No abstract

No abstract

No abstract

Abstract:With the exponential rise in the number of viable novel drug targets, computational methods are being increasingly applied to accelerate the drug discovery process. Virtual High Throughput Screening (vHTS) is one such established methodology to identify drug candidates from large collection of compound libraries. Although it complements the expensive and time consuming High Throughput Screening (HTS) of compound libraries, vHTS possess inherent challenges. The successful vHTS requires the careful implementation of each phase of computational screening experiment right from target preparation to hit identification and lead optimization. This article discusses some of the important considerations that are imperative for designing a successful vHTS experiment.Keywords: virtual high throughput screening; receptor based and ligand based screening; homology models; chemical databases; ADME filters; toxicity filters Background:The discovery of novel drug targets has increased exponentially in recent years due to advances in genomic and molecular biology techniques. Experimental and computational methods are effectively applied to accelerate the process of lead identification and optimization. The chemical leads are small potential drug like molecules which are capable of modulating the function of the target proteins that are further optimized to act as a therapeutic drug against a targeted disease. Conventional experimental methods like High Throughput Screening (HTS) continue to be the best method for rapid identification of drug leads. HTS identifies lead molecules by performing individual biochemical assays with over millions of compounds. However, the huge cost and time consumed with this technology has lead to the integration of cheaper and effective computational methodology namely virtual High Throughput Screening (vHTS). vHTS is a computational screening method which is widely applied to screen insilico collection of compound libraries to check the binding affinity of the target receptor with the library compounds [1]. This is achieved by using a scoring function which computes the complementarity of the target receptor with the compounds. HTS and vHTS are complementary methods [2] and vHTS has been shown to reduce false positives in HTS [3]. Several vHTS strategies have been practiced [4] and the technique is being continuously optimized for better performance.

SummaryAlkali metal uranyl chloride (M