Dimensional Relationship Research Articles

Weightbearing Computed Tomography for Assessment of Foot and Ankle Deformities: The Iowa Experience

Category:Ankle; Ankle Arthritis; OtherIntroduction/Purpose:Weightbearing computed tomography (WBCT) is a reliable and precise modality for the measurement and analysis of bone position in the foot and ankle, as well as associated deformities. WBCT to assess three dimensional relationships among bones allowed the development of new measurements, as the Foot and Ankle Offset (FAO), which has high inter-rater and intra-rater reliability. This study reports our institution's experience utilizing WBCT for the care of foot and ankle patients by describing its utility across different orthopedic diseases in improving diagnostic assessment, aiding surgical planning, and expanding the use for objective clinical follow-up.Methods:The medical records of consecutive patients with various foot and ankle disorders that underwent WBCT examination as part of the standard of care at a single institution between November 2014 and August 2020 were retrospectively reviewed. Patient factors, including body mass index (BMI), sex, and patient comorbidities were collected. 3D coordinates for calculation of FAO were harvested using the Multiplanar Reconstruction (MPR) views were calculated from the obtained exams. Descriptive statistics were performed with Shapiro-Wilk test and the Anderson-Darling tests.Results:1175 feet and ankles (820 patients) had a WBCT performed over the studied 68 months. 53% of the subjects were male and 47% female. 588 of the acquisitions were from the right side (50.04%) and 587 from the left side (49.96%). Diabetes was present in 15.47% of, Rheumatic diagnoses in 4.52% and smoking habits in 44.10% of patients. Mean BMI of the sample was found to be 32.47 (32.03-32.90, 95% CI). The mean Foot and Ankle Offset (FAO) encountered in the study's population was 2.43 (2.05- 2.82, 95% CI; min -30.8, max 37.65; median 2.39).Conclusion:This study contains the largest cohort of WBCTs with accompanied FAO measurements to date, which can aid with establishing a new baseline FAO measurement for multiple pathological conditions. Acquiring WBCTs resulted in more specific diagnoses for patients with foot and ankle complaints. The ability to utilize WBCT for presurgical planning, its capability to provide a 3D reconstruction of patient anatomy, and use for assessment of advanced relational foot and ankle measurements, like FAO, demonstrate how WBCT may serve as a remarkable utility in clinical practice and has become a standard of care in our practice at the University of Iowa.

Discovery of Novel Tetrahydropyrido-Pyrazole based Cathepsin S Inhibitors: Implications of Two Dimensional Quantitative Structure Activity Relationship Analysis

The anti-arthritic activity of cathepsin S enzyme has been acknowledged and regarded as an emerging target for the development of novel therapeutic agents for the treatment of various autoimmune disorders and other inflammatory diseases. Two dimensional-quantitative structure-activity relationships have been performed on a series of tetrahydropyrido-pyrazole nucleus using TSAR 3.3. Attempts have been made to derive and comprehend a correlation between biological activity (dependent variable) and descriptors (independent variables). The study was performed using 268 compounds (data set) by division into training and test set by the random selection method. 179 compounds generated a final quantitative structure-activity relationship model with the leave-out one row method of cross-validation to evaluate the predictive ability of the model. The most significant model with n=179, regression coefficient (0.851), correlation coefficient (0.725), cross-validated correlation coefficient (0.709), standard error (0.349), Fischer statistic value (114.706) was developed using multiple linear regression analysis. For partial least squares, a statistical significance value of 0.988 and a fraction of variance explained 0.723 were observed. A comparable partial least squares model with correlation coefficient (0.723) and neural model with correlation coefficient (0.731) indicated good internal predictability of the model. External test set validation provided correlation coefficient values of 0.708 and 0.706 for multiple linear regressions and partial least squares analysis respectively. Quantitative structure-activity relationship model indicated the importance of hydrophobic (log P (substituent 1)), topological (kier chi 5 (path) index (whole molecule)), electronic (bond dipole moment (substituent 5)) and (dipole moment Z component (substituent 1)) descriptors for the activity of Cathepsin S inhibitors. This study will be effective in designing novel and more potent cathepsin S inhibitors.

Порівняльний аналіз результатів визначення припусків за нормативами та за розрахунково-аналітичним методом з використанням розмірного аналізу технологічних процесів

A comparative analysis of the results of determining the general allowance according to the standards and the allowance determined using the calculation-analytical method on the example of processing by boring the main hole in the workpiece of the body part was performed. The studies were carried out on the example of the technological process of mechanical processing of the workpiece of the "Hull" type part. The determination of technological dimensions and dimensions of the initial workpiece, as well as intermediate allowances and general allowance for all transitions of processing (boring) of one of the main holes is considered. It was believed that the initial workpiece is casting in shell molds. To determine one of the components of the minimum pass, namely the spatial deviations of the surface of the hole relative to technological bases, the dimensional analysis apparatus of the technological process was used, which takes into account the specific conditions of this process, in particular, the peculiarities of the scheme of basing on the first operation. A comparison of the amount of the total minimum allowance determined using the calculation-analytical method with the amount of the total allowance determined according to the normative tables showed that the calculated allowance exceeds the standard by almost 30%, and the most significant influence on the amount of the calculated total allowance is the value of the spatial deviation of the axis of the hole in the initial workpiece relative to the technological bases. Therefore, if the first operation of the technological process solves the problem of ensuring the dimensional relationship between the processed and untreated surfaces, then the allowance determined according to the standards during the processing of a batch of blanks on a set machine may not be enough to ensure the required surface quality details Therefore, in this case, it is necessary to use the calculation and analytical method to determine both the intermediate allowances and the total allowance.

DIMENSIONAL MODELING TAKING INTO ACCOUNT THE MUTUAL INFLUENCE IN THE PROCESSING OF FLAT SURFACES AND MAIN HOLES IN BODY WORKPIECES WHEN BASING ON THREE PLANES

In this paper, we consider a dimensional modeling algorithm that allows us to describe the technology of mechanical processing of a body billet with the subsequent calculation of technological dimensional relationships, which takes into account the unevenness of the removed allowance associated with the spatial deviation of the axis of the main hole being processed.

Exploring the dimensional relationships of story world absorption

Abstract Absorption has proven to be an important mediator of reading enjoyment and persuasive text effects (Green & Brock, 2000; Kuijpers et al., 2014). Typically, absorbing experiences with narrative media are captured using self-report measuring instruments. One such instrument is the Story World Absorption Scale, which is comprised of four dimensions: Attention, Emotional Engagement, Mental Imagery, and Transportation (Kuijpers et al., 2014). As of yet, we do not know how these dimensions relate to one another. Data from four different studies (one survey and three experiments) using the Story World Absorption Scale were investigated with the use of structural equation modeling to attempt to answer this question. The results show that attention fulfills a crucial role in the absorption experience confirming the work of Kuiken and Douglas (2017, 2018) on absorption-like states. The findings inspire a discussion on how we (should) use multi-dimensional instruments in the field of empirical literary studies.

Growth variability, dimensional scaling, and the interpretation of osteohistological growth data.

Osteohistological data are commonly used to study the life history of extant and extinct tetrapods. While recent advances have permitted detailed reconstructions of growth patterns, physiology and other features using these data, they are most commonly used in assessments of ontogenetic stage and relative growth in extinct animals. These methods have seen widespread adoption in recent years, rapidly becoming a common component of the taxonomic description of new fossil taxa, but are often applied without close consideration of the sources of variation present or the dimensional scaling relationships that exist among different osteohistological measurements. Here, we use a combination of theoretical models and empirical data from a range of extant and extinct tetrapods to review sources of variability in common osteohistological measurements, their dimensional scaling relationships and the resulting interpretations that can be made from those data. In particular, we provide recommendations on the usage and interpretation of growth mark spacing/zonal thickness data, when these are likely to be unreliable, and under what conditions they can provide useful inferences for studies of growth and life history.

New Trends in Precision Medicine: A Pilot Study of Pure Light Scattering Analysis as a Useful Tool for Non-Small Cell Lung Cancer (NSCLC) Diagnosis.

Simple SummaryA reliable method for a fast diagnosis of non-small cell lung cancer (NSCLC) would greatly help in improving therapeutic success in personalized medicine approaches. Thus, in the present study, a new idea was proposed: a morphological single-cell analysis approach combined with a microfluidic device for liquid biopsy. The investigation of the NSCLC sample at different culturing times created the possibility of understanding the evolution of different cell types and their morphological changes, making the Circulating Tumour Cells (CTC) predominance against all other cell classes visible.Background: To date, in personalized medicine approaches, single-cell analyses such as circulating tumour cells (CTC) are able to reveal small structural cell modifications, and therefore can retrieve several biophysical cell properties, such as the cell dimension, the dimensional relationship between the nucleus and the cytoplasm and the optical density of cellular sub-compartments. On this basis, we present in this study a new morphological measurement approach for the detection of vital CTC from pleural washing in individual non-small cell lung cancer (NSCLC) patients. Materials and methods: After a diagnosis of pulmonary malignancy, pleural washing was collected from nine NSCLC patients. The collected samples were processed with a density gradient separation process. Light scattering analysis was performed on a single cell. The results of this analysis were used to obtain the cell’s biophysical pattern and, later on, as basis for Machine Learning (ML) on unknown samples. Results: Morphological single-cell analysis followed by ML show a predictive picture for an NSCLC patient, screening that it is possible to distinguish CTC from other cells. Moreover, we find that the proposed measurement approach was fast, reliable, label-free, identifying and count CTC in a biological fluid. Conclusions: Our findings demonstrate that CTC Biophysical Profile by Pure Light Scattering in NSCLC could be used as a promising diagnostic candidate in NSCLC patients.

Relationship of ventral striatum activation during effort discounting to clinical amotivation severity in schizophrenia

Motivational deficits play a central role in disability due to negative symptoms of schizophrenia (SZ), but limited pathophysiological understanding impedes critically needed therapeutic development. We applied an fMRI Effort Discounting Task (EDT) that quantifies motivation using a neuroeconomic decision-making approach, capturing the degree to which effort requirements produce reductions in the subjective value (SV) of monetary reward. An analyzed sample of 21 individuals with SZ and 23 group-matched controls performed the EDT during fMRI. We hypothesized that ventral striatum (VS) as well as extended brain motivation circuitry would encode SV, integrating reward and effort costs. We also hypothesized that VS hypoactivation during EDT decisions would demonstrate a dimensional relationship with clinical amotivation severity, reflecting greater suppression by effort costs. As hypothesized, VS as well as a broader cortico-limbic network were activated during the EDT and this activation correlated positively with SV. In SZ, activation to task decisions was reduced selectively in VS. Greater VS reductions correlated with more severe clinical amotivation in SZ and across all participants. However, these diagnosis and amotivation effects could not be explained by the response to parametric variation in reward, effort, or model-based SV. Our findings demonstrate that VS hypofunction in schizophrenia is manifested during effort-based decisions and reflects dimensional motivation impairment. Dysfunction of VS impacting effort-based decision-making can provide a target for biomarker development to guide novel efforts to assess and treat disabling amotivation.

AI Predicted Competency Model to Maximize Job Performance

Human resources are concerned with recruiting, training and keeping talent. The correct selection of personnel is key to the success of a business because regardless of the outstanding business strategy, those who put it into practice are most important. A carefully developed strategy is as bad as having no strategy if the wrong person is placed in the wrong position. There are no studies to predict the competency of job applicants based on dimensional values such as level of knowledge, self-motivation, self-concern and role perception. This study proposes a prediction model that uses AI (Artificial Intelligence), this includes a quantitative mathematical model that identifies the level of personnel competency to optimize job performance. The model verifies the discrete and continuous relationship between competency dimensions and their synergetic effects. Four AI algorithms are used to train a data set that contains 362 data elements, consisting of two optimized combinations of dimensional values in step 1, and 360 data elements that are derived from the dimensional relationship that produces the synergetic effects. The proposed model predicts the competence of job applicants and compares this competence with the value gives optimized job performance to optimize the selection of human resources.

A machine-learning approach to predicting the energy conversion performance of centrifugal pump impeller influenced by blade profile

Centrifugal pump is a kind of energy conversion machine for fluid delivering. It transfers the mechanical energy of impeller to the potential and kinetic energy of fluid. As a key factor in influencing the energy conversion performance of centrifugal pump, blade profile design is crucial. Traditional design concepts have ideal assumptions. To have a better design guidance, machine-learning based on neural network is used in this study. A typical centrifugal pump with simplified blade profile is numerically studied with experimental validation for a better discussion. Statistical results show that, for the high dimensional nonlinear relationship between blade angle and performance of centrifugal pump, neural network can adapt to this complex correlation better. The blade installation angle at leading-edge ( βLE′) and trailing-edge ( βTE′) and the wrap angle (Δ θ′) has significant correlation with the performance including pump head H, pump efficiency η, impeller head Himp, impeller efficiency ηimp and volute loss Δ Hvol. The influence level of blade angle follows the high-to-low order of Δ θ′, βLE′ and βTE′. Determination of blade profile can be done for improving the energy conversion efficiency. Optimal blade profiles have higher βLE′ and Δ θ′ with better flow-control ability. Compared with the blade parameters of the initial pump, the blade profile with the best centrifugal pump efficiency is the best βLE′ increased by 1.926°, Δ θ′ increased by 9.858°, Optimization of impeller efficiency βLE′ increased by 1.855°, Δ θ′ increased by 9.421°. Computational fluid dynamics indicate the elimination of vortex in impeller after optimal selection. Then, βTE′ and Δ θ′ are found influential in aggravating the circumferential flow component in this special circular-volute with generating higher loss. βTE′ has a positive correlation with impeller head which suits traditional theory. In general, the machine-learning using neural network is effective in determining blade profiles for enhancing the performance of centrifugal pump.

3D QSAR analysis on quinoxaline derivatives as anti-malarial using K-nearest neighbour molecular field analysis

In the present article, k nearest neighbour molecular field analysis (kNN-MFA) method was used to develop a three dimensional quantitative structure activity relationship (3D-QSAR) model. In this study 37 derivatives of quinoxaline having antimalarial activity were used. Sphere exclusion (SE) algorithm was used to create the biological activity data set in to into training and test set. For model generation kNN-MFA method has coupled with stepwise, simulated annealing and genetic algorithm this method provides various models, in which the most significant model developed by stepwise backward-forward method with predictive internal q2=0.7589 and external predictivity (pred_r2 = 0.4752). In the presented model electrostatic descriptors play crucial role for activity. Electrostatic descriptor (E_137) indicates regions in which electron withdrawing groups are favourable and descriptor (E_939) represents electron rich or electron donating groups are advantageous in particular region. The counter map/ plot of this model further helps to understand the relationship of structural feature of derivative of quinoxaline and its biological activity this would be applied for designing of new potent antimalarial containing quinoxaline as lead.

A critical analysis of sustainable micro-manufacturing from the perspective of the triple bottom line: A social network analysis

Nowadays, substantial improvements in sustainable micro-manufacturing are explicitly addressed based on the triple bottom line (TBL) concept. However, strong criticisms are leveled for the applications of TBL as immense complexities of inner relationships of items and dimensional relationships within TBL, which they cause an inefficacy of accessing critical information in introducing the TBL concept to sustainable micro-manufacturing. In this study, social network analysis (SNA) is used for developing a TBL network of sustainable micro-manufacturing to find out precise meanings of individual items of various dimensions of TBL and the relationships between them. The main metrics of the dominant items of TBL such as in-degree, out-degree, betweenness centrality and closeness centrality are detailly discussed with 16 nodes for three dimensions in the TBL networks. The related findings are further analyzed to reveal the current situation, technical gaps and chances for the sustainable development of the micro-manufacturing sector. This study aims to reveal the relationship between the items of TBL of micro-manufacturing, and delivers the significant roles of the items of TBL according to the findings of metrics and visual analyses for sustainable micro-manufacturing, supporting micro-manufacturing sectors to implement effective sustainable strategies for production activities.

Ensuring the collection of mechanical engineering products, taking into account the tolerances for computer-aided design in “GePARD.3D”

The article discusses a geometric approach to ensuring the assembly of mechanical engineering products, taking into account the spatial permissible deviations of components in computer-aided design using configuration manifolds and biquaternions. The main advantage of this approach is the modeling of assemblies taking into account the tolerances with the possibility of direct access to the tree for constructing the 3D model of the product, which greatly facilitates the user’s work. The developed configuration model of the assembly and the technology for analyzing spatial dimensional relationships in the product, taking into account the tolerances and using biquaternions, allow obtaining analysis results with predictable accuracy already at the stage of geometric modeling.

Distinct Aeolian-fluvial Interbedded Landscapes in Three Watersheds of the Northern China

Due to the complex dynamic of aeolian and fluvial interacted processes behind the landform development, most of previous works started from classifying the types of landscape characterized by various aeolian and fluvial features. Such classifications are usually generalized based on large geomorphic data set abstracted from satellite images without field verification and dynamic field data. In this study, we identified river banks in deserts as a unique geographical unit dominated by aeolian-fluvial processes. Three distinct locations have been identified as representative study cases, which are in the Keriya River Basin in the west, the Mu Bulag River Basin in the middle and the Xar Moron River Basin in the east of the northern China. The aeolian-fluvial interaction types were quantified based on site observation and measurement, topographic mapping and remote-sensing image analysis. Dimensional morphological relationship between river channel and adjacent sand dunes areas were explored. We concluded that different channels are often associated with different distributions of riparian dunes. The quantitative data enabled us to distinguish statistically four different types of landscape in aeolian-fluvial dominant environment, namely riverside dunes-straight channel, symmetrical interleaving dunes-meandering channel, river-island dunes- braiding channel, and grid-like dunes-anastomosing channel, aiming to provide compensational information to current aeolian-fluvial interaction studies. The angle of interaction between aeolian and fluvial systems, the windward and leeward sites of the bank, vegetation coverage and underlying landform determines the distribution, morphology, scale and direction of extension of the riparian dunes. The results of the work study can provide a reference for study of aeolian-fluvial interactions at different spatial scales in arid region.

Whole-Brain Functional Dynamics Track Depressive Symptom Severity

Depressive symptoms are reported by 20% of the population and are related to altered functional integrity of large-scale brain networks. The link between moment-to-moment brain function and depressive symptomatology, and the implications of these relationships for clinical and community populations alike, remain understudied. The present study examined relationships between functional brain dynamics and subclinical-to-mild depressive symptomatology in a large community sample of adults with and without psychiatric diagnoses. This study used data made available through the Enhanced Nathan Kline Institute-Rockland Sample; 445 participants between 18 and 65years of age completed a 10-min resting-state functional MRI scan. Coactivation pattern analysis was used to examine the dimensional relationship between depressive symptoms and whole-brain states. Elevated levels of depressive symptoms were associated with increased frequency and dwell time of the default mode network, a brain network associated with self-referential thought, evaluative judgment, and social cognition. Furthermore, increased depressive symptom severity was associated with less frequent occurrences of a hybrid brain network implicated in cognitive control and goal-directed behavior, which may impair the inhibition of negative thinking patterns in depressed individuals. These findings demonstrate how temporally dynamic techniques offer novel insights into time-varying neural processes underlying subclinical and clinically meaningful depressive symptomatology.

Altered patterns of brain dynamics linked with body mass index in youth with autism.

Children with autism spectrum disorder (ASD) have higher rates of overweight and obesity (OWOB) compared with typically developing (TD) children. Brain functional connectivity differences have been shown in both ASD and OWOB. However, only one study to date has examined ASD and OWOB concurrently, so little is known regarding the neural mechanisms associated with the higher prevalence of OWOB and its behavioral impacts in ASD. We investigated co-activation patterns (CAPs) of brain regions identified by independent component analysis in 129 children and adolescents between 6 and 18 years of age (n= 68 ASD). We examined the interaction between body mass index (BMI) and diagnosis in predicting dynamic brain metrics (dwell time, DT; frequency of occurrence, and transitions between states) as well as dimensional brain-behavior relationships. The relationship between BMI and brain dynamics was moderated by diagnosis (ASD, TD), particularly among the frequency of CAP 4, characterized by co-activation of lateral frontoparietal, temporal, and frontal networks. This pattern was negatively associated with parent-reported inhibition skills. Children with ASD had shorter CAP 1, characterized by co-activation of the subcortical, temporal, sensorimotor, and frontal networks, and CAP 4 DTs compared with TD children. CAP 1 DT was negatively associated with cognitive flexibility, inhibition, social functioning, and BMI. Cognitive flexibility moderated the relationship between BMI and brain dynamics in the visual network. Our findings provide novel evidence of neural mechanisms associated with OWOB in children with ASD. Further, poorer cognitive flexibility may result in increased vulnerability for children with ASD and co-occurring OWOB. LAY SUMMARY: Obesity is a societal epidemic and is common in autism, however, little is known about the neural mechanisms associated with the higher rates of obesity in autism. Here, we find unique patterns of brain dynamics associated with obesity in autism that were not observed in typically developing children. Further, the relationship between body mass index and brain dynamics depended on cognitive flexibility. These findings suggest that individuals with autism may be more vulnerable to the effects of obesity on brain function. Autism Res 2021, 14: 873-886. © 2021 International Society for Autism Research, Wiley Periodicals LLC.

Transdiagnostic Dimensions of Psychiatric Comorbidity in Individuals at Clinical High Risk for Psychosis: A Preliminary Study Informed by HiTOP.

Background: Although psychiatric comorbidity is the norm among individuals at clinical high risk for psychotic disorders (CHR), research has yet to examine transdiagnostic dimensional models of comorbidity in this critical population.Methods: This study analyzed quantitative measures of eleven psychiatric syndromes in a group at CHR (n = 71) and a matched healthy comparison group (n = 73) to determine these syndromes' dimensional structure and relationships to cognition, functioning, and risk of conversion to psychotic disorders.Results: Relative to the comparison group, the CHR group was elevated on all eleven psychiatric syndromes. Exploratory factor analysis found three psychopathology dimensions: internalizing, negative symptoms, and positive symptoms. Depression cross-loaded onto the internalizing and negative symptom dimensions. Hypomania loaded positively on positive symptoms but negatively on negative symptoms. The negative symptom factor was associated with poorer cognition and functioning and a higher risk of conversion to psychosis.Conclusions: These dimensions align with internalizing, detachment, and thought disorder, three of the five spectra in higher-order models such as the Hierarchical Taxonomy of Psychopathology (HiTOP). In the CHR state, detachment appears to be particularly insidious and predictive of psychosis. Further research is required to distinguish depression and hypomania from attenuated psychotic symptoms in this population.

Design and Synthesis of New CDK2 Inhibitors Containing Thiazolone and Thiazolthione Scafold with Apoptotic Activity.

Cyclin dependent kinase 2 (CDK2) inhibition is a well-established strategy for treating cancer. Different series of novel thiazolone (1, 7-9) together with fused thiazolthione (2-6, and 10) derivatives were designed, then synthesized and evaluated for their biological inhibitory activity against CDK2. Additionally, the cytotoxicity of the new compounds was explored against breast and colon cancer cell lines. The novel thiazolone and the fused thiazolthione derivatives exhibited potent CDK2/cyclin A2 inhibitory effect of an IC50 values ranging 105.39-742.78 nM. Amongst them compounds 4 and 6 revealed highest IC50 of 105.39 and 139.27 nM, respectively. Most compounds showed significant inhibition on both breast cancer and colon cancer cell lines with IC50 range 0.54-5.26 and 0.83-278 µM, respectively. Further investigations involved flow cytometry analysis on MCF-7 cancer cell line for compounds 5 and 7 which resulted in arrest cell-cycle at two phases Pre G1/G2-M and re-enforced apoptosis via activation of caspase-7. Molecular modeling simulation of the designed compounds revealed that they were well fitted into CDK2 active site and their complexes were stabilized through the essential hydrogen bonding. Three dimensional quantitative structure activity relationship (3D QSAR) pharmacophore, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies were also carried out showing proper pharmacokinetic and drug-likeness which aided in the prediction of the structure requirements responsible for the observed antitumor activity.

Caspase-3 Inhibition Prediction of Pyrrolo[3,4-c] Quinoline-1,3-Diones Derivatives Using Computational Tools

In the present work, two dimensional quantitative structure activity relationship, molecular docking and absorption, distribution, metabolism, excretion and toxicity analyses were performed to pyrrolo[3,4-c] quinoline-1,3-diones derivatives, previously reported as caspase-3 inhibitors. A total of one hundred fifteen compounds were used to build linear multiple linear regression (multiple linear regression) and non-linear (artificial neural networks) quantitative structure activity relationship models, using genetic algorithm as a feature selection method. Both models were thoroughly validated following Organization for economic cooperation and development principles by internal and external validation as well as the domain of application (antiphase domain). Both Genetic algorithm-multiple linear regression (Rtrain=0.88, Rtest=0.94, mapetest=5.3 and rmsetest=0.41) and Genetic algorithm-artificial neural network (Rtrain=0.9, Rtest=0.93, mapetest=4.5 and rmsetest=0.4) models are statistically robust with high external predictive ability. Molecular docking simulations were performed on selected inhibitors revealed that binding energy values are in accordance with inhibitory activity values against caspase-3, which is modulated by hydrogen bondings, Pi stacking and hydrophobic interactions. The docking studies suggest that the inhibitors bind with an allosteric site of the enzyme formed by ARG207B, SER251B, PHE250 and PHE256 of the B chain. Besides, in silico, absorption, distribution, metabolism, excretion and toxicity profiles of selected inhibitors were checked to evaluate the key pharmacokinetic, physiochemical and druglikeness features.

Three Dimensional Quantitative Structure Activity Relationship and Molecular Docking Studies of Flavonoids as Reverse Transcriptase Inhibitors

A set of 29 flavonoid molecules are used to generate comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. The best CoMFA model showed a cross-validated correlation coefficient (q2) = 0.762, noncross- validated correlation coefficient (r2) = 0.939, standard error of estimate (S) = 0.038 and F = 396. And that for CoMSIA model were q2 = 0.758, r2 = 0.957, S = 0.063 and F = 236. The models show a high predictive ability, validated by 11 favonoid molecules. The docking studies shows the hydrogen bonding interaction is mostly responsible for binding of the flavonoids molecules in the binding pocket of HIV 1-RT protein (3HVT.pdb).