Saif Khan

Computer Aided Drug Design: Success and Limitations.

Over the last few decades, computer-aided drug design has emerged as a powerful technique playing a crucial role in the development of new drug molecules. Structure-based drug design and ligand-based drug design are two methods commonly used in computer-aided drug design. In this article, we discuss the theory behind both methods, as well as their successful applications and limitations. To accomplish this, we reviewed structure based and ligand based virtual screening processes. Molecular dynamics simulation, which has become one of the most influential tool for prediction of the conformation of small molecules and changes in their conformation within the biological target, has also been taken into account. Finally, we discuss the principles and concepts of molecular docking, pharmacophores and other methods used in computer-aided drug design.

Implication of Caspase-3 as a Common Therapeutic Target for Multineurodegenerative Disorders and Its Inhibition Using Nonpeptidyl Natural Compounds

Caspase-3 has been identified as a key mediator of neuronal apoptosis. The present study identifies caspase-3 as a common player involved in the regulation of multineurodegenerative disorders, namely, Alzheimers disease (AD), Parkinsons disease (PD), Huntingtons disease (HD), and amyotrophic lateral sclerosis (ALS). The protein interaction network prepared using STRING database provides a strong evidence of caspase-3 interactions with the metabolic cascade of the said multineurodegenerative disorders, thus characterizing it as a potential therapeutic target for multiple neurodegenerative disorders. In silico molecular docking of selected nonpeptidyl natural compounds against caspase-3 exposed potent leads against this common therapeutic target. Rosmarinic acid and curcumin proved to be the most promising ligands (leads) mimicking the inhibitory action of peptidyl inhibitors with the highest Gold fitness scores 57.38 and 53.51, respectively. These results were in close agreement with the fitness score predicted using X-score, a consensus based scoring function to calculate the binding affinity. Nonpeptidyl inhibitors of caspase-3 identified in the present study expeditiously mimic the inhibitory action of the previously identified peptidyl inhibitors. Since, nonpeptidyl inhibitors are preferred drug candidates, hence, discovery of natural compounds as nonpeptidyl inhibitors is a significant transition towards feasible drug development for neurodegenerative disorders.

Structure based molecular inhibition of Caspase-8 for treatment of multi-neurodegenerative diseases using known natural compounds.

Neurodegenerative disorders are often associated with excessive neuronal apoptosis. It is well known that apoptosis is regulated by some intracellular proteases, such as, Caspases (cysteine-dependent, aspartate-specific proteases). In fact, Caspase-8 which is an initiator caspase, has been identified as a key mediator of neuronal apoptosis. In addition, Caspase-8 is found to be coupled with the regulation of various neurodegenerative disorders including Alzheimer׳s disease (AD), Parkinson׳s disease (PD), Huntington׳s Diseases (HD) and Dentatorubral Pallidoluysian Atrophy (DRPLA). Caspase-8 inhibition may provide an effective means of treatment for multiple neurodegenerative disorders. Therefore, the present study describes the molecular interaction of some selected natural compounds with known anti neurodegenerative properties with Caspase-8. Docking between Caspase-8 and each of these compounds (separately) was performed using ‘Autodock4.2’. Out of all the selected compounds, rosmarinic acid and curcumin proved to be the most potent inhibitors of Caspase-8 with binding energy (ΔG) of -7.10 Kcal/mol and -7.08 Kcal/mol, respectively. However, further in vitro and in vivo studies are needed to validate the anti-neurodegenerative potential of these compounds.

Artificial Intelligence versus Statistical Modeling and Optimization of Cholesterol Oxidase Production by using Streptomyces Sp.

Cholesterol oxidase (COD) is a bi-functional FAD-containing oxidoreductase which catalyzes the oxidation of cholesterol into 4-cholesten-3-one. The wider biological functions and clinical applications of COD have urged the screening, isolation and characterization of newer microbes from diverse habitats as a source of COD and optimization and over-production of COD for various uses. The practicability of statistical/ artificial intelligence techniques, such as response surface methodology (RSM), artificial neural network (ANN) and genetic algorithm (GA) have been tested to optimize the medium composition for the production of COD from novel strain Streptomyces sp. NCIM 5500. All experiments were performed according to the five factor central composite design (CCD) and the generated data was analysed using RSM and ANN. GA was employed to optimize the models generated by RSM and ANN. Based upon the predicted COD concentration, the model developed with ANN was found to be superior to the model developed with RSM. The RSM-GA approach predicted maximum of 6.283 U/mL COD production, whereas the ANN-GA approach predicted a maximum of 9.93 U/mL COD concentration. The optimum concentrations of the medium variables predicted through ANN-GA approach were: 1.431 g/50 mL soybean, 1.389 g/50 mL maltose, 0.029 g/50 mL MgSO4, 0.45 g/50 mL NaCl and 2.235 ml/50 mL glycerol. The experimental COD concentration was concurrent with the GA predicted yield and led to 9.75 U/mL COD production, which was nearly two times higher than the yield (4.2 U/mL) obtained with the un-optimized medium. This is the very first time we are reporting the statistical versus artificial intelligence based modeling and optimization of COD production by Streptomyces sp. NCIM 5500.

G894T and 4a/b Polymorphisms of NOS3 Gene are Not Associated with Cancer Risk: a Meta-analysis

Endothelial nitric oxide synthase (eNOS or NOS3) produces nitric oxide and genetic polymorphisms of NOS3 gene play significant roles in various processes of carcinogenesis. The results from published studies on the association between NOS3 G894T and NOS3 intron 4 (4a/b) polymorphisms and cancer risk are conflicting and inconclusive. However, i n order to assess this relationship more precisely, a meta-analysis was performed with PubMed (Medline), EMBASE and Google web searches until February 2014 to select all published case- control and cohort studies. Genotype distribution data were collected to calculate the pooled odd ratios (ORs) and 95% confidence intervals (CIs) to evaluate the strength of association. A total of 10,546 cancer cases and 10,550 controls were included from twenty four case-control studies for the NOS3 G894T polymorphism. The results indicated no significant association with cancer risk as observed in allelic (T vs G: OR=1.024, 95%CI=0.954 to 1.099, p=0.508), homozygous (TT vs GG: OR=1.137, 95%CI=0.944 to 1.370, p=0.176), heterozygous (GT vs GG: OR=0.993, 95%CI=0.932 to 1.059, p=0.835), recessive (TT vs GG+GT: OR=1.100, 95%CI=0.936 to 1.293, p=0.249) and dominant (TT+GT vs GG: OR=1.012, 95%CI=0.927 to 1.105, p=0.789) genetic models. Similarly, a total of 3,449 cancer cases and 3,691 controls were recruited from fourteen case-control studies for NOS3 4a/b polymorphism. Pooled results indicated no significant association under allelic (A vs B: OR=0.981, 95%CI=0.725 to 1.329, p=0.902), homozygous (AA vs BB: OR=1.166, 95%CI=0.524 to 2.593, p=0.707), heterozygous (BA vs BB: OR=1.129, 95%CI=0.896 to 1.422, p=0.305), dominant (AA+BA vs BB: OR=1.046, 95%CI=0.779 to 1.405, p=0.763) and recessive (AA vs BB+BA: OR=1.196, 95%CI=0.587 to 2.439, p=0.622) genetic contrast models. This meta-analysis suggests that G894T and 4a/b polymorphisms of NOS3 gene are not associated with increased or decreased risk of overall cancer.

Identification of Potent Caspase-3 Inhibitors for Treatment of Multi- Neurodegenerative Diseases Using Pharmacophore Modeling and Docking Approaches

Neurodegenerative disorders are due to excessive neuronal apoptosis and the caspase-3 plays a key role in the apoptotic pathway. The caspase-3 inhibition may be a validated therapeutic approach for neurodegenerative disorders and an interesting target for molecular modeling studies using both Ligand and structure based approaches. In view of the above we have generated the Ligand based pharmacophore model using the Discovery studio 2.0 software. In addition to this a structure based approach has been used to validate the developed pharmacophoric features to gain a deeper insight into its molecular recognition process. This validated pharmacophore and the docking model was then implemented as a query for pharmacophore based virtual screening to prioritize the probable hits for the Caspase-3. Two ligands, ZINC12405015 and ZINC12405043 were finally selected on the basis of their fit values and docking scores. This study also reveals the important amino acids viz. His-121, Ser-205, Arg-207 which were found to be playing crucial role in the binding of the selected compounds within the active site of caspase-3.

Optimization of Extraction Parameters for Enhanced Production of Ovotransferrin from Egg White for Antimicrobial Applications

Ovotransferrin is the second most abundant protein (~12-13% of the total egg protein) in egg white after ovalbumin. Ovotransferrin is a potent natural antimicrobial agent as it possesses antibacterial, antifungal, and antiviral properties and is also the major metal binding protein found in egg, which makes it an industrially important protein. Ovotransferrin was extracted from egg white using its metal (iron) binding properties. In the present study, eggs from two different sources were used (fresh local eggs from domestic household source and poultry eggs from shops) to compare the results and Response Surface Methodology was used for the experiment design and data analysis. The following extraction conditions were optimized so as to maximize the yield of ovotransferrin from egg white: ethanol % (v/v) and pH and volume (mL) of 25 mM FeCl3/50 mL of egg white. A maximum yield of ~85 ± 2.5% was obtained near the optimum extraction conditions. The yield was calculated based on the theoretical value (934 mg) of ovotransferrin in 100 mL of 1.5x diluted egg white solution. Our results suggest that efficient downstream processing may reduce the cost of overall production process of this promising enzyme, making it a natural and cost-effective alternative to the existing chemically synthesized antimicrobial agents.

Inhibition of C298S mutant of human aldose reductase for antidiabetic applications: Evidence from in silico elementary mode analysis of biological network model

Human aldose reductase (hAR) is the key enzyme in sorbitol pathway of glucose utilization and is implicated in the etiology of secondary complications of diabetes, such as, cardiovascular complications, neuropathy, nephropathy, retinopathy, and cataract genesis. It reduces glucose to sorbitol in the presence of NADPH and the major cause of diabetes complications could be the change in the osmotic pressure due to the accumulation of sorbitol. An activated form of hAR (activated hAR or ahAR) poses a potential obstacle in the development of diabetes drugs as hAR‐inhibitors are ineffective against ahAR. The therapeutic efficacy of such drugs is compromised when a large fraction of the enzyme (hAR) undergoes conversion to the activated ahAR form as has been observed in the diabetic tissues. In the present study, attempts have been made to employ systems biology strategies to identify the elementary nodes of human polyol metabolic pathway, responsible for normal metabolic states, followed by the identification of natural potent inhibitors of the activated form of hAR represented by the mutant C298S for possible antidiabetic applications. Quantum Mechanical Molecular Mechanical docking strategy was used to determine the probable inhibitors of ahAR. Rosmarinic acid was found as the most potent natural ahAR inhibitor and warrants for experimental validation in the near future.

Effect of pH, temperature and incubation time on cordycepin production from Cordyceps militaris using solid-state fermentation on various substrates

ABSTRACT Cordyceps militaris has been a keystone in combating myriad health problems with innumerable far-reaching therapeutic effects. The present study focuses on effect of fermentation conditions such as (pH, temperature and incubation time) and solid-state fermentation (SSF) using solid substrates (wheat, oat and rice) on production of cordycepin. Temperature, pH and incubation time was found to have a direct effect on cordycepin production. The best possible combination of temperature, pH and incubation time was found to be 25°C, 5.5 and 21 days, respectively, for maximum cordycepin production. SSF of solid substrate medium culture leads to the production of cordycepin. Among the solid substrates, rice medium had highest cordycepin production (814.60 mg/g) followed by oat and wheat medium (638.85 and 565.20 mg/g, respectively). This method provides an effective way for increasing the cordycepin production at a large scale. This study could have a wide application in other fermentation processes at industrial level.

Artificial Intelligence vs. Statistical Modeling and Optimization of Continuous Bead Milling Process for Bacterial Cell Lysis

For a commercially viable recombinant intracellular protein production process, efficient cell lysis and protein release is a major bottleneck. The recovery of recombinant protein, cholesterol oxidase (COD) was studied in a continuous bead milling process. A full factorial response surface methodology (RSM) design was employed and compared to artificial neural networks coupled with genetic algorithm (ANN-GA). Significant process variables, cell slurry feed rate (A), bead load (B), cell load (C), and run time (D), were investigated and optimized for maximizing COD recovery. RSM predicted an optimum of feed rate of 310.73 mL/h, bead loading of 79.9% (v/v), cell loading OD600 nm of 74, and run time of 29.9 min with a recovery of ~3.2 g/L. ANN-GA predicted a maximum COD recovery of ~3.5 g/L at an optimum feed rate (mL/h): 258.08, bead loading (%, v/v): 80%, cell loading (OD600 nm): 73.99, and run time of 32 min. An overall 3.7-fold increase in productivity is obtained when compared to a batch process. Optimization and comparison of statistical vs. artificial intelligence techniques in continuous bead milling process has been attempted for the very first time in our study. We were able to successfully represent the complex non-linear multivariable dependence of enzyme recovery on bead milling parameters. The quadratic second order response functions are not flexible enough to represent such complex non-linear dependence. ANN being a summation function of multiple layers are capable to represent complex non-linear dependence of variables in this case; enzyme recovery as a function of bead milling parameters. Since GA can even optimize discontinuous functions present study cites a perfect example of using machine learning (ANN) in combination with evolutionary optimization (GA) for representing undefined biological functions which is the case for common industrial processes involving biological moieties.