Abstract

Studying disease models at the molecular level is vital for drug development in order to improve treatment and prevent a wide range of human pathologies. Microbial infections are still a major challenge because pathogens rapidly and continually evolve developing drug resistance. Cancer cells also change genetically, and current therapeutic techniques may be (or may become) ineffective in many cases. The pathology of many neurological diseases remains an enigma, and the exact etiology and underlying mechanisms are still largely unknown. Viral infections spread and develop much more quickly than does the corresponding research needed to prevent and combat these infections; the present and most relevant outbreak of SARS-CoV-2, which originated in Wuhan, China, illustrates the critical and immediate need to improve drug design and development techniques. Modern day drug discovery is a time-consuming, expensive process. Each new drug takes in excess of 10 years to develop and costs on average more than a billion US dollars. This demonstrates the need of a complete redesign or novel strategies. Nuclear Magnetic Resonance (NMR) has played a critical role in drug discovery ever since its introduction several decades ago. In just three decades, NMR has become a “gold standard” platform technology in medical and pharmacology studies. In this review, we present the major applications of NMR spectroscopy in medical drug discovery and development. The basic concepts, theories, and applications of the most commonly used NMR techniques are presented. We also summarize the advantages and limitations of the primary NMR methods in drug development.

Highlights

  • The unexpected SARS-CoV-2/COVID-19 outbreak, with over 34 million confirmed cases globally (Oct. 2020) and the struggle for survival in the absence of a proven and efficient treatments, emphasizesMolecules 2020, 25, 4597; doi:10.3390/molecules25204597 www.mdpi.com/journal/molecules emphasizes the critical need to develop effective, novel, and rapid drug discovery methodologies

  • In the following subsections we briefly describe Nuclear Magnetic Resonance (NMR) methods that have been used in drug design, and discuss how NMR principles are used in drug discovery research

  • This study demonstrated that NMR can be an effective validation tool for known drugs and for new drugs generated by a screening approach

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Summary

Introduction

Molecules 2020, 25, 4597; doi:10.3390/molecules25204597 www.mdpi.com/journal/molecules emphasizes the critical need to develop effective, novel, and rapid drug discovery methodologies. The typical development cost is usually spread out over the course of 14 years [1,2,3], making investment even mMoorleecduliefsfi2c0u20lt, 2(i5.,e4.5c9o7st recovery delay). This high investment barrier for drug development is a resu2ltof 63 of numerous testing phases (Scheme 1), with each phase requiring a statistically significant number ofthceascersi.tiAcaltlhnoeuegdhtothdereevealroepseevffeercatlivoet,hnerovsuelb,satnandtiraalpciodsdtsrutogddriusgcodveevreylompemtheondt,otlhoagtiedsi.scEuvsesniotnhoofugh exthpeerpimhaernmtaal cmeuetthicoadlsintoduresdtruycewcoorsktss icsobnesytaonntdlythteo sdciospceovoefrthainsdredveievwel.op novel drugs, the process is stillTshloewemanerdgeenxpceenosfiavep.aTnhdeemcoisctaonfdintthreodeumceinrggeancnieews itdcrruegatheasswinocrrldeawseiddesutenaddeirlyst,awnidthabcluyrdrernivtecost anedstimmoattievsapteretdhiectirnagpitdhadteavfeulotuprme ednrtuganwdi/lolrcoospttiinmeizxacetisosnofof$2d.6rubgilsl.ioHno. wTheevetry,ppicaatliednetvsealofeptmy eanntdcost suisbsuesquuaellnytseparrenaeddopuutbolvicertrtuhsetciosuarsperiomf a1r4yyreeaqrus i[r1e–m3]e,nmt.aDkirnuggirnevdeisrtemcteinngt /erveepnurmpoorseindgiffi(Sccuhletm(i.ee.1,)cost israencoevffeicryiendteslahyo)r.t-Tcuhitsmheitghhoidnivnedstimseeanset tbraerartimerenfotrthdartuugtidliezveesleoxpismtienngttiosoalsr,easnudltcoomf nbuinmeesraorutisfitceiaslting inptehlalisgeesn(cSec,hmemacehi1n)e, wleiathrneinacghaplghoarsiethrmeqsu, iarnindgeaxpsteartimisteincatalllyNsiMgnRifiteccahnnt inquumesb(eir.eo. Numerical data were reported from Meigs et al [3]

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