Drug discovery is an exhaustive and time-consuming process involving numerous stages like target identification, validation, lead optimization, preclinical trials, clinical trials and finally postmarketing vigilance for drug safety. The application of computer-aided drug designing (CADD) is an indispensable approach for developing safe and effective drugs. Previous methods based on combinatorial chemistry (CC) and high throughput screening (HTS) consumed a lot of time as well as expenditure. CADD based approaches including pharmacophore modeling (PM), molecular docking (MD), inverse docking, chemical similarity (CS), quantitative structure-activity relationship (QSAR), virtual screening (VS) and molecular dynamics simulations have been quite productive in predicting the therapeutic outcome of candidate drugs/compounds besides saving precious time. CADD tools exploit structural and other information available regarding the target (enzyme/receptor) and the ligands to identify the compounds with the ability to treat diseases notably cancer, neurodegenerative disorders, malaria, Ebola, HIV-AIDS and many more. Computational approaches have led to the discovery of many drugs that have passed preclinical and clinical trials and become novel therapeutics in the treatment of a variety of diseases. Some notable examples of CADD derived novel drugs include dorzolamide, saquinavir, ritonavir, indinavir, captopril and tirofiban. CADD plays important role in predicting absorption, distribution, metabolism, excretion and toxicity (ADME/T) of candidate drugs. Overall, CADD represents an effective and much-needed strategy for designing therapeutically effective drugs to combat human diseases.

Protein-protein interactions (PPIs) drive major signalling cascades and play critical role in cell proliferation, apoptosis, angiogenesis and trafficking. Deregulated PPIs are implicated in multiple malignancies and represent the critical targets for treating cancer. Herein we discuss the key protein-protein interacting domains implicated in cancer notably PDZ, SH2, SH3, LIM, PTB, SAM and PH. These domains are present in numerous enzymes/kinases, growth factors, transcription factors, adaptor proteins, receptors and scaffolding proteins and thus represent essential sites for targeting cancer. This review explores the candidature of various proteins involved in cellular trafficking (small GTPases, molecular motors, matrix degrading enzymes, integrin), transcription (p53, cMyc), signalling (membrane receptor proteins), angiogenesis (VEGFs) and apoptosis (BCL-2family), which could possibly serve as targets for developing effective anti-cancer regimen. Interactions between Ras/Raf; X-linked inhibitor of apoptosis protein (XIAP)/second mitochondria derived activator of caspases (Smac/DIABLO); Frizzled (FRZ)/Dishevelled (DVL) protein; beta-catenin/T cell factor (TCF) have also been studied as prospective anticancer targets. Efficacy of diverse molecules/drugs targeting such PPIs although evaluated in various animal models/cell lines, there is essential need for human based clinical trials. Therapeutic strategies like the use of biologicals, high throughput screening (HTS) and fragment based technology could play imperative role in designing cancer therapeutics. Moreover, bioinformatic/computational strategies based on genome sequence, protein sequence/structure and domain data could serve as competent tools for predicting PPIs. Exploring hot spots in proteomic networks represents another approach for developing target specific therapeutics. Over-all, this review lays emphasis on productive amalgamation of proteomics, genomics, biochemistry, and molecular dynamics for successful treatment of cancer.

No abstract

No abstract

No abstract