Background:: Computational or in silico studies are undertaken to assess the drug like properties of lead compounds. These studies help in fast prediction of relevant properties. Objective: : Through this review, an effort is made to encapsulate some of the important parameters which should be met by a compound for it to be considered as a potential drug candidate along with an overview of automated softwares which can be used for making various predictions. Methods:: Drug uptake, its absorption, evacuation and associated hazardous effects are important factors for consideration in drug designing and should be known in early stages of drug development. Several important physicochemical properties like molecular weight, polar surface area (PSA), molecular flexibility etc. have to be taken into consideration in drug designing. Toxicological assessment is another important aspect of drug discovery which predicts the safety and adverse effects of a drug. Results: : Additionally, bioactivity scores of probable drug leads against various human receptors can also be predicted to evaluate the probability of them to act as a potential drug candidate. The in vivo biological targets of a molecule can also be efficiently predicted by molecular docking studies. Conclusion:: Some important software like iGEMDOCK, AutoDock, OSIRIS property explorer, Molinspiration, MetaPrint2D, admetSAR and their working methodology and principle of working have been summarized in this review.

''India currently bears the largest number of indoor air pollution (IAP) related health problems in world. An estimated 500,000 women & children die in India each year due to IAP-related cause--this is 25% of estimated IAP-related deaths worldwide. This study will be useful for policy makers, health related officials, academicians and Scientists who have interest in countries of developing world''.

Hydrogen sulfide (HS) emissions were measured periodically over the course of 2 yr at three sow waste lagoons representing humid mesothermal (North Carolina, NC), humid microthermal (Indiana, IN), and semiarid (Oklahoma, OK) climates. Emissions were determined using a backward Lagrangian stochastic model in conjunction with line-sampled HS concentrations and measured turbulence. The median annual sow-specific (area-specific) lagoon emissions at the OK farm were approximately 1.6 g head [hd] d (5880 µg m s), whereas those at the IN and NC sow farms were 0.035 g hd d (130 µg m s), and 0.041 g hd d (260 µg m s), respectively. Hydrogen sulfide emissions generally increased with wind speed. The daily HS emissions from the OK lagoon were greatest during the first half of the year and decreased as the year progressed. Emissions were episodic at the NC and IN lagoons. The generally low emissions at the NC and IN lagoons were probably a result of significant populations of purple sulfur bacteria maintained in the humid mesothermal and humid microthermal climates. Most of the large HS emission events at the NC and IN lagoons appeared to be a result of either precipitation events or liquid pump-out events. The high emissions at the OK lagoon in a semiarid climate were largely a result of high wind speeds enhancing both lagoon and air boundary layer mixing. The climate (air temperature, winds, and precipitation) appeared to influence the HS emissions from lagoons.

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