Quantum mechanics implementation in drug-design workflows: does it really help?

Abstract

The pharmaceutical industry is progressively operating in an era where development costs are constantly under pressure, higher percentages of drugs are demanded, and the drug-discovery process is a trial-and-error run. The profit that flows in with the discovery of new drugs has always been the motivation for the industry to keep up the pace and keep abreast with the endless demand for medicines. The process of finding a molecule that binds to the target protein using in silico tools has made computational chemistry a valuable tool in drug discovery in both academic research and pharmaceutical industry. However, the complexity of many protein–ligand interactions challenges the accuracy and efficiency of the commonly used empirical methods. The usefulness of quantum mechanics (QM) in drug–protein interaction cannot be overemphasized; however, this approach has little significance in some empirical methods. In this review, we discuss recent developments in, and application of, QM to medically relevant biomolecules. We critically discuss the different types of QM-based methods and their proposed application to incorporating them into drug-design and -discovery workflows while trying to answer a critical question: are QM-based methods of real help in drug-design and -discovery research and industry?

Insights from Incorporating Quantum Computing into Drug Design Workflows

“…al. 2012), improving QM/MM calculation in molecular docking (Arodola et. al., 2017), modeling with neural-network quantum states (Choo et.…”

Immunoinformatics and Computer-Aided Drug Design as New Approaches against Emerging and Re-Emerging Infectious Diseases

“…Quantum mechanics has been leading a valuable method for drug discovery through characterizing the structure, dynamics, and energies of protein-ligand interaction [66]. In the medicinal industry and academic research, it is an inevitable part of drug design that fixes the problem by calculating chemical reactivity and helps to optimize structure [67].…”

The importance of genotoxicity tests in new drug development process<p>Genotoksisite testlerinin yeni ilaç geliştirme sürecindeki önemi

“…İlacı kullanmakta olan geniş hasta topluluklarının söz konusu olduğu bu çalışmaların ana amacı, uzun süreli güvenlilik verilerinin toplanmasıdır. Ayrıca, ilacın maliyet-yarar-risk oranlarının analiz edilmesi, etkililiğinin daha geniş hasta gruplarında gösterilmesi, ilaca bağlı gelişen ve ender rastlanan advers reaksiyonların ve ilaç etkileşimlerinin belirlenmesi, ilaçla ilgili cevaplanmamış soruların cevaplanması ve aynı endikasyon için kullanılan ilaçlarla yeni ilacın karşılaştırılması da amaçlanır (İskit, 2006;Ciociola ve ark, 2014;Williams, 2016;Arodola 2017). Faz IV takibi sırasında ruhsat almış bir ilacın güvenlilik profilinde bir değişiklik bildirildiğinde risk değerlendirilir ve yönetilir.…”