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Antibacterial

How it works

Drug discovery screening software that ranks a series before the plate

Antibacterial sits between a library and a plate. It reads the published antibacterial neighborhood of your compound, rolls the evidence up per strain, and returns a ranked read-out you can defend in a program meeting. Here is exactly what happens, and what does not.

Run a screen

The method

Four steps, about ten seconds

01

Submit the compound

A SMILES string, an InChI, or the name of a known agent. Batch runs take an SDF or a CSV with one structure per row, up to the limit on your plan.

Accepted
SMILES, InChI, compound name
Batch
SDF or CSV upload
Not needed
A target, a protein structure or a docking setup
02

Choose the strain panel

The unit of work is compound times strain. Pick one of the standard panels or assemble a custom set of clinical isolates. Enterprise can load an internal isolate library so the panel matches your own collection.

ESKAPE
S. aureus, E. coli, K. pneumoniae, A. baumannii, P. aeruginosa, E. faecium
Gram-negative
Adds E. cloacae and S. Typhimurium
Gram-positive
Adds MSSA, E. faecalis, S. pneumoniae, S. epidermidis
03

The model reads the published neighborhood

Reported antibacterial activity for the compound itself where it exists, then for its closest structural analogs, then what the surveillance and mechanism literature says about resistance in each species. The scaffold, the charge, the size and the polarity all matter, because in antibacterials uptake usually decides the outcome before affinity does.

Signal 1
Measured activity for the compound, when published
Signal 2
Activity of close analogs and the shape of the series
Signal 3
Species level resistance mechanisms and how common they are
04

Read the matrix and rank the series

One row per strain: a predicted MIC band in µg/mL, an S, I or R call, the mechanism the model expects, a one sentence reason, and a confidence level from one to four. Batch runs add a ranking across the whole series.

Export
CSV on every plan, SDF and PDF from Discovery
API
REST, from Discovery upwards
Honesty
No published basis returns no number, not a guess

The screening cascade

Where in silico triage sits between the library and the bench

Every later stage costs more per compound than the one before it. The point of screening software is to make the second stage cheap enough that the third only sees compounds with a reason to be there.

If you are pricing the stage itself, the drug discovery software cost comparison sets a screen against what the modeling suites charge, and MIC prediction software covers the read-out in more depth. Teams that want the same call inside their own pipeline use the antibacterial screening API.

What it does

Triage, ranking and a reason

  • Predicts a doubling dilution MIC band per strain, not a single false precision number.
  • Names the resistance mechanism it expects for that species, such as efflux through AcrAB-TolC or a KPC carbapenemase.
  • Returns the closest published analogs it can actually name, with their reported activity.
  • Ranks a series so the plate list is a decision, not a shortlist of everything.
  • Says when it has no basis, with a confidence level of one and no invented number.

What it does not do

The limits, stated up front

  • It does not measure anything. Every number is a computational prediction from published data.
  • It is not a diagnostic and not an antibiogram. Nothing it returns should reach a patient decision.
  • It does not model your specific in-house isolate unless you are on Enterprise and have loaded it.
  • It does not predict toxicity, PK or formulation behavior. Those are different questions.
  • It does not invent citations, accession numbers or p-values, so it will sometimes say less than you want.

Confidence

Every row says how much it is standing on

A prediction without a confidence level is a guess with good manners. Each row carries a four segment meter, and the meaning of each level is fixed.

Level Meaning Typical case How to use it
4 Extensively characterized A marketed agent against a species with decades of surveillance data Treat the band as a strong prior
3 Well supported A known scaffold with several published MIC datasets nearby Good enough to order a series
2 Inferred from close analogs A new analog in a well described family Use for ranking, confirm the top calls
1 Little or no published data A novel scaffold with no antibacterial neighborhood Treat as unknown, the model will often decline to give a band

The same discipline applies to the numbers themselves. A band such as 0.5-2 is a doubling dilution range, which is the resolution a broth microdilution plate actually has. If you want the detail behind that, the minimum inhibitory concentration guide walks through how the number is read, and high throughput screening covers where in silico triage sits relative to a real plate run.

Before you buy

Questions teams ask before the first batch

Batch limits on this page are read from the plan you buy, so they match the pricing page exactly.

No. The screen works from the structure alone and reads activity at the organism level, so it needs no target, no protein structure and no docking setup. That matters for antibacterials, where uptake and efflux decide most outcomes before binding affinity does.

A single screen takes a SMILES string, an InChI or the name of a known agent. Batch runs take an SDF or a CSV with one structure per row. Results export as CSV on every plan, and as SDF or a PDF report from Discovery upwards.

Up to 50 compounds per batch on Lab, 1,000 on Discovery and 10,000 on Program. Each compound counts as one screen against the panel you pick, and the whole batch comes back ranked by how much of the panel each compound holds.

It is accurate to the resolution a plate has, a doubling dilution band, when there is published activity nearby, and it says so when there is not. Every row carries a confidence level from one to four. Use it to rank a series and confirm the top calls on a real plate.

Yes, from the Discovery plan upwards. A REST endpoint with an API key returns the same matrix as the web screen, so predictions can be written back into a registry or a pipeline next to each structure.

No. A prediction decides which compounds earn plate time and in what order. It is research triage, never a result to report and never a clinical read. The measured MIC on your own strains is still the number that goes in the paper or the program review.

Reference pages behind the method

The science the model reasons over, written out in full.

Screen the compound you are arguing about this week

Run a screen on the homepage without an account. When the read-out is useful, create your account and run the whole series.

Run a screen first

What you are agreeing to

  • Your compounds stay yours
  • Never used for model training
  • Deletable on request
  • No card needed to create your account

Screen your own compound.
No card required.