazoles as topoisomerase I poisons and antitumor...
Exploring Quantitative Structure-Activity Relationships (QSARs) of Cyclooxygenase-2 (COX-2) Inhibitors by MLR, PLS and PC-ANN.
Holistic prediction of enantioselectivity in asymmetric catalysis | Nature
A k-nearest neighbor classification of hERG K+ channel blockers | Journal of Computer-Aided Molecular Design
Quantitative Structure Activity Relationship Studies of Some New 4-Thiazolidinone Derivatives as Antimicrobial Agents | Jacob |...
Structure activity relationship (SAR) and quantitative structure activity relationship (QSAR) studies showed plant flavonoids...
Development of quantitative structure-activity relationships for explanatory modeling of fast reacting (meth)acrylate monomers...
IJMS | Free Full-Text | Beyond the Flavour: The Potential Druggability of Chemosensory G Protein-Coupled Receptors
Machine Learning-Based Quantitative Structure-Activity Relationship and ADMET Prediction Models for ERα Activity of Anti-Breast...
Staff Listing - The University of Nottingham
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QSAR26
- Quantitative structure-activity relationship models (QSAR models) are regression or classification models used in the chemical and biological sciences and engineering. (wikipedia.org)
- the QSAR response-variable could be a biological activity of the chemicals. (wikipedia.org)
- QSAR models first summarize a supposed relationship between chemical structures and biological activity in a data-set of chemicals. (wikipedia.org)
- Second, QSAR models predict the activities of new chemicals. (wikipedia.org)
- A QSAR has the form of a mathematical model: Activity = f (physiochemical properties and/or structural properties) + error The error includes model error (bias) and observational variability, that is, the variability in observations even on a correct model. (wikipedia.org)
- All OPERA models were built using curated data sets split into training and test sets and molecular descriptors developed from standardized QSAR-ready chemical structures. (nih.gov)
- A comparative QSAR analysis was therefore undertaken, in order to discern the antiparasitic activity of STLs against T. brucei and cytotoxicity. (unibas.ch)
- Conclusion: The QSAR model obtained suggests that substituents with a lesser value of the index of refraction and less electronegative groups were favourable for the activity, whereas indomethacin derivatives with a CH2CH2NHCONH (CH2)3ONO2 group at R1 position were unfavourable for the activity. (currentmedicinalchemistry.com)
- The new European chemicals regulation Registration, Evaluation, Authorization and Restriction of Chemicals entered into force in June 2007 and accelerated the development of quantitative structure-activity relationship (QSAR) models for a variety of endpoints, including carcinogenicity. (nih.gov)
- Many QSAR tools are well developed that can predict the toxicity level of a chemical substance just by feeding its chemical structure. (girliciousbeauty.com)
- To achieve that, we constructed a novel approach by incorporating the drug's Mode of Action (MOA) into Quantitative Structure-Activity Relationship (QSAR) modeling. (nih.gov)
- Quantitative Structure-Activity Relationship (QSAR) analysis attempts to develop a predictive model of biological activity based on molecular descriptors. (njit.edu)
- Through topographical descriptors , quantitative structure-activity relationships ( QSAR ) were developed in order to identify the most effective PRMT1 inhibitors among 17 compounds. (bvsalud.org)
- Computational modeling approaches have emerged as low-cost alternatives, especially those used to develop quantitative structure-activity relationship (QSAR) models. (researchwithnj.com)
- This paper discusses some major hurdles on the way to full understanding of Quantitative Structure-Activity Relationships (QSAR) of skin permeation. (cdc.gov)
- QSAR modelling was performed on thirty-five (35) newly discovered compounds of N-(2-phenoxy) ethyl imidazo[1,2-a] pyridine-3-carboxamide (IPA) to predict their biological activities against Mycobacterium tuberculosis (MTB-H37Rv strain) by using some numerical data derived from structural and chemical features (descriptors) of the compounds. (springeropen.com)
- The quantitative structure-activity relationship (QSAR) technique provides a mathematical model containing some structural features represented as numerical data which predicts the response properties of the compound such as activity, toxicity, and so on (Ibrahim et al. (springeropen.com)
- People are probably more familiar with the term "QSAR"-quantitative structure-activity relationship. (nih.gov)
- The indirect drug design is sub-segmented into pharmacophore, quantitative structure-activity relationships (QSAR), and others. (medgadget.com)
- In the present study 3D quantitative structure activity relationship (3D QSAR) studies involving comparative molecular field analysis (CoFMA) were performed on 28 thiotetrazole alkynylacetanilides. (hindawi.com)
- QSAR, for those outside the business, stands for Quantitative Structure-Activity Relationship(s), an attempt to rationalize the behavior of a series of drug candidate compounds through computational means. (corante.com)
- Quantitative structure-activity/property relationship (QSAR/QSPR) models provide predictions of chemical activity that can augment non-animal approaches for predicting toxicity. (nih.gov)
- Then, a quantitative structure-activity relationship (QSAR) analysis was performed using Bayesian regularized artificial neural networks to model the relationships between in silico molecular descriptors and the observed antiproliferative activity of molecules across the tested cell lines. (rsc.org)
- A statistically valid QSAR model was obtained (internal validation Q 2 = 0.663, RMSE CV = 0.071, 10-fold cross-validation procedure, and external validation R pred 2 = 0.740, RMSE = 0.077), which allowed the analysis of the involved relationships between molecular descriptors and the reliable prediction of the antiproliferative activity for hypothetical related compounds in the studied cell lines. (rsc.org)
- This allowed for further investigation of its therapeutic potential and provided new opportunities to modify the molecule for lead optimization and analysis of quantitative structure activity relationships (QSAR). (lsus.edu)
- In quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR) studies, computation of topological indices is a vital tool to predict biochemical and physio-chemical properties of chemical structures. (techscience.com)
QSPR1
- Related terms include quantitative structure-property relationships (QSPR) when a chemical property is modeled as the response variable. (wikipedia.org)
Prediction13
- This activity prediction may assist the contribution of certain pharmacophore features encoded by respective fragments toward activity improvement and/or detrimental effects. (wikipedia.org)
- For consistency and transparency, OPERA also provides a tool for standardizing chemical structures, an estimate of prediction accuracy, an assessment of applicability domain, and incorporation of experimental values when available. (nih.gov)
- Here, we would like to present quantitative (continuous) and qualitative (categorical) models for non-congeneric chemicals for prediction of carcinogenic potency. (nih.gov)
- A quantitative prediction of the biological, ecotoxicological or pharmaceutical activity of a molecule. (nih.gov)
- Application of Quantitative Structure-Activity Relationships in the Prediction of New Compounds with Anti-Leukemic Activity. (bvsalud.org)
- Binding affinity prediction continues to be a challenge for computer-aided drug design, especially in the case where there is no high-resolution experimental structure of the target of interest. (springer.com)
- Traditionally people use chemical structures to make a prediction. (nih.gov)
- We don't rely on the chemical structures to make a prediction, but we will use the biological activity profiles of those compounds. (nih.gov)
- Basically, you apply a computational model based on the biological activity profiles of compounds and then make a prediction on their activity against, for example, COVID-19. (nih.gov)
- You can make a prediction on anything, so you can profile the activity of a compound or a substance-or anything-against a panel of assays and then just use this biological activity profile signature to predict this new activity against a new target. (nih.gov)
- Then we cannot use the traditional structure-based modeling, but we can apply this biological activity-based modeling, and then we can still make a prediction on those chemicals or substances. (nih.gov)
- Eldred DV, Weikel CL, Jurs P, Kaiser KLE (1999) Prediction of fathead minnow acute toxicity or organic compounds from molecular structure. (springer.com)
- Pantakar SJ, Jurs PC (2000) Prediction of IC 50 values for ACAT inhibitors from molecular structure. (springer.com)
Descriptors6
- GQSAR also considers cross-terms fragment descriptors, which could be helpful in identification of key fragment interactions in determining variation of activity. (wikipedia.org)
- 3D structures of compounds were also drawn on Gauss View software for calculations of various density functional theory (DFT) based quantum chemical descriptors, such as total energy (TE), softness (S), hardness (η), chemical potential (μ), highest occupied molecular orbital energy (HOMO), and lowest unoccupied molecular orbital energy (LUMO). (currentmedicinalchemistry.com)
- These kinds of descriptors are obtained by treating the structure of the chemical compound as a graph. (girliciousbeauty.com)
- A genetic algorithm - partial least squares (GA-PLS) approach was used to identify the molecular descriptors that correlate to the biological activity (binding affinity) of a set of 80 methylphenidate analogues and to construct a predictive model. (njit.edu)
- Partial Least Squares Regression was then applied to the selected descriptors to create a predictive model of biological activity (q 2 = 0.78, fitness = 0.77). (njit.edu)
- The diverse chemometric descriptors were computed from the optimized structures using the PaDEL descriptors software, and the division of the dataset into training and test sets was done based on Kennard-Stone's algorithm. (springeropen.com)
Toxicity6
- Some examples are quantitative structure-reactivity relationships (QSRRs), quantitative structure-chromatography relationships (QSCRs) and, quantitative structure-toxicity relationships (QSTRs), quantitative structure-electrochemistry relationships (QSERs), and quantitative structure-biodegradability relationships (QSBRs). (wikipedia.org)
- A dataset of 805 substances was obtained after a preliminary screening of findings of rodent carcinogenicity for 1,481 chemicals accessible via Distributed Structure-Searchable Toxicity (DSSTox) Public Database Network originated from the Lois Gold Carcinogenic Potency Database (CPDB). (nih.gov)
- We have come so far with technology that we actually have computer programs that can help us determine a chemical's toxicity just by knowing its structure. (cdc.gov)
- Part of my work is determining how well that process, called Quantitative Structure-Activity Relationships (QSARs), works and if it can be used to supply toxicity data when animal or human data is not available for a chemical," said Jona. (cdc.gov)
- Maybe you can avoid some kind of toxicity with this new structure and improve activity. (nih.gov)
- These findings suggest quantitative considerations for building scientific confidence in NAM-based systemic toxicity predictions. (nih.gov)
Chemical structures3
- The mathematical expression, if carefully validated, can then be used to predict the modeled response of other chemical structures. (wikipedia.org)
- Traditionally people just use chemical structures to try to predict the biological activity for small molecule compounds against a biological target or disease, such as COVID-19 or another viral disease, or some other diseases such as cancer-or anything. (nih.gov)
- You can use this approach to actually discover new chemical structures or new scaffolds. (nih.gov)
Compounds9
- Some of the compounds possess high activity, especially against T. brucei (e.g. helenalin and some of its esters with IC(50)-values of 0.05-0.1 microM, which is about 10 times lower than their cytotoxic activity). (unibas.ch)
- It is based upon structure and activity information gathered from a series of similar compounds. (nih.gov)
- At first, the structure of the compounds was accurately drawn and optimized using the Spartan 14 software at DFT level of theory with B3LYP/6-31G** basis set in a vacuum. (springeropen.com)
- Based on the information obtained from model 1, six (6) designed compounds with higher anti-tubercular activity were obtained. (springeropen.com)
- They know the activities of some compounds with known structure, and then when you come up with a new chemical with the new structure, you look at the structure of the new chemical to see if it looks similar to the existing chemical. (nih.gov)
- At NCATS, we do a lot of high-throughput screening, so we generate a lot of biological activity data and activity profiles on those compounds. (nih.gov)
- Then we can use this data to make predictions about the activities of those compounds against new targets or new diseases. (nih.gov)
- Can you speak about how you and others have used the biological activity-based modeling to predict 311 potential compounds to be used against severe COVID-19? (nih.gov)
- Interestingly, among the compounds prepared, the molecules containing chloro atoms in their structure demonstrated a relevant potency and a selective antiproliferative activity against a novel hepatic cancer cell line (HepaRG) without exhibiting noticeable cytotoxicity in normal dermal cells (NHDF). (rsc.org)
Modeling5
- To begin, will you please define what biological activity-based modeling is and what the advantages are of doing this type of modeling? (nih.gov)
- This is a traditional method called "structure-based modeling. (nih.gov)
- Then there's this biological activity-based modeling. (nih.gov)
- That's basically the concept behind the biology activity-based modeling. (nih.gov)
- 13. Discovery of novel chemotypes to a G-protein-coupled receptor through ligand-steered homology modeling and structure-based virtual screening. (nih.gov)
Chemicals2
Models3
- Quantitative models were developed exploring the relationship between the experimental and predicted carcinogenic potency expressed as a tumorgenic dose TD(50) for rats. (nih.gov)
- We introduce the QuanSA method for inducing physically meaningful field-based models of ligand binding pockets based on structure-activity data alone. (springer.com)
- This strong and varied response results not least from the fact that plausibilistic Bayesian models of structures and processes can be robust and stable representations of causal relationships. (intechopen.com)
Theoretical1
- But, it is just a theoretical approach to calculate a quantitative measure of the relationship between a chemical structure and its physical or biological activity. (girliciousbeauty.com)
Molecules5
- The basic assumption for all molecule-based hypotheses is that similar molecules have similar activities. (wikipedia.org)
- The SAR paradox refers to the fact that it is not the case that all similar molecules have similar activities. (wikipedia.org)
- We explored the anticancer activity of two synthetic flavonoid-based small molecules, HMDC and HMDF, with bioactive methylenedioxy functionality. (researchgate.net)
- It describes generation, manipulation or representation of three-dimensional structures of molecules and their associated physic-chemical properties. (medgadget.com)
- Thus, a series of molecules was synthesized through the Biginelli reaction and their in vitro antiproliferative activity was evaluated in different human cell lines. (rsc.org)
Substances1
- Not all substances have a defined chemical structure. (nih.gov)
Inhibition1
- The anti-inflammatory activity of analogs 3a and 3c may be associated with their inhibition of the phosphorylation of extracellular signal-regulated kinase and the activation of nuclear factor-kappa B. In addition, 3c exhibited significant protection against LPS-induced septic death in vivo. (dovepress.com)
Physicochemical1
- Additionally, when physicochemical properties or structures are expressed by numbers, one can find a mathematical relationship, or quantitative structure-activity relationship, between the two. (wikipedia.org)
Potency1
- 2019 ). Researches have shown that imidazo[1,2-a] pyridine-3-carboxamides (IPA) as an anti-tubercular candidate is currently in the second phase of clinical trials, and it was reported to have resilient inhibitory potency or anti-mycobacterial activity (Wang et al. (springeropen.com)
Analogue1
- 4'-N,N-Dimethylamino-3-hydroxyflavone (DMAHF), a synthetic fluorescent flavone analogue with potent antioxidant activity, was explored as a molecular rotor-like fluoroprobe for amyloid aggregations, a causative factor in Alzheimer's disease, Parkinson's disease, type-2 diabetes, etc. (researchgate.net)
Analysis1
- Antileukemic activity is predicted using a multilinear regression analysis , and it can account for more than 56% of the variation. (bvsalud.org)
Inhibitory1
- Several studies have indicated that some natural products exhibit inhibitory activities against SARS-CoV-2. (hindawi.com)
Biological activity based2
Cytotoxic1
- Furthermore, cytotoxic activity against L6 rat skeletal myoblast cells was assessed. (unibas.ch)
Studies2
- Prompted by results of our previous studies where we found high activity of some sesquiterpene lactones (STLs) against Trypanosoma brucei rhodesiense (which causes East African sleeping sickness), we have now conducted a structure-(in-vitro)-activity study on a set of 40 STLs against T. brucei rhodesiense, T. cruzi, Leishmania donovani and Plasmodium falciparum. (unibas.ch)
- 4. 3D-Quantitative structure-activity relationship and docking studies of the tachykinin NK3 receptor. (nih.gov)
Receptor3
- 7. The tachykinin NK3 receptor agonist senktide induces locomotor activity in male Mongolian gerbils. (nih.gov)
- 11. Synthesis of new 4-heteroaryl-2-phenylquinolines and their pharmacological activity as NK-2/NK-3 receptor ligands. (nih.gov)
- Selective melatonin receptor agonists Tasimelteon, Ramelteon, and combined melatonergic-serotonin Agomelatine, and other agonists with registered structures in CHEMBL were not yet investigated as cardioprotective or cardiovascular drugs. (mdpi.com)
Calculate1
- Structure-activity relationship ( commonly known as SAR) is an approach to calculate and evaluate the relationship between the molecular or chemical structure and its biological activity. (girliciousbeauty.com)
Analogs1
- Here, we synthesized 26 asymmetric monocarbonyl analogs of curcumin and evaluated their anti-inflammatory activity by inhibiting the LPS-induced secretion of tumor necrosis factor-α and interleukin-6 in mouse RAW264.7 macrophages. (dovepress.com)
Experimental2
- Experimental structure determination remains challenging for many pharmaceutical targets such as ligand-gated ion channels, membrane transporters, and (now to a lesser extent) membrane-spanning G-protein coupled receptors. (springer.com)
- For the former methods, in the case where experimental structures are known for all ligands under consideration, performance can be quite variable based on the specific protein target (Pearson's r \(^2\) range of 0.0-0.8 for individual proteins) [ 19 ], though careful work has shown more consistent results in some cases (r \(^2\) of 0.5-0.6 for three enzyme targets) [ 14 ]. (springer.com)
Molecular structure1
- They withhold the properties relevant to the molecular structure of the compound. (girliciousbeauty.com)
Compound1
- It is centered on a compound known as fusarochromanone (FC101), an anti-cancer agent with unique structure and function. (lsus.edu)
Data2
- We provide algorithmic details along with performance results on sixteen structure-activity data sets covering many pharmaceutically relevant targets. (springer.com)
- they can be applied purely from structure and activity data. (springer.com)
SMILES1
- The most common molecular file formats accepted in E-Dragon software were SMILES notations created online by Babel software and 2D structures of various derivatives, which were converted into 3D optimized structures using online CORINA, provided by Molecular Networks GMBH. (currentmedicinalchemistry.com)
Mechanism1
- While FC101's exact mechanism of action is currently unknown, we have shown that it simultaneously inhibits the activity of two major oncogenic pathways, MAPK (corresponding to p-ERK reduction) and mTOR (corresponding to p-S6K, and p-S6 reduction) in cultured cancer cells. (lsus.edu)
Topological1
- In this article, we derive formulae of the ev-degree and ve-degree based topological indices for chemical structure of Si 2 C 3 − I [ a , b ]. (techscience.com)
Structural2
- It was found that all investigated antiprotozoal activities are significantly correlated with cytotoxicity and the major determinants for activity are a,b-unsaturated structural elements, also known to be essential for other biological activities of STLs. (unibas.ch)
- Both activities were found to depend to a large extent on the same structural elements and molecular properties. (unibas.ch)
Research Article1
- The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. (acs.org)
Properties3
- 2D - A 2D structure formula is inferred and the properties of the structure of the chemical are considered. (girliciousbeauty.com)
- xMaP-An Interpretable Alignment-Free Four-Dimensional Quantitative Structure-Activity Relationship Technique Based on Molecular Surface Properties and Conformer Ensembles. (acs.org)
- Similarly, the difference between forming a crucial hydrogen bond and not forming one is a big difference, and it can be realized by a very small change in structure and properties. (corante.com)
Generation3
- We look forward to continuing our legacy relationships and welcoming a new generation of NanoBCA members. (vincentcaprio.org)
- We elaborated protocols for two common conformer generation use cases and applied them to both programs: (i) high-throughput settings for processing large databases and (ii) high-quality settings for binding site exploration or lead structure refinement. (acs.org)
- Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials. (acs.org)
Cell2
- This vocabulary was reorganized to group the various components of a cell together under Cell Structures (A11.284) and add 27 new cell structure terms. (nih.gov)
- Clarke, J, Uzarski, RL & Uzarski, DG 2000, Trichothecene-induced apoptosis in B cell lymphomas: quantitative structure activity relationships . (cmich.edu)
Search1
- Search Result "structure activity relationship. (eurekaselect.com)
Drawn1
- Two-dimensional (2D) structures of fifteen indomethacin derivatives were drawn using the ACD Lab Chem Sketch version. (currentmedicinalchemistry.com)
Hypotheses1
- We can generate so many hypotheses, relating convoluted molecular factors to activity in such complicated ways, that the process of careful hypothesis testing so critical to scientific understanding has been circumvented in favor of blind validation tests with low resulting information content. (corante.com)