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Peptidomimetics is a novel drug designing strategy in which an Insilico inhibitor is designed by mimicking the framework of a short peptide. Novel drug design strategies shall only pave way for developing unique and safer anti-HIV drugs. In the present study, we propose a Peptidomimetics based gp120 attachment inhibitor. In human biological system, HIV-1 interacts with CD4 receptor of the host via its surface glycoprotein gp120 establishing initial attachment. This protein-protein interaction interface forms the base to derive an inhibitor mimicking backbone of the receptor. The mimicked inhibitor derived in this study is based on the insilico interactions of soluble CD4 (SCD4) (precursor of CD4) with gp120. The molecular interactions of SCD4 with gp120 were identified by MEDock software. Furthermore, the interacting interface was analyzed manually for topology, and the backbone of the ligand molecule was sketched based on it with chemsketch. Moreover, the sketched ligand was optimized and was docked with gp120 using Argus lab. Docking results show six hydrogen bonds formation between the ligand and binding interface of gp120. The ligand was also found to be fit with good druggable character, as per Lipinski's rule of five. Hence, this work addresses the drug likeness of the peptidomimetic ligand proposed.

Molecular modeling is the atomic‐level description of molecular systems. The development of molecular modeling programs and their application in pharmaceutical research has been formalized as a field of study known as computer‐assisted drug design (CADD) or computer‐assisted molecular design (CAMD). Molecular modeling methods are now routinely used to investigate the structure, dynamics and thermodynamics of biological, inorganic and polymeric systems. Although initially models were physically drawn or made using appropriate materials, the development of computer programs introduced CADD or CAMD. Stages of molecular modeling are covered in this chapter and a few in silico tools available are discussed. Molecular modeling has been of great use to many scientists by decreasing time taken for the otherwise tedious task of modeling and associated analysis such as potential drug candidate identification, docking, protein–protein interactions, etc.

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Cheminformatics is the use of computer and informational techniques, applied to a range of problems in the field of chemistry. It is also known as chemoinformatics and chemical informatics. These in silico techniques are used in pharmaceutical companies in the process of drug discovery. Cheminformatics can also be applied to data analysis for various industries such as paper and pulp, dyes and such allied industries. The primary application of cheminformatics is in the storage of information relating to compounds. Quantitative structure–activity relationship (QSAR) analysis also forms a part of cheminformatics. Several in silico cheminformatic tools are currently available for predicting physio‐chemical properties and biological activity of many different chemical molecules. Thus, chemoinformatics helps to reduce the time taken for identifying potential drug targets as well as to understand physical, chemical and biological properties of several chemical compounds. Outputs of chemoinformatics may also direct the course of wet laboratory experiments.