Hi everyone! I’m a 20-year-old chemistry student. I’m passionate about programming and the world of computers (I’m a total nerd).

In my search for disciplines that combine both things, I discovered bioinformatics a while back and was interested in it as a career, but I’ve read in various places—including outside of Reddit—that the demand in the field doesn't match the supply of graduates.

Then I discovered chemoinformatics, which honestly sounds really interesting, especially regarding analytical and organic chemistry (I love organic chemistry).

Is this field oversaturated too? Is there real demand? And if there are opportunities, where are they and how can I get into that world?

Hey everyone,

I’m working on a small in-silico project and would appreciate some opinions from people with more experience with molecular docking.

I designed a novel compound against an enzyme target and compared it with a known inhibitor of the same target. The docking scores were:

Reference inhibitor: -10.05 kcal/mol

My compound: -8.57 kcal/mol

So there's about a 1.5 kcal/mol difference in favor of the reference.

The reference and my compound are structurally different, and my compound doesn't reproduce all of the same interactions as the reference. Instead, it adopts a different binding orientation while still making several interactions with residues in the binding site, including hydrogen bonds, hydrophobic contacts and π-interactions.

The reference was mainly used as a benchmark against a known inhibitor, rather than as a template that my compound was expected to reproduce exactly.

This is where I'm unsure how much importance to give the docking score.

1. Would you consider a ~1.5 kcal/mol difference significant enough to conclude that the novel compound is unlikely to be competitive, or is that too strong a conclusion from docking scores alone?

2. If two compounds have different scaffolds and binding modes, how meaningful is it to compare their docking scores directly?

3. If the novel compound has a weaker score but a plausible binding mode involving relevant residues, would you consider it reasonable to describe it as a potential alternative scaffold, rather than claiming superior binding?

I'm trying to present the result fairly. I don't want to pretend that -8.57 is better than -10.05, but I also don't want to discard the compound just because its docking score is lower.

I built webgpu-q — an electronic-structure stack that runs entirely client-side in a browser tab: RHF/UHF, DFT (LDA/GGA/hybrids), MP2, CCSD, CCSD(T), EOM-CCSD (EE/IP/EA), geometry optimization, frequencies/IR/Raman, TDA/TDDFT spectra, polarizabilities. TypeScript + Rust/WASM, with some kernels on WebGPU.

Validation is the part I'd want to see first, so: every method is cross-checked against PySCF (and FCI where feasible) in CI — agreement gates run on every commit, and the reference comparisons are in the repo, not in my claims. Where the browser loses, that's documented too: WebGPU has no f64, so f32 GPU paths are validated against the exact f64 CPU/WASM path, and the GPU hybrid we measured as not-worth-it got demoted to opt-in. It is not a PySCF competitor at production basis sets — that boundary is measured and committed (LIMITATIONS.md), not hand-waved.

What it's actually for: teaching and quick checks. Every calculation is a shareable URL — molecule, method, basis in the link — so a student can open a full CCSD(T)/cc-pVDZ water calculation with one click, no install, no cluster account. There's also a distributed mode: open the page in more tabs and they form a swarm — one tab dispatches HF tiles, the others compute and report back.

Free, MIT: https://webgpu-q.vercel.app · https://github.com/abgnydn/webgpu-q

Hi all,

I'm looking to use GROMACS to perform a molecular dynamics simulation of a poly beta amino ester (PBAE) polymer assembling with its mRNA cargo in order to obtain values like radius of gyration and hydrophobic and hydrophilic surface area.

I know that GROMACS requires a .pdb file to start with, but how could I get that for a PBAE polymer? I'm also not sure how to go about doing this in GROMACS (I'm pretty new to molecular dynamics simulations) so any guidance would be helpful!

Hello everyone!

I am a postdoctoral student in Hungary and did my PhD in bioinformatics/cheminformatics, namely (mostly) in molecular dynamics of proteins. Around this time I read some articles about metadynamics as a tool to explore the free energy surface of certain processes, including small ligand binding to proteins, conformational changes or peptide-peptide association, etc... This kind of approach also gave me insights in statistical thermodynamics, while also keeping the fun-factor high and staying intuitive. I did not start to apply it until recently however, which makes me a novice in setting the right parameters, collective variables, for the right processes. I try to read research papers in this topic, but to challenge myself, I also wanted to make something new.

I started using the ASE/RDKit/OpenFF combo recently for the extraction of offxml parametrizations to standard GROMACS top/itp files. While doing this, I noticed that (afaik) there are no metadynamics extensions for ASE besides PLUMED. Since I am also somewhat familiar with PyTorch (and not really familiar with PLUMED), I figured I should create a package that uses PyTorch's autodiff modality for the implementation of metadynamics in ASE. So I created MePTASE (Metadynamics with PyTorch in the Atomic Simulation Environment), a small, still under development Python package, available from PyPI using pip install meptase[tblite] or pip install meptase[mace] (depending on the "force field" you want to use). You can use it within Python or from the CLI using JSON config files. I would appreciate any feedback you guys can give me, either regarding code quality, ease of use, possible extensions or anything else. I am especially proud of the CLI/JSON run option, which allows users to run simulations without writing Python code. You can also run well tempered metadynamics, but I have to test this feature more thoroughly.

Here is my repo: https://github.com/fazekaszs/meptase/tree/master

I know that there is some hate for AI assisted coding in this community. I love coding, so about 90%-95% of the codebase is written only by me. For the remaining part, I used OpenCode, mainly for some very trivial code snippets, to discuss optimal architectural choices for my code or to write documentation. Thank you for your observations in forward!

I have been trying to do a vc relax calculation for material Na15Sn9 with 38 atoms and even after resubmitting calculations 7 times with adjustments to the memory, tstress parameters etc, everytime bad termination pops up.

Below lie the ending lines of the output file:

----------------------------------------------------

atom 27 type 1 force = -0.00000158 0.00000052 -0.00000387

atom 28 type 1 force = -0.00000052 -0.00000387 0.00000158

atom 29 type 1 force = 0.00000387 0.00000158 0.00000052

atom 30 type 1 force = 0.00000158 0.00000052 0.00000387

atom 31 type 2 force = 0.00000052 0.00000052 -0.00000052

atom 32 type 2 force = -0.00000052 0.00000052 0.00000052

atom 33 type 2 force = 0.00000052 -0.00000052 0.00000052

atom 34 type 2 force = -0.00000052 -0.00000052 -0.00000052

atom 35 type 2 force = 0.00000052 -0.00000052 0.00000052

atom 36 type 2 force = -0.00000052 -0.00000052 -0.00000052

atom 37 type 2 force = -0.00000052 0.00000052 0.00000052

atom 38 type 2 force = 0.00000052 0.00000052 -0.00000052

Total force = 0.001812 Total SCF correction = 0.000021

Computing stress (Cartesian axis) and pressure

= BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES

= RANK 0 PID 1952 RUNNING AT cn047

= KILLED BY SIGNAL: 9 (Killed)

= BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES

= RANK 1 PID 1953 RUNNING AT cn047

= KILLED BY SIGNAL: 9 (Killed)

= BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES

= RANK 2 PID 1954 RUNNING AT cn047

= KILLED BY SIGNAL: 9 (Killed)

= BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES

= RANK 3 PID 1955 RUNNING AT cn047

= KILLED BY SIGNAL: 9 (Killed)

= BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES

= RANK 4 PID 1956 RUNNING AT cn047

= KILLED BY SIGNAL: 9 (Killed)

= BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES

= RANK 5 PID 1957 RUNNING AT cn047

= KILLED BY SIGNAL: 9 (Killed)

= BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES

= RANK 6 PID 1958 RUNNING AT cn047

= KILLED BY SIGNAL: 7 (Bus error)

= BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES

= RANK 7 PID 1959 RUNNING AT cn047

= KILLED BY SIGNAL: 9 (Killed)

The total forces and SCF were converging nicely before

--------------------------------------------------------

NaSn2_vcnew.out: Total force = 0.000892 Total SCF correction = 0.000426

NaSn2_vcnew.out: Total force = 0.000783 Total SCF correction = 0.000014

NaSn2_vcnew.out: Total force = 0.000796 Total SCF correction = 0.000012

NaSn2_vcnew.out: Total force = 0.000837 Total SCF correction = 0.000010

NaSn2_vcnew.out: Total force = 0.000872 Total SCF correction = 0.000024

NaSn2_vcnew.out: Total force = 0.000819 Total SCF correction = 0.000006

NaSn2_vcnew.out: Total force = 0.000726 Total SCF correction = 0.000023

---------------------------------------------------------

Additionally this is the error file

----------------------------------------------------------

Loading compiler version 2021.2.0

Loading mpi version 2021.2.0

Loading mkl version 2021.2.0

Loading compiler-rt version 2021.2.0

Loading tbb version 2021.2.0

[cn047:1958 :0:1958] Caught signal 7 (Bus error: nonexistent physical address)

==== backtrace (tid: 1958) ====

0 0x000000000080adc1 usnldiag_() /scratch/apps/qe-7.2/PW/src/usnldiag.f90:103

1 0x0000000000694092 diag_bands_IP_diag_bands_k_() /scratch/apps/qe-7.2/PW/src/c_bands.f90:995

2 0x0000000000692c0c diag_bands_() /scratch/apps/qe-7.2/PW/src/c_bands.f90:323

3 0x0000000000691305 c_bands_() /scratch/apps/qe-7.2/PW/src/c_bands.f90:132

4 0x000000000040ced4 electrons_scf_() /scratch/apps/qe-7.2/PW/src/electrons.f90:678

5 0x000000000040a19d electrons_() /scratch/apps/qe-7.2/PW/src/electrons.f90:189

6 0x0000000000579452 run_pwscf_() /scratch/apps/qe-7.2/PW/src/run_pwscf.f90:187

7 0x00000000004072cf MAIN__() /scratch/apps/qe-7.2/PW/src/pwscf.f90:85

8 0x000000000040714e main() ???:0

9 0x0000000000022555 __libc_start_main() ???:0

10 0x0000000000407069 _start() ???:0

[cn047:1956 :0:1956] Caught signal 7 (Bus error: nonexistent physical address)

==== backtrace (tid: 1956) ====

0 0x00000000010b73d0 __intel_cpu_features_init_body() cpu_feature_disp.c:0

1 0x0000000001040e1d for_cpstr() ???:0

2 0x0000000000f00e85 stop_clock_() /scratch/apps/qe-7.2/UtilXlib/clocks_handler.f90:352

3 0x0000000000e26479 invfft_y_() /scratch/apps/qe-7.2/FFTXlib/src/fft_fwinv.f90:109

4 0x0000000000a0b430 fft_wave_mp_wave_g2r_() /scratch/apps/qe-7.2/Modules/fft_wave.f90:152

5 0x00000000005be13d sum_band_IP_sum_band_k_() /scratch/apps/qe-7.2/PW/src/sum_band.f90:703

6 0x00000000005baa54 sum_band_() /scratch/apps/qe-7.2/PW/src/sum_band.f90:175

7 0x000000000040cf74 electrons_scf_() /scratch/apps/qe-7.2/PW/src/electrons.f90:716

8 0x000000000040a19d electrons_() /scratch/apps/qe-7.2/PW/src/electrons.f90:189

9 0x0000000000579452 run_pwscf_() /scratch/apps/qe-7.2/PW/src/run_pwscf.f90:187

10 0x00000000004072cf MAIN__() /scratch/apps/qe-7.2/PW/src/pwscf.f90:85

11 0x000000000040714e main() ???:0

12 0x0000000000022555 __libc_start_main() ???:0

13 0x0000000000407069 _start() ???:0

Please help me solve this upcoming error

The postdoctoral position is available on nonadiabatic dynamics (computational chemistry). You can google “Jian-Ge Zhou” + “nonadiabatic dynamics“ to search the job information (it doesn’t allow to post the job link). My email: jiange.zhou@jsums.edu. If you have any questions, please contact me.

Is A star A star A in bio chem math (respectively) possible to get into imperial chemistry? I’m taking my math resit this week but I don’t think I could get that star for math as it has always been my weaker subject.

I am a doctor in computational chemistry based in France , my thesis is purely DFT / SAR and docking Ididn’t have teaching experience during my PhD I have one article main author and another one in 5th position, in this year I developed some skills in python and ML still beginner tho , don’t know what I am doing wrong ? I am disappointed and helpless

Hello, I am a master’s student in organic chemistry, conducting small-scale research in computational chemistry.

In this study, after predicting the reaction site of a fluorescent probe as either ESP or LAEA, we began a research project to predict the actual reaction pathway and reactivity of the reactants using transition states and Gibbs free energy, and then to plot the reaction pathway.

So far, I have tried many variations with SCAN and NEB-TS, but I have been unable to achieve the desired results at all, and I keep failing over and over.

I want to ask a few questions

1. Can NEB-TS be applied to large molecules such as fluorescent probes?

2. Is it correct to first look for changes in the response through scanning?

3. Must an H2O molecule be present in the obligate state between the reactant site and the reactant?

4. What is the workflow for determining the actual TS and reactivity?

I would appreciate any advice or comments you could give.

For reference, the calculation programs I can use are Gaussian 09 and Orca.

I look forward to your valuable comment.

The CMD open and close. How fix that. Help

The postdoctoral position is available on nonadiabatic dynamics (computational chemistry). You can google “Jian-Ge Zhou” + “nonadiabatic dynamics“ to search the job information (it doesn’t allow to post the job link). My email: jiange.zhou@jsums.edu. If you have any questions, please contact me.

I have been applying for PhD positions since 2 years almost. Last year, I got a few interviews but no positions. But this year is parched. No reply to even emails.

I have worked in the industry for 2.5 years now and I have two second author papers. Do I need to expand on my skill set? I am an MD simulation person (mostly GROMACS, coarse-grained and all-atom, plus some Python)

Hi everyone,

Thanks to this sub for sharing information/ resources the past year. I am a chemist by training I'm currently working in biotech, particularly in siRNA. Over the past year, I have good opportunity to run a MD workflow to support our team's understanding of oligo. This motivates me to further pursue a Master's or even PhD degree in regards to computational science or Chemistry with focus on computer-aided drug discovery. My weakness is that I have 0 publication, and i am eager to contribute to any existing research in this space. If you have any lead, please let me know!

I have just started my msc chemistry 2 yr program.

Here all my peer are saying that if I have to pursue this degree than one has to go through NET exam . So can someone tell me about relevant sources from where I can start my preparation.

Also are there other options than teaching in this field cuz I'm more inclined towards industrial aspect,research and synthesis. So will this exam make any difference if I made through??

just tell me anything I'm completely newbie

Thanking in anticipation

Hello everyone I'm currently studying how to dock Xanthine oxidase but I got stuck on vina not recognizing the Mo atom of the Xanthine Oxidase, is there any script or parameters I can use to make autodock vina accept my receptor. The workflow I'm currently doing is Pymol -- Meeko --- Autodock vina

Greetings, dear chemists,

I am a second year PhD student working in medicinal chemistry and mainly doing synthesis. Although my main focus is wet lab, I am also trying to expand myself into computational side of drug design. Problem is that my programming skills are pretty weak and it is hard for me to understand how to use various non-GUI based softwares. I found out about Shrodinger and took it's intro course. From what I had seen, it would possibly help with my synthesis planning. On the other hand I do not have university access to Shrodinger software. Maybe you have any idea how much the license costs?

P.S. At this moment I would mainly be interested in docking with metalloproteins.
P.S.S. If you have any other recommendations or ideas I would be happy to hear it out.

I’m working on a sandwich complex containing six-membered B–N rings coordinated to Cr. In the QTAIM analysis, I find a bond critical point (BCP) between Cr and N, but on the Cr–B side I observe a ring critical point (RCP) instead of a BCP.

Interestingly, the ETS-NOCV analysis suggests that the N atoms interact with Cr predominantly through donation, whereas the B atoms are involved mainly in back-donation.

How should the RCP between Cr and B be interpreted in this case? Does the presence of an RCP indicate an multicenter Cr-B interaction mediated through the B–N ring, rather than a localized Cr–B bond?

I’d appreciate insights from a QTAIM perspective on how the RCP can be correlated with the ETS-NOCV results.

I'm a High School student who recently got an idea for what seems to be a promising compound that could potentially be helpful in cancer research. Opportunities aren't common where I come from, therefore I wanted to create the best piece of work possible before showing it to a professor or a sponsor to ask for funding (I still don't understand how the transition to lab work goes)
I have been compiling my paper studying different aspects of my compound and ultimately a lot of changes were made, however, I'm finally at the stage where I need to run molecular dynamics simulations on my compound to study its properties and also use an online AI model to predict the results of using my compound (I'm hoping that this helps prove my concept moving forward). The AI model asks for multiple values (some of which can be switched out for the mean or median of data sets the model compiled I believe), but I really have no idea how to come up with these values through simulations. I have no coding, research, or even chemistry experience so I understand how what I'm doing is laughable but it really means a lot to me to keep going and try my best nonetheless.
I keep trying to find ways to come up with values such as the zeta potential, hydrodynamic radius, size, shape, charge, etc but I don't know how. Most models or programs expect me to be a masters student already familiar with the environment but just 3 months ago I was still learning how to cite sources. This is the Github repository link for the AI model I'm using if anyone wants to take a look at the values I'm trying to find
[https://github.com/AmirKhak/NanoPK-AI/blob/main/AI_QS_MT.ipynb]

If anyone happens to know a way to simulate these values or an online tutorial that can help please let me know. I tried to search all over the place but most videos discuss the values and not the means to compute them. Thank you for giving me the time.

​

Hi everyone, I’m trying to understand the current and future job market for computational chemistry.

How good are the career prospects, and how difficult is it to get a job compared with fields like materials science, data science, or experimental chemistry? What types of roles are available in **drug discovery/pharma** and materials science?

I’d especially appreciate insights from people working in the industry about salary, job stability, skills that are in demand, and long-term growth.

I’m calculating condensed Fukui functions using Hirshfeld atomic charges for a structurally symmetric molecule.
For the neutral system, symmetry-equivalent atoms have very similar Hirshfeld charges, as expected. However, after calculating the N−1 system and obtaining the condensed (f^-) values, equivalent atoms show a strong asymmetry.
For example, consider a generic symmetric molecule containing two symmetry-equivalent oxygen atoms. One oxygen gives an (f^-) value of approximately +0.12, while the equivalent oxygen gives a slightly negative value (approximately −0.0001).
This surprised me because the atoms are symmetry-equivalent in the neutral molecule, yet their condensed Fukui functions are very different, and one of them is even negative.
Could this behavior arise from symmetry breaking or localization of the electron hole in the N−1 state?
Also, can small negative condensed Fukui values be physically meaningful, or are they generally associated with the population analysis?
I

PS I knew to cdft

Hello everyone can I ask on how to prepare receptors with metal cofactors or what specific autodock tools that specializes in that kind of proteins and what parameters should I input to prepare them.