Many papers mention either in the main document or supplemental information that IRC calculations were used to confirm transition state connects the starting materials and products of a given step and that's the end of it. It seems like this is common practice, but without any IRC plots or coordinates of the structures resulting from the IRC calculation, this claim has no proof.

Why it is satisfactory just to say that IRCs were performed without showing any IRC results?

I have molecular crystal system with 44 atoms in the unit cell and symmetry is P-1, triclinic which was extracted from single crystal diffraction, experimental data. When I try to vc-relax in QE the volume goes from ~940 Ato ~400 A and the relaxation stops altogether.

I have set ibrav in celldofree to keep the structure but it is changing way too much and breaks it. How do you guys optimize crystal structures like that? I wanted to test convergence against the lattice constants but no avail.

I am stuck with the lattice optimization part for so long, thanks for any help.

Who took chem 103 through portage and how was it and how long did it take you? I have 4 months to complete chemistry to be accepted into the nursing program I want to go to. Also, how is the math in it? I suck at math and am also going to take a intermediate algebra through my CC at the same time

how does one compute the exact bond angles of molecules? For example, the angle of a tetrahedron is 109.5 degrees so one would expect that to be the bond angle for water but its 104.5 like, as far as I managed to understand, that has to do with the two extra electron pairs on the oxygen that don't behave exactly as a covalent bond, but how would I go about modeling this? I figure I could have to place "point electrons" around a center and iteratively compute the repulsion, but I do I take bond length vs atomic radius into account? Is there any popular method that can generalize?

How does one construct hybrid topologies for small molecules specifically? For proteins there is PMX, but I haven’t found a protocol/ don’t know how to go about constructing the hybrid topology for something like water to propanol.

Hi, I am calculating Glycine Zwitterions in different solvents, but they always go back into normal form, no matter the solvent. I am using C-PCM and tried it with the

B3LYP and BHANDHLYP basis sets. Is there a way of stopping any topology change or a better calculation method?

Hi, how do you get CASSCF energies across a reaction, do you manually set the active space for each geometry?

Or is it valid to converge a CASSCF wavefunction at the reactant geometry (Frank Condon) and then use that as the guess for the next structure? I use ORCA, so do I just feed a structure's .gbw file to the adjacent image?

Hi everyone,

I’m working on a TDDFT to study the excitation spectra of a Squaraine dye ligand in water. However, I’ve run into an issue: the spectra I get from two different subsets of snapshots (first 100 vs. second 100) are noticeably different. You can see this in the plot below.

• Sampled data from 290 ns MD simulation (14500 frames total).
• Selected every 30th frame (to avoid correlation) for TDDFT calculations, focusing on the ligand + nearby salt (~8 Å region), with water modeled using the Effective Fragment Potential (EFP).
• wb97x-D/def2-svpd for dye and nearby ions
• Generated spectra by averaging excitation energies with Gaussian broadening.

https://imgur.com/a/9kwjpWl

I assumed 200 snapshots would be enough for convergence, but the spectra from the first 100 vs. the second 100 differ significantly. Since this is just water, I’m worried this might get worse when I move to my next system: choline amino acid-based ionic liquids.

1. Is this kind of variability normal, even with well-spaced snapshots?
2. Could this be due to rare events or transient interactions in water?
3. Any advice for improving convergence or ensuring snapshots represent the ensemble well?

Hi,

As the title states im intrested in running some bog standard MD on a protein ligand complex. I have figured out running normal proteins using openmm but parametrizing small molecules proved more difficult.

It seems that the easy way to do it is openff toolkit and its associated systems generators. However, protein setup takes an eternity compared to openmm force fields. That said it seems openmm and openfe also have some way of doing this.

Does anyone here have a good workflow/method/cookbook/advice for preparing a periodic protein ligand complex simulation? Since im not very spicy i want to run amber ff14 with the Sage force field for small molecules.

Best, Erikna

As the title states, I am wondering how long did it take some of you to complete your PHD in Computational Chemistry? I am an undergrad who has been very interested in the field but am curious about the length it takes before I can get decent roles in industry. (If you could please include what concentration you did for your PHD (i.e Molecular Dynamics, Materials, AI, etc.) that would be helpful). Thank you!

Side note, would you do a PHD in this field again if you went back in time?

Helloo everyone,

so it's been like three hours of me trying to generate a topology for pdb file and figure out how the command -ff in gmx pdb2gmx works. Two errors that the computer gives me are: "Invalid command-line options, In command-line option -ff, Too few (valid) values" and "Invalid command-line options, In command-line option -ff, Too many values". I've tried many different combinations of the input (different brackets etc.), but nothing worked. It always gives the same error of too many or too few values and nothing in between. I've tried following the help guide on the internet, but also to no avail.

Previously I used following command line to generate topology:

gmx pdb2gmx -f filename.pdb -o othername.gro -water spce

This worked fine and I thought that just substituting -f command with -ff command followed by the specific force field and again name of the source file should work just fine.

So I wanted to ask for help with how in detail (including any brackets ...) should I write the -ff command. Thank you for your time reading the post :) I would be very grateful for any bit of help.

Hi, I am running Gaussian calculations. I am doing optimisations, frequency and SPE calculations requesting 32cpus and 64gb memory. It works very well for me but I was wondering if it was worth optimising this to the specific type of molecule I am investigating?

Hello all I have tried to run a

#p opt freq b3lyp/6-311++g(d,p) geom=connectivity

Then

td=(nstates=50) b3lyp/6-311++g(d,p) scrf=(smd,solvent=toluene) Guess

=Read geom=connectivity

And my values are off the nm for absorption is too low what am I doing wrong please I am new to comp chem

Hello all I have tried to run a #p opt freq b3lyp/6-311++g(d,p) geom=connectivity

Then

td=(nstates=50) b3lyp/6-311++g(d,p) scrf=(smd,solvent=toluene) Guess

=Read geom=connectivity

And had no success my uv vis graph is really off for oil red o it has a lower molar absorption could I have some help please I am quite new to computational chemistry

I am doing geometry optimization on water as a sample calculation with the file named "water.inp". When I tried to use the command C:\Users\obill\Downloads\orca>orca water.inp > water.out

it sends the following message: 'orca' is not recognized as an internal or external command, operable program or batch file.

How do i troubleshoot this?

Dear community,

I recently started a computational project on an open-shell transition metal complex, trying to calculate its UV/Vis spectrum using TD-DFT, among other things. Starting with trusted PBE0 I got a spectrum that is as expected blue-shifted by 0.2-0.3 eV. To better get a handle on how this might impact further studies on more complex systems that also include this fragment, I tried different functional such as TPSS, TPSSh, TPPS0 and M06-L. They all adhered to the observed trend of GGAs and hybrids with increasing amounts of HF exchange.

To check for the presence of a (strongly) correlated system, I turned to the FOD approach by Grimme and got a value of >1.5 with TPSS and >2.5 with PBE0, with the plot showing most of it located on the central metal atom ----> as per suggestion go for a hybrid with low/no HF. (Wavefunction approaches would not be feasible for me here...)

The TPSS and TPPSh calculations gave the closest results. However, using a pure GGA is not feasible in future systems as they might be mixed-valent and GGAs always overestimate the extent of delocalization IME. On the other hand TPSSh with its 10% of HF is also not the best for TDDFT in general.

So I thought if maybe a tuned RSH would do the trick. I turned to LC-PBE as it is fairly straightforward.
Starting from the unturned version, 0% short-range (SR), 100% long-range (LR), and a µ of 0.47, I got a way blue-shifted spectrum (offset of 0.5 eV for the lowest transition). In several steps I then went down to 5% SR and only 25% LR (basically PBE0 in the long-range) with a µ= 0.2, giving me the best result, not only for the lowest energy transition but the rest as well.

I'm aware that this is a case of making the computer generate the number I want, but still, I'm interested from the perspective of if this can be a somewhat viable approach to get an idea of the excited state properties in these systems ( quite a bit of correlation but located) or if this is a case of the right answer for the wrong reasons (aka SIE and HF-exchange battling it out) ?

EDIT: I'm aware people are tuning RSH all the time, but I have never found one with such low values for LR, which ofc is not what you want normally.

I'd be super grateful for some input on this.

Best.

How many trials of a Molecular Dynamic simulation do we need at minimum in order to have a strong study?

Here's the information about our simulation:

Simulation type: NVT (Constant number of atoms, volume, and temperature)

Temperature : 312 K

pH: 7.3

Equilibration Steps: 1,000,000 (2 nanoseconds)

Step Size: 0.002*picoseconds

Friction: 1/picosecond

Normal Steps: 100,000,000 (200 nanoseconds)

Snapshot interval: 50,000

Integrator: Langevin Middle Integrator

Force fields: 'protein.ff14SB.xml', 'implicit/obc1.xml' ('UNK_6D5600.xml' which is a custom force field for the ligand we are adding onto the simulation)

Solvent type: Implicit solvation in water

Other info: Non-bonded Method = CutoffNonPeriodic, Non-bonded Cutoff = 1 nanometer, Constraints = Hydrogen Bonds (Code from the simulation used these)

Goal: See how Minocycline (ligand/drug) affects microglial activation markers' (proteins) stability and structure.

I got really bad marks in computational chemistry last exam... I knew the formulas, but couldn't implement them. Plus I don't know how to frame my answers so was hoping to find help regarding such. Seniors said "just yt the specific topics" but that doesn't help with the answer framing...

Edit: Sorry for not including this...

Stuff I need to cover include:

Syllabus:

Quantum Chemistry Historical development, Bohr’s atomic model, de Broglie wavelength, Heisenberg uncertainty principle, Schrodinger equation, Wave function, particle in a box, Hydrogen atom, radial and angular solution to hydrogen atom, applications and limitations

Thermodynamics Intensive and extensive variables, state and path functions, Laws of Thermodynamics (First law and enthalpy; second law and entropy, spontaneity, and equilibrium; third law and absolute entropy) free energy, Gibbs and Maxwell's relations, Ideal and real gases

Potential Energy Surfaces Chemical bonds and intermolecular interactions, Types of intermolecular interactions (charge distribution of isolated molecules, electrostatic interaction, induction interaction, London or dispersion forces, hydrogen bonding, repulsive interaction, relative contribution of different terms), representing the potential energy surfaces (pair additivity, rare gas), intramolecular interactions (bond stretching, angle bending, torsional and improper terms)

Molecular Dynamics Introduction to ensembles, force fields, integration of Newton’s laws of motion, force calculation, energy minimization, periodic boundary conditions, choice of input configuration, velocities, and time-step, applications, and calculation of simple thermodynamic variables.

Good morning everyone, I noticed that in the xTB version for Mac arm64 the spin polarization calculations doesn't work. It seems that it doesn't load correctly the library.

What's your experience?

kindly suggest me the free software to study computational chemistry.

(Yes we're the same group of high schoolers that posted before, this time with another issue)

So for our Molecular Dynamic Simulations within OpenMM we have been using a XML file for Minocycline that is not exactly but similar in structure to a OpenMM force field file. This allowed OpenMM to work with the force field from what we saw as we got no errors when running the simulation. But when it comes time to analyze data and we need to know specific information about minocycline there is no way to do it due to the slight formatting changes. We also got our XML file from PubChem, but we're not sure if its a reliable source to get these kinds of files and might negatively effect the reliability of our data.

We don't want to do docking with minocycline as we're simply looking at the effect that minocycline has on the whole protein structure. Since there are also multiple possible binding sites, each with a possibility of having unique effects on the protein, there are just too many cases to consider and due to computational and time constraints cannot run every possibility. We are using implicit solvation along with protein.ff14SB.xml and implicit/obc1.xml (for implicit solvation) as force fields in our simulation. Other information about the simulation includes:

Simulation type: NVT (Constant number of atoms, volume, and temperature)

Temperature : 312 K

pH: 7.3

Equilibration Steps: 1,000,000

Step Size: 0.002*picoseconds

Friction: 1/picosecond

Normal Steps: 100,000,000

Snapshot interval: 100,000

Integrator: Langevin Middle Integrator

Force fields: 'protein.ff14SB.xml', 'implicit/obc1.xml' ('Conformer3D_COMPOUND_CID_54675783.xml' for experimental, it is the xml file for minocycline; downloaded from PubChem (link: https://pubchem.ncbi.nlm.nih.gov/compound/54675783)

Solvent type: Implicit solvation in water

Other info: Non-bonded Method = CutoffNonPeriodic, Non-bonded Cutoff = 1 nanometer, Constraints = Hydrogen Bonds (Code from the simulation used these)

So should we generate a custom force field from a 3D structure of Minocycline or is there another easier way to figure out the information regarding the distance between the protein and the ligand without docking. And is it fine that our force field file is coming from PubChem?

Calling all medicinal chemists, what is your typical workflow for analyzing the patentability of your compounds during Hit-to-Lead? What software tools do you typically use and are there any pain points in the process that you want to be automated?

Greetings everyone. The tl:dr of this post is: what tools and mechanisms would you suggest to study the bond nature and redox potential of organometallic systems?

I've just started a new side project, where I have to study the nature and bonding of a few new organometallic new complexes. They are really cool and I'm very excited, but I've specialized in mechanism reaction and have little experience in this field. I'll be using ORCA to perform every job (with Multifwn and NBO).

As we have one example where we have 2 identical metals with different oxidation state, and systems that are closed-shell and other open-shell, my ideas are as follow:

• Optimize the XR structures.
• Use Gibbs energy to calculate redox potential between the different species.
• Obtain Mulliken analysis and Spin Density.
• Use the optimizations to perform QTAIM and NBO analysis.
• Finaly, perform EDA calculations.

With all of this, I expect to get all I need to propose an answer for the bonding between metals (or their bridge), their oxidation and redox potential. My quesion is: do you think all of this makes sense? Would you propose any other tool? I'm open to suggestions.

Hey team! I’m trying to make a script that does rasscf on a bunch of different small molecules in an automated way.

My initial scf spits out a bunch of orbitals. But for the rasscf to work, I need to rotate the n, pi, and pi* orbitals into the active space manually, once I identify them by looking.

Is there any way that I can automate this process - with software or preferably python packages, that takes the Molden file, then returns which orbital numbers are the lone pair n, pi and pi*?

Hello everyone,

I'm currently trying to perform conical intersection (CI) calculations using ORCA and would appreciate some guidance. My current input setup for CI optimizations is as follows:

!B3LYP DEF2-SVP CI-OPT
%TDDFT IROOT 1 END

I am exploring the CI between the ground state and the first excited state. Here are a few questions I have:

1. Spin-Flip Inclusion: Should I include Spin-Flip (SF) in my TDDFT calculations for better accuracy in finding conical intersections, especially if I expect spin contamination or if the excited states involve different spin multiplicities?
2. Input Settings: Is the !B3LYP DEF2-SVP CI-OPT along with %TDDFT IROOT 1 END configuration adequate for CI calculations involving the first excited state? Are there additional parameters I should consider to improve the accuracy or efficiency of the calculation?
3. General Advice: If anyone has experience with similar systems or settings and could share any tips or common pitfalls, it would be greatly helpful.

Thank you in advance for your help and suggestions!

Hello fellow comp chemists,

I am in the delightful position to be receiving a new laptop. I can either choose a Linux laptop (Dell XPS), or a MacBook. Now, I currently have an XPS for my own personal use, and I think its pretty good, except the battery life is crap and its a bit heavy. I have never used mac, but know they have excellent battery lives.

As such, I would like to hear from anyone here who has experience using both for general comp chem stuff.

Thanks in advance!

Hello, everyone!
I am currently pursuing a bachelor's degree in chemistry and will graduate next year. I plan to continue my studies with a master's program in computational chemistry.

I am particularly interested in studying in the USA but feel a bit overwhelmed when choosing the best universities for this field. Could anyone recommend universities with strong computational chemistry programs? Any advice or insights would be greatly appreciated!

Thank you in advance!

Hello, fellow researchers! 👋

I am currently planning to write a research/review article in the field of computational biology and am looking for fellow peoples to engage and collabrate, creating a meaningfull network.
I am also open to contributing to ongoing research work to gain experience and strengthen my expertise.

My intrest includes Drug discovery, Natural Products Research, QM modelling.

If you’re interested in collaborating, sharing ideas, or have ongoing projects where I could contribute, feel free to comment below or DM me let’s connect. 

I studied Chemistry in undergrad with a decent publication record in materials/synthesis, but since graduating have worked as a software engineer in high performance computing for about 5 years, with good experience at both a national lab and cloud-scale tech companies. I'm looking to get into AI+Chemistry and really appreciate the community's input on approaches for doing this.

The explosion of interest in AI + Chemistry, especially bayesian experiment design and generative AI, is extremely interesting to me. It wasn't nearly as prominent when I was in school, but it seems to be the perfect way to combine my background in chemistry and computing. Courses in this area didn't exist in my Chemistry department 5+ years ago, I don't have direct ML training projects beyond what I've self-taught. From my big tech roles I do have plenty of experience with high-performance computing and data infrastructure that feed into ML pipelines though.

What might my options be for getting into a ML Engineering for Chemistry role? I'm a few years out of school and already have a master's degree, and lifestyle wise I don't have too much appetite for another degree program, including a PhD. Having worked in tech for a bit, I'm okay to go back to academic pay bands for 1-2 years, but definitely not 5.

Some options that come to mind:

1. Apply for entry-level ML engineering roles, noting that while I have data engineering experience, all my experience with training/ developing new models is self-taught. I'm not sure how competitive my software/data engineering experience will be compared to someone with a pure ML background.
2. Apply for a senior data engineering role, but find a company where people can wear many hats and I can network my way into doing model training/development.
3. Find a staff research engineering role at a lab working in/ adjacent to this area, in the US or abroad, and similarly network my way into contributing to the science and not just the engineering.
4. Work for free for a year at a university ML + Chemistry lab near my home in the US.
5. Self-fund working for a lab in this area outside the United States in a lower cost of living country where I can get an unrestricted work visa using my big-tech experience. I've studied abroad in the past, so this doesn't sound unrealistically crazy to me. 
6. Apply for grants (Fulbright? Any others?) to do a year-long research rotation at a lab in this space, here or abroad.

All options are on the table. For #1, I've only found 1 company that does ML+Chemistry with entry-level non-PhD ML engineer openings, but I'm on the lookout for more. For #2 I've applied and interviewed. I have found no roles just browsing online for #3, but I haven't yet started reaching out directly to PI's to ask about openings. #4-5 are on the table, but given the financial considerations this is more of a last resort for me. #6 I'm not aware of any grants that will fund research for people that are graduated but without a PhD.

Any advice or other ideas I'm missing? I really appreciate the community's suggestions here, which include just getting a PhD for next year's cycle if that's unavoidable.