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computer science

HH-suite

HH-suite is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand HH-suite rather than just read about it. In short: The HH-suite is an open-source software package for sensitive protein sequence searching. It contains programs that can search for similar protein sequences in protein sequence databases.

HH-suite — main illustration
HH-suite — illustration

Key takeaways

  • HH-suite belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect HH-suite to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of HH-suite from memory before moving on to harder problems.

Reference excerpt

The HH-suite is an open-source software package for sensitive protein sequence searching. It contains programs that can search for similar protein sequences in protein sequence databases. Sequence searches are a standard tool in modern biology with which the function of unknown proteins can be inferred from the functions of proteins with similar sequences. HHsearch and HHblits are two main programs in the package and the entry point to its search function, the latter being a faster iteration. HHpred is an online server for protein structure prediction that uses homology information from HH-suite. The HH-suite searches for sequences using hidden Markov models (HMMs). The name comes from the fact that it performs HMM-HMM alignments. Among the most popular methods for protein sequence matching, the programs have been cited more than 5000 times total according to Google Scholar.

Background Proteins are central players in all of life's processes. Understanding them is central to understanding molecular processes in cells. This is particularly important in order to understand the origin of diseases. But for a large fraction of the approximately 20 000 human proteins the structures and functions remain unknown. Many proteins have been investigated in model organisms such as many bacteria, baker's yeast, fruit flies, zebra fish or mice, for which experiments can be often done more easily than with human cells. To predict the function, structure, or other properties of a protein for which only its sequence of amino acids is known, the protein sequence is compared to the sequences of other proteins in public databases. If a protein with sufficiently similar sequence is found, the two proteins are likely to be evolutionarily related ("homologous"). In that case, they are likely to share similar structures and functions. Therefore, if a protein with a sufficiently similar sequence and with known functions and/or structure can be found by the sequence search, the unknown protein's functions, structure, and domain composition can be predicted. Such predictions greatly facilitate the determination of the function or structure by targeted validation experiments. Sequence searches are frequently performed by biologists to infer the function of an unknown protein from its sequence. For this purpose, the protein's sequence is compared to the sequences of other proteins in public databases and its function is deduced from those of the most similar sequences. Often, no sequences with annotated functions can be found in such a search. In this case, more sensitive methods are required to identify more remotely related proteins or protein families. From these relationships, hypotheses about the protein's functions, structure, and domain composition can be inferred. HHsearch performs searches with a protein sequence through databases. The HHpred server and the HH-suite software package offer many popular, regularly updated databases, such as the Protein Data Bank, as well as the InterPro, Pfam, COG, and SCOP databases.

Algorithm

Modern sensitive methods for protein search utilize sequence profiles. They may be used to compare a sequence to a profile, or in more advanced cases such as HH-suite, to match among profiles. Profiles and alignments are themselves derived from matches, using for example PSI-BLAST or HHblits. A position-specific scoring matrix (PSSM) profile contains for each position in the query sequence the similarity score for the 20 amino acids. The profiles are derived from multiple sequence alignments (MSAs), in which related proteins are written together (aligned), such that the frequencies of amino acids in each position can be interpreted as probabilities for amino acids in new related proteins, and be used to derive the "similarity scores". Because profiles contain much more information than a single sequence (e.g. the position-specific degree of conservation), profile-profile comparison methods are much more powerful than sequence-sequence comparison methods like BLAST or profile-sequence comparison methods like PSI-BLAST. HHpred and HHsearch represent query and database proteins by profile hidden Markov models (HMMs), an extension of PSSM sequence profiles that also records position-specific amino acid insertion and deletion frequencies. HHsearch searches a database of HMMs with a query HMM. Before starting the search through the actual database of HMMs, HHsearch/HHpred builds a multiple sequence alignment of sequences related to the query sequence/MSA using the HHblits program. From this alignment, a profile HMM is calculated. The databases contain HMMs that are precalculated in the same fashion using PSI-BLAST. The output of HHpred and HHsearch is a ranked list of database matches (including E-values and probabilities for a true relationship) and the pairwise query-database sequence alignments. HHblits, a part of the HH-suite since 2001, builds high-quality multiple sequence alignments (MSAs) starting from a single query sequence or a MSA. As in PSI-BLAST, it works iteratively, repeatedly constructing new query profiles by adding the results found in the previous round. It matches against a pre-built HMM databases derived from protein sequence databases, each representing a "cluster" of related proteins. In the case of HHblits, such matches are done on the level of HMM-HMM profiles, which grants additional sensitivity. Its prefiltering reduces the tens of millions HMMs to match against to a few thousands of them, thus speeding up the slow HMM-HMM comparison process. The HH-suite comes with a number of pre-built profile HMMs that can be searched using HHblits and HHsearch, among them a clustered version of the UniProt database, of the Protein Data Bank of proteins with known structures, of Pfam protein family alignments, of SCOP structural protein domains, and many more.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with HH-suite

Start with the simplest possible case. Write down what HH-suite claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to HH-suite before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about HH-suite ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of HH-suite

In research
HH-suite appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses HH-suite in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
HH-suite is common in secondary-school and first-year university syllabi. It links to neighbouring topics Bioinformatics software, Computational science, so understanding it makes those chapters shorter.
In everyday life
Look for HH-suite outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study HH-suite in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what HH-suite means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain HH-suite out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is HH-suite in simple terms?

The HH-suite is an open-source software package for sensitive protein sequence searching. It contains programs that can search for similar protein sequences in protein sequence databases.

Why does HH-suite matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study HH-suite?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on HH-suite.

Tags

  • Bioinformatics software
  • Computational science

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