Drug Design: Where We Are and Future Prospects

Abstract

Medicinal chemistry is facing new challenges in approaching precision medicine. Several powerful new tools or improvements of already used tools are now available to medicinal chemists to help in the process of drug discovery, from a hit molecule to a clinically used drug. Among the new tools, the possibility of considering folding intermediates or the catalytic process of a protein as a target for discovering new hits has emerged. In addition, machine learning is a new valuable approach helping medicinal chemists to discover new hits. Other abilities, ranging from the better understanding of the time evolution of biochemical processes to the comprehension of the biological meaning of the data originated from genetic analyses, are on their way to progress further in the drug discovery field toward improved patient care. In this sense, the new approaches to the delivery of drugs targeted to the central nervous system, together with the advancements in understanding the metabolic pathways for a growing number of drugs and relating them to the genetic characteristics of patients, constitute important progress in the field.

Towards Integrated Bio Design-Related and Translational Platforms to Determine Co-Development for Adaptation of Innovative Biotechnologies and to Predict and to Prognosticate the Future of the Healthcare and Life Science Bioindustry

“…Meanwhile, engineering biology and Bio design present a suite of opportunities to solve the problems people and the planet face, now and tomorrow. As well as bringing cheaper, greener, and customdesigned products to market, engineering biology can dramatically transform the processes that underpin existing industries, such as helping to lessen the impacts fossil fuels have while they are still an embedded component of our lives [6]. Engineering biology and Bio design are addressed along with stakeholders and policymakers, to practitioners, encouraging greater collaboration between different disciplines and industries that can achieve vastly more together, building on the precedent set by the private Biomanufacturing and government's Bioeconomy strategy.…”

Machine learning‐assisted search for novel coagulants: When machine learning can be efficient even if data availability is low

“…During the last decade, we witness a wave of ML‐powered approaches in biochemical domain (see, for example, References 4–10). There are a few favoring factors here: (i) successes of ML in other areas, like computer vision, autonomous driving, natural language processing, (ii) growing availability of data, (iii) complex problems can be solved in a data‐driven manner (in particular, artificial neural networks are often referred as “universal approximators”).…”

From a Molecule to a Drug: Chemical Features Enhancing Pharmacological Potential

“…Everaldo F. Krake and Wolfgang Baumann used NMR to investigate the reactivity of clopidogrel towards reactive halogen species [8]. Giuseppe Zagotto and Marco Bortoli provided a perspective on the evolution of medicinal chemistry, which nowadays faces novel challenges in the context of precision medicine and advanced drug delivery [9]. This aspect was also approached by Karolina Wanat and El żbieta Brzezi ńska, who studied the effects of protein binding on drug bioavailability by means of statistical methods related to molecular and chromatographic descriptors [10], and by Tsun-Thai Chai and colleagues, who predicted pharmacokinetic and pharmacodynamic properties of seafood paramyosins peptides though computational tools [11].…”