bio-remote-homology
Detect distant homologs using profile and structure-aware methods that go beyond standard BLAST. Use when sequence identity falls into the twilight zone (<35% pairwise), when BLAST fails to find homologs that should exist, when working at metagenomic scale (DIAMOND, MMseqs2), or when structure beats sequence (Foldseek). Covers PSI-BLAST (iterative PSSM), jackhmmer (iterative HMM), HHblits/HHsearch (profile-profile), DIAMOND, MMseqs2, and Foldseek (3Di structural alphabet, van Kempen 2024).
npx skills add BioTender-max/awesome-bio-agent-skills --skill remote-homology --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
It instructs the agent to detect distant homologs beyond standard BLAST by selecting and running profile or structure-aware tools, including PSI-BLAST, jackhmmer, HHblits/HHsearch, MMseqs2, DIAMOND, and Foldseek, to improve sensitivity when sequence identity is in the twilight zone or structure informs homology.
How it works
The skill covers installing and verifying versions of the relevant tools, then applying the appropriate method depending on the scenario:
- For quick large-scale searches: run MMseqs2 or DIAMOND with appropriate speed/sensitivity settings.
- For distant single-query homology: prefer jackhmmer or MMseqs2 iterative searches, with iterative HMMs or profiles.
- For structure-aware analysis: use Foldseek (with AlphaFoldDB) or ProstT5 for sequence-only cases, parsing the m8 output accordingly.
- For domain assignment and depth: use HHblits/HHsearch for profile-profile comparisons, and hmmscan for Pfam domains.
- For iterative HMMER workflows: run jackhmmer and then use the final HMM with hmmsearch.
- For PSI-BLAST workflows: manage iterations (usually 2-3) to avoid drift, save and reuse PSSMs if needed.
The skill provides concrete command blocks and parameters, including how to build and search against databases, and how to interpret outputs (e.g., using --outfmt 6 for results). It emphasizes using version-specific flags via --help when necessary.
When to use it
Use when:
- sequence identity is below ~35% and standard BLAST misses homologs (twilight zone).
- aiming to analyze metagenomic data at scale (MMseqs2, DIAMOND).
- structure-guided homology is advantageous (Foldseek) or when sequence alone is insufficient.
What it can touch
Tools listed: psiblast, jackhmmer, hmmsearch, hhblits, mmseqs, diamond, foldseek. Parsing of outputs via Python (Bio.SearchIO) is mentioned, and optional web or ColabFold interfaces are noted.
Caveats
Notes include potential PSI-BLAST PSSM drift if iterating beyond 3 iterations, Foldseek hits without true homology, default MMseqs2 sensitivity pitfalls, DIAMOND default mode sensitivity considerations, and the need to mask low-complexity regions to avoid spurious hits. It also documents version compatibility checks and the need to align database versions with tool versions.
## Version Compatibility Reference examples tested with: NCBI BLAST+ 2.15+, HMMER 3.4+, MMseqs2 15+, DIAMOND 2.1+, HH-suite3 3.3+, Foldseek 9+ Before using code patterns, verify installed versions match. If versions differ: - CLI: `<tool> --version` then `<tool> --help` to confirm flags - Python: `pip show <package>` then introspect signatures If a flag is unrecognized or behavior changes, introspect with `--help` and adapt the example to match the installed version rather than retrying. # Remote Homology **"Find homologs my BLAST missed"** -> Standard BLAST detects similarity reliably down to ~35% pairwise identity (the "twilight zone", Rost 1999 *Protein Eng* 12:85). Below that, profile methods (PSSMs, HMMs) and structure-aware methods (Foldseek) recover homologs that pairwise alignment misses. This skill covers the decision: which method, when, against what database. The competition has shifted substantially since 2015: PSI-BLAST is no longer the de-facto standard; MMseqs2 and DIAMOND have replaced BLAST in most large-scale workflows; Foldseek (van Kempen et al. 2024 *Nat Biotechnol* 42:243) detects homologs no sequence method can reach by searching with a 3Di structural alphabe
- Version Compatibility
- Required Setup
- Decision matrix: which method when
- Foldseek: the 2024 revolution
- PSI-BLAST: still useful, but watch the drift
- HMMER 3 (hmmsearch, jackhmmer)
- HHblits / HHsearch (HH-suite3)
- MMseqs2 (the modern protein search workhorse)
- DIAMOND (the modern blastp replacement)
- Iterative HMMER (jackhmmer)
- Code patterns
- Foldseek search against AlphaFoldDB
- Sequence-only Foldseek via ProstT5
- PSI-BLAST with saved PSSM
Install via conda conda install -c bioconda hmmer mmseqs2 diamond hhsuite foldseek conda install -c bioconda blast Verify hmmsearch -h | head -3 # HMMER 3.4+ mmseqs version # MMseqs2 15+ diamond --version # DIAMOND 2.1+ hhblits -h | head -3 # HH-suite3 3.3+ foldseek --version # Foldseek 9+ Build domain database once
What does the bio-remote-homology skill do?
Detect distant homologs using profile and structure-aware methods that go beyond standard BLAST. Use when sequence identity falls into the twilight zone (<35% pairwise), when BLAST fails to find homologs that should exist, when working at metagenomic scale (DIAMOND, MMseqs2), or when structure beats sequence (Foldseek). Covers PSI-BLAST (iterative PSSM), jackhmmer (iterative HMM), HHblits/HHsearch (profile-profile), DIAMOND, MMseqs2, and Foldseek (3Di structural alphabet, van Kempen 2024).
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill remote-homology --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.