Journal of Molecular Biology and Drug Design

Drug discovery and development is a process through which potential new therapeutic entities are discovered for the treatment of a particular disease by acting on its specific target. The conventional drug designing process includes identification of promising-lead by experimental high-throughput screening, but it is costly and lengthy. Despite the advent in biotechnology, drug discovery is still tremendously complex, unbelievably strenuous, and efficient process with a high attrition rate of new therapeutic discovery. The current drug discovery process involves the recognition of screening hits, medicinal chemistry characterizing the efficacy of the compound, its probable safety profile, and bioavailability. Drug design is an integrated developing discipline in which novel molecules are designed based on the knowledge of a biological target. Computer-Aided Drug Design (CADD), a in silico method of drug designing is cost-effective and it takes less time for a drug to reach the market. CADD methods can be broadly categorized into structure-based drug design and ligand-based drug design. The indirect approaches in drug design are applied whenever there is uncertainty regarding the active site and the model of the active site is built on the knowledge of biological molecules that bind to it. Some of the examples of these techniques are quantitative structure-activity relationship (QSAR), molecular similarity or diversity technique, and combinatorial chemistry. Direct approaches in drug discovery, also known as structure-based drug design, are used whenever the 3D structural information for the biological target is known such as X-ray crystallography, nuclear magnetic resonance (NMR), molecular modeling, synthetic organic chemistry, and biological assays. X-ray crystallography is a difficult task and it has made the largest contribution to understanding a protein structure. Information on proteins in solution can be determined by NMR. NMR spectroscopy directly observes chemical compounds and target biomolecules by building a model of the protein that shows the location of each atom. Quantum mechanics methods study reactions for biological systems consisting of hundreds of atoms. Automation and robotics in drug discovery are growing exponentially to implement high-throughput strategies. Artificial intelligence can be applied ubiquitously in various stages of drug development from target selection, hit identification, lead optimization through to preclinical studies, and clinical trials.

The Journal of Molecular Biology and Drug Design encourages innovative research and encompasses the two most significant multidisciplinary fields, molecular biology, and drug design. This is a scientific journal that strives to manage high standards in peer reviewing and it spans the study of drug design, discovery, and development throughout clinical applications. The journal covers research areas like genomics, proteomics, high-throughput genome sequencing, lipidomics, metabolomics, biocomputing, cytomics, and pharmacogenomics. It promotes the international exchange of new knowledge and by exploring the ideas of the scientific researchers on the most current topics of interest. The journal’s objective is to publish significant research on drug discovery that provides insight into the new and emerging progress and models within the scope of molecular biology and drug design.