Role of a highly conserved proline-126 in ThDP binding of Mycobacterium tuberculosis acetohydroxyacid synthase

Baig, I.A.,Gedi, V.,Lee, S.C.,Koh, S.H.,Yoon, M.Y. IPC Science and Technology Press ; Elsevier Scienc 2013 Enzyme and microbial technology Vol.53 No.4

Acetohydroxyacid synthase (AHAS) of Mycobacterium tuberculosis is a promising target for the development of anti-tuberculosis agents. With the absence of an available bacterial AHAS crystal structure, that of M. tuberculosis, site-directed mutagenesis has been a useful tool for determining its structural and functional features. In this study, a highly conserved proline residue (P126 of M. tuberculosis AHAS) was selected, and the possible role was evaluated by site-directed mutagenesis. P126 was replaced by valine, threonine, alanine, and glutamate to yield P126V, P126T, P126A, and P126E, respectively. All variants were expressed in their soluble forms in Escherichia coli and purified to near homogeneity. The molecular mass (SDS-PAGE) of the purified variants was ~68kDa, which is similar to that of wild-type AHAS. The P126V, P126T, and P126A variants exhibited significantly lower activity than wild-type AHAS, whereas P126E was inactive under the tested assay conditions. Furthermore, the P126V and P126T variants showed a significantly decreased preference toward pyruvate and ThDP as substrate and cofactor respectively, whereas the P126A showed similar kinetics to that of wild-type AHAS. Like in AHAS from yeast Saccharomyces cerevisiae (PDB ID: 1N0H), residue P126 is located in the ThDP binding pocket of M. tuberculosis AHAS homology model. Collectively, these results suggest that the conserved P126 plays a significant role in the ThDP binding of M. tuberculosis AHAS.

Interaction of Glucagon G-Protein Coupled Receptor with Known Natural Antidiabetic Compounds: Multiscoring <i>In Silico</i> Approach

Baig, M. H.,Ahmad, K.,Hasan, Q.,Khan, M. K. A.,Rao, N. S.,Kamal, M. A.,Choi, I. Hindawi Publishing Corporation 2015 Evidence-based Complementary and Alternative Medic Vol.2015 No.-

<P>Glucagon receptor (GCGR) is a secretin-like (class B) family of G-protein coupled receptors (GPCRs) in humans that plays an important role in elevating the glucose concentration in blood and has thus become one of the promising therapeutic targets for treatment of type 2 diabetes mellitus. GCGR based inhibitors for the treatment of type 2 diabetes are either glucagon neutralizers or small molecular antagonists. Management of diabetes without any side effects is still a challenge to the medical system, and the search for a new and effective natural GCGR antagonist is an important area for the treatment of type 2 diabetes. In the present study, a number of natural compounds containing antidiabetic properties were selected from the literature and their binding potential against GCGR was determined using molecular docking and other<I> in silico</I> approaches. Among all selected natural compounds, curcumin was found to be the most effective compound against GCGR followed by amorfrutin 1 and 4-hydroxyderricin. These compounds were rescored to confirm the accuracy of binding using another scoring function (<I>x</I>-score). The final conclusions were drawn based on the results obtained from the GOLD and <I>x</I>-score. Further experiments were conducted to identify the atomic level interactions of selected compounds with GCGR.</P>

GeneXpert MTB/RIF Testing in the Management of Patients with Active Tuberculosis; A Real Life Experience from Saudi Arabia

Ali S. Omrani,Mohammed F. Al-Otaibi,Souad M. Al-Ateah,Fahad M. Al-Onazi,Kamran Baig,Noura A. El-Khizzi,Ali M. Albarrak 대한감염학회 2014 Infection and Chemotherapy Vol.46 No.1

Background: GeneXpert MTB/RIF is a real-time PCR assay with established diagnostic performance in pulmonary and extra-pulmonaryforms of tuberculosis. The aim of this study was to assess the contribution of GeneXpert MTB/RIF assay to the management ofpatients with any form of active tuberculosis in a single large tertiary center in Saudi Arabia, with a special focus on the impact ontime to start of antituberculous therapy compared with Ziehl-Neelsen (ZN) smears and mycobacterial cultures. Materials and Methods: Clinical, radiological and laboratory records for all patients who were commenced on antituberculous therapybetween March 2011 and February 2013 were retrospectively reviewed. Results: A total of 140 patients were included, 38.6% of which had pulmonary tuberculosis. GeneXpert MTB/RIF was requested for only39.2% of patients and was the only reason for starting antituberculous therapy for only 12.1%. The median time to a positive GeneXpertMTB/RIF result was 0 days (IQR 3) compared with 0 day (IQR 1) for smear microscopy (P > 0.999) and 22 days (IQR 21) for mycobacterialcultures (P < 0.001). No patients discontinued antituberculous therapy because of a negative GeneXpert MTB/RIF result. Conclusions: In a setting wherein physicians are highly experienced in the diagnosis and treatment of tuberculosis, GeneXpertMTB/RIF was remarkably under-utilized and had only a limited impact on decisions related to starting or stopping antituberculoustherapy. Cost-effectiveness and clinical utility of routine testing of all smear-negative clinical samples submitted for tuberculosisinvestigations by GeneXpert MTB/RIF warrant further study.

CODING THEOREMS ON A GENERALIZED INFORMATION MEASURES

M.A.K Baig,Rayees Ahmad Dar 한국산업응용수학회 2007 Journal of the Korean Society for Industrial and A Vol.11 No.2

In this paper a generalized parametric mean length L(P<SUP>v</SUP>, R) has been defined and bounds for L(P<SUP>v</SUP>, R) are obtained in terms of generalized R-norm information measure.

Coding Theorems on A Generalized Information Measures

( M. A. K. Baig ),( Rayees Ahmad Dar ) 한국산업응용수학회(구 한국산업정보응용수학회) 2007 한국산업정보응용수학회 Vol.11 No.2

In this paper a generalized parametric mean length L(Pv, R) has been defined an bounds for L(Pv, R) are obtained in terms of generalized R-norm information measure.

Some Generalized Bounds on Relative Entropies

( M. A. K Baig ),( Rayees Ahmad ) 한국산업응용수학회(구 한국산업정보응용수학회) 2006 한국산업정보응용수학회 Vol.10 No.2

SOME GENERALIZED BOUNDS ON RELATIVE ENTROPIES

M.A.K. Baig,Rayees Ahmad Dar 한국산업응용수학회 2006 Journal of the Korean Society for Industrial and A Vol.10 No.2-1

Divergence measures and information inequalities are well known in the literature of information theory. In this paper we proposed some generalized bounds on Csiszar's f-divergence in terms of relative J-divergence of type s. The bounds in terms well known divergence measures such as relative J-divergence, Chi-square divergence and triangular discrimination becomes the particular cases of our proposed bounds.

Deep Spectral Time-Variant Feature Analytic Model for Cardiac Disease Prediction Using Soft Max Recurrent Neural Network in WSN-IoT

Safa M.,Pandian A.,Mohammad Gouse Baig,Reddy Sadda Bharath,Kumar K. Satish,Banu A. S. Gousia,Srihari K.,Chandragandhi S. 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.4

Cardiac disease analysis in big data is an emerging factor for human health protection against heart attacks. Most cardiovascular diseases lead to heart failure due to an imbalance of immunity and attention in health conditions. Hence, immunity-based feature analysis of patients’ records is essential to predict accurate results. The machine learning methods make predictions depending on the extended-lasting features to analyze the health data. But the marginal features expose non-relational feature observation to reduce the classifi cation prediction accuracy. We propose a Deep Spectral Time-Variant Feature Analytic Model (DSTV-FAM) using SoftMax Recurrent Neural Network (SMRNN) in a wireless sensor network to improve cardiac disease prediction accuracy. Initially, the IoT sensor devices collect the data from patient observation to validate the data transmission in route propagation. The collected data is organized as features in the collective dataset. The parts are initially preprocessed into the redundant dataset and estimate the Cardiac Immunity Infl uence Rate (CIIR) depending on the time-variant feature selection model. The estimated weights are marginalized as spectral features trained into the classifi ers. Further, Soft-Max Activation Function (SMAF) creates a logical function depending on the Cardiac Aff ection Rate (CAR). Then the trained, rational neurons are constructed into a Recurrent Neural Network (RNN) Feed-forward feature values using a classifi er and Rate of Disease Aff ection (RDA) by Class Type. The proposed structure yields high prescient exactness concerning order, accuracy, and review to help early treatment for early cardiovascular gamble expectation.

Identification of common therapeutic targets for selected neurodegenerative disorders: An in silico approach

Ahmad, K.,Baig, M.H.,Gupta, G.K.,Kamal, M.A.,Pathak, N.,Choi, I. Elsevier 2016 Journal of computational science Vol.17 No.1

<P>Neurodegenerative disorders (NDs) are a heterogeneous group of disorders generally characterized by a profound decrease in the size and volume of the human brain due to death of neurons. These disorders include a variety of progressive disorders that result in cognitive and/or motor degradation. The present study was conducted to identify common potential targets for multi-neurodegenerative diseases. To accomplish this, we have selected six common neurodegenerative diseases, Alzheimer's disease (AD), Parkinson's disease (PD), Amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), Prion disease and Dentatorubral-pallidoluysian atrophy (DRPLA) for identification of common regulatory target proteins. A total of sixteen common proteins were identified as target proteins by disease pathway analysis and previous studies based on their association with more than two NDs, including AD. An interaction network of each of the sixteen target proteins was then constructed against causative proteins selected from all six NDs by using the STRING 9.1 program. Pathway analysis and the protein-protein interaction network suggested that CASP-3 and CASP-8 were associated with the maximum number of selected NDs and may therefore be the most potent target proteins for, treatment of multi-neurodegenerative diseases. (C) 2016 Elsevier B.V. All rights reserved.</P>

Binding of erucic acid with human serum albumin using a spectroscopic and molecular docking study

Rabbani, G.,Baig, M.H.,Jan, A.T.,Ju Lee, E.,Khan, M.V.,Zaman, M.,Farouk, A.E.,Khan, R.H.,Choi, I. Elsevier 2017 International journal of biological macromolecules Vol.105 No.3

Erucic acid (EA) is one of the key fatty acids usually found in canola oil, mustard oil and rapeseed oil. Consumption of EA in primates was found to cause myocardial lipidosis and cardiac steatosis. To have an insight of the effect of EA in humans, we performed in vitro interaction studies of EA with the primary plasma protein, human serum albumin (HSA). Spectroscopic (UV-vis and fluorescence) analysis of the HSA-EA interaction revealed a static mode of quenching with binding constant K<SUB>b</SUB> ~10<SUP>4</SUP> reflecting high affinity of EA for HSA. The negative value of ΔG<SUP>o</SUP> for binding of EA to HSA in the fluorescence studies indicates the process to be spontaneous. Thermodynamic signatures of the HSA-EA interaction in the complex reflect dominance of hydrogen bonds. Despite predominance of hydrogen bonds, hydrophobic interactions in the HSA-EA complex were found acting as a contributing factor in the binding of EA to HSA, observed as structural change in the far-UV CD spectra. Forster's resonance energy transfer of the EA-HSA complex revealed a distance of 3.2nm between acceptor molecules (EA) and the donor Trp residue of HSA. To have a deeper insight of the structural dependence of the HSA-EA interaction in the complex, thermodynamic study was supplemented with molecular docking. The molecular docking analysis further highlighted the EA binding in the subdomain IIIA (Sudlow site II) of HSA. The information generated in the study reflects greater pharmacological significance of EA and highlights its importance in the clinical medicine.