Photoresponsive 'chemo-free' phytotherapy: formulation development for the treatment of triple-negative breast cancer.

Aim: The present investigation aimed to develop a chemo-free, nanophytosomal system to treat triple-negative breast cancer (TNBC) via a phyto-photo dual treatment strategy. Method: Size, shape, surface analysis, photoprovoked release profile, photothermal stability, (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide assay, apoptotic assay, DNA fragmentation, in vitro cellular uptake evaluation, mitochondrial membrane potential and caspase-3 assay, and photodynamic evaluation. Results: Biological experiments using MDA-MB-231 cells displayed dose-dependent synergistic anti-TNBC activity of PhytoS/Houttuynia cordata extract (HCE)/IR780 as compared with Phyto/HCE, PhytoS/IR780 and even more promising under laser treatment. Apoptotic assay and DNA fragmentation analysis also showed enhanced anti-TNBC effects. Investigation found that HCE acts via suppression of mitochondrial membrane potential and inducing caspase-3 activity in cells. Conclusion: Our findings suggested that photo-empowered phytotherapy can be employed effectively and safely against TNBC.

Effect of supported sitting position during second stage of labor on its outcome in primigravidae: A quasi-experimental study.

Background: The childbirth position has a significant influence on labor, maternal comfort, and neonatal outcome. In sitting position, there is a faster fetal descent with the effect of gravity. The information on this subject is relatively scant. Therefore, this study aimed to examine the effect of a supported sitting position during second stage of labor on its outcome in primigravidae. Materials and Methods: A quasi-experimental study with a post-test only control group design was used. 60 primigravidae were selected using total enumerative sampling. The labor outcome was assessed by self-structured maternal neonatal outcome checklist and socio-demographic proforma. Results: Statistically significant difference was observed on the mean duration of second stage of labor among primigravidae in control and experimental group (t = 5.87, P < 0.001) and also in the APGAR score of newborns (t = -3.98, P < 0.001). A statistical significant association of duration of second stage of labor with height and intensity of maternal work was also observed. Conclusions: A supported sitting position during labor was found to be effective in reducing duration of the second stage of labor. This can be used as a nursing intervention while providing care during labor especially at primary healthcare centers that can help in reducing the duration of second stage of labor.

A cross-sectional study to assess the anxiety and coping mechanism among primary caregivers of children admitted in PICU.

Introduction: PICU admission of a child may cause anxiety and stress among the caregivers. The criteria for admission to a PICU are terrifying and may legitimately cause parents to fear that their child may pass away or suffer a serious disability. They may be overburdened with stress and anxiety of illness and compliment medical information while trying to maintain a balance with other family demands. They must learn coping mechanisms and use resources to stay stable when they face challenges. Evidence on the coping mechanisms used by primary caregivers to control their stress and anxiety is scarce so this study assessed the anxiety and coping mechanism among the primary caregivers of children admitted in PICU. Materials and Methods: A cross-sectional study was conducted among 143 primary caregivers by using convenience sampling technique at PICU, AIIMS, Jodhpur, from April 31, 2021, to January 20, 2022. The participants were enrolled after obtaining informed consent and were interviewed by the researcher. Results: Study findings revealed that primary caregivers had 38% severe anxiety, 54% moderate anxiety, and 8% mild anxiety. They used emotion-focused coping (43.5%) followed by problem focused coping (37.2%) and avoidant coping (19.3%). Also, there was a significant association found between anxiety of primary caregivers and gender of the child (P = 0.012). Conclusion: Anxiety and stress are one of the expected psychological problems faced by caregivers of children admitted in PICU. Healthcare workers must make concerted attempts to support caregivers adaptive coping mechanisms, so they can retain a sense of balance.

A cross sectional study to assess the expressed COVID-19 preventive practices among the health care workers and public visiting tertiary care hospital, AIIMS, Jodhpur.

BACKGROUND: The corona virus disease-2019 (COVID-19) infection is a current public health crisis, and it is challenging to the world health-care system. As there is no treatment, prevention is the crucial importance to break the chain of transmission of infection and prevent fatality among the high-risk populations. The aim of the study was to assess the Expressed COVID-19 preventive practices among health-care workers (HCWs) and the public visiting tertiary care hospital, AIIMS, Jodhpur. METHODOLOGY: A cross-sectional study was conducted among 406 HCWs and 238 public, recruited by convenient sampling technique. A validated and pretested self-structured practice questionnaire used to collect the data regarding COVID-19 preventive practice. The data were collected through online Google Forms and interview techniques and analyzed by software SPSS 26 version. RESULTS: Majority of 87.7% HCWs and 76.5% public always followed practice of hand wash with soap and water and sanitize for 20 s. Majority of 79.6% HCWs and 49.2% public maintain social distance in public place. Gender (χ 2 = 18.806 P ≤ 0.001) and education (χ 2 = 43.270 P ≤ 0.001) among HCWs and in public demographic variable income (χ 2 = 21.102 P = 0.002), religion (χ 2 = 13.302 P = 0.006) and source of information (χ 2 = 17.030 P = 0.026) was significantly associated with level of COVID-19 preventive practice. CONCLUSION: The study showed moderate level of COVID-19 preventive practice among HCWs and public. Based on this result, an effective IEC intervention programs can be designed to educate public and HCWs and follow a safe COVID-19 preventive practice.

Awareness, Attitude, and Acceptability of Healthcare Workers About COVID-19 Vaccination in Western India.

Introduction In the coronavirus disease 2019 (COVID-19) pandemic, healthcare workers (HCWs) are at the frontline around the world and categorized as a priority group for COVID-19 vaccines. Our study aimed to find out the COVID-19 vaccine awareness, attitude, and acceptance in HCWs in western India. Methods A cross-sectional study was carried out between January 14 and January 28, 2021, at a tertiary care hospital located in western India. Data were collected anonymously using Google Forms. Descriptive statistics were used to determine the sociodemographic variables. The knowledge and attitude of HCWs were analyzed using mean and SD. Multivariate analysis was done to find out the association between participants' attitudes with demographic characteristics. Results Of the total health care workers, 498 answered the survey. The mean age of participants was 29.8 years (SD 6.4), and 354 (71.1%) were male. Among the respondents, 445 (89.4%) would accept a COVID-19 vaccine when available. Four-hundred seventy-six (476) HCWs (95.6%) had excellent knowledge regarding COVID-19 and COVID-19-appropriate behavior. The majority of the subjects (399) had a neutral attitude toward COVID-19 vaccination. Health care professionals (doctors and nurses) had higher acceptance for vaccination against COVID-19 than non-professionals. Conclusions The higher rates of COVID-19 vaccine acceptability and the excellent knowledge among HCWs will directly enhance the level and acceptability of vaccine among the general population and will definitely help in reducing the mortality and morbidity related to COVID-19.

Investigation on Quantitative Structure Activity Relationships of a Series of Inducible Nitric Oxide.

A series of 2-dihydro-4-quinazolin with potent highly selective inhibitors of inducible nitric oxide synthase activities was subjected to quantitative structure activity relationships (QSAR) analysis. Statistically significant equations with high correlation coefficient (r 2 = 0.8219) were developed. The k-nearest neighbor model has showed good cross-validated correlation coefficient and external validation values of 0.7866 and 0.7133, respectively. The selected electrostatic field descriptors the presence of blue ball around R1 and R4 in the quinazolinamine moiety showed electronegative groups favorable for nitric oxide synthase activity. The QSAR models may lead to the structural requirements of inducible nitric oxide compounds and help in the design of new compounds.

Identification of 3-Nitro-2,4,6-trihydroxybenzamide Derivatives as Photosynthetic Electron Transport Inhibitors by QSAR and Pharmacophore Studies.

In the present investigation, quantitative structure-activity relationship (QSAR) analysis was performed on a data set consisting of structurally diverse compounds in order to investigate the role of their structural features on their photosynthetic electron transport Inhibitors. The best 2D-QSAR model was selected, having correlation coefficient r (2) = 0.8544 and cross-validated squared correlation coefficient q (2) = 0.7139 with external predictive ability of pred_r (2) = 0.7753. The results obtained in this study indicate that the presence of hydroxy and nitro groups, expressed by the SsOHcount and SddsN (nitro) count, is the most relevant molecular property determining efficiency of photosynthetic inhibitory. Molecular field analysis was used to construct the best k-nearest neighbor (kNN-MFA)-based 3D-QSAR model using SA-PLS method, showing good correlative and predictive capabilities in terms of [Formula: see text] and [Formula: see text]. The pharmacophore model includes three features viz. hydrogen bond donor, hydrogen bond acceptor, and one aromatic feature. The developed model was found to be predictive and can be used to design potent photosynthetic electron transport activities prior to their synthesis for further lead modification.

A Structure-Activity Relationship Study of Imidazole-5-Carboxylic Acid Derivatives as Angiotensin II Receptor Antagonists Combining 2D and 3D QSAR Methods.

Two-dimensional (2D) and three-dimensional (3D) quantitative structure-activity relationship (QSAR) studies were performed for correlating the chemical composition of imidazole-5-carboxylic acid analogs and their angiotensin II [Formula: see text] receptor antagonist activity using partial least squares and k-nearest neighbor, respectively. For comparing the three different feature selection methods of 2D-QSAR, k-nearest neighbor models were used in conjunction with simulated annealing (SA), genetic algorithm and stepwise coupled with partial least square (PLS) showed variation in biological activity. The statistically significant best 2D-QSAR model having good predictive ability with statistical values of [Formula: see text] and [Formula: see text] was developed by SA-partial least square with the descriptors like [Formula: see text]count, 5Chain count, SdsCHE-index, and H-acceptor count, showing that increase in the values of these descriptors is beneficial to the activity. The 3D-QSAR studies were performed using the SA-PLS. A leave-one-out cross-validated correlation coefficient [Formula: see text] and predicate activity [Formula: see text] = 0.7226 were obtained. The information rendered by QSAR models may lead to a better understanding of structural requirements of substituted imidazole-5-carboxylic acid derivatives and also aid in designing novel potent antihypertensive molecules.

Structural Requirements of Some 2-(1-Propylpiperidin-4-yl)-1H-benzimidazole-4-carboxamide Derivatives as Poly (ADP-Ribose) Polymerase (PARP) for the Treatment of Cancer: QSAR Approach.

The present study is aimed to elucidate the structural features of substituted 2-(1-propylpiperidin-4-yl)-1H-benzimidazole-4-carboxamide required for poly (ADP-ribose) polymerase inhibition and to obtain predictive 2D QSAR models to guide the rational synthesis of novel poly (ADP-ribose) polymerase inhibitors. The statistical analysis has shown that excellent results are obtained by using partial least regression based on simulated annealing method. The best model was selected based on the highest correlation coefficient r (2) = 0.8590, and cross-validated squared correlation coefficient q (2) = 0.7875 with external predictive ability of [Formula: see text] was developed by stepwise PLS method with the descriptors like T_N_F_1, SdsCHcount, and Rotatable Bond Count. The generated models provide insight into the influence of various interactive fields on the activity and, thus, can help in designing and forecasting the inhibition activity of novel (ADP-ribose) polymerase molecules.

Discovery of Potent Antihypertensive Ligands Substituted Imidazolyl Biphenyl Sulfonylureas Analogs as Angiotensin II AT1 Receptor Antagonists by Molecular Modelling Studies.

To elucidate the structural properties required for antihypertensive activity, three different molecular modelling techniques, two-dimensional quantitative structure activity relationship (2D-QSAR), group-based quantitative structure activity relationship (G-QSAR), and three-dimensional quantitative structure activity relationship (3D-QSAR) studies, have been carried out on a series of substituted imidazolyl biphenyl sulfonylureas derivatives. Multiple linear regressions methodology, viz. variable simulated annealing and stepwise methods, was applied to derive models which were further validated for statistical significance and predictive ability by internal and external validation. The best 2D-QSAR model was selected, having showed best predictability of activity with cross-validated value [Formula: see text], coefficient of determination [Formula: see text]. The [Formula: see text]_pred value of 0.7651 indicates predictability of test set analogues and reveals a significant and robust model, and best G-QSAR model having [Formula: see text] and [Formula: see text] with pred_[Formula: see text] was developed by SA-MLR. Using k-nearest neighbour approach, various 3D-QSAR models were generated and selected on the basis of [Formula: see text] and predictive [Formula: see text] values. The analysed best 3D-QSAR model revealed a good fit, having [Formula: see text] value of 0.8240 and [Formula: see text] value of 0.7523. The predictive power of the model generated was validated using a test set comprising molecules with pred_[Formula: see text] value of 0.7299. The results of two-dimensional QSAR and group-based QSAR showed that a combination of revealed the key role of Baumann's alignment-independent topological descriptors along with other descriptors such as the number of SsssCH count, SaasCE-index, SsOHcount indices properties could be explored to design potent antihypertensive agents. Finally, it is hoped that the work presented here will play an important role in understanding the relationship of physiochemical parameters with structure and biological activity.

QSAR studies on 3-(4-biphenylmethyl) 4, 5-dihydro-4-oxo-3H-imidazo [4, 5-c] Pyridine derivatives as angiotensin II (AT1) receptor antagonist.

QSAR studies were performed for correlating the chemical composition of 3-(4-biphenylmethyl) 4, 5-dihydro-4-oxo-3H-imidazo [4, 5-c] pyridines bearing aryl acetic acid esters and acetamides as angiotensin II AT(1) receptor antagonist. Four different quantitative structure-property relationship (QSAR) methods namely two-dimensional (2D-QSAR), group-based QSAR, k-nearest neighbor and Pharmacophore Modeling were employed to obtain statistically significant models. The statistically significant best 2D-QSAR model having correlation coefficient r(2) = 0:8940 and cross-validated squared correlation coefficient q(2) = 0:7648 with external predictive ability of pred_r(2) = 0:8177,pred_r(2)se = 0.4119 and best group-based QSAR model having r(2) = 0:7392 and q(2) = 0:6710with pred_r(2) = 0:7503was developed by SA-principal component regression. The most predictive k-nearest neighbor model derived from the superposition of conformations has good cross-validated q(2) = 0:7637 and satisfied predictive ability r(2)_pred = 0.7143. Continuing with compounds of substituted 4, 5-dihydro-4-oxo-3H-imidazo [4, 5-c] pyridine derivatives chemical feature-based pharmacophore models with lowest RMSD value (0.3292 Å) consists of two Hac (Hydrogen bond acceptor), negative ionizable, and two AroC (Aromatic) features are important for the activity. The study suggested that substitution of group at R, R 1, R 2 and Ar, and position on 4, 5-dihydro-4-oxo-3H-imidazo [4, 5-c] pyridine ring with more electronegative nature and low bulkiness are favorable for the antihypertensive activity. These theoretical results may provide a useful reference for understanding the action mechanism and designing potential angiotensin II (AT1) receptor antagonist.

Comparative Pharmacophore Modeling and QSAR Studies for Structural Requirements of some Substituted 2-Aminopyridine Derivatives as Inhibitors of Nitric Oxide Synthases.

The present study is an attempt in this direction seeking for the development and comparison of QSAR models of substituted 2-aminopyridine derivatives as inhibitors of nitric oxide synthases by different feature selection methods. The QSAR study was carried out on V-life Molecular Design Suite software, and the derived best QSAR model was derived by partial component regression method. The statistically significant best model with high correlation coefficient ([Formula: see text]) was selected for further study. The model was further validated by means of crossed squared correlation coefficient ([Formula: see text] and [Formula: see text]) which shows model has good predictive ability. The best 3D-QSAR model showed [Formula: see text] and standard error = 0.1954. The predictive ability of the resultant model was evaluated using a test set molecules and the predicted [Formula: see text] The results reveal that the acceptor, donor, aliphatic, and aromatic pharmacophore properties are favorable contour sites for both the activities. The two-dimensional and k-nearest-neighbor contour plots were required for further understanding of the relationship between structural features of substituted 2-aminopyridine derivatives and their activities which should be applicable to design newer potential inducible nitric oxide synthases.

Prospective QSAR-Based Prediction Models with Pharmacophore Studies of Oxadiazole-Substituted α-Isopropoxy Phenylpropanoic Acids with Dual Activators of PPARα and PPARγ.

A series of oxadiazole-substituted [Formula: see text]-isopropoxy phenylpropanoic acids with dual activators of PPARα and PPARγ derivatives were subjected to two-dimensional and k-Nearest Neighbors molecular field analysis. The statistically significant best 2D-QSAR (PPARα ) model having good predictive ability with statistical values of r(2) = 0:8725; q(2) = 0:7957and pred_r(2) = 0:8136 was developed by GA-PLS with the descriptors like SsClcount, SddsN (nitro) count and SsOHcount that contribute significantly to the biological activity. The best 3D-QSAR studies (PPARα ) were performed using the genetic algorithm selection k-nearest neighbor molecular field analysis approach; a leave-one-out cross-validated correlation coefficient q(2) = 0:7188 and predicate activity pred_r(2) = 0.7508 were obtained. The influences of steric and electrostatic field effects generated by the contribution plots are discussed. The best pharmacophore model includes three features, viz. hydrogen bond donor, hydrogen bond acceptor and aromatic features. The information rendered by 2D-QSAR and 3D-QSAR models may lead to a better understanding of structural requirements of substituted α-isopropoxy phenylpropanoic derivatives and also aid in designing novel potent PPARα and PPARγ for antihyperglycemic molecules.

A Structure-Activity Relationship Study of Naphthoquinone Derivatives as Antitubercular Agents Using Molecular Modeling Techniques.

Tuberculosis (TB) is one of the major causes of death worldwide. Mycobacterium tuberculosis, the leading causative agent of TB, is responsible for the morbidity and mortality of a large population worldwide. In view of above and as a part of our effort to develop new and potent anti-TB agents, a series of substituted naphthoquinone derivatives were subjected to molecular modeling using various feature selection methods. The statistically significant best 2D-QSAR model having correlation coefficient [Formula: see text] and cross-validated squared correlation coefficient [Formula: see text] with external predictive ability of [Formula: see text] was developed by SA-PLS, and group-based QSAR model having [Formula: see text] and [Formula: see text] with [Formula: see text] was developed by SA-PLS. Further analysis using three-dimensional QSAR technique identifies a suitable model obtained by SA-partial least square method leading to antitubercular activity prediction. k-nearest neighbor molecular field analysis was used to construct the best 3D-QSAR model using SA-PLS method, showing good correlative and predictive capabilities in terms of [Formula: see text] and [Formula: see text]. The pharmacophore analysis results obtained from this study show that the distance between the aromatic/hydrophobic and the naphthoquinone moiety sites to the aliphatic and acceptor groups should be connected with almost the same distance for significant antitubercular activity. The information rendered by QSAR models may lead to a better understanding of structural requirements of antitubercular activity and also can help in the design of novel potent antitubercular activity.

Comparative pharmacophore modeling and QSAR studies for structural requirements of some substituted 2-aminopyridines derivatives as inhibitors nitric oxide synthases.

The present studies are an attempt in this direction seeking for the development and comparison of QSAR models of substituted 2-aminopyridines derivatives as inhibitors of nitric oxide synthases by different feature selection methods. Comparing the two different feature selection methods, it is implicit that the model built with the selected variables by simulated annealing (SA) method gives better prediction in case of 2D and 3D QSAR modeling. The QSAR study was carried out on V-life Molecular Design Suite software and the derived best QSAR model was derived by partial component regression (PCR) method. The statistically significant best model with high correlation coefficient (r2 = 0.8408) was selected for further study. The model was further validated by means of crossed squared correlation coefficient (q2 = 0.7270 and pred r2 = 0.7889) which shows model has good predictive ability. 3D-QSAR analysis has been performed on a series of substituted 2-aminopyridines derivatives as which were screened as inhibitors of nitric oxide synthases, using the simulated annealing and step wise k-nearest neighbour Molecular Field Analysis. The best QSAR model showed q2 = 0.8377, r2 = 0.8739 and standard error = 0.1954. It was observed that steric properties predicted by k-nearest neighbour MFA contours can be related to inhibitors of nitric oxide synthases. The predictive ability of the resultant model was evaluated using a test set molecules and the predicted r2 = 0.8159. The distances between the pharmacophore sites were measured in order to confirm their significance to the activities. The results reveal that the acceptor (acc), donor (don), aliphatic and aromatic pharmacophore properties are favorable contours sites for both the activities. The two dimensional and k-nearest neighbour contour plots required for further understanding of the relationship between structural features of substituted 2-aminopyridines derivatives and their activities which should be applicable to design newer potential inducible nitric oxide synthases.

Discovery of potent antihypertensive ligands substituted imidazolyl biphenyl sulfonylureas analogs as angiotensin II AT1 receptor antagonists by molecular modelling studies.

To elucidate the structural properties required for antihypertensive activity, three different molecular modeling techniques; two-dimensional Quantitative structure activity relationship (2D-QSAR), Group-Based Quantitative structure activity relationship (G-QSAR), and three-dimensional Quantitative structure activity relationship (3D-QSAR) studies have been carried out on a series of substituted imidazolyl biphenyl sulfonylureas derivatives. Multiple linear regressions methodology, viz. variable simulated annealing (SA) and stepwise (SW) methods, was applied to derive models which were further validated for statistical significance and predictive ability by internal and external validation. The best 2D-QSAR model was selected, having showed best predictability of activity with cross validated value (q2) = 0.7866, coefficient of determination (r2) =0.8003. The r2_pred value of 0.7651 indicates predictability of test set analogues and reveals a significant and robust model and best G-QSAR model having r2 = 0.7459 and q2 = 0.6712 with pred_r2 = 0.7105 was developed by SA -MLR. Using k-nearest neighbour (kNN) approach, various 3D QSAR models were generated and selected on the basis of q2 and predictive r2 values. The analyzed best 3D-QSAR model revealed a good fit, having r2 value of 0.8240 and q2 value of 0.7523. The predictive power of the model generated was validated using a test set comprising molecules with pred_r2 value of 0.7299. The results of two-dimensional QSAR, Group based QSAR showed that a combination of revealed the key role of Baumann's alignment independent topological descriptors along with other descriptors such as the number of hydrogen bond acceptors, hydrogen bond donors, rotatable bonds indices properties and auto-correlation descriptors of different atomic properties could be explored to design potent antihypertensive agents. Finally, it is hoped that the work presented here will play an important role in understanding the relationship of physiochemical parameters with structure and biological activity.

Prospective QSAR-based prediction models with pharmacophore studies of oxadiazole-substituted α-isopropoxy phenylpropanoic acids on with dual activators of PPARα and PPARγ

A series of oxadiazole-substituted α-isopropoxy phenylpropanoic acids with dual activators of PPARα and PPARγ derivatives were subjected to two dimensional and k-nearest neighbour Molecular field analysis. The statistically significant best 2D-QSAR (PPARα) model having good predictive ability with statistical values of r2 = 0.8725, q2 = 0.7957 and pred_r2 = 0.8136, was developed by GA-PLS with the descriptors like SsClcount, SddsN (nitro) count and SsOHcount contribute significantly to the biological activity. The best 3D-QSAR studies (PPARα) were performed using the genetic algorithm selection k-nearest neighbor molecular field analysis approach; a leave-one-out cross-validated correlation coefficient q2=0.7188 and predicate activity pred_r2 =0.7508 were obtained. The influences of steric and electrostatic field effects generated by the contribution plots are discussed. The best pharmacophore model includes three features viz. hydrogen bond donor, hydrogen bond acceptor, and aromatic features were developed. The information rendered by 2D, 3D QSAR models may lead to a better understanding of structural requirements of substituted α-isopropoxy phenylpropanoic derivatives and also aid in designing novel potent PPARα and PPARγ for antihyperglycemic molecules.

A structure-activity relationship study of imidazole-5-carboxylic acids derivatives as angiotensin II receptor antagonists combining 2D and 3D QSAR methods.

Two Dimensional (2D) and Three Dimensional (3D) Quantitative Structure-Activity Relationship (QSAR) studies were performed for correlating the chemical composition of Imidazole-5-carboxylic Acids analogues and their Angiotensin II AT1 Receptor Antagonists activity using partial least squares and k Nearest Neighbor respectively. For Comparing the three different feature selection methods of 2D-QSAR, k Nearest Neighbor models was used in conjunction with simulated annealing (SA), genetic algorithm (GA) and stepwise (SW) coupled with Partial least square (PLS) showed variation in biological activity. The statistically significant best 2D-QSAR model having good predictive ability with statistical values of r2 = 0.8040, and pred_r2 = 0.7764, was developed by SA-Partial least square with the descriptors like SsCH3Count, 5Chain Count, SdsCHE-index and H-acceptor count showed that increase in the values of these descriptors are beneficial for the activity. The 3D-QSAR studies were performed using the SA-PLS a leave-one-out cross-validated correlation coefficient q2=0.7188 and predicate activity pred_r2 =0.7226 were obtained. The information rendered by QSAR models may lead to a better understanding of structural requirements of substituted Imidazole-5-carboxylic Acids derivatives and also aid in designing novel potent antihypertensive molecules.

Structural requirements of some 2-(1-propylpiperidin-4-yl)-1H-benzimidazole-4-carboxamide derivatives as poly (ADP-ribose) polymerase (PARP) for the treatment of cancer: QSAR approach.

The present study is aimed to elucidate the structural features of substituted 2-(1-propylpiperidin-4-yl)-1H-benzimidazole-4-carboxamide required for poly (ADP-ribose) polymerase inhibition and to obtain predictive 2D QSAR models to guide the rational synthesis of novel poly (ADP-ribose) polymerase inhibitors. The statistical analysis has shown that excellent results are obtained by using partial least regression based on simulated annealing method. The best model was selected based on the highest correlation coefficient r2 = 0.8590 and cross validated squared correlation coefficient q2 = 0.7875 with external predictive ability of pred_r2 = 0.7407 was developed by stepwise PLS method with the descriptors like T_N_F_1, SdsCHcount, and Rotatable Bond Count. The generated models provide insight into the influence of various interactive fields on the activity and, thus, can help in designing and forecasting the inhibition activity of novel (ADP-ribose) polymerase molecules.

Identification of 3-nitro-2, 4, 6-trihydroxybenzamide derivatives as photosynthetic electron transport inhibitors by QSAR and pharmacophore studies.

In the present investigation, QSAR analysis was performed on a data set consist of structurally diverse compounds in order to investigate the role of its structural features on their Photosynthetic Electron Transport Inhibitors. The herbicidal activity co-related with certain topological and hydrophobicity based descriptors, 3D descriptors dependent steric, electrostatic and hydrophobic. The best 2D QSAR model was selected, having correlation coefficient r2 = 0.8544 and cross validated squared correlation coefficient q2 = 0.7139 with external predictive ability of pred_r2 = 0.7753 was developed. The results obtained in this study indicate that hydroxy and nitro groups, as expressed by the SsOHcount, SddsN (nitro) count, is the most relevant molecular property determining efficiency of photosynthetic inhibitory. Molecular field analysis was used to construct the best k-nearest neighbor (kNN-MFA)-based 3DQSAR model using SA-PLS method, showing good correlative and predictive capabilities in terms of q2 = 0.7694 and pred_r2 = 0.7381. The influences of steric, electrostatic and hydrophobic field effects generated by the contribution plots are discussed. The pharmacophore model includes three features viz. hydrogen bond donor, hydrogen bond acceptor, and one aromatic feature was developed. The developed model was found to be predictive and can be used to design potent Photosynthetic Electron Transport activities prior to their synthesis for further lead modification. The results obtained suggest that the 3-nitro-2, 4, 6-trihydroxybenzamide analogues represent promising candidates for the development of new active principles targeting photosynthesis to be used as herbicides.