HOs as in Harmonic Oscillator basis functions

Hi, everyone!

I’ve recently started working with metalloenzymes and am using ASH with OpenMM and ORCA 6.0 for QM/MM calculations at the PBE0/def-DZVP level of theory.

I’m currently investigating the decarboxylation step. When I perform a relaxed scan along the C–C bond distance, the bond breaks, but the calculated energy barrier is very high. The spin density also does not seem to redistribute as expected between the radical and the metal center along the reaction coordinate.

I have two questions:

Is ASH one of the most efficient freely available options for coupling OpenMM and ORCA in QM/MM calculations, particularly in terms of communication between the two programs?

Does anyone have suggestions for troubleshooting this issue? I’ve tried different spin states, but the same problem occurs in all of them.

Thanks in advance!

Hi, I am a undergrad chemistry major looking to pivot to computational chemistry. Based on my courses so far, I spent more time studying organic and physical chemistry thus much more versed in chem than math/cs. I only know Python (planning on learning C++) and math up to linear algebra. I'm trying to gauge whether it plausible to catch up in three semesters I have left. Are math classes like data/discrete structures essential? What courses would be most fundamental in learning in grad school? I'm also going to try to join a comp chem lab asap.

Dear colleagues,

I want to find out more about why it takes so much time to optimize (or run freq calculations) on metal containing compounds.

I have been running software for years but lack the knowledge of how optimization actually works and what makes it slower for metals.

Previously, I rely a lot on GPTs, but the answer just doesn't sit well with me.

Help of any kind in this direction that what structural optimization actually does and why it takes a lot of time for metals to optimize? The best one will be how to speed it up.

Thanks and regards

Dev

A month ago I shared Megane, a browser-based molecular viewer. I’ve now added a builder for making initial structures.

GUI builders I know follow fixed recipes or are commercial, and open-source tools for mixtures and polymers are scripts. I couldn’t find one that does both, so I made one (tell me if I missed it).

• Flow mode: wire blocks like SMILES, polymer chains, slabs, packmol boxes and solvation, then run
• Manual mode: fix any atom by hand, then save as XYZ / PDB / CIF / POSCAR
• Runs in the browser, Jupyter, VS Code, or your own app
• Add your own Python tools as MCP servers

No force field assignment yet. That’s next, likely by wrapping OpenFF / foyer / GAFF2. Which force field and engine would you want first?

Demo (no install): https://megane-labs.github.io/megane/app/builder.html
GitHub (MIT): https://github.com/megane-labs/megane

I hope this isn't inappropriate to ask here. I am a college student doing a docking project for my graduation and need an old version of MOE (molecular operating environment) 2012+ windows. I am a third worlder so the official version is incredibly expensive and inaccessible to me and my professor is demanding this particular site and wouldn't offer it to us so we are on our own.

I was trying Claude and found that it can inatall packages to run certain things like python and so on to give you answer, so I told Claude can you install Quantum Espresso in your server? And guess what? It did and done some calculations! That's really insane, I tested using Silicon structure and it did it.

I can't believe what I'm seeing here, is this normal thing? Or something we should be afraid of or what exactly?

Dear colleagues, I have a simple question: has anyone tried using a trackball to manipulate molecules in PyMOL, ChimeraX, or Avogadro? Is it worth buying one?

Hey everyone,

I recently built MolTalk, an open-source molecular visualization tool that was just accepted into the ChatGPT Plugin Marketplace.

The idea came from tutoring organic chemistry students who were using ChatGPT to understand molecular structures, only to get incorrect structures or stereochemical assignments.

MolTalk uses RDKit, OPSIN, and PubChem to validate structures rather than relying on the LLM's memory. It lets users interactively move between 2D and 3D representations, examine stereochemistry, and modify molecules through natural language.

It also supports exporting structures to ChemDraw (CDXML), SDF, MOL, PDB, and other formats.

It's free, open source, and currently under review for Claude as well.

I'd love to hear any feedback or suggestions!

GitHub: https://github.com/DomFico/moltalk

Demo: https://youtu.be/EZACxMWyzcs

i'm working for a platform called Vecura that bundles 200+ computational drug discovery tools behind a no-setup interface. I have personally tried their boltz 2.1, diffdock, RFdiffusion and gromacs (and other docking models as well). Full disclosure: I’m affiliated with them as a campus lead, so this is partly an event for them and a networking event as well.
I’m running a small in-person workshop and The idea is for people who have a project in mind but aren’t sure which workflow fits.

What we’ll do:

• Get a target-ligand pair (easy to hard) and plan a docking workflow, going beyond AutoDock Vina and comparing how other models score the same complex
• Work through guided pipelines (repurposing, virtual screening, synthetic feasibility, ADMET, DTI, or docking) chained from 3-4 simple tools
• Share results and talk honestly about what worked, what didn’t, and how the no-setup tools felt compared with running things locally

this is vecura's website- vecura.com/en

i hope i have new people from life sciences or even computer chem/ cheminformatics on board :))

Hi r/comp_chem!

I'm an independent developer building MolDesign, a free Windows desktop application that I hope to evolve into an integrated development environment (IDE) for early-stage drug discovery.

The objective is to bring computational methods, molecular preparation, visualization, and reproducible scientific workflows into one environment, rather than requiring researchers to manually coordinate multiple tools and scripts.

What MolDesign currently supports

• AutoDock Vina 1.2.7: Local docking execution without manually configuring Python, Conda, or command-line workflows.
• Molecular preparation: Import your own PDB/mmCIF receptor structures and prepare ligands from SMILES or a molecular editor.
• Experiment reproducibility: Preserve docking parameters, random seeds, grid boxes, receptor hashes, software versions, and warnings.
• Collaboration: Save and transfer docking execution records between researchers, allowing colleagues to inspect the computational setup and results.
• Molcy (shown in the video): Generate 3D animations from recorded docking search information, including molecular poses, search steps, and interactions.

All docking calculations run locally. Molcy uses Blender for rendering.

Where we're heading

The long-term objective is to make MolDesign modular, allowing researchers to use different computational methods within the same application.

We're exploring future integrations with additional local docking engines, API-accessible computational tools, and complementary approaches such as Boltz-2 for biomolecular complex and affinity prediction.

If development progresses successfully, we'd also like to incorporate molecular dynamics workflows.

Ultimately, we'd like researchers to prepare experiments, select computational methods, analyze results, and exchange reproducible research records within a unified Windows environment.

Scientific limitations and transparency

MolDesign currently uses AutoDock Vina's scoring and search algorithms. It does not claim improved predictive accuracy over Vina.

Docking scores are not experimental binding affinities, and the included receptor catalog is intended for exploration rather than representing experimentally validated docking protocols.

Molcy's animations visualize recorded docking search information. They are not molecular dynamics trajectories and should not be interpreted as physically realistic molecular motion.

The current application does not perform molecular dynamics, free energy perturbation, or experimental activity prediction.

Availability

MolDesign is completely free to download and use through the Microsoft Store. No subscription is required.

Its source code is available under a noncommercial license (source-available, not OSI-approved open source).

Microsoft Store:
https://apps.microsoft.com/detail/9N96SW3GBK8V

I'd particularly appreciate feedback from computational chemists:

• What are the most common reproducibility problems you encounter in docking workflows?
• Which engines or computational methods would be most valuable to integrate?
• Would portable experiment records and visualizations be useful when collaborating with other researchers?

I'm especially interested in constructive scientific criticism, including limitations in receptor preparation, docking protocols, and the interpretation of results.

Thanks for taking a look!

Web MolDesign

Dear colleague,

Have you come across any good lightweight molecule renderer for standalone GUI to make and interact with small and large molecules?

Pymol and Chimerax like but lighter and open-source

TL;DR: what are the key checks experienced RBFEers use to ensure their calculations are reliable and not just technically correct?

Hi all, I am a PhD student looking to run some RBFE calculations that will be used for further modelling.

I've been reading around free energy predictions and the factors influence their accuracy. I've also followed some tutorials from pmx and OpenFE tutorials. Leaning towards OpenFE as my engine.

I am trying to be very careful about how I approach RBFE because I worry about committing compute and getting ∆GG values that are 'technically' correct but inaccurate due to something that could have been caught with the right insight or diagnostic check.

I have a high resolution ligand bound structure to start from, and have seen some sanity checks from the tutorials, but suspect there are other important checks that may not be so obvious to someone doing it for the first time.

For anyone experienced with RBFE, are there any routine checks you do along the way to assess whether the calculations will be within a MD simulation-range of reliability? Are there certain failure modes or diagnostic checks you do at set up at each step?

edit: I plan to do a do RBFE on a chemical series that I have experimental values for before going rogue!

I'm optimizing the geometries of some highly reactive intermediates. In most cases, the intermediates (which are often generated experimentally via a photochemical reaction) are not stationary points themselves, but instead optimize to a stable product via an internal rearrangement. These rearrangements agree with what is observed to occur experimentally: a single rearranged product is observed, even in cases where competition might lead to alternative products.

In a few cases, however, optimization leads to a stationary point with a single imaginary frequency (i.e., a TS structure). Following the imaginary frequency via IRC leads to one of the experimentally observed rearranged products (the "product" is identical on either side of the IRC calculation due to symmetry). However, experimentally, in addition to the observed products predicted by this computational approach, a secondary product, resulting from rearrangement of another nearby bond, have been reported. When I analyze the positive frequencies of the aforementioned TS structure, I have located a frequency (~ 400 cm-1) that lead to these second products if the TS structure is deformed according to the frequency and further optimized. Any attempt to locate an additional TS that would lead to formation of the secondary products failed, however, suggesting that it is a near barrierless rearrangement process.

Because these second products could be formed via a simple molecular vibration, and the observed TSs are expected to be formed in a vibrationally "hot" state via photochemical generation, is it reasonable to expect competition of the two pathways and formation of both products?

Hi everyone, Currently I'm working with lipid systems. The system is coarse grained, but need to simulate in particular pH. I don't have experience with CpHMD either. I would like to know if anyone have used Titratable Martini force field for lipids? Or any suggestions for simulating large lipid systems in different pHs.

For context, I am trying to simulate a helical peptide with PEG attachment on the Cys residue. For the first time, I am trying to use cgenff but it fail miserably because the helical structure is changing completely. For another attempt, I try to manually patch cgenff on PEG part and the rest of peptide will be charmm36. But I don’t know why it also fails but a part of helical structure is still intact. Anyone has any idea to resolve it? Especially the S-PEG bonding, it’s hard to deal with it. Any tutorial I need to go through? I’m still undergrad student and this is my first time to deal with this problems. I mostly deal with unmodified structure so this is hard 🥲

Thanks in advance 🙏

Let's say I'm a bit tired from Comp Chem (to make it brief). I have around 10 years postdoc experience in the area and before I did my undergrad in Chemistry.

What options do you think are out there? Preferably not research related, maybe something like manufacturing in the Chemical Industry?

Asking for some guides here to point me in the right direction. Thanks

​

I've been working on a project called LAMMPS Web GUI, which lets you explore and run molecular dynamics simulations directly in your browser.

The idea is to make molecular simulation workflows more accessible, with features like:

- Browser-based simulations with WebGPU acceleration and CPU execution

- Interactive 3D molecular visualization

- Visual input-script building

- Trajectory playback and analysis

- Tools for exploring simulation results

I built this with some help from Claude by Anthropic, and I'm continuing to improve it.

Try it out:

- Live demo: https://shuvam-banerji-seal.github.io/lammps-web-gui/

- Demo video: https://youtu.be/bqGnbRRuwa8

- Source code: https://github.com/Shuvam-Banerji-Seal/lammps-web-gui

The project is open source, and I'm accepting issues and pull requests. If you're into molecular dynamics, computational chemistry, materials science, or scientific computing, I'd appreciate feedback and contributions.

Feel free to give the repository a star if you find it useful.

Hi everyone,

I am looking for a collaborator / co-author to evaluate and expand a highly unique, interdisciplinary project at the intersection of archaeometry, historical biochemistry, and computational chemistry. This research has been time-stamped and secured on Zenodo and holds strong potential for a scientific publication or even a PhD thesis.

The Hypothesis:

Bronze and copper cauldrons are an archaeological constant—they draw a continuous "red line" through human history. However, science has completely overlooked how these metallic vessels actively reacted with biological matrices in ancient ritual preparations.

Based on archaeological findings of ruminant blood residues in prehistoric cauldrons, my hypothesis is that boiling blood serum ex vivo inside a copper vessel created a unique macromolecular filtering system. The protein matrix of caprine serum albumin, combined with dissolved copper ions from the cauldron walls, likely acted as a reversible buffer for lethal alkaloid peaks (e.g., atropine, muscimol, scopolamine) from toxic plants. Essentially, it functioned as a crude, prehistoric sustained-release system to prevent toxic shock during rituals.

Current Progress & Preliminary Data:

A technical pilot blind-docking run was performed using AutoDock Vina on caprine serum albumin (PDB: 5ORI). The results look highly promising: the algorithm consistently identified a strong binding pocket in subdomain IIIB, with Atropine showing binding affinities around -6.4 to -6.8 kcal/mol.

What I need:

I am the author of the historical and conceptual framework, but I am not a computational chemist. I need an expert to help evaluate if these Vina scores are physically plausible or artifacts of rigid docking. More importantly, I want to set up proper Molecular Dynamics simulations (e.g., GROMACS at elevated temperatures like 333 K) and model the specific copper-protein interactions (ATCUN motif) to see how the "building" of the protein reacts to the metal.

If you are interested in a fresh, unmapped field of historical biochemistry with a guaranteed preprint/Zenodo foundation, please send me a Message. I can share the full docking report and raw files.

Thanks in advance.

Michael from Germany

Hey guys , Iam Karthik from India . Iam a bsc ( ug) student . Planning for Computational chemistry. I have zero knowledge in coding stuff , Is their any one who could help me by providing a roadmap for Computational chemistry , including all the skills from scratch to advanced . Also suggest a me a good laptop

NOTE: Iam from non maths background.

hi, I posted a video with the latest updates to my Julia molecular dynamics package. there is also a link to the GitHub repo. If someone wants to try it, and tell me the bugs and limitations they find I will be grateful. All comments and critiques are welcome!

https://youtu.be/SwXXO7a-9Z8