The present work significantly emphasizes the curatively designed new small drug-like molecule (Scaffold analog) and in silico performance of comparative studies with a naturally found bioactive constituent (Cyperene) of the plant through ligand based approach (chemical similarity criteria) to unveil prospective target sites, genomic interactions, cellular signaling pathways, and their associated diseases/disorders through proteogenomic analysis to better understand their mode of action. Herbal medicine has been used by humans for healing purposes in many treatment systems (Ayurveda, Unani, Homeopathy, and Siddha) from ancient times, and has been described as an essential source of medicine even in the present period. Obesity, remittent fever, monthly irregularities, bowel disorders, colitis, diarrhea, vomiting, uterine contraction, bad breath, and other neuromuscular-related issues are all treated by Nut Sedge (Cyperus rotundus L.)[2, 3]. The major therapeutic agents are found in rhizomes of the herb. The plethora of bioactive constituents is found in it including cyperene, α-cyperone, humulin, β-selinene, α-selinene, cyperotundone, zierone, α-calacorene, campholenic aldehyde, pinene, γ-muurolene, longiverbenone, β-caryophyllene oxide, and limonene which represents different classes of secondary metabolites such as alkaloids, phenols, tannins, saponins, steroids, coumarins, flavonoids diterpenoids, and triterpenoids[5, 6]. Herbal-derived ligands and targeted therapeutic approaches may be successfully worked on using in silico approaches. The ligands (bioactive component, scaffold analog) of Cyperus rotundus L. were evaluated to find its molecular activities at different target sites by maintaining a curative space for drug discovery, drug reuse, development, advancement, and innovative results. These efforts include an in silico approach to cheminformatics, and proteogenomic analysis including physicochemical analysis, pharmacokinetics, pharmacodynamics, medicinal chemistry, drug similarities, designing of novel scaffolding analog, target predictions, molecular docking, identification of genes, genomic interactions, cellular signaling, and their biological insights (top ten diseases/ disorders regulated by these interactive genes via identifying the target sites of ligands) through representative overexpression analysis (ORA), and Network Topology-based Analysis (NTA). The topological polar surface area (TPSA) of a molecule is defined as the surface sum of all polar atoms or molecules including oxygen, nitrogen, and their attached hydrogen atoms. Log P is the logarithm of the partition coefficient (P) when one of the solvents is water and the other is a non-polar solvent. For the optimal results, the log P value is 0<LogP<3, LogP<0: poor lipid bilayer permeability, and LogP>3: poor aqueous solubility. It is a measure of the lipophilicity or hydrophobicity of the compound. XLogP3 predicts the octanol/water partition coefficient of an organic compound. It is based on the group contribution method with suitable corrections. Water solubility (log S) is represented from insoluble <-10<poorly<-6<moderately<-4<soluble<-2very<0<highly soluble. The pharmacokinetics parameters include the absorption (gastrointestinal absorption, p-glycoprotein substrate), distribution (blood-brain barrier), metabolism (CYP1A2 inhibitor, CYP2C19 inhibitor, CYP2C9 inhibitor, CYP2D6 inhibitor, and CYP3A4 inhibitor), elimination (elimination half time (T1/2):3h<T1/2<8h and clearance (cl): 5ml/min/kg<cl<15ml/min/kg, and toxicity (human ether-a-go-go-related gene(hERG- category 0: non blocker; category 1: blocker), human hepatotoxicity (H-HT- category 0: negative; category 1: positive), Ames mutagenicity-category 0: negative; category 1: positive, skin sensitization-category 0: non sensitizer; category 1: sensitizer, drug-induced liver injuries (DILI-category 0: negative; category 1: positive), and FDA maximum recommended daily dose-category 0: FDAMDD negative; category 1: FDAMDD positive). The bioactivity scores of the ligands on different target sites such as GPCR ligand, ion channel modulator, kinase inhibitor, nuclear receptor ligand, protease inhibitor, and enzyme inhibitor activities are covered under pharmacodynamics. The bioactivity of screened molecules may then be calculated as a sum of activity contributions of fragments in these molecules. This provides a molecule activity score (a number, typically between -3 and 3). Molecules with the highest activity score have the highest probability to be active. The drug-likeness properties were evaluated by the application of ‘Lipinski Rule of Five’, ‘Ghose’s Rule’, ‘Veber’s Rule’, ‘Muegge’s Rule’, and ‘Egan Rule’[14–16]. Pan-assay interference structure (PAINS) analysis is performed on compounds having desirable physicochemical properties to determine their toxicity. This assay is also called toxicophores because of the presence of some group elements that disrupt the biological processes through interference with DNA or protein which results in fatal conditions such as carcinogenicity and hepatotoxicity. Brenk analysis gives an idea about structural alert including chirality and steric hindrances. The lead-likeness comprises the ligands having 250≤MW≤350, XLogP≤3.5, and no. of rotatable bonds≤7. The synthetic accessibility score from 1 (very easy) to 10 (very difficult) to synthesize.