Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Molecular Models

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.

Molecular Orbital Theory I

Molecular Orbital Theory I

Overview of Molecular Orbital Theory

Predicting Molecular Geometry

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries

Hybridization of Atomic Orbitals I

Hybridization of Atomic Orbitals I

The mathematical expression known as the wave function, ψ, contains information about each orbital and the wavelike properties of electrons in an isolated atom. When atoms are bound together in a molecule, the wave functions combine to produce new mathematical descriptions that have different shapes. This process of combining the wave functions for atomic orbitals is called hybridization and is mathematically accomplished by the linear combination of atomic orbitals. The new orbitals that...

MO Theory and Covalent Bonding

MO Theory and Covalent Bonding

The molecular orbital theory describes the distribution of electrons in molecules in a manner similar to the distribution of electrons in atomic orbitals. The region of space in which a valence electron in a molecule is likely to be found is called a molecular orbital. Mathematically, the linear combination of atomic orbitals (LCAO) generates molecular orbitals. Combinations of in-phase atomic orbital wave functions result in regions with a high probability of electron density, while...

Hybridization of Atomic Orbitals II

Hybridization of Atomic Orbitals II

sp3d and sp3d 2 Hybridization

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A deep learning-based classification method for subclinical zonular laxity in AS-OCT images.

Frontiers in cell and developmental biology·2026

Same author

Achieving 1.0-s Thermally Activated Delayed Fluorescence via Synergistic Control of Reverse Intersystem Crossing and Exciton Cycling.

Angewandte Chemie (International ed. in English)·2026

Same author

Differences in hepatocyte-related indicators within occupational hazardous factor exposure between genders.

Frontiers in public health·2026

Same author

A High-Affinity Antibody for Rapid Screening of PFAS: Breaking Immunological Inertness through Descriptor-Guided Hapten Design.

Analytical chemistry·2026

Same author

Multiferroic-Centric Materials and Systems Engineering for Battery Applications: An Insight Into Mechanisms, Strategies, and Characterizations.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Same author

Investigating magnetostatics of Fe-Ni nanosphere assemblies by electron holography and micromagnetic simulations.

Nanoscale·2026

Same journal

Complementing Onsager's Conductivity Theory by Grotthuss Mechanism Mitigation via Ion-Induced Depletion of Hydrogen-Bond-Donating Water.

Journal of chemical theory and computation·2026

Same journal

Microscopic Stress in Biomembranes: A Perspective on Key Concepts, Methods, and Applications.

Journal of chemical theory and computation·2026

Same journal

Analytic Nuclear Gradients Including Oriented External Electric Fields in a Molecule-Fixed Frame.

Journal of chemical theory and computation·2026

Same journal

Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model.

Journal of chemical theory and computation·2026

Same journal

Generalizable Protein Folding Pathway Exploration with DA2-GRASP: Extending Beyond Miniproteins.

Journal of chemical theory and computation·2026

Same journal

Improving PCM in Protic Media: Markov State Models for TD-DFT Calculations.

Journal of chemical theory and computation·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 8, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

Encoding Molecular Docking for Quantum Computers.

Jinyin Zha^1,2, Jiaqi Su¹, Tiange Li¹

¹Beijing QBoson Quantum Technology Co., Ltd., Beijing 100015, China.

Journal of Chemical Theory and Computation

|December 13, 2023

Summary

This summary is machine-generated.

Quantum computing accelerates molecular docking for drug discovery. New methods, Grid Point Matching (GPM) and Feature Atom Matching (FAM), encode docking problems for quantum solvers, enabling faster virtual screening of small molecules and peptides.

More Related Videos

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

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

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

Published on: September 8, 2023

Related Experiment Videos

Last Updated: Jul 8, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

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

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

Published on: September 8, 2023

Area of Science:

Computational chemistry
Quantum computing applications
Drug discovery and development

Background:

Molecular docking is a crucial but computationally intensive technique in drug discovery.
Classical computers face limitations in handling the extensive search space required for accurate molecular docking.
Accelerating molecular docking is essential for efficient virtual drug screening.

Purpose of the Study:

To develop novel computational methods for accelerating molecular docking.
To leverage quantum computing for solving molecular docking problems.
To enhance the efficiency of virtual screening for drug discovery.

Main Methods:

Introduction of Grid Point Matching (GPM) and Feature Atom Matching (FAM) algorithms.
Encoding molecular docking as Quadratic Unconstrained Binary Optimization (QUBO) models.
Utilizing quantum computers, specifically the coherent Ising machine (CIM), for solving QUBO models.

Main Results:

Grid Point Matching (GPM) demonstrated sampling power comparable to established methods like Glide SP.
The proposed methods are estimated to be 1000 times faster on a coherent Ising machine (CIM) compared to classical computers.
Successful encoding of molecular docking into QUBO models for quantum computation.

Conclusions:

The developed GPM and FAM methods offer a significant speedup for molecular docking using quantum computers.
These quantum-accelerated approaches have the potential to revolutionize virtual drug screening for small molecules and peptides.
This work paves the way for more efficient and scalable drug discovery pipelines.