SEARCH · PubMed Health

Results for “Model”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31Linked to original sources

PubMed1999

The utility of animal models in the preclinical study of interventions to prevent human coronary artery restenosis: analysis and recommendations. On behalf of the Subcommittee on Animal, Cellular and Molecular Models of Thrombosis and Haemostasis of the Scientific and Standardization Committee of the International Society on Thrombosis and Haemostasis.

Small animal models have several advantageous characteristics, but those used in preclinical restenosis research have lacked efficacy in predicting the success of interventions to inhibit restenosis in humans. Large animal models have been more successful than small animal models in predicting efficacy of interventions to inhibit restenosis in humans, but the results of studies carried out with these models have not been uniformly predictive. Confirmation of the results of small animal studies in large animals has not always yielded information predictive of success in humans; however, the absence of such confirmation has had strong negative predictive value. Small animal models used for evaluation of interventions to inhibit luminal narrowing following arterial instrumentation have failed to closely simulate human atherosclerosis and the stenotic lesions subjected to instrumentation in humans. Transgenic, atherosclerotic animals hold promise for the development of more useful small animal models to study mechanisms of the response of diseased arteries to angioplasty and stents. The pig has been the most useful large animal to study stenosis/ restenosis, but more information is needed to overcome the limitations of this model.

Animals↗

PubMedDate not supplied

[Modeling of the plant community: individual oriented approach. II. A model of a community].

The individual-based approach to modeling of the plant cover dynamics is discussed. This approach takes into account that the cover consists of individual interacting plants, i.e., is a community. According to the principle of "minimal angle of viewing", this approach can be considered as approaching the object earlier considered from the energy standpoint (Monsi and Saeki, 1953; Khil'rni, 1957). An element of the model of community, balance model of plant dynamics, was considered in part I of the article. The community model is 2-D, i.e., it considers the growth and dying of plants in relation to their mutual geometrical arrangement in the community. Mechanisms of division and re-division of the territory among the plants of community are important elements of the community model. These mechanisms use the Voronoi mosaic. Some results of the development and analysis of the model of community are considered, such as the possibility of non-monotonous competition in homogeneous communities and -3/2 rule considered as "one of the most general principles of plant population biology" (White, 1980). The 2-D individual-based approach to modeling can be an effective tool for analysis of the influence of many "microscopic" features of the community structure on its macroscopic behavior.

Algorithms↗

PubMed1975

The simulated drinking gang: an experimental model for the study of a systems approach to alcoholism. I. Description of the model.

This two-part paper deals with an experimental model for studying interactional behavior from a systems point of view. The experimental model incorporates a research strategy utilizing both a token economy and the simulation of a naturally occurring clinical phenomenon, the alcoholic drinking gang. The model is primarily geared to do two things: a) study the changes in clinical behavior that occur when experimental conditions are manipulated to facilitate the formation of the behavioral "system" as opposed to experimental conditions which interfere with system formation; and b) build into the model tasks which produce measurable performance data as a method of monitoring behavior deemed essential for the successful development of an operational system. The experimental model involved admitting up to six alcoholic individuals to a research ward specifically designed for studies utilizing experimentally induced intoxication. Each study was divided into a 7-day predrinking period, a 10- to 14-day drinking period, during which time alcohol was available to research subjects, and a 5- to 7-day withdrawal period. A token economy was established which allowed for the following essential features to be present: a) a group of chronic alcoholic individuals who desire to go through a drinking experience together; b) the pooling of resources in order to purchase alcohol; c) rules established by the group for the sharing of whatever alcohol becomes available to the group; and d) the opportunity to earn money for the purchase of additional alcohol after the initial supply runs out, in order to keep the group drinking experience going. All "money", or tokens, could be earned only via successful performance at the Cooperative Task Device (CTD), a cooperative, two-person game, and tokens could be utilized to purchase three types of commodities from an automated dispensing machine, alcohol, cigarettes, and television time. Automated data recording provided detailed data about CTD performance and commodity-purchasing records. The discussion centers around difficulties inherent in a simulated model of natural behavior. It is pointed out that laboratory simulation vs. natural setting, as the preferred site for carrying on behavioral research, remains an active controversy, and the arguments on both sides are presented. Difficulties inherent in doing "systems" research are also discussed. A series of alternative hypotheses to explain behavior within the simulated drinking gang are listed, and the data that would be necessary in order to substantiate these alternative hypotheses are also listed. It is maintained that the simulated drinking gang is an advantageous experimental model in that it closely approximates the basic criteria of the naturally occurring phenomenon, while at the same time allowing subjects a range of behaviors, each of which substantiates a different hypothesis about the central organizing feature in alcoholic groups.

Alcohol Drinking↗

PubMed2004

A model of 3D-structure of H+, K+-ATPase catalytic subunit derived by homology modeling.

AIM: To build a model of 3D-structure of H(+), K(+)-ATPase catalytic subunit for theoretical study and anti-ulcer drug design. METHODS: The model was built on the basis of structural data from the Ca(2+)-ATPase. Structurally conserved regions were defined by amino acid sequence comparisons, optimum interconnecting loops were selected from the protein databank, and amino (N)- and carboxyl (C)-terminal ends were generated as random coil structures. Applying molecular mechanics method then minimized the model energy. Molecular dynamics technique was used to do further structural optimization. RESULTS: The model of 3D-structure of H(+), K(+)-ATPase was derived. The model is reasonable according to several validation criteria. There were ten transmembrane helices (TM1-TM10) in the model and inhibitor-binding site was identified on the TM5-8 riched negatively charged residues. CONCLUSION: The 3D-structure model from our study is informative to guide future molecular biology study about H(+), K(+)-ATPase and drug design based on database searching.

Amino Acid Sequence↗

PubMed2004

Model once, use multiple times: reusing HL7 domain models from one domain to the other.

The Dutch national ICT institute in healthcare (www.nictiz.nl) developed a domain information model for perinatology, to map to the Health Level 7 Reference Information Model (HL7 RIM). This model was constructed with the intention to make it reusable for other domains in order to achieve a national infrastructure based on the HL7 RIM. In two projects, the perinatology model was reused, which lead to some changes to better express the domain. It proves valuable to have a kind of generic domain model, which can be adapted easily to other domains. In these projects, information for hart infarction (cardiology) and stroke (neurology) was modelled. Few domain specific changes where necessary, which could be made following the same methodology. Both the models and the methodology prove to be re-usable.

Cardiology↗

PubMed1994

Methodological issues in the application of the minimal model: effects of glucose dose, basal glucose concentration, test duration and modelling constraint.

An intravenous glucose tolerance test (IVGTT) glucose dose of 0.3 g/kg has been adopted for measurement of insulin sensitivity using the minimal model. Traditionally, however, a dose of 0.5 g/kg has been used, which might be expected to improve the IVGTT insulin response and hence the effectiveness of minimal model analysis. In a preliminary study of 5 subjects given 0.3 and 0.5 g/kg IVGTTs, each lasting 120 minutes, we found a 53% increase in IVGTT insulin response at the higher dose, but there was a marked discrepancy in the difference between fasting and final glucose concentrations (-0.17 mmol.l-1 at 0.3 g/kg and -1.01 mmol.l-1 at 0.5 g/kg). Good agreement obtained between estimates of Si derived from 0.3 and 0.5 g/kg IVGTTs (mean Si: 0.3 g/kg test = 6.0 min-1.microU-1.ml, 0.5 g/kg test = 5.8 min-1.microU-1.ml: r = 0.97, p < 0.001) providing the final IVGTT glucose concentration rather than the fasting concentration was taken as the basal level for modelling analysis. These findings were confirmed and extended in two further studies; firstly in an analysis of the effects of choice of basal glucose concentration and the application of various modelling constraints in a cross-section of 66 subjects with a wide range of insulin sensitivities; then in a further study in which seven subjects were each given two 0.3 g/kg IVGTTs and one 0.5 g/kg IVGTT, with each test being prolonged to 300 minutes. Agreement between estimates of Si at the two different doses was again only achieved by taking the final IVGTT glucose concentration as basal (mean Si: 0.3 g/kg test = 4.7 min-1.microU-1.ml, 0.5 g/kg test = 3.8 min-1.microU-1.ml: r = 0.75, p < 0.05), although one anomalous test required that a constraint be applied to the modelling process for this agreement to obtain. Closest agreement between the 300 minute 0.3 and 0.5 g/kg IVGTTs was found when tests were modelled up to 180 minutes. An IVGTT duration of 180 minutes appears to be optimum for re-establishing the basal concentration necessary for effective modelling analysis. Application of constraints can markedly affect certain analyses and may introduce some bias; their use should be carefully monitored, although their effect on large datasets is likely to be small.

Adult↗

PubMedDate not supplied

Test of the Health Promotion Model as a causal model of workers' use of hearing protection.

The Health Promotion Model (HPM) was tested as a causal model to predict workers' use of hearing protection (N = 645). Measures indicated an excellent fit of the theoretical model. The exploratory analyses found the same cognitive-perceptual factors most important in predicting use. However, in contrast to the theoretical model, two modifying factors (job category and situational factors) had direct effects on use. The hypothesized model accounted for 49.3% of variance and the exploratory models accounted for 50.7% to 52.7% of variance in hearing protection use. Results of testing the HPM are consistent with the recently proposed revision of the model by Pender, Walker, Frank-Stromborg, and Sechrist (1990a, 1990b). The strongest effects on behavior came from the behavior-specific influences and demographic characteristics. Situational factors had a direct effect on the health behavior.

Cognition↗

PubMed2005

From continuum Fokker-Planck models to discrete kinetic models.

Two theoretical formalisms are widely used in modeling mechanochemical systems such as protein motors: continuum Fokker-Planck models and discrete kinetic models. Both have advantages and disadvantages. Here we present a "finite volume" procedure to solve Fokker-Planck equations. The procedure relates the continuum equations to a discrete mechanochemical kinetic model while retaining many of the features of the continuum formulation. The resulting numerical algorithm is a generalization of the algorithm developed previously by Fricks, Wang, and Elston through relaxing the local linearization approximation of the potential functions, and a more accurate treatment of chemical transitions. The new algorithm dramatically reduces the number of numerical cells required for a prescribed accuracy. The kinetic models constructed in this fashion retain some features of the continuum potentials, so that the algorithm provides a systematic and consistent treatment of mechanical-chemical responses such as load-velocity relations, which are difficult to capture with a priori kinetic models. Several numerical examples are given to illustrate the performance of the method.

Adenosine Triphosphate↗

PubMed1997

Structural identifiability of PBPK models: practical consequences for modeling strategies and study designs.

Physiologically based pharmacokinetic (PBPK) models usually contain unknown parameters that need to be estimated by calibration to concentration-time profiles from in vivo experiments. However, even with error-free data, the number of parameters that can be estimated in this way is limited, depending on the particular situation. This paper introduces the concept of structural identifiability of a model, a requirement to make the estimation of parameters by calibration a meaningful undertaking. We briefly discuss the techniques-available from systems analysis-for examining the identifiability of models. Two conditions of uniqueness are involved, one relating to the model's equations and its parameters, the other to the number of available observations in time. The assessment of the first uniqueness condition involves rather tedious matrix algebra, requiring the appropriate mathematical expertise. We therefore give some general results for a particular class of PBPK models, indicating in what situations the first uniqueness condition either holds or does not. The assessment of the second uniqueness condition does not require specialized skills, and the minimum number of observations in time necessary can be easily determined for any particular situation. The practical implications for both modeling strategies and experimental protocols are discussed.

Animals↗

PubMed2005

Modeling anti-KLH ELISA data using two-stage and mixed effects models in support of immunotoxicological studies.

During preclinical drug development, the immune system is specifically evaluated after prolonged treatment with drug candidates, because the immune system may be an important target system. The response of antibodies against a T-cell-dependent antigen is recommenced by the FDA and EMEA for the evaluation of immunosuppression/enhancement. For that reason, we developed a semiquantitative enzyme-linked immunosorbent assay to measure antibodies against keyhole limpet hemocyanin. To our knowledge, the analysis of this kind of data is at this moment not yet fully explored. In this article, we describe two approaches for modeling immunotoxic data using nonlinear models. The first is a two-stage model in which we fit an individual nonlinear model for each animal in the first stage, and the second stage consists of testing possible treatment effects using the individual maximum likelihood estimates obtained in the first stage. In the second approach, the inference about treatment effects is based on a nonlinear mixed model, which accounts for heterogeneity between animals. In both approaches, we use a three-parameter logistic model for the mean structure.

Analysis of Variance↗

PubMed2006

Applying FSL to the FIAC data: model-based and model-free analysis of voice and sentence repetition priming.

This article presents results obtained from applying various tools from FSL (FMRIB Software Library) to data from the repetition priming experiment used for the HBM'05 Functional Image Analysis Contest. We present analyses from the model-based General Linear Model (GLM) tool (FEAT) and from the model-free independent component analysis tool (MELODIC). We also discuss the application of tools for the correction of image distortions prior to the statistical analysis and the utility of recent advances in functional magnetic resonance imaging (FMRI) time series modeling and inference such as the use of optimal constrained HRF basis function modeling and mixture modeling inference. The combination of hemodynamic response function (HRF) and mixture modeling, in particular, revealed that both sentence content and speaker voice priming effects occurred bilaterally along the length of the superior temporal sulcus (STS). These results suggest that both are processed in a single underlying system without any significant asymmetries for content vs. voice processing.

Brain Mapping↗

PubMed2007

An overall strategy based on regression models to estimate relative survival and model the effects of prognostic factors in cancer survival studies.

Relative survival provides a measure of the proportion of patients dying from the disease under study without requiring the knowledge of the cause of death. We propose an overall strategy based on regression models to estimate the relative survival and model the effects of potential prognostic factors. The baseline hazard was modelled until 10 years follow-up using parametric continuous functions. Six models including cubic regression splines were considered and the Akaike Information Criterion was used to select the final model. This approach yielded smooth and reliable estimates of mortality hazard and allowed us to deal with sparse data taking into account all the available information. Splines were also used to model simultaneously non-linear effects of continuous covariates and time-dependent hazard ratios. This led to a graphical representation of the hazard ratio that can be useful for clinical interpretation. Estimates of these models were obtained by likelihood maximization. We showed that these estimates could be also obtained using standard algorithms for Poisson regression.

Aged↗

PubMed2001

Modeling magnetization transfer using a three-pool model and physically meaningful constraints on the fitting parameters.

A model for water-macromolecular magnetization transfer is presented which addresses the mechanism of coupling between the hydrogen populations and the extraction of physically meaningful parameters from experimental magnetization transfer data. Both physical exchange between bulk-solvent and site-specific hydration-layer hydrogens and intermolecular magnetic dipolar coupling between these specific hydration-layer-solvent and macromolecular hydrogens are explicitly included, leading to a three-pool model for magnetization transfer. It is shown that the three-pool model is well approximated by a two-pool model for coupling between the bulk-solvent and macromolecular hydrogens when the dipolar-coupled solvent hydrogens are a small fraction of the total solvent, and the solvent-macromolecular coupling constant includes both dipolar magnetic, kappa(dip), and physical exchange, kappa(ex), coupling rates. The model is also extended to multiple solvent systems. The model results in a set of coupled equations that predict magnetization transfer spectra as a function of temperature and composition. Physically meaningful constraints on the coupling and relaxation parameters are established for systems in which magnetization transfer has been observed including solvated cross-linked proteins and lipid bilayers. Using parameter estimates based on these constraints, empirical magnetization transfer spectra are well predicted by the model. It is found that the degree of magnetization transfer becomes independent of kappa(dip) and kappa(ex) when these parameters become greater than about 50 s(-1). In the semi-rigid cross-linked protein systems where the mobility of the macromolecular matrix is insensitive to temperature, the magnitude of the observed magnetization transfer is consistent with being limited by the intermolecular dipolar coupling and spin-lattice relaxation in the bulk-solvent phase.

Journal Article↗

PubMed1996

Structure and Activity of Membrane Receptors: Modeling and Computational Simulation of Ligand Recognition in a Three-Dimensional Model of the 5-Hydroxytryptamine(1A) Receptor.

A three-dimensional molecular model of the transmembrane domain of the 5-HT(1A) receptor (5-HT(1A)R) is presented in the context of a general strategy for modeling the macromolecular structure of a guanine nucleotide binding, regulatory protein coupled receptor (GPCR). The model of the 5-HT(1A)R rests on the definition of the putative residues of the ligand-binding site guided by criteria based on specific models proposed from structure-activity studies and on published results of modifications of GPCRs using methods of molecular biology. The resulting requirements for matching recognition sites in the agonist-binding pocket define the molecular details of the interaction between the agonist 5-HT and the human 5-HT(1A)R that includes: (1) the interaction between the protonated amine moiety and the conserved negative Asp-116, located in TMH 3; (2) the hydrogen bond between the hydroxyl group and Thr-199, located in TMH 5; and (3) the interaction complex between the aromatic ring portion of the ligand and the neutral form of His-192, located in TMH 5. Results from quantum mechanical calculations of the interaction between an agonist and the proposed recognition pocket of the 5-HT(1A)R model suggest a trigger of the receptor activation mechanism resulting from ligand binding. The antagonist-binding pocket of the human 5-HT(1A)R is inferred from the interaction sites of pindolol with the receptor model: (1) the ionic interaction between the protonated amine of the ligand and the side chain of the conserved Asp-116, located in TMH 3; and (2) the hydrogen bonds between the ether oxygen and the hydroxyl group of the ligand and Asn-385, located in TMH 7. Use of the model is proposed to facilitate the identification of the structural elements of agonists and antagonists that are key for their specific functions, in order to achieve the design of new compounds with predetermined pharmacological properties. Copyright 1996 S. Karger AG, Basel

Journal Article↗

PubMed2005

The effects of modeling dietary restraint on food consumption: do restrained models promote restrained eating?

Sixty-nine female undergraduates completed the restraint scale, a dieting checklist, and the Eating Attribution Style Questionnaire (EASQ). The participants were exposed either to no model, a peer model who behaviorally demonstrated dietary restraint, or a peer model who behaviorally and verbally demonstrated dietary restraint. The participants had an opportunity to consume food as part of a taste test. The findings revealed that attribution style, but not restraint or current dieting status, moderated the effects of exposure to the peer models. Females who had an internal attribution style for indulgent food consumption decreased their consumption of food as a function of the dietary restraint of the models, whereas females who had an external attribution style for indulgent food consumption increased their consumption of food as a function of the dietary restraint of the models. The latter disinhibitory effect was attributed to negative social comparison and learned helplessness. The results supported the conclusion that the effectiveness of modeling dietary restraint is dependent on the attribution style of the observers.

Adolescent↗

PubMed2026

Dual β-lactam therapy against high-risk Pseudomonas aeruginosa isolates: a dynamic in-vitro infection model study integrating population genomics with quantitative systems pharmacology modelling and simulations.

BACKGROUND: Pseudomonas aeruginosa has an extraordinary capacity for resistance emergence during treatment, even with newer antipseudomonals. There is a gap in understanding how resistance mechanisms affect the time-course of bacterial response to these newer agents. Traditional approaches for predicting pathogen response to an antibiotic do not apply to combination therapy. We aimed to develop a modelling framework to predict treatment response based on resistome information, using isolates of the worldwide-disseminated high-risk clone sequence type (ST) 235 and β-lactam antibiotics as the example. METHODS: In this hollow-fibre in-vitro infection study, we used three extensively drug-resistant ST235 clinical isolates from the national collection of the Clinical Microbiology Department of the Hospital Son Espases (Palma de Mallorca, Spain) that were hospital-acquired, were isolated following routine microbiological procedures from different patients between 2017 and 2022, were susceptible to ceftolozane-tazobactam, and had different levels of meropenem resistance. The selected isolates (ST235-05, ST235-09, and ST235-10) showed classical β-lactam resistance mechanisms pre-treatment. The isolates were investigated in 240-h dynamic hollow-fibre in-vitro infection models (HFIMs). The studies exposed the isolates to pharmacokinetic profiles of ceftolozane-tazobactam (simulating 1 g of ceftolozane and 0·5 g of tazobactam as a 3-h infusion every 8 h) and meropenem (simulating 6 g per day continuous infusion) as observed in hospitalised patients, as monotherapy and in combination. Treatment response was assessed through the quantification of the time-courses of viable total and resistant bacteria. Whole-genome sequencing identified the mechanisms of emerging resistance. A quantitative systems pharmacology (QSP) approach was used to model total and resistant bacterial counts and corresponding pharmacokinetic data from the HFIM. Monte Carlo simulations were used to predict treatment responses in 1000 virtual infected patients treated with ceftolozane-tazobactam and meropenem as monotherapies or in combination over 10 days. FINDINGS: In the HFIMs, each antibiotic alone amplified resistance by approximately 48 h for all isolates; that is, monotherapies resulted in a higher concentration of resistant bacteria compared with the control treatment at the respective time, except ceftolozane-tazobactam against ST235-10. Combination of ceftolozane-tazobactam and meropenem was synergistic (bacterial counts ≥2 log10 colony forming units [CFU] per mL lower than the best performing monotherapy and initial inoculum) against all isolates and suppressed resistance. Against ST235-10, ceftolozane-tazobactam monotherapy reduced counts to less than 1 log10 CFU per mL from 192 h onwards, whereas the combination reached less than 1 log10 CFU per mL by 24 h. Across strains, population genomics confirmed monotherapy failures were associated with emerging resistance mechanisms (ceftolozane-tazobactam: ampC Ω-loop mutations; meropenem: ftsl mutation). The developed QSP model incorporated baseline resistance mechanisms and those emerging in resistant mutant subpopulations. The model explained and predicted the monotherapy failures involving amplification of these subpopulations, and synergistic killing and resistance suppression by the combination. Simulations using the model predicted bacterial regrowth above the initial inoculum for more than 90% of patients after 0 to approximately 3 days for meropenem monotherapy across all strains and for ceftolozane-tazobactam monotherapy against ST235-05 and ST235-09. For ceftolozane-tazobactam monotherapy against ST235-10, regrowth was predicted for approximately 30% of patients. In contrast, the simulations predicted sustained bacterial killing of at least 2 log10 CFU per mL compared with the initial inoculum by the combination for more than 89% of patients across all strains. INTERPRETATION: To our knowledge, this model is the first to characterise and predict the time-course of responses of clinical isolates to antibiotics only by the resistance mechanisms present and their complex interplay, representing a step towards pathogen-specific, personalised medicine. FUNDING: Australian National Health and Medical Research Council.

Pseudomonas aeruginosa↗

PubMed2004

Using a linked soil model emulator and unsaturated zone leaching model to account for preferential flow when assessing the spatially distributed risk of pesticide leaching to groundwater in England and Wales.

Although macropore flow is recognized as an important process for the transport of pesticides through a wide range of soils, none of the existing spatially distributed methods for assessing the risk of pesticide leaching to groundwater account for this phenomenon. The present paper presents a spatially distributed modelling system for predicting pesticide losses to groundwater through micro- and macropore flow paths. The system combines a meta version of the mechanistic, dual porosity, preferential flow pesticide leaching model MACRO (the MACRO emulator), which describes pesticide transport and attenuation in the soil zone, to an attenuation factor leaching model for the unsaturated zone. The development of the emulator was based on the results of over 4000 MACRO model simulations. Model runs describe pesticide leaching for the range of soil types, climate regimes, pesticide properties and application patterns in England and Wales. Linking the MACRO emulator to existing spatial databases of soil, climate and compound-specific loads allowed the prediction of the concentration of pesticide leaching from the base of the soil profile (at 1 m depth) for a wide range of pesticides. Attenuation and retardation of the pesticide during transit through the unsaturated zone to the watertable was simulated using the substrate attenuation factor model AQUAT. The MACRO emulator simulated pesticide loss in 10 of 12 lysimeter soil-pesticide combinations, for which pesticide leaching was shown to occur and also successfully predicted no loss from 3 soil-pesticide combinations. Although the qualitative aspect of leaching was satisfactorily predicted, actual pesticide concentrations in leachate were relatively poorly predicted. At the national scale, the linked MACRO emulator/AQUAT system was found to predict the relative order of, and realistic regional patterns of, pesticide leaching for atrazine, isoproturon, chlorotoluron and lindane. The methodology provides a first-step assessment of the potential for pesticide leaching to groundwater in England and Wales. Further research is required to improve the modelling concept proposed. The system can be used to refine regional groundwater monitoring system designs and sampling strategies and improve the cost-effectiveness of the measures needed to achieve 'good status' of groundwater quality as required by the Water Framework Directive.

Journal Article↗

PubMed2005

Geometry of simple molecules. 2. Modeling the geometry of AX3E and AX2E2 molecules through the nonbonded interaction (NBI) model.

A new conceptual model of molecular geometry is presented, called the nonbonded interaction (NBI) model. This model is applied to the geometries of the AX3E and AX2E2 (A = N, O, P, S, As, Se, or Te; X = H, F, Cl, Br, I, CH(3), tBu, CF3, SiH3, Sn(tBu)3, or SnPh3) molecule types. For these molecules, the NBI model can be quantified on the basis of a balance between terminal atom-terminal atom (X-X) interactions and lone pair-terminal atom (E-X) interactions. The empirically observed X-A-X angles range from 91.0 degrees (SeH2) to 180 degrees (O(Sn(tBu)3)2), and the NBI model predicts the X-A-X angle with a mean unsigned error of 1.0 degrees using the empirical A-X distance, 1.5 degrees using the LMP2/6-31G** A-X distance, and 1.1 degrees using the MMFF94 A-X distance. This level of precision compares well to the LMP2/6-31G**-predicted X-A-X angles and is significantly better than the MMFF94-predicted X-A-X angles. Terminal groups that are not sufficiently spherical (CF3, SiH3, and SnPh3) can still be addressed qualitatively by the NBI model, as can molecules with a mixture of terminal groups. The NBI model is able to explain, often quantitatively, the geometry of all of the molecules studied, without any additional postulates or extensive parametrization.

Journal Article↗