Computational and Synthetic Approaches of Drug Discovery in Cancer and Neurological Disorders

Dear Colleagues,

Cancer is one of the world's most miserable diseases; while advances in molecular and cellular biology have resulted in a decrease in cancer-related mortality, drug discovery and cancer development are time-consuming and costly processes. In the past few years, there have been constant improvements in the research and development of new anticancer drugs. Several compounds including small molecules, antibodies, and immunomodulators have been approved to treat cancer. Despite significant advances in the field of drug discovery of anti-cancer agents, there is still a considerable need for novel and improved drug therapies in combination with conventional techniques. With numerous studies reporting significant results in the treatment of various types of cancer, computational and synthetic approaches are  among the most promising fields of drug discovery research.

Neurodegenerative diseases are multifactorial debilitating disorders of the central nervous system (CNS) affecting 30 million people around the globe. Neurological disorders, such as Alzheimer’s (AD), Parkinson’s (PD), Huntington’s diseases (HD), amyotrophic lateral sclerosis (ALS), and epilepsy comprise a group of neuropathologies characterized by specific etiologies with distinct morphological and pathophysiological features of the involved targets. In this Special Issue, we gather more recent information to understand the structure–function relationship of potential CNS modulator ligands that will advance the understanding of many aspects of brain function at the molecular, cellular, and systems level, in order to provide new treatment modalities. Moreover, taking stock of these target selective compounds reminds us that the future is bright, and that the persistent, thoughtful, creative, and collaborative efforts stand an excellent chance of solving the most stubborn and intractable neurological problems.

Currently, in silico approaches are an essential part of the drug discovery process, primarily because they can accelerate the entire drug development pathway by finding and discovering new prospective therapeutics with significant savings in terms of cost and time. Furthermore, computer-aided drug design (CADD) benefits from the use of artificial intelligence (AI) approaches at many stages of the drug development pipeline. Computational approaches, such as  structure-based drug designing, ligand-based drug designing, and combined structure-based and ligand-based approaches can be used at different levels for target identification or lead discovery, representing a key resource for medicinal scientists to foster the optimization of small molecules.

For this Special issue, we invite researchers to submit their original research articles, short communications, and review articles addressing the use of CADD in the design and optimization of small molecules for the treatment of cancer and neurological disorders. We urge the submission of purely in silico studies, as well as computational studies with experimental validations.

Dr. Deepak K. Lokwani
Dr. Aniket P. Sarkate
Dr. Vinod G. Ugale
Guest Editors

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