| Abstract: | Positive strand RNA viruses, which include hepatitis C virus (HCV), human immunodeficiency virus (HIV,
and Bovine Viral Diarrhea Virus (BVDV), are known to create havoc for humans and animal health alike.
Although vaccines have helped to control several of the most important viral pathogens, there is currently little
prospect of an effective vaccine for either HCV or HIV. These pathogens infect ~170 million and ~40 million
people worldwide, respectively, hastening the need for effective antiviral drugs. Likewise BVDV infects
domesticated livestock causing significant economic losses worldwide. The development of new, effective
antiviral compounds for combating these debilitating human (HIV and HCV) and animal pathogen (BVDV) is
therefore of paramount importance, and is the focus of this thesis.
Herein, polymerases of three positive strand RNA viruses, viz HCV, BVDV and HIV have been targeted with the
goal of improving the efficacy of antivirals against wide range of resistant mutations. Lack of effective therapies
for these viral infections as most of the established treatments are not always effective or well tolerated,
highlights an urgent need for further refinement and development of antiviral drugs. It is not only the specific
need that has inspired this work but also the idea to test and develop protocols that might enable a more
rational structurebased
drug design to be performed by keeping a tradeoff among rapidity, accuracy, and
efficacy.
Traditional methods for general drug discovery typically include evaluating random compound libraries for
activity in relevant cellfree
or cellbased
assays. Success in antiviral development has emerged from the
discovery of more focused libraries that provide clues about structureactivity
relationships. Combining these
with more recent approaches including structural biology and computational modeling can work efficiently to
hasten discovery of active molecules. The ability to design drugs interfering with the progression of infection
of virus comes with i)the
knowledge of pathological, cellular and molecular mechanism involved in the
disease; and ii)the
identification of macromolecule (i.e possible drug target) involved in pathological
pathways, their 3D structures and their functions. The biological activity of drug molecules is dependent on
the threedimensional
arrangement of its functional groups, which specifically bind to their target.
Consequently, the structural information of the target protein is essential in drug development.
Proteins are dynamic molecules and often undergo conformational change upon ligand binding. The flexible
loop regions and in general the flexibility of the structure have a critical functional role in enzymes, but those
features and their connection with the functionality of protein are hard to retrieve from xray,
NMR techniques
and cryoEM
techniques.
Being aware of the importance of the relationship structurefunction
and structureactivity
at large, i.e.,
including dynamics and interactions with solvent, in our work we are trying to address some of the relevant
problems of drug development; basic key determinants in proteinligand
stability, mechanism of inhibition,
why and how, flexibility and collective motion of the protein is essential part in improvement of rational drug
design, how mutation renders the protein resistant again potent drugs; the effect of resistance mutation on the
flexibility and stability of protein, what is the mechanism of drug resistance, change in energetics
consequences, affecting the conformation in wild and mutant systems. Various biophysical techniques of the
computational arsenal we have applied have provided huge wealth of information related to protein dynamics
and proteinligand
recognition. These methods have grown in their effectiveness not only by offering a deeper
understanding of the basic science, the biological events and molecular interactions that define a target for
therapeutic intervention, but also because of advances in algorithms, representations, and mathematical
procedures for studying such processes.
This work represents the application of several computational techniques, such as docking, molecular
dynamics, algorithms to calculate free energy of binding of ligands into the binding pocket (ex MMPBSA)
and
algorithms to study rare events (for ex. binding and unbinding of ligand from the binding site, Metadynamics)
to explore, at microscopic level, the key pattern of interaction between protein and ligand, to understand the
effect of mutations, to get an insight of the full docking and undocking path and to calculate binding
energetics.
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