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Drug Discovery: Overview01:26

Drug Discovery: Overview

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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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Preclinical development consists of a series of tests that ensure the safety and efficacy of a new therapeutic compound before it is tested in humans. There are four main phases to this process. First, safety pharmacology tests are conducted to ensure the drug does not produce any acutely harmful effects. These tests examine parameters such as bronchoconstriction, cardiac dysrhythmias, blood pressure changes, and ataxia. Next, preliminary toxicological testing is performed to determine the...
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The receptor occupancy theory connects a drug's response to the number of occupied receptors. With higher drug concentrations, more receptors are occupied, leading to increased responses. The formation of drug-receptor complexes involves association and dissociation rates, which reach equilibrium when the forward and backward reactions are equal. The equilibrium association constant (Ka) and its inverse, the equilibrium dissociation constant (Kd), indicate drug affinity. Higher Ka and lower...
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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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The Quantum-Mechanical Model of an Atom02:45

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Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra.
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Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
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Updated: Jul 16, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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The Future of Drug Development with Quantum Computing.

Bhushan Bonde1,2, Pratik Patil3,4, Bhaskar Choubey4,5

  • 1Evotec (UK) Ltd., Oxfordshire, UK. bhushan.bonde@evotec.com.

Methods in Molecular Biology (Clifton, N.J.)
|September 13, 2023
PubMed
Summary
This summary is machine-generated.

Quantum computing (QC) is revolutionizing drug discovery by accelerating complex processes. This technology offers new solutions for challenges like protein folding and molecular docking, significantly reducing development time and costs.

Keywords:
Drug developmentDrug discoveryHybrid computeNoisy intermediate-scale quantum (NISQ) eraProtein foldingQuantum computingVariational quantum eigensolver (VQE)

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Area of Science:

  • Computational chemistry
  • Quantum computing applications
  • Drug discovery and development

Background:

  • Traditional drug development is lengthy and costly.
  • Advancements in computational models, including AI and machine learning, are accelerating research.
  • Quantum computing (QC) presents a transformative approach to pharmaceutical research.

Conclusions:

  • Quantum computing offers significant opportunities to overcome drug discovery hurdles.
  • Current NISQ-era methods provide practical applications despite limitations.
  • The QC landscape presents both challenges and promising avenues for future pharmaceutical innovation.