Recently, we have studied drug-receptor interaction of the peptidic HIV-1 protease inhibitors based on polar and hydrophobic interactions. We have also studied pharmacokinetics of these inhibitors based on Lipinski’s rule of five and its extended form. After that there was a need to study intermolecular interactions. From literatures, drug-receptor interaction involves hydrogen bonds between acceptor and donor sites of drug and its receptor. These donor acceptor sites must be more than four to be dominant. As single intermolecular H-bond is relatively weak and unlikely to support this type of interaction. It is also clear from literature that this interaction contribute to the alignment of reacting species in proper three-dimensional space in such a position that strong and effective polar or hydrophobic or both interaction occurs to form drug-receptor adduct or enzyme inhibitor complex as appropriate. The strength of H-bonds formed between drug and receptor was judged by bond lengths, bond angles and bond orders. As well as, its nature (strong, moderate or weak) and its number, too. Along with H-bonding, we have also studied Van der Walls i.e. non-bonding type interaction. These non-bonding interactions were studied using charge transfer from donor to acceptor and this results transfer of electron flux from donor molecule (drug/receptor) towards acceptor (receptor/ drug). Thus, lowering of energy of the system under investigation will occur. For this resulted interaction energy was also studied that very clearly explain feasibility of interactions. As we know that all above phenomena are molecular properties and do not cover involvement of orbitals. To cover this we have also studied drug-receptor interaction involving molecular orbital. It was HOMO of one reacting molecule (B) that donates electron pair, electron cloud or electron density to LUMO of another reacting molecule (A) that accepts or accommodates this electron pair, electron cloud or electron density. The quantity of the electron flux from HOMO to LUMO was judged by the value of ∆E_LH. A lower value of this will support strong and effective drug-receptor interaction. Results of orbital based study have also been found to supports the results as abstracted from interaction energy.

Polychlorinated biphenyls (PCBs) are important class of persist organic pollutants that were used as a component of paints especially in printings, as plastificator of plastics and insulating materials in transformers and capacitors, heat transfer fluids, additives in hydraulic fluids in vacuum and turbine pumps. There is always a need to establish reliable procedures for predicting the bioconcentration potential of chemicals from the knowledge of their molecular structure, or from readily measurable properties of the substance. Hence, correlation and prediction of biococentration factors (BCFs) based on λ_max and vibration frequencies of various bonds viz υ(C-H) and υ(C=C) of biphenyl and its fifty-seven derivatives have been made. For the study, the molecular modeling and geometry optimization of the PCBs have been performed on workspace program of CAChe Pro 5.04 software of Fujitsu using DFT method. UV-visible spectra for each compound were created by electron transition between molecular orbitals as electromagnetic radiation in the visible and ultraviolet (UV-visible) region is absorbed by the molecule. The energies of excited electronic states were computed quantum mechanically. IR spectra of transitions for each compound were created by coordinated motions of the atoms as electromagnetic radiation in the infrared region is absorbed by the molecule. The force necessary to distort the molecule was computed quantum mechanically from its equilibrium geometry and thus frequency of vibrational transitions was predicted. Project Leader Program associated with CAChe has been used for multiple linear regression (MLR) analysis using above spectroscopic data as independent variables and BCFs of PCBs as dependent variables. The reliability of correlation and predicting ability of the MLR equations (models) are judged by R², R²_adj, se, q²_L10O and F values. This study reflected clearly that UV and IR spectroscopic data can be used to predict BCFs of a large number of related compounds within limited time without any difficulty.