Cleveland-IBM quantum computer drug design is full of lies.

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Quantum mechanics is useless

Quantum mechanics, which cannot solve its Schrödinger equations nor predict any multi-electron molecular behavior, is useless in drug design, whether (impractical) quantum computers or classical computers are used, contrary to hypes.

(Fig.1)  Cleveland-IBM's deceptive hybrid computer relies on empirical protein potential energy and a classical computer optimizing energy with No quantum mechanical prediction nor quantum computation nor quantum advantage.

Fake quantum computer advantage in drugs.

Cleveland, IBM quantum computer predicting drug molecules is fake, heavily relying on a classical computer and empirical (= determined by experiments, Not by a quantum mechanical theory ) potential energy irrelevant to quantum mechanical prediction.

The recent news on Cleveland clinic using IBM quantum computers outperforming classical computers in predicting some protein fragments is fake.

↑ They just chose different classical and empirical methods for predicting some short protein fragments (= Not predicted by quantum mechanics or computer ) as a deceptive hybrid quantum computing method (= just classical computer ) compared with another classical method (= which was unfairly forced to use worse empirical potential enregy ) to claim fake quantum advantage.

Quantum mechanics cannot solve Schrödinger equations nor predict energies of any multi-electron atoms nor molecules ( this-9th-paragraph ), much less design drug molecules.

Today's impractical error-prone quantum computers cannot even factor the simplest 21, let alone drug design or quantum advantage, contrary to the overhyped fake news ↓

Cleveland clinic, IBM used a deceptive hybrid quantum-classical computer method called quantum variational eigensolver (= VQE ) which just relies on artificial empirical potential energy and a classical computer optimizing energy irrelevant to quantum mechanics or quantum computer, contrary to their overhyped fake news.

↑ This recent fake news on Cleveland-IBM quantum drug design (2026) ↓

2nd-paragraph says  -- Useless quantum mechanics
"One of the main challenges of drug design is the complex calculations required to predict ( = false. Quantum mechanics can Not predict anything ) how minute changes in molecules and proteins will affect a drug’s effectiveness. These calculations are so complex that even the most powerful supercomputers have difficulty completing them (= today's mainstream quantum mechanics is proven useless ). "

4th paragraph says  -- Overhyped quantum advantage
"Quantum computing is a new method of computing that is faster and more powerful than even the most advanced supercomputer"  ← Overhyped fake news ( this-lower-Challenges ).

9th-paragraph-1 says  -- Deceptive hybrid computer
"Variational Quantum Eigensolver (VQE)... is a hybrid method that combines the power of a quantum computer with the accuracy of a classical computer (= actually just a classical computer ).

9th-paragraph-2 says  -- Classical computer needed
First, the researchers used IBM Quantum System One on Cleveland Clinic's main campus to predict all the possible shapes of the protein (= total lie ). Then, investigators used a classical computer (= optimizer ) to cut the results down to shapes with low energy. This process is repeated until only the lowest energy fragments are left (= this quantum method VQE is useless, this-middle )."

11th-paragraph says  -- Fake quantum advantage
"This method was able to predict (= false, quantum mechanics or computers can not predict anything ) the structures of 23 protein fragments (= Not proteins but just very short amino acids ) and seven real-world drug targets. For these tests, it was also able to outperform current classical computing methods (= total lie, again ), including AlphaFold3 (= useless ), in accuracy and drug binding"

3rd-last-paragraph says  -- Useless quantum computer after all
"Though quantum computing holds the potential to solve some of healthcare’s toughest challenges, this computing method is still in its early stages (= still useless quantum computing )"

This misleading Cleveland-IBM research used only a classical computer with empirically-obtained potential energy to get some amino acids' structures, and their error-prone quantum computer and quantum mechanics were useless, did nothing.

In this Cleveland-IBM quantum computing research, they tried to predict structures and energies of some very short amino acids by a deceptive hybrid quantum-classical method called variational quantum eigensolver (= VQE using a classical computer for optimizing energy parameters θ and finding the stable amino acids' structures ) based on empirically-obtained artificial peptide potential energy called Miyazawa–Jernigan interaction irrelevant to quantum mechanics.

This research relies on an empirical protein potential energy and a classical computer as the deceptive hybrid-quantum-classical method.  Quantum mechanics or computers cannot predict any proteins nor drugs.

This Cleveland's paper-p.3-3rd-paragraph-(5) says  -- No quantum mechanics
"This sequence is first modeled using the Miyazawa–Jernigan interaction (= empirical potential irrelevant to quantum mechanics, this-abstract-middle ).....
hybrid Variational Quantum Eigensolver (VQE) is then executed, combining quantum sampling with a classical optimizer (= classical computer was needed to get the optimal amino acids' structures with the lowest energy ) running locally. The optimization loop in the VQE continues iterating until the minimum energy is found"

This-p.1-right-1st-paragraph says  -- Empirical potential, No quantum
"Protein molecules... Miyazawa– Jernigan (MJ) potential. MJ potentials are empirically derived ( this-p.2-last-paragraph,  this-p.2-right-1st-paragraph )"  ← Not predicted by quantum mechanics

Using two different empirical potential energies caused fake quantum advantage.

This Cleveland research just compared two different classical (or empirical ) methods (= a better empirical one was used for deceptive hybrid-quantum-classical method, the other worse empirical one was unfairly used for a classical method ) to claim fake (hybrid) quantum advantage.

This Cleveland research unfairly used two different classical or empirical methods in the deceptive hybrid-quantum-classical method (= using better empirical Miyazawa-Jernigan potential energy and the classical computer's optimizer ) and another classical method (= using deliberately-chosen worse empirical force field potential ) to claim fake (hybrid) quantum computer's advantage (= ← So this research is just about comparison between two different empirical methods, Not quantum vs. classical methods' comparison, so No quantum advantage nor quantum mechanical prediction, contrary to the above fake news ).

↑ The final amino acids' structures were determined only by the empirical protein Miyazawa-Jernigan (= MJ ) potential and the classical computer optimizing or finding the most stable structures with No quantum mechanical prediction.

The useless IBM quantum computer, which did Not compute or determine the amino acids' structures, was used just to measure qubits changed by the classical computer's optimizer ( this-2., 3. ) with No quantum mechanical prediction nor quantum advantage.

This research used just empirical potential energy and a classical computer to find the stable amino acids' structures with No quantum advantage nor quantum mechanical prediction.

↑ This hyped research paper ( this-3rd-paragraph-link ) for drug design, this ↓

p.2-introduction-1st-paragraph-1 says  -- Today's physics failed
"Traditional physics-based methods, such as molecular dynamics (MD), can in principle sample native-like structures but suffer from prohibitive computational costs and scalability issues"  ← Traditional physics or unrealistic quantum mechanics failed to predict proteins.

p.2-introduction-1st-paragraph-2 says  -- AI, Alphafold failed
"AlphaFold2 and AlphaFold3,... However, their performance substantially deteriorates when applied to short peptide fragments or highly flexible local domains, where limited sequence context and sparse evolutionary information lead to structural ambiguities and reduced accuracy (= useless Alphafold or today's AI )"

p.3-3rd-paragraph-(1) says  -- Empirical potential, No quantum
"Sequence-based quantum modeling, where the input amino acid sequence is used to construct a quantum formulation of the structural problem, incorporating Miyazawa–Jernigan interactions (= empirical potential Not predicted by quantum mechanics nor computer,  this-p.1-right-1st-paragraph ) and additional geometric constraints,"

p.3-3rd-paragraph-(3) says  -- Classical computer needed
"Hybrid variational optimization, in which the Qiskit Runtime middleware orchestrates VQE execution across quantum and classical resources (= classical computer optimizing energy and structures was needed ), iteratively updating circuit parameters to minimize system energy"

p.3-3rd-paragraph-(5) says  -- Empirical, classical computer
"the framework takes an amino acid sequence represented as a string as input. This sequence is first modeled using the ( empirical ) Miyazawa–Jernigan interaction along with additional structural constraints."
"hybrid Variational Quantum Eigensolver (VQE) is then executed, combining quantum sampling with a classical optimizer running locally"

p.7-Table 1 shows  -- Fake quantum computer, No proteins
This research used only less than 102 qubits (= one qubit can take only 0 or 1 value, so still Not a quantum computer ) for calculating energy of very short (~ 14 ) amino acids, Not proteins

p.8-upper says  -- No drug discovery
"Although solving a complete drug discovery pipeline with the current framework remains challenging, "

p.11-top says  -- Fake quantum advantage
"the overall ranking of RMSD performance (= expressing how exact structures were predicted, the lower RMSD is better ) follows: Quantum < AF3 < Classical, confirming the progressive improvement from classical to quantum methods (← No.  This research treated the empirical and classical methods as deceptive hybrid quantum methods )"

p.14-2nd-paragraph says  -- Useless hybrid quantum VQE
"Consequently, noise accumulation becomes more pronounced, which can slow (hybrid quantum) VQE convergence, trap the system in local minima, or shift the estimated energy away from its true value, all of which undermine the accuracy of the protein backbone conformation"

p.16-~p.17  -- Hamiltonian energy, No quantum
Creating artificial amino-acids' Hamiltonian (= H = total ) energy using qubits constrained by many freely-adjustable (= empirically-determined ) parameters with No quantum mechanical prediction

This research unfairly used worse empirical (force field) potential energy for a classical computer method to claim fake (hybrid) quantum computer's advantage.

This same paper-p.28-Classical baseline pipeline (= classical method ) says
"for each peptide sequence, an initial 3D conformation was constructed using PeptideBuilder, which sequentially connects amino acid residues into an extended backbone model without prior structural bias.... comparability with the quantum-generated outputs. Finally, we performed potential energy minimization using OpenMM with the Amber14 force field (= another different artificial empirical potential that gives different inconsistent results, this-p.2-3rd-paragraph )"

↑ So this research's classical computer's method was unfairly forced to use worse empirical force-field potential energy (+ cheap peptidebuilder ) than the better empirical Miyazawa-Jenigan potential energy used for the deceptive hybrid-quantum-classical method to claim fake (hybrid) quantum advantage, which is Not a true quantum advantage based on better quantum computers.

Because to claim true quantum computer's advantage, they have to use the same empirical protein potential energy, which is Not the case in this research .

Fake quantum computer advantage caused by choosing different empirical methods.

This Cleveland's fake quantum computer advantage is caused by using different empirical (or classical ) methods in the deceptive hybrid-quantum-classical method (= using better empirical potential energy ) and the classical method (= using worse empirical potential ), irrelevant to better quantum computer or mechanics.

↑ Instead of comparing a purely quantum and a classical method, this research just compared the fake (hybrid) quantum method (= using the better empirical Miyazawa-Jenigan peptide potential and a classical computer's VQE optimizer ) and the classical computer's method using another worse empirical Amber force field potential compatible with quantum output (= which often failed,  this-p.3, despite using quantum mechanics ).

↑ This Cleveland-IBM's fake (hybrid) quantum computer's advantage is caused by using different empirical (or classical ) methods (= the empirical potential energy used for the hybrid-quantum-classical method is better than the empirical potential used for a classical computer's method ), Not by the better quantum computer nor quantum mechanics.

Quantum mechanics cannot predict anything.

Quantum mechanics, which cannot solve its Schrödinger equation nor predict any multi-electron atomic behavior, is impractical and too time-consuming to choose fake trial wavefunctions out of infinite candidates.

Quantum mechanics is useless, cannot solve its Schrödinger equation nor predict energies of any multi-electron atoms nor molecules.

All the quantum mechanical approximate methods such as variational methods, Hartree-Fock, configuration interaction (= CI ), DFT treating the whole molecules as one fake electron model are impractical, too time-consuming, unable to predict anything ( this-(9.80),   this-p.2-p.3,  this-p.5 ).

Because all these quantum mechanical approximations just artificially choose fake trial wavefunctions (= basis sets ) and pseudo-potentials out of infinite candidates and infinite free parameters ( this-4~5th-paragraphs ), which takes infinite time, impractical ( this-1.4 ) and proven wrong.

Unreal quantum mechanics hampers technology.

It is far better to use experimental values from the beginning than to waste too much time in meaningless quantum mechanics that cannot predict anything. But quantum mechanics prevents us from using experimentally-observed real atomic shape, and hampers technology.

It is far better to use experimental values such as each atomic shape and properties than to waste too much time in the meaningless time-consuming quantum mechanics that cannot predict anything.

But the unrealistic quantum mechanics prevents each atom or molecule from having its shape, which hampers developing useful multi-probe atomic force microscopes (= deadend now ) manipulating atoms or clarifying proteins structures.

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